semvec/pypi-packages huggingface dataset:
reasy 0.0.9
A tool for quick downloading videos from BT7086
License: MIT

# Reasy

A crawler for BT7086 and fast and simple m3u8 downloader.

## Get Start

Download and install [Python3](https://www.python.org/downloads/), [Aria2](https://aria2.github.io/) and [FFmpeg](https://www.ffmpeg.org/), both of them are the key components for Reasy.

Install Reasy. Sometimes you may use `pip3` instead of `pip`, and it also works for `python3` which will be used later on. When you got `reasy version 0.0.4`, it means installation is succeed.

```bash
pip install reasy
reasy -v
```

Download templates from [GitHub](https://github.com/dekofejld/reasy), including two files: `config.yaml.example` and `aria2.conf.example`.

Set environment variable for Reasy.

- REASY_CONFIG: The path for config of Reasy. Please move `config.yaml.example` to the config folder and rename it to `config.yaml`. To make clear, I presume config path you use is `/.reasy/config.yaml`.

```bash
# set env on Linux
export REASY_CONFIG=/.reasy/config.yaml
```

Modify config.yaml to meet your requirements. Here we go:

- aria2.config: This is for Aria2, a light-weight downloader. You can use `aria2.conf.example` as template.
- aria2.download_path: The path your videos are saved.
- session.enabled: A mechanism to prevent from download repeated. Unless you know what it is, you should enable it as default.
- session.path: The path for session file. You just need to create a empty file by `touch /.reasy/reasy.session`.

For now, you can run and enjoy it.

```bash
reasy run
# for more usage
reasy run --help
```

## Not Implement Yet

- Get more data if the number of videos not meet the requirements of `maximum_download_num` defined in the `config.yaml` (v0.1.0)
- Multi-threading load m3u8 (v0.1.0)
- Session management by CLI Tool (v0.1.0)
- Web UI to control remotely (v1.0.0)
zuid 0.1.1
Random prefixed ids
License: MIT
Requires Python: >=3.5,<4.0

# zuid

Generates URL-safe random ids with a prefix and optional timestamp.


## Installing

```
pip install zuid
```

## Usage

The `ZUID` class works as a callable id factory for a given prefix:

```
>>> from zuid import ZUID
>>> generator = ZUID(prefix='user_')
>>> generator()
'user_03QewpfEIpPWUICXdgtvdR'
>>> generator()
'user_1LJSXMoyH6p7VsiL8wwIm1'
```

The factory generates ids that are 22 chars long by default, which in
base 62 corresponds to 131 random bits. For comparison, a v4 UUID has
122 random bits. It can be changed with the `length` parameter:

```
>>> generator = ZUID(prefix='user_', length=27)
>>> generator()
'user_X5fSIStIKpYWcg07nqEfPbMvmME'
```

With the `timestamped` parameter, the factory uses the current nanoseconds since epoch as the first 8 bytes, preserving the order when sorting by id.

```
>>> generator = ZUID(prefix='user_', timestamped=True)
>>> generator()
'user_1qzuvBwgHdQVO2gA4GelYX'
>>> generator()
'user_1qzuvCscVyClzGaqakgvsl'
>>> generator()
'user_1qzuvDb0TuCuIJJON103Of'
>>> generator()
'user_1qzuvES4mTQ7fWykywvjNb

```
german 0.1.0
Preprocess German texts for serious NLP.
License: MIT

# German Preprocessing [![Build Status](https://travis-ci.com/jfilter/german-preprocessing.svg?branch=master)](https://travis-ci.com/jfilter/german-preprocessing) [![PyPI](https://img.shields.io/pypi/v/german.svg)](https://pypi.org/project/german/) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/german.svg)](https://pypi.org/project/german/)

Preprocess German texts to do some serious natural-language processing.

-   [clean texts](https://github.com/jfilter/clean-text)
-   remove stopwords (as defined by [spaCy](https://github.com/explosion/spaCy/blob/master/spacy/lang/de/stop_words.py))
-   [lemmatize](https://github.com/jfilter/german-lemmatizer)
-   lower-case, and remove all punctions, digits are replaced with "0"

## Installation

`pip install german`

## Usage

```python
from german import preprocess

preprocess(['Johannes war einer von vielen guten Schülern.', 'Julia trinkt gern Tee.'], remove_stop=True)
# ['johannes gut schüler', 'julia trinken tee']
```

## License

MIT.

## Sponsoring

This work was created as part of a [project](https://github.com/jfilter/ptf) that was funded by the German [Federal Ministry of Education and Research](https://www.bmbf.de/en/index.html).

<img src="./bmbf_funded.svg">