semvec/pypi-packages huggingface dataset:
pymobility 0.0.8
Python mobility library
Requires Python: >=3.6

# pymobility
###### Work done by South Asia Poverty Team, The World Bank

_pymobility_ is the Python package built on top of PySpark API, which faciliates big data processing. This package has
several sub-packages and modules for quantifying mobility and migration from raw GPS data. The package takes _delta_
formatted geo-tagged raw dataset and generates various datasets like Origin Destination matrix and net migration figures,
and various statistics like average records in a time-period, average devices registered in a time period, etc.

_pymobility_ has three sub-packages: _odm_, _stm_, and _eda_. _odm_ is used for generating origin-destination figures.
_stm_ helps to quantify short term migration depending on whatever definition we use for short term migrants. The _stm_
sub-package is made modular, and there are a number of parameters which can be set according to the definition of short
term migrant used. Another sub-package, _eda_, helps to do exploratory data analysis. We can get statistics like average
devices in some time-period, or average records in some time-period, etc. More documentation about the individual
sub-packages is done on the sub-package README file itself.

## Dependencies
As the package is built on top of _PySpark API_, _Python_ API for _Spark_ (or _PySpark API_) should be installed. The code is
well tested on _Python 3.6_, so users are encouraged to have _Python 3.6+_ version.

Other _Python_ packages used herein are _Pandas_.

## Installation

Both _pyspark_ and _pandas_ can be installed using _pip_. The commands for them are given below:

```
pip install pandas
pip install pyspark
```
More details about _pyspark_ can be found [here](https://github.com/apache/spark/tree/master/python).

## Usage
This package can be used for quantifying mobility and migration from geo-taggged raw _delta_ files. It facilitates
following features.
1. Origin Destination Matrix (OD matrix): Details about use of this library for quantifying origin-destination movement
can be found in the [README.md](mobility/odm/README.md) file inside the _odm_ sub-package itself.
   
2. Short Term Migration: This type of migration is quantified using _stm_ sub-package, which facilitates flexibility in
short term migrants' definition with the help of different parameters like away time period required, definition of 
   home, etc.
   
3. Exploratory Data Analysis: The exploratory data analysis can be done using the _eda_ sub-package. Under _eda_
commuter aggregates and mobility summary can be quantified. Details about its use can be found in the [README.md](mobility/eda/README.md).
kuriyama-lxnet 1.3.0
A framework for OICQ(QQ, made by Tencent) headless client "Mirai".
Requires Python: >=3.7
Keywords: oicq qq qqbot

mirai-python-sdk
================

基于 kuriyama（Python SDK v3）的修改版本

这是什么?
~~~~~~~~~

以 OICQ(QQ) 协议驱动的高性能机器人开发框架
`Mirai <https://github.com/mamoe/mirai>`__ 的 Python 接口, 通过其提供的
``HTTP API`` 与无头客户端 ``Mirai`` 交互.

开始使用
~~~~~~~~

从 Pypi 安装
^^^^^^^^^^^^

.. code:: bash

    pip install kuriyama-lxnet

开始开发
^^^^^^^^

由于 ``python-mirai`` 依赖于 ``mirai`` 提供的 ``mirai-http-api`` 插件,
所以你需要先运行一个 ``mirai-core`` 或是 ``mirai-console``
实例以支撑你的应用运行.

仓库地址: https://github.com/Lxns-Network/mirai-python-sdk

依赖版本
~~~~~~~~

-  mirai-core-all *v2.6.5*\ ：https://github.com/mamoe/mirai
-  mirai-api-http
   *v1.11.0*\ ：https://github.com/project-mirai/mirai-api-http ###
   语音组件 #### 第三方依赖 ffmpeg 环境：https://ffmpeg.org/ ####
   使用方法
   MessageChain：\ ``Voice.fromFileSystem(Path, convert_type="silk")``
   ### 示例 \`\`\`python from mirai import Mirai, Plain, MessageChain,
   Friend, Group, Member, Source, BotInvitedJoinGroupRequestEvent import
   asyncio

app = Mirai( host = "127.0.0.1", port = "8880", authKey = "INITKEY", qq
= "114514", websocket = True )

@app.receiver("FriendMessage") async def \_(app: Mirai, friend: Friend,
message: MessageChain): pass

@app.receiver("GroupMessage") async def \_(app: Mirai, group: Group,
member: Member, message: MessageChain, source: Source): await
app.sendGroupMessage(group, [ Plain(text="收到消息：" +
message.toString()) ], quoteSource=source) return True

@app.receiver("BotInvitedJoinGroupRequestEvent") async def \_(app:
Mirai, event: BotInvitedJoinGroupRequestEvent): await
app.respondRequest(event, 1) # 自动同意入群邀请 return True

@app.receiver("AppInitEvent") async def \_(app: Mirai):
print("应用初始化完成，您可以在此直接获取到 app")

if **name** == "**main**\ ": app.run() \`\`\`

许可证
~~~~~~

我们使用
```GNU AGPLv3`` <https://choosealicense.com/licenses/agpl-3.0/>`__
作为本项目的开源许可证, 而由于原项目
```mirai`` <https://github.com/mamoe/mirai>`__ 同样使用了 ``GNU AGPLv3``
作为开源许可证, 因此你在使用时需要遵守相应的规则.