Set of tools that makes input data validation easier
Project description
Schematec
Schematec is a set of tools that makes input data validation easier. The purpose of this code is attempt to bring simplicity to applications logics using separation of data validation and actual data processing.
Quickstart
import schematec as s
schema = s.dictionary(
id=[s.integer, s.required],
name=s.string,
tags=s.array(s.string),
)
>>> data = {
... 'id': '1',
... 'name': 'Red Hot Chili Peppers',
... 'tags': ['funk', 'rock'],
... 'rank': '1',
... }
>>> schema(data)
{'id': 1, 'name': u'Red Hot Chili Peppers', 'tags': [u'funk', u'rock']}
Concepts
Schematec module is based on three basic concepts:
Schema
Validator
Converter
Schema
Term “schema” is used to describe complex data struct such as dictionary(hashmap) or array(list). Schemas has two different types of validation (it is not related to array schemas):
Strict - requires all values
Non-strict - tolerate to missed values
schematec.exc.SchemaError is raised in case provided data is incorrect.
Order of schema validations:
Unbound Validators
Schemas(inner)
Converters
Bound Validators
Validator
Term “validator” describes callable objects that perform different types of checks. There are two types of validators in schematec:
Bound - type related, for example “max length” validator is bound to sized type.
Unbound - universal, for example “required” validator.
Raises schematec.exc.ValidationError.
Converter
Term “converter” is used to describe cast functions. Schematec supports subset of JSON data types.
Basic types:
integer(int)
string(str)
boolean(bool)
Containers:
array(list)
dictionary(dict)
Raises schematec.exc.ConvertationError.
Examples
Recursive schema
import schematec as s
schema = s.dictionary(
id=[s.integer, s.required],
entity=s.dictionary(
name=[s.string, s.required],
value=s.string,
)
)
>>> data = {
... 'id': 1,
... 'entity': {
... 'name': 'song',
... 'value': 'californication',
... }
... }
>>> schema(data)
{'id': 1, 'entity': {'name': u'song', 'value': u'californication'}}
Errors handling
import schematec as s
schema = s.dictionary(
id=[s.integer, s.required],
entity=s.dictionary(
name=[s.string, s.required],
value=s.string,
)
)
>>> data = {
... 'id': 1,
... 'entity': {
... 'value': 'californication',
... }
... }
>>> schema(data)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "schematec/schema.py", line 44, in __call__
value = schema(value, strict=strict)
File "schematec/schema.py", line 32, in __call__
validator(name, data)
File "schematec/validators.py", line 12, in __call__
raise exc.ValidationError(name)
schematec.exc.ValidationError: name
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