pyaddict 2.1.0

yet another dict library

pyaddict

Description

Yet another python library to safely work with json data. It implements many useful features such as optional chaining, schema validation, type casting, safe indexing and default values.

Installation

pip install pyaddict

Usage

Accessing json data

from pyaddict import JDict

data = {
    "name": "John",
    "age": 30,
    "cars": [
        {"model": "BMW 230", "mpg": 27.5},
        {"model": "Ford Edge", "mpg": 24.1}
    ]
}

jdict = JDict(data).chain()  # enable chaining

jdict.expect("name", str)  # "John"
jdict.expect("name", int)  # TypeError: name is str, not int
jdict.expect("address", str)  # KeyError: key 'address' not found
jdict.expect("cars[0].mpg", float)  # 27.5 (because we enabled chaining)

# if we prefer None
jdict.optional_get("name", str)  # "John"
jdict.optional_get("name", int)  # None
jdict.optional_get("address", str)  # None
jdict.optional_get("address.street", str)  # KeyError: address not found
jdict.optional_get("address?.street", str)  # None
jdict.optional_get("cars[2].mpg", str)  # IndexError: out of range
jdict.optional_get("cars[2]?.mpg", str)  # None

# if we don't care whether it exists or not
jdict.ensure("name", str)  # "John"
jdict.ensure("name", int)  # 0, because name is not an int
jdict.ensure("age", int)  # 30
jdict.ensure("age", str)  # "", because age is not a string
jdict.ensure("address", str, "moon")  # "moon"
jdict.ensure("cars[].model", list)  # [ "BMW 230", "Ford Edge" ]
jdict.ensure("cars[0].mpg", float)  # 27.5
jdict.ensure("cars[0].mpg", int)  # 0, because cars[0].model is not an int

# or cast to the desired type
jdict.ensure_cast("cars[0].mpg", int) # 27

Similar rules apply when working with lists:

from pyaddict import JList

data = [{"name": "John", "age": 20}, {"name": "Jane", "age": 22}]

jlist = JList(data)

jlist.expect(0, dict)  # {"name": "John", "age": 20}
jlist.expect(0, int)  # TypeError: item is dict, not int
jlist.expect(2, dict)  # IndexError: out of range
jlist.expect("0.name", str)  # ValueError: invalid int

# if we enable chaining:
jlist = JList(data).chain()
jlist.expect("0.name", str)  # "John"
jlist.expect("[].name", list)  # ["John", "Jane"]

Validating json data

from pyaddict.schema import Anything, Array, Integer, Object, OneOf, String

schema = Object({
    "name": String(),
    "age": Integer().coerce(),
    "dogs": Array(
        OneOf(
            String(),
            Object({}, additional_properties=True)
        )
    ).min(1).optional(),
    "wildcard": Anything(),
    "valid": True
})

result = schema.validate({
    "name": "John",
    "age": 20.0,
    "wildcard": [1, 2, 3],
    "valid": True
})
result.valid  # True
result.unwrap()  # { "name": "John", "age": 20, "wildcard": [1, 2, 3], "valid": True }

result = schema.validate({
    "name": "John",
    "age": 5,
    "dogs": 1,
    "wildcard": True,
    "valid": True
})
result.valid  # False
result.unwrap()  # ValueError (invalid)
result.error  # 'dogs' should be list, not int

The library is fully typed and thus can be used with mypy & pylint. Check out the wiki for more information.

License

MIT

Author

davidohnee