python-voluptuous
Port variant v12
Summary Python data validation library (3.12)
BROKEN
Package version 0.15.2
Homepage https://github.com/alecthomas/voluptuous
Keywords python
Maintainer Python Automaton
License Not yet specified
Other variants v13
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Last modified 11 NOV 2024, 23:28:05 UTC
Port created 05 MAR 2024, 06:30:48 UTC
Subpackage Descriptions
single # CONTRIBUTIONS ONLY **What does this mean?** I do not have time to fix issues myself. The only way fixes or new features will be added is by people submitting PRs. **Current status:** Voluptuous is largely feature stable. There hasn't been a need to add new features in a while, but there are some bugs that should be fixed. **Why?** I no longer use Voluptuous personally (in fact I no longer regularly write Python code). Rather than leave the project in a limbo of people filing issues and wondering why they're not being worked on, I believe this notice will more clearly set expectations. # Voluptuous is a Python data validation library [image] [image] [image] [Test status] [Coverage status] [Gitter chat] Voluptuous, *despite* the name, is a Python data validation library. It is primarily intended for validating data coming into Python as JSON, YAML, etc. It has three goals: 1. Simplicity. 2. Support for complex data structures. 3. Provide useful error messages. ## Contact Voluptuous now has a mailing list! Send a mail to [] to subscribe. Instructions will follow. You can also contact me directly via [email] or [Twitter]. To file a bug, create a [new issue] on GitHub with a short example of how to replicate the issue. ## Documentation The documentation is provided [here]. ## Contribution to Documentation Documentation is built using `Sphinx`. You can install it by pip install -r requirements.txt For building `sphinx-apidoc` from scratch you need to set PYTHONPATH to `voluptuous/voluptuous` repository. The documentation is provided [here.] ## Changelog See [CHANGELOG.md]. ## Why use Voluptuous over another validation library? **Validators are simple callables:** No need to subclass anything, just use a function. **Errors are simple exceptions:** A validator can just `raise Invalid(msg)` and expect the user to get useful messages. **Schemas are basic Python data structures:** Should your data be a dictionary of integer keys to strings? `{int: str}` does what you expect. List of integers, floats or strings? `[int, float, str]`. **Designed from the ground up for validating more than just forms:** Nested data structures are treated in the same way as any other type. Need a list of dictionaries? `[{}]` **Consistency:** Types in the schema are checked as types. Values are compared as values. Callables are called to validate. Simple. ## Show me an example Twitter's [user search API] accepts query URLs like: ```bash $ curl 'https://api.twitter.com/1.1/users/search.json?q=python&per_page=20&page=1' ``` To validate this we might use a schema like: ```pycon
Configuration Switches (platform-specific settings discarded)
PY312 ON Build using Python 3.12 PY313 OFF Build using Python 3.13
Package Dependencies by Type
Build (only) python312:dev:std
python-pip:single:v12
autoselect-python:single:std
Build and Runtime python312:primary:std
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main mirror://PYPIWHL/db/a8/8f9cc6749331186e6a513bfe3745454f81d25f6e34c6024f88f80c71ed28
Distribution File Information
016348bc7788a9af9520b1764ebd4de0df41fe2138ebe9e06fa036bf86a65566 31349 voluptuous-0.15.2-py3-none-any.whl
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