AIM-PIbd-32-Kurbanova-A-A/aimenv/Lib/site-packages/traitlets-5.14.3.dist-info/METADATA

Metadata-Version: 2.3
Name: traitlets
Version: 5.14.3
Summary: Traitlets Python configuration system
Project-URL: Homepage, https://github.com/ipython/traitlets
Project-URL: Documentation, https://traitlets.readthedocs.io
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Keywords: Interactive,Interpreter,Shell,Web
Classifier: Framework :: IPython
Classifier: Framework :: Jupyter
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Classifier: Intended Audience :: Science/Research
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Description-Content-Type: text/markdown

# Traitlets

[![Tests](https://github.com/ipython/traitlets/actions/workflows/tests.yml/badge.svg)](https://github.com/ipython/traitlets/actions/workflows/tests.yml)
[![Documentation Status](https://readthedocs.org/projects/traitlets/badge/?version=latest)](https://traitlets.readthedocs.io/en/latest/?badge=latest)
[![Tidelift](https://tidelift.com/subscription/pkg/pypi-traitlets)](https://tidelift.com/badges/package/pypi/traitlets)

|               |                                      |
| ------------- | ------------------------------------ |
| **home**      | https://github.com/ipython/traitlets |
| **pypi-repo** | https://pypi.org/project/traitlets/  |
| **docs**      | https://traitlets.readthedocs.io/    |
| **license**   | Modified BSD License                 |

Traitlets is a pure Python library enabling:

- the enforcement of strong typing for attributes of Python objects
  (typed attributes are called _"traits"_);
- dynamically calculated default values;
- automatic validation and coercion of trait attributes when attempting a
  change;
- registering for receiving notifications when trait values change;
- reading configuring values from files or from command line
  arguments - a distinct layer on top of traitlets, so you may use
  traitlets without the configuration machinery.

Its implementation relies on the [descriptor](https://docs.python.org/howto/descriptor.html)
pattern, and it is a lightweight pure-python alternative of the
[_traits_ library](https://docs.enthought.com/traits/).

Traitlets powers the configuration system of IPython and Jupyter
and the declarative API of IPython interactive widgets.

## Installation

For a local installation, make sure you have
[pip installed](https://pip.pypa.io/en/stable/installing/) and run:

```bash
pip install traitlets
```

For a **development installation**, clone this repository, change into the
`traitlets` root directory, and run pip:

```bash
git clone https://github.com/ipython/traitlets.git
cd traitlets
pip install -e .
```

## Running the tests

```bash
pip install "traitlets[test]"
py.test traitlets
```

## Code Styling

`traitlets` has adopted automatic code formatting so you shouldn't
need to worry too much about your code style.
As long as your code is valid,
the pre-commit hook should take care of how it should look.

To install `pre-commit` locally, run the following::

```
pip install pre-commit
pre-commit install
```

You can invoke the pre-commit hook by hand at any time with::

```
pre-commit run
```

which should run any autoformatting on your code
and tell you about any errors it couldn't fix automatically.
You may also install [black integration](https://github.com/psf/black#editor-integration)
into your text editor to format code automatically.

If you have already committed files before setting up the pre-commit
hook with `pre-commit install`, you can fix everything up using
`pre-commit run --all-files`. You need to make the fixing commit
yourself after that.

Some of the hooks only run on CI by default, but you can invoke them by
running with the `--hook-stage manual` argument.

## Usage

Any class with trait attributes must inherit from `HasTraits`.
For the list of available trait types and their properties, see the
[Trait Types](https://traitlets.readthedocs.io/en/latest/trait_types.html)
section of the documentation.

### Dynamic default values

To calculate a default value dynamically, decorate a method of your class with
`@default({traitname})`. This method will be called on the instance, and
should return the default value. In this example, the `_username_default`
method is decorated with `@default('username')`:

```Python
import getpass
from traitlets import HasTraits, Unicode, default

class Identity(HasTraits):
    username = Unicode()

    @default('username')
    def _username_default(self):
        return getpass.getuser()
```

### Callbacks when a trait attribute changes

When a trait changes, an application can follow this trait change with
additional actions.

To do something when a trait attribute is changed, decorate a method with
[`traitlets.observe()`](https://traitlets.readthedocs.io/en/latest/api.html?highlight=observe#traitlets.observe).
The method will be called with a single argument, a dictionary which contains
an owner, new value, old value, name of the changed trait, and the event type.

In this example, the `_num_changed` method is decorated with `` @observe(`num`) ``:

```Python
from traitlets import HasTraits, Integer, observe

class TraitletsExample(HasTraits):
    num = Integer(5, help="a number").tag(config=True)

    @observe('num')
    def _num_changed(self, change):
        print("{name} changed from {old} to {new}".format(**change))
```

and is passed the following dictionary when called:

```Python
{
  'owner': object,  # The HasTraits instance
  'new': 6,         # The new value
  'old': 5,         # The old value
  'name': "foo",    # The name of the changed trait
  'type': 'change', # The event type of the notification, usually 'change'
}
```

### Validation and coercion

Each trait type (`Int`, `Unicode`, `Dict` etc.) may have its own validation or
coercion logic. In addition, we can register custom cross-validators
that may depend on the state of other attributes. For example:

```Python
from traitlets import HasTraits, TraitError, Int, Bool, validate

class Parity(HasTraits):
    value = Int()
    parity = Int()

    @validate('value')
    def _valid_value(self, proposal):
        if proposal['value'] % 2 != self.parity:
            raise TraitError('value and parity should be consistent')
        return proposal['value']

    @validate('parity')
    def _valid_parity(self, proposal):
        parity = proposal['value']
        if parity not in [0, 1]:
            raise TraitError('parity should be 0 or 1')
        if self.value % 2 != parity:
            raise TraitError('value and parity should be consistent')
        return proposal['value']

parity_check = Parity(value=2)

# Changing required parity and value together while holding cross validation
with parity_check.hold_trait_notifications():
    parity_check.value = 1
    parity_check.parity = 1
```

However, we **recommend** that custom cross-validators don't modify the state
of the HasTraits instance.

## About the IPython Development Team

The IPython Development Team is the set of all contributors to the IPython project.
This includes all of the IPython subprojects.

The core team that coordinates development on GitHub can be found here:
https://github.com/jupyter/.

## Our Copyright Policy

IPython uses a shared copyright model. Each contributor maintains copyright
over their contributions to IPython. But, it is important to note that these
contributions are typically only changes to the repositories. Thus, the IPython
source code, in its entirety is not the copyright of any single person or
institution. Instead, it is the collective copyright of the entire IPython
Development Team. If individual contributors want to maintain a record of what
changes/contributions they have specific copyright on, they should indicate
their copyright in the commit message of the change, when they commit the
change to one of the IPython repositories.

With this in mind, the following banner should be used in any source code file
to indicate the copyright and license terms:

```
# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.
```