semvec/pypi-packages huggingface dataset:
pydantic-graphql 1.2.0
non intrusive python graphql client library wrapped around pydantic
Requires Python: <4.0,>=3.12
Keywords: graphql, pydantic, library

# ql
Graphql client library, wrapped around pydantic classes for type validation,
provide simple, safe and pythonic way to query data from a graphql api.

using pydantic for creating python objects from rest api is common, it is easy and 
it has type validation, so why not make it easy also for graphql apis?

features:
  * python objects to valid graphql string
  * http send and recv information
  * scalar query responses

## install
```console
pip3 install pydantic-graphql
```

## documentation 
[https://dsal3389.github.io/ql/](https://dsal3389.github.io/ql/)

# local development

## install
install locally
```sh
git clone git@github.com:dsal3389/ql.git
```

## documentation
make sure you are at the project root
```sh
poetry run mkdocs serve
```

## tests
library uses pytest to validate that behavior is expected
```sh
poetry run pytest
```
post-train 0.0.2a0
Post-training framework
Requires Python: <4.0,>=3.8

# post-train

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

Post-training framework

- **Github repository**: <https://github.com/nlile/post-train/>
- **Documentation** <https://nlile.github.io/post-train/>

## 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 master
git add .
git commit -m "init commit"
git remote add origin git@github.com:nlile/post-train.git
git push -u origin master
```

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 master, 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/nlile/post-train/settings/secrets/actions/new).
- Create a [new release](https://github.com/nlile/post-train/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).