semvec/pypi-packages huggingface dataset:
gitflow-linter 0.1.0
Checks if GitFlow is respected in a given repository, considering provided rules
License: MIT
Requires Python: >3.8

# gitflow-linter

# About

gitflow-linter is command line tool written in Python. It checks given repository against provided rules to ensure that Gitflow is respected.

What is Gitflow? [Based on Atlassian:](https://www.atlassian.com/git/tutorials/comparing-workflows/gitflow-workflow)

> The Gitflow Workflow defines a **strict branching model** designed around the project release.

> […]

> It assigns **very specific roles to different branches and defines how and when they should interact**. In addition to feature branches, it uses individual branches for preparing, maintaining, and recording releases.

As they wrote: *Gitflow is ideally suited for projects that have a scheduled release cycle*. It means that Gitflow is not always recommended, but when it is, you’d better stick to the rules!

And this is when gitflow-linter can help ;-)

# Quick Start

## Installation

You can install the linter from


* pip

```
pip install gitflow-linter
```


* or the source code

```
git clone [https://github.com/fighterpoul/gitflow_linter.git](https://github.com/fighterpoul/gitflow_linter.git)
cd gitflow_linter
git checkout 0.1.0
python setup.py install
```

## Usages

```
Usage: gitflow-linter [OPTIONS] GIT_DIRECTORY

  Evaluate given repository and check if gitflow is respected

Options:
  -s, --settings FILENAME
  -o, --output [console|json]
  -p, --fetch-prune            Linter will refresh the repo before checking
  -d, --allow-dirty            Linter will ignore the fact that the given repo
                               is considered dirty

  -w, --fatal-warnings         Returned code will be 1 anyway, even if there
                               are warnings but no errors

  -F, --date-from [%Y-%m-%d]   Issues introduced before this date will be
                               ignored.

  -T, --date-to [%Y-%m-%d]     Issues introduced after this date will be
                               ignored.

  --help                       Show this message and exit.
```

Standard use case looks pretty simple:

```
gitflow-linter /path/to/git/repository
```

**WARNING**: URL to a remote is not supported. Passing [https://github.com/fighterpoul/gitflow_linter.git](https://github.com/fighterpoul/gitflow_linter.git) as the argument will fail.

**HINT**: Run `git fetch --prune` before to make the repo clean and clear
**HINT**: In some cases it might be usefull to pull master and develop firstly, before running the linter: `git checkout master && git checkout develop`

# Documentation

A bit more detailed documentation can be found here: [https://fighterpoul.github.io/gitflow_linter/](https://fighterpoul.github.io/gitflow_linter/)
automl-sphinx-theme 0.2.0
AutoML Theme for Sphinx
License: MIT
Requires Python: >=3.7


# AutoML Sphinx Theme

The goal of this repository is to set up a documentation as fast and as clean as possible. In your
source project you only need to install `automl_sphinx_theme` to get all the features you need.
Those include automatic API generation, beautiful theme, numpy docstring interpretation, and
executing/plotting examples.

<b>NO COMPLICATED `.conf` OR SPHINX KNOWLEDGE ARE NECESSARY!</b><br />
:sparkling_heart: You're welcome. :sparkling_heart:


## Installation

- Include `name`, `version`, `author`, `copyright` in `{PACKAGE_NAME}/__init__.py`.
- Copy the `docs` and `examples` directories to your root folder. You don't have to include all
files but you should at least include `docs/conf.py` and `docs/Makefile`.
- In `docs/conf.py` change `src` to `{PACKAGE_NAME}`. Adapt the file if needed.
- Install this repo via pypi:
```
pip install automl_sphinx_theme
```
- You can generate the docs via `make html` inside the docs directory. Have a look inside the
`Makefile` to get more information and commands.

We recommend using the repository `automl_template` which incorporates `automl_sphinx_theme`
automatically.


## Github

The documentation can be pushed automatically to a branch, which is used to display a webpage.
Follow the steps to enable it:
- Copy `.github/workflows/docs.yml` to you root folder.
- Create a new branch called `gh-pages`.
- Go to `settings > pages` and select `gh-pages` as source.


## Version Switching

AutoML Sphinx Theme provides the user to link older versions of documentations (must be done manually!). Specify ``versions`` in the options to enable it. We recommend setting up a Github workflow which automatically pushes the latest tag to the gh-pages. From there, you could link the version directly.


## Customization

- Logo: Add docs/images/logo.png.
- Favicon: Add docs/images/favicon.ico.
iquaflow 1.0.1
Image quality framework
License: MIT
Requires Python: >=3.6

# ![iquaflow](https://github.com/satellogic/iquaflow/raw/main/docs/source/iquaflow_logo_mini.png) <br /> An image quality framework

iquaflow is an image quality framework that aims at providing a set of tools to assess image quality. One of the main contributions of this framework is that it allows to measure quality by using the performance of AI models trained on the images as a proxy. The framework includes ready-to-use metrics such as SNR, MTF, FWHM or RER. It also includes modifiers to alter images (noise, blur, jpeg compression, quantization, etc). In both cases, metrics and modifiers, it is easy to implement new ones. Adittionaly, we include dataset preparation and sanity check tools and all the necessary tools to carry new experiments. 

Usage examples and a detailed description of our framwework can be found within [our documentation](http://iquaflow.readthedocs.io/) on Read the Docs.

## Use cases

[Cookiecutter use case](https://github.com/satellogic/iquaflow-use-case-cookiecutter)

[Mnist use case](https://github.com/satellogic/iquaflow-mnist-use-case)

[Single image super-resolution use case](https://github.com/satellogic/iquaflow-sisr-use-case)

[Multi-frame super-resolution use case](https://github.com/satellogic/iquaflow-mfsr-use-case)

[Oriented-object detection with compression use case](https://github.com/satellogic/iquaflow-dota-obb-use-case)

[Object detection with compression use case](https://github.com/satellogic/iquaflow-dota-use-case)

[Airplane detection use case](https://github.com/satellogic/iquaflow-airport-use-case)

## Installation

You can install iquaflow using pip:

```
pip install iquaflow 
```

Read more complete installation instructions at [our documentation](http://iquaflow.readthedocs.io/).

iquaflow is a pure Python library, and therefore should work on Linux, OS X and Windows
provided that you can install its dependencies. If you find any problem,
[please open an issue](https://github.com/satellogic/iquaflow/issues/new)
and we will take care of it.

## Support

For any questions or suggestions you can use the issues section or reach us at iquaflow@satellogic.com.
key-guard 0.1
A CLI tool to help you guard your sensitive information from being pushed to a remote repository
License: MIT
Requires Python: >=3.8

# key-guard

A python tool that checks to find exposed authentication keys in a project and throws a warning. This prevents the sharing of sensitive data and enforces the use of best practices like saving authentication keys to .env files.

## Features

- [x] Scan Project for exposed keys and passwords
- [x] Add words to guarded_words list to look out for when scanning
- [x] Exclude files from scanning
- [x] Include files for scanning

## Core Requirements

- Click

## Using the CLI tool from Pip

- Install the tool from pip by running:

```bash
pip install key-guard
```

- Quickly Scan your working directory by running:

```bash
key-guard -s
```

- Start by initializing the tool by running:

```bash
key-guard -i
```

- Add the `--help` option the command to check out the available options.

```bash
Usage: key_guard.py [OPTIONS] [PATH]

  CLI tool to scan a project for any key or token

Options:
  -e, --exempt TEXT     exempt a file from scanning by removing from
                        .guard/.fileignore
  -inc, --include TEXT  include a word to scan by adding it to
                        .guard/.fileignore
  -a, --add TEXT        Add new words to .guard/.keyignore
  -i, --init            Initialize the key_guard
  -l, --list            List all the guarded words
  -s, --scan            Scan the project for any key or token
  --help                Show this message and exit.
```

## Setting up the tool for local development

- Clone this repository to your local machine.
- Create a virtual environment for your project and activate it. Install all dependencies from  requirements.txt file.

```bash
python3 -m venv .venv/
source .venv/bin/activate
pip install -r requirements.txt
```
  
- In the root directory of the project, develop the project locally from the setup configuration.
  
```bash
python3 setup.py develop
```

- A `*.egg-info` directory is created in your root directory for you to use the tool locally. Get started by running the following command:

```bash
key-guard -i
```

- the `--help` option the command to check out the available options.

```bash
Usage: key_guard.py [OPTIONS] [PATH]

  CLI tool to scan a project for any key or token
  
Options:
-e, --exempt TEXT     exempt a file from scanning by removing from
                        .guard/.fileignore
  -inc, --include TEXT  include a word to scan by adding it to
                        .guard/.fileignore
  -a, --add TEXT        Add new words to .guard/.keyignore
  -i, --init            Initialize the key_guard
  -l, --list            List all the guarded words
  -s, --scan            Scan the project for any key or token
  --help                Show this message and exit.
```

## Contributing

- Fork this repository to your GitHub account.
- Clone the forked repository to your local machine.
- Create a new branch for the feature you want to work on.
- Make your contributions.
- Push your local branch to your remote repository.
- Open a pull request to the develop branch of this repository.