semvec/pypi-packages huggingface dataset:
conductor-celery 0.0.3a0
This is a template repository for Python projects that use Poetry for their dependency management.
Requires Python: >=3.8,<4.0

# conductor-celery

This project is a test!!! Do not use it

[![Release](https://img.shields.io/github/v/release/tomas_correa/conductor-celery)](https://img.shields.io/github/v/release/tomas_correa/conductor-celery)
[![Build status](https://img.shields.io/github/actions/workflow/status/tomas_correa/conductor-celery/main.yml?branch=main)](https://github.com/tomas_correa/conductor-celery/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/tomas_correa/conductor-celery/branch/main/graph/badge.svg)](https://codecov.io/gh/tomas_correa/conductor-celery)
[![Commit activity](https://img.shields.io/github/commit-activity/m/tomas_correa/conductor-celery)](https://img.shields.io/github/commit-activity/m/tomas_correa/conductor-celery)
[![License](https://img.shields.io/github/license/tomas_correa/conductor-celery)](https://img.shields.io/github/license/tomas_correa/conductor-celery)

This is a template repository for Python projects that use Poetry for their dependency management.

- **Github repository**: <https://github.com/tomas_correa/conductor-celery/>
- **Documentation** <https://tomas_correa.github.io/conductor-celery/>

## Getting started with your project

First, create a repository on GitHub with the same name as this project, and then run the following commands:

``` bash
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:tomas_correa/conductor-celery.git
git push -u origin main
```

Finally, install the environment and the pre-commit hooks with 

```bash
make install
```

You are now ready to start development on your project! The CI/CD
pipeline will be triggered when you open a pull request, merge to main,
or when you create a new release.

To finalize the set-up for publishing to PyPi or Artifactory, see
[here](https://fpgmaas.github.io/cookiecutter-poetry/features/publishing/#set-up-for-pypi).
For activating the automatic documentation with MkDocs, see
[here](https://fpgmaas.github.io/cookiecutter-poetry/features/mkdocs/#enabling-the-documentation-on-github).
To enable the code coverage reports, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/codecov/).

## Releasing a new version

- Create an API Token on [Pypi](https://pypi.org/).
- Add the API Token to your projects secrets with the name `PYPI_TOKEN` by visiting 
[this page](https://github.com/tomas_correa/conductor-celery/settings/secrets/actions/new).
- Create a [new release](https://github.com/tomas_correa/conductor-celery/releases/new) on Github. 
Create a new tag in the form ``*.*.*``.

For more details, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/cicd/#how-to-trigger-a-release).

---

Repository initiated with [fpgmaas/cookiecutter-poetry](https://github.com/fpgmaas/cookiecutter-poetry).
autotypedict 1.0.0
Dictionary-like class that automatically typecasts string-like values to standard types
Requires Python: >=3.8

# autotypedict

Dictionary-like class that automatically typecasts string-like values to standard types.

## Installation

### Using pip

```shell
python -m pip install -U autotypedict
```

## Usage

### Importing the class

```py
from autotypedict import AutoTypeDict
```

### Examples

```python
>>> d = {"foo": {"baz": "42"}, "bar": {"baz": "n/a", "qux": "true"}}
>>> AutoTypeDict(d)  # typecast every value
{'foo': {'baz': 42}, 'bar': {'baz': None, 'qux': True}}
>>> AutoTypeDict(d, ignored_keys=("baz",))  # ignore "baz"
{'foo': {'baz': '42'}, 'bar': {'baz': 'n/a', 'qux': True}}
>>> AutoTypeDict(d, ignored_keys=("bar.baz",))  # ignore d["bar"]["baz"]
{'foo': {'baz': 42}, 'bar': {'baz': 'n/a', 'qux': True}}
>>> td = AutoTypeDict()
>>> td.data = d  # updating data attribute to ignore typecasting
>>> td
{'foo': {'baz': '42'}, 'bar': {'baz': 'n/a', 'qux': 'true'}}
```

## Caveats

Values are only typecasted when the `AutoTypeDict` instance is updated directly, so avoid using type-specific operations on mutable objects within the dictionary (e.g. `list.append`, `dict.update`).

If using these methods is unavoidable, call the `.refresh()` instance method to re-process the dictionary.

Alternatives to common type operations:

Operation | Non-typecasted | Typecasted
:--- | :--- | :---
Append to list | `td["list"].append(v)` | `td["list"] += [v]`
Update dict | `td["dict"].update({k: v})` | `td["dict"][k] = v`
Merge dict | `td["dict"].update(other_dict)` | `td["dict"] \|= merge_dict` <sup>[1]</sup>

[1]: Python 3.9 or later