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Project Description

PyDTO is a data conversion library. It can validate data, that comes from various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydtoz import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at various data serialization formats like JSON, YAML, etc. and convert it to native Python datatypes. It can also convert native Python objects to described DTO.

A taste of this library:

>>> from decimal import Decimal
>>> from pydto import Schema, Required, List, Enum
>>> SCHEMA = Schema(List({
...     Required('price'): Decimal,
...     Required('category'): Enum('laptops', 'tablets', 'phones'),
...     Required('quantity'): int,
...     Required('serial'): (str, int)
... }))
>>> result = SCHEMA([
... {'price': '399.99', 'category': 'tablets', 'quantity': '2', 'serial': ['ta', '237']},
... {'price': '899.99', 'category': 'laptops', 'quantity': '1', 'serial': ['ag', '863']},
... {'price': '199.99', 'category': 'phones', 'quantity': '3', 'serial': ['lz', '659']}
])
>>> assert result == [
... {'price': Decimal('399.99'), 'category': 'tablets', 'quantity': 2, 'serial': ['ta', 237]},
... {'price': Decimal('899.99'), 'category': 'laptops', 'quantity': 1, 'serial': ['ag', 863]},
... {'price': Decimal('199.99'), 'category': 'phones', 'quantity': 3, 'serial': ['lz', 659]}
]

Check out documentation for more detailed review at Github repo.

Release History

Release History

0.5.1

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.4.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.4.0

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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0.3.3

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.3.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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0.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

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Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
pydto-0.5.1.tar.gz (17.6 kB) Copy SHA256 Checksum SHA256 Source Aug 21, 2015

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