Forked from schematics/schematics: Python Data Structures for Humans, supporting python 3.10 plus.
Project description
About
This is a Fork from the hard work of the maintainers at https://github.com/schematics/schematics. Here’s a summary of the changes: + add support for python 3.10+ + drop support for python version 3.6, 3.7, and 3.8 + run black and isort on the code base + package with flit, updating to pyproject.toml + add development environment setup with nix and package as a nix flake. + and that’s it!
I don’t plan on any changes to this library aside from maintaining support for modern python versions as long as this library is still a dependency for projects that I’m involved with which is unlikely to be forever. I would recommend planning on porting your validation code to another validation / serialization library that is actively maintained. But until then I’ll do my best to keep this current with new python versions. Thank you to the original maintainers for all of their work!
Project documentation: https://schematics.readthedocs.io/en/latest/
Schematics is a Python library to combine types into structures, validate them, and transform the shapes of your data based on simple descriptions.
The internals are similar to ORM type systems, but there is no database layer in Schematics. Instead, we believe that building a database layer is made significantly easier when Schematics handles everything but writing the query.
Further, it can be used for a range of tasks where having a database involved may not make sense.
Some common use cases:
Design and document specific data structures
Convert structures to and from different formats such as JSON or MsgPack
Validate API inputs
Remove fields based on access rights of some data’s recipient
Define message formats for communications protocols, like an RPC
Custom persistence layers
Example
This is a simple Model.
>>> from schematics.models import Model
>>> from schematics.types import StringType, URLType
>>> class Person(Model):
... name = StringType(required=True)
... website = URLType()
...
>>> person = Person({'name': u'Joe Strummer',
... 'website': 'http://soundcloud.com/joestrummer'})
>>> person.name
u'Joe Strummer'
Serializing the data to JSON.
>>> import json
>>> json.dumps(person.to_primitive())
{"name": "Joe Strummer", "website": "http://soundcloud.com/joestrummer"}
Let’s try validating without a name value, since it’s required.
>>> person = Person()
>>> person.website = 'http://www.amontobin.com/'
>>> person.validate()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "schematics/models.py", line 231, in validate
raise DataError(e.messages)
schematics.exceptions.DataError: {'name': ['This field is required.']}
Add the field and validation passes.
>>> person = Person()
>>> person.name = 'Amon Tobin'
>>> person.website = 'http://www.amontobin.com/'
>>> person.validate()
>>>
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for schematics-py310-plus-0.0.2.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 11ecd248e7ce4f565628e312029b38df727b7f7211e67551139c134333c41b55 |
|
MD5 | 98a7240628a3614ad59938defb5ec454 |
|
BLAKE2b-256 | ca56bf810eddfcfc10706f496debc51c4a7fba867a12fdd058637992c9ec81e8 |
Hashes for schematics_py310_plus-0.0.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f1d98176f8d3667ba50dad29c1c695f7d76f0fac75f65e167d220f8fa89b91c3 |
|
MD5 | 86dd5a0b5c0184a59e3f1e6933dccd53 |
|
BLAKE2b-256 | 4410b695a3a2a2c88622435c81f30b18d03b743bb96e5e929c82bad43ac4b207 |