py-data-analysis/.venv/lib/python3.12/site-packages/attrs-25.4.0.dist-info/METADATA

Metadata-Version: 2.4
Name: attrs
Version: 25.4.0
Summary: Classes Without Boilerplate
Project-URL: Documentation, https://www.attrs.org/
Project-URL: Changelog, https://www.attrs.org/en/stable/changelog.html
Project-URL: GitHub, https://github.com/python-attrs/attrs
Project-URL: Funding, https://github.com/sponsors/hynek
Project-URL: Tidelift, https://tidelift.com/subscription/pkg/pypi-attrs?utm_source=pypi-attrs&utm_medium=pypi
Author-email: Hynek Schlawack <hs@ox.cx>
License-Expression: MIT
License-File: LICENSE
Keywords: attribute,boilerplate,class
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Typing :: Typed
Requires-Python: >=3.9
Description-Content-Type: text/markdown

<p align="center">
  <a href="https://www.attrs.org/">
    <img src="https://raw.githubusercontent.com/python-attrs/attrs/main/docs/_static/attrs_logo.svg" width="35%" alt="attrs" />
  </a>
</p>


*attrs* is the Python package that will bring back the **joy** of **writing classes** by relieving you from the drudgery of implementing object protocols (aka [dunder methods](https://www.attrs.org/en/latest/glossary.html#term-dunder-methods)).
Trusted by NASA for [Mars missions since 2020](https://github.com/readme/featured/nasa-ingenuity-helicopter)!

Its main goal is to help you to write **concise** and **correct** software without slowing down your code.


## Sponsors

*attrs* would not be possible without our [amazing sponsors](https://github.com/sponsors/hynek).
Especially those generously supporting us at the *The Organization* tier and higher:

<!-- sponsor-break-begin -->

<p align="center">

<!-- [[[cog
import pathlib, tomllib

for sponsor in tomllib.loads(pathlib.Path("pyproject.toml").read_text())["tool"]["sponcon"]["sponsors"]:
      print(f'<a href="{sponsor["url"]}"><img title="{sponsor["title"]}" src="https://www.attrs.org/en/25.4.0/_static/sponsors/{sponsor["img"]}" width="190" /></a>')
]]] -->
<a href="https://www.variomedia.de/"><img title="Variomedia AG" src="https://www.attrs.org/en/25.4.0/_static/sponsors/Variomedia.svg" width="190" /></a>
<a href="https://tidelift.com/?utm_source=lifter&utm_medium=referral&utm_campaign=hynek"><img title="Tidelift" src="https://www.attrs.org/en/25.4.0/_static/sponsors/Tidelift.svg" width="190" /></a>
<a href="https://privacy-solutions.org/"><img title="Privacy Solutions" src="https://www.attrs.org/en/25.4.0/_static/sponsors/Privacy-Solutions.svg" width="190" /></a>
<a href="https://filepreviews.io/"><img title="FilePreviews" src="https://www.attrs.org/en/25.4.0/_static/sponsors/FilePreviews.svg" width="190" /></a>
<a href="https://polar.sh/"><img title="Polar" src="https://www.attrs.org/en/25.4.0/_static/sponsors/Polar.svg" width="190" /></a>
<!-- [[[end]]] -->

</p>

<!-- sponsor-break-end -->

<p align="center">
   <strong>Please consider <a href="https://github.com/sponsors/hynek">joining them</a> to help make <em>attrs</em>’s maintenance more sustainable!</strong>
</p>

<!-- teaser-end -->

## Example

*attrs* gives you a class decorator and a way to declaratively define the attributes on that class:

<!-- code-begin -->

```pycon
>>> from attrs import asdict, define, make_class, Factory

>>> @define
... class SomeClass:
...     a_number: int = 42
...     list_of_numbers: list[int] = Factory(list)
...
...     def hard_math(self, another_number):
...         return self.a_number + sum(self.list_of_numbers) * another_number


>>> sc = SomeClass(1, [1, 2, 3])
>>> sc
SomeClass(a_number=1, list_of_numbers=[1, 2, 3])

>>> sc.hard_math(3)
19
>>> sc == SomeClass(1, [1, 2, 3])
True
>>> sc != SomeClass(2, [3, 2, 1])
True

>>> asdict(sc)
{'a_number': 1, 'list_of_numbers': [1, 2, 3]}

>>> SomeClass()
SomeClass(a_number=42, list_of_numbers=[])

>>> C = make_class("C", ["a", "b"])
>>> C("foo", "bar")
C(a='foo', b='bar')
```

After *declaring* your attributes, *attrs* gives you:

- a concise and explicit overview of the class's attributes,
- a nice human-readable `__repr__`,
- equality-checking methods,
- an initializer,
- and much more,

*without* writing dull boilerplate code again and again and *without* runtime performance penalties.

---

This example uses *attrs*'s modern APIs that have been introduced in version 20.1.0, and the *attrs* package import name that has been added in version 21.3.0.
The classic APIs (`@attr.s`, `attr.ib`, plus their serious-business aliases) and the `attr` package import name will remain **indefinitely**.

Check out [*On The Core API Names*](https://www.attrs.org/en/latest/names.html) for an in-depth explanation!


### Hate Type Annotations!?

No problem!
Types are entirely **optional** with *attrs*.
Simply assign `attrs.field()` to the attributes instead of annotating them with types:

```python
from attrs import define, field

@define
class SomeClass:
    a_number = field(default=42)
    list_of_numbers = field(factory=list)
```


## Data Classes

On the tin, *attrs* might remind you of `dataclasses` (and indeed, `dataclasses` [are a descendant](https://hynek.me/articles/import-attrs/) of *attrs*).
In practice it does a lot more and is more flexible.
For instance, it allows you to define [special handling of NumPy arrays for equality checks](https://www.attrs.org/en/stable/comparison.html#customization), allows more ways to [plug into the initialization process](https://www.attrs.org/en/stable/init.html#hooking-yourself-into-initialization), has a replacement for `__init_subclass__`, and allows for stepping through the generated methods using a debugger.

For more details, please refer to our [comparison page](https://www.attrs.org/en/stable/why.html#data-classes), but generally speaking, we are more likely to commit crimes against nature to make things work that one would expect to work, but that are quite complicated in practice.


## Project Information

- [**Changelog**](https://www.attrs.org/en/stable/changelog.html)
- [**Documentation**](https://www.attrs.org/)
- [**PyPI**](https://pypi.org/project/attrs/)
- [**Source Code**](https://github.com/python-attrs/attrs)
- [**Contributing**](https://github.com/python-attrs/attrs/blob/main/.github/CONTRIBUTING.md)
- [**Third-party Extensions**](https://github.com/python-attrs/attrs/wiki/Extensions-to-attrs)
- **Get Help**: use the `python-attrs` tag on [Stack Overflow](https://stackoverflow.com/questions/tagged/python-attrs)


### *attrs* for Enterprise

Available as part of the [Tidelift Subscription](https://tidelift.com/?utm_source=lifter&utm_medium=referral&utm_campaign=hynek).

The maintainers of *attrs* and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source packages you use to build your applications.
Save time, reduce risk, and improve code health, while paying the maintainers of the exact packages you use.

## Release Information

### Backwards-incompatible Changes

- Class-level `kw_only=True` behavior is now consistent with `dataclasses`.

  Previously, a class that sets `kw_only=True` makes all attributes keyword-only, including those from base classes.
  If an attribute sets `kw_only=False`, that setting is ignored, and it is still made keyword-only.

  Now, only the attributes defined in that class that doesn't explicitly set `kw_only=False` are made keyword-only.

  This shouldn't be a problem for most users, unless you have a pattern like this:

  ```python
  @attrs.define(kw_only=True)
  class Base:
      a: int
      b: int = attrs.field(default=1, kw_only=False)

  @attrs.define
  class Subclass(Base):
      c: int
  ```

  Here, we have a `kw_only=True` *attrs* class (`Base`) with an attribute that sets `kw_only=False` and has a default (`Base.b`), and then create a subclass (`Subclass`) with required arguments (`Subclass.c`).
  Previously this would work, since it would make `Base.b` keyword-only, but now this fails since `Base.b` is positional, and we have a required positional argument (`Subclass.c`) following another argument with defaults.
  [#1457](https://github.com/python-attrs/attrs/issues/1457)


### Changes

- Values passed to the `__init__()` method of `attrs` classes are now correctly passed to `__attrs_pre_init__()` instead of their default values (in cases where *kw_only* was not specified).
  [#1427](https://github.com/python-attrs/attrs/issues/1427)
- Added support for Python 3.14 and [PEP 749](https://peps.python.org/pep-0749/).
  [#1446](https://github.com/python-attrs/attrs/issues/1446),
  [#1451](https://github.com/python-attrs/attrs/issues/1451)
- `attrs.validators.deep_mapping()` now allows to leave out either *key_validator* xor *value_validator*.
  [#1448](https://github.com/python-attrs/attrs/issues/1448)
- `attrs.validators.deep_iterator()` and `attrs.validators.deep_mapping()` now accept lists and tuples for all validators and wrap them into a `attrs.validators.and_()`.
  [#1449](https://github.com/python-attrs/attrs/issues/1449)
- Added a new **experimental** way to inspect classes:

  `attrs.inspect(cls)` returns the _effective_ class-wide parameters that were used by *attrs* to construct the class.

  The returned class is the same data structure that *attrs* uses internally to decide how to construct the final class.
  [#1454](https://github.com/python-attrs/attrs/issues/1454)
- Fixed annotations for `attrs.field(converter=...)`.
  Previously, a `tuple` of converters was only accepted if it had exactly one element.
  [#1461](https://github.com/python-attrs/attrs/issues/1461)
- The performance of `attrs.asdict()` has been improved by 45–260%.
  [#1463](https://github.com/python-attrs/attrs/issues/1463)
- The performance of `attrs.astuple()` has been improved by 49–270%.
  [#1469](https://github.com/python-attrs/attrs/issues/1469)
- The type annotation for `attrs.validators.or_()` now allows for different types of validators.

  This was only an issue on Pyright.
  [#1474](https://github.com/python-attrs/attrs/issues/1474)



---

[Full changelog →](https://www.attrs.org/en/stable/changelog.html)