python-cattrs
Port variant py39
Summary Composable complex class support for attrs (3.9)
Package version 22.2.0
Homepage https://github.com/python-attrs/cattrs
Keywords python
Maintainer Python Automaton
License Not yet specified
Other variants py310
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Last modified 04 OCT 2022, 12:01:25 UTC
Port created 03 JAN 2020, 01:03:23 UTC
Subpackage Descriptions
single ====== cattrs ====== :alt: Documentation Status :alt: Supported Python versions ---- cattrs is an open source Python library for structuring and unstructuring data. cattrs works best with attrs classes, dataclasses and the usual Python collections, but other kinds of classes are supported by manually registering converters. Python has a rich set of powerful, easy to use, built-in data types like dictionaries, lists and tuples. These data types are also the lingua franca of most data serialization libraries, for formats like json, msgpack, yaml or toml. Data types like this, and mappings like dict s in particular, represent unstructured data. Your data is, in all likelihood, structured: not all combinations of field names or values are valid inputs to your programs. In Python, structured data is better represented with classes and enumerations. attrs is an excellent library for declaratively describing the structure of your data, and validating it. When you're handed unstructured data (by your network, file system, database...), cattrs helps to convert this data into structured data. When you have to convert your structured data into data types other libraries can handle, cattrs turns your classes and enumerations into dictionaries, integers and strings. Here's a simple taste. The list containing a float, an int and a string gets converted into a tuple of three ints. .. code-block:: pycon >>> import cattrs >>> >>> cattrs.structure([1.0, 2, "3"], tuple[int, int, int]) (1, 2, 3) cattrs works well with attrs classes out of the box. .. code-block:: pycon >>> from attrs import frozen >>> import cattrs >>> >>> @frozen # It works with non-frozen classes too. ... class C: ... a: int ... b: str ... >>> instance = C(1, 'a') >>> cattrs.unstructure(instance) {'a': 1, 'b': 'a'} >>> cattrs.structure({'a': 1, 'b': 'a'}, C) C(a=1, b='a') Here's a much more complex example, involving attrs classes with type metadata. .. code-block:: pycon >>> from enum import unique, Enum >>> from typing import Optional, Sequence, Union >>> from cattrs import structure, unstructure >>> from attrs import define, field >>> >>> @unique ... class CatBreed(Enum): ... SIAMESE = "siamese" ... MAINE_COON = "maine_coon" ... SACRED_BIRMAN = "birman" ... >>> @define ... class Cat: ... breed: CatBreed ... names: Sequence[str] ... >>> @define ... class DogMicrochip: ... chip_id = field() # Type annotations are optional, but recommended ... time_chipped: float = field() ... >>> @define ... class Dog: ... cuteness: int ... chip: Optional[DogMicrochip] = None ... >>> p = unstructure([Dog(cuteness=1, chip=DogMicrochip(chip_id=1, time_chipped=10.0)), ... Cat(breed=CatBreed.MAINE_COON, names=('Fluffly', 'Fluffer'))])
Configuration Switches (platform-specific settings discarded)
PY310 OFF Build using Python 3.10 PY39 ON Build using Python 3.9
Package Dependencies by Type
Build (only) python-pip:single:py39
autoselect-python:single:standard
Build and Runtime python39:single:standard
Runtime (only) python-attrs:single:py39
python-exceptiongroup:single:py39
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main mirror://PYPIWHL/43/3b/1d34fc4449174dfd2bc5ad7047a23edb6558b2e4b5a41b25a8ad6655c6c7
Distribution File Information
bc12b1f0d000b9f9bee83335887d532a1d3e99a833d1bf0882151c97d3e68c21 35673 cattrs-22.2.0-py3-none-any.whl
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