semvec/pypi-packages huggingface dataset:
hjpmatch 0.0.1
A CSV driven solver for the resident/hospital style matching markets
Requires Python: >=3.7

[![Build Status](https://travis-ci.org/klittlepage/hgpmatch.svg?branch=master)](https://travis-ci.org/klittlepage/hgpmatch)
[![Documentation Status](https://readthedocs.org/projects/hgpmatch/badge/?version=latest)](https://hgpmatch.readthedocs.io/en/latest/?badge=latest)
[![Coverage Status](https://coveralls.io/repos/github/klittlepage/hgpmatch/badge.svg?branch=master)](https://coveralls.io/github/klittlepage/hgpmatch?branch=master)

# Project Documentation

Documentation on `hgpmatch` lives [here](https://hgpmatch.readthedocs.io/).
knowledge-exporter 1.1.2
Export content from knowledge plaform.
Requires Python: >=3.6
Keywords: pdf,knowledge,download

# Knowledge Exporter

Export your purchased content from paid knowledge providers, supported format including column, video, audio, etc.

#### How to install

pip install knowledge-exporter

#### How to use

```
Usage: knowledge-exporter [OPTIONS] COLUMN_ID

  📑 -> 📚 导出知识付费平台内容

Options:
  -t, --target [GeekTime]         知识付费平台  [required]
  -u, --username TEXT             手机号/用户名  [required]
  -p, --password TEXT             密码  [required]
  --merge / --no-merge            合并专栏文章
  --help                          Show this message and exit.
```


#### PS

导出已购买的知识付费产品，包括专栏、视频、音频等。

项目还很早期，欢迎 Issue / Pull Request / Fork。

支持平台：

- [x] 极客时间
- [ ] 慕课网
- [ ] 得到
- [ ] 拉钩教育
- [ ] 其他

支持格式：

- [x] PDF（方便iPad查阅、批注）
- [ ] 视频合集
pytpixel 0.1.3
A python wrapper for Hypixel's API
Requires Python: >=3.6

**Hypixel API Wrapper**

This is a python package for the Hypixel API, last updated **2020-09-20**.
It is important you install this from pip as the file is more organized and easier to understand.

Features:
☑ Player Stats
☑ Guild Stats
☑ Watchdog/Staff Stats
☑ Skyblock Stats (In progress)
☑ Boosters Stats

Examples:
```
import pypixel

user = pypixel.player.User()
guild = pypixel.guild.Guild()
booster = pypixel.boosters.Boosters()
staff = pypixel.bans.Staff()
watchdog = pypixel.bans.Watchdog()
skyblockprof = pypixel.skyblock.SkyblockProfile()
```
rtorrent-migrate 1.0.0
rTorrent migration utility
Requires Python: >=3.6
Keywords: bittorrent rtorrent

# rtorrent-migrate
rtorrent-migrate is a command-line utility used to bulk-convert your data and/or session directory of torrents in rTorrent

It also includes a class that can be used in Python scripts

Usage documentation and examples are available [here](https://adralioh.gitlab.io/rtorrent-migrate)

## Requirements
- [Python 3.6+](https://www.python.org/)
- [benparse](https://gitlab.com/adralioh/benparse)

## Installation
Install from PyPI:
```shell
pip3 install rtorrent-migrate
```

Install from source:
```shell
git clone https://gitlab.com/adralioh/rtorrent-migrate.git
pip3 install ./rtorrent-migrate
```

If you don't want to install, you can also run the module directly:
```shell
# Run from within the git repo
python3 -m rtorrent_migrate --help
```

## Tests
Tests are run using the built-in `unittest` module, and [Coverage.py](https://coverage.readthedocs.io/) is used to measure code coverage

Run tests without measuring coverage:
```shell
python3 -m unittest discover -s tests -t .
```

Run tests and measure coverage:
```shell
coverage run -m unittest discover -s tests -t .
```

View the results:
```shell
coverage report
```

Generate a detailed report, outputted to `./htmlcov`:
```shell
coverage html
```

## Building documentation
Sphinx is used to build documentation

Build requirements:
- [Sphinx](https://www.sphinx-doc.org/)
- [sphinx-argparse](https://github.com/alex-rudakov/sphinx-argparse)

How to build:
```shell
cd docs
make html
```
focmech3d 0.0.1
Package for displaying 3D focal mechanisms
Requires Python: >=3.6

# 3DFocal_Mechanism
This python script serves the purpose of plotting 3D Focal Mechanisms using matplotlib and starting from a database where Focal Mechanism Solutions (FMS) attributes are compiled.

You should have an Excel list or ASCII text file with following information per row:
Latitude (°-coordinate degrees), Longitude (°-coordinate degrees), Depth (km), Strike1 (°-arcdegree), Dip1 (°-arcdegree), Rake1 (°-arcdegree), Strike2 (°-arcdegree), Dip2 (°-arcdegree), Rake2 (°-arcdegree), Moment magnitude (Mw), Scalar Moment (N.m), Moment tensor parameters such as Mnn, Mee, Mdd, Mne, Mnd and Med (N.m [x 1+ePOWER]).

After this you can insert yout FMS list to be read by the python script using pandas dataframe function or any other method of your choice. The beachball list must be organized in this structure*: beachball list=[[R1, C1, NP1],[R2, C2, NP2],...,[Ri, Ci, NPi]] from i = 1 to n number of FMS, where Ri=Mw, Ci=[Xi,Yi,Zi], NPi=[Si, Di, Ri].

*Note: It is not necessary to build the list with both nodal planes (NP) for each beachball as the programm plots the auxiliary plane given that this is always perpendicular to the one inserted by you.

You are set to go, run the script and verify that FMS are plotted with size relative to their magnitude, right polarity and accordingly to their position in space.

Please note that this package is in very early development and is subject to substantial change as we refactor it.