semvec/pypi-packages huggingface dataset:
autobackuper 1.0.0
Automatic tool to backup a file to git
Requires Python: >=3.6

# AutoBackuper

Python3 utility for backing up files. Intended use is to automatically back up word or latex files in case of corruption or need to reference an older version of a file.

# Usage

Navigate to the folder where you want git repository to be located and execute: 

`autobackuper FILENAME [poll interval in seconds]`

Utility will init a git repository, after that specifie file will be checked for changes, and automatically commited.

# Requirements

- git must be available in path
typeRacerScraper-pkg-Mohammad-Kheir 0.0.1
A small package that allows users to scrape date from typeracer
Requires Python: >=3.6

# Typeracer scraper

This is a simple example package. You can use
[Github-flavored Markdown](https://github.com/Mohammad-Kheir/TypeRacerScraper)
given a user id and a number of scores it will return list of scores.
om-helper 0.0.4
a common helper
Requires Python: >=3.6

# OmHelper
[python.org](https://packaging.python.org/tutorials/packaging-projects/#packaging-python-projects)

## Dependence
```bash
nothing
```

## Build
```bash
python -m build --no-isolation
```

## Upload
```bash
twine upload --repository-url https://upload.pypi.org/legacy/ dist/*
```

## OM.helper
- md5() -> hash
- rstr() -> random string
- rone() -> random one from list
- ip_to_int() -> convert ip string to int
- int_to_ip() -> convert int ip to ip string
- SingletonBase -> base singleton class
- async_loop() -> return a asyncio loop
- to_async() -> warp a sync func to async func
- SuperDict -> warp dict, more funcions
biome-text 3.3.0
Biome-text is a light-weight open source Natural Language Processing toolbox built with AllenNLP
Requires Python: >=3.6.1

<p align="center">
    <br>
    <img src="https://github.com/recognai/biome-text/raw/master/docs/biome_text_logo_for_readme.png" width="600"/>
    <br>
<p>
<p align="center">
    <a href="https://github.com/recognai/biome-text/actions">
        <img alt="CI" src="https://github.com/recognai/biome-text/workflows/CI/badge.svg?branch=master&event=push">
    </a>
    <a href="https://codecov.io/gh/recognai/biome-text">
        <img src="https://codecov.io/gh/recognai/biome-text/branch/master/graph/badge.svg?token=943463Z6F7"/>
    </a>
    <a href="https://github.com/recognai/biome-text/blob/master/LICENSE.txt">
        <img alt="GitHub" src="https://img.shields.io/github/license/recognai/biome-text.svg?color=blue">
    </a>
    <a href="https://www.recogn.ai/biome-text/">
        <img alt="Documentation" src="https://img.shields.io/website/http/recognai.github.io/biome-text/index.html.svg?down_color=red&down_message=offline&up_message=online">
    </a>
    <a href="https://github.com/recognai/biome-text/releases">
        <img alt="GitHub release" src="https://img.shields.io/github/release/recognai/biome-text.svg">
    </a>
</p>

<h3 align="center">
<p>Natural Language Processing library built with AllenNLP
</h3>

## Quick Links
- [Documentation](https://recognai.github.io/biome-text/)


## Features
* State-of-the-art and not so state-of-the-art models trained with **your own data** with simple workflows.

* **Efficient data reading** for (large) datasets in multiple formats and sources (CSV, Parquet, JSON, etc.).

* **Modular configuration and extensibility** of models, datasets and training runs programmatically or via config files.

* Use via **`cli`** or as plain Python (e.g., inside a Jupyter Notebook)

* **Compatible with AllenNLP**

## Installation

For the installation we recommend setting up a fresh [conda](https://docs.conda.io/en/latest/miniconda.html) environment:

```shell script
conda create -n biome python~=3.7.0 pip>=20.3.0
conda activate biome
```

Once the conda environment is activated, you can install the latest release via pip:

````shell script
pip install -U biome-text
````

After installing *biome.text*, the best way to test your installation is by running the *biome.text* cli command:

```shell script
biome --help
```

## Get started

The best way to see how *biome.text* works is to go through our [first tutorial](https://recognai.github.io/biome-text/master/documentation/tutorials/1-Training_a_text_classifier.html).

Please refer to our [documentation](https://recognai.github.io/biome-text) for more tutorials, detailed user guides and how you can [contribute](https://recognai.github.io/biome-text/master/documentation/community/1-contributing.html) to *biome.text*.

## Licensing

The code in this project is licensed under Apache 2 license.