semvec/pypi-packages huggingface dataset:
pp.core2 0.5.3
pp.core
Keywords: Python Produce & Publish

pp.core - Produce & Publish Foundation
======================================

``pp.core`` implements some core foundation functionalities
of the Produce & Publish framework.

Provided functionality
----------------------

- filesystem abstraction
- integration with Dropbox and other cloud file services
- resource base
- resources registry
- filesystem registry  

Internals
---------

This module abstracts Produce & Publish basic functionality in order to make
the core implementation as re-usable as possible.  It uses the ``pyfilesystem``
to abstract arbitrary file operations independent of the underlaying storage
layer. Through this approach we are able to support local filesystems, network
filesystems or cloud storages like Dropbox without changing the application.
All storage subsystems can be accessed using the same API.

Requirements
------------

- Python 2.7 

For using the Dropbox storage API of ``pp.core`` you need to have ``Phantomjs``
installed (the ``phantomjs`` binary must be available in the ``$PATH``. PhantomJS
is required to fake the OAuth process of Dropbox.

Source code
-----------

https://bitbucket.org/ajung/pp.core

Bug tracker
-----------

https://bitbucket.org/ajung/pp.core/issues

Support
-------

Support for Produce & Publish Server is currently only available on a project
basis.

License
-------
``pp.core`` is published under the GNU Public License V2 (GPL 2).

Contact
-------

| Andreas Jung/ZOPYX 
| Hundskapfklinge 33
| D-72074 Tuebingen, Germany
| info@zopyx.com
| www.zopyx.com


CHANGES
=======

0.5.3 (2018/12/13)
------------------
- improved Python 3 compatibility
- various fixes for Python 2/3 compatibility


0.5.1 (2018/12/12)
------------------
- improved Python 3 compatibility


0.5.0 (2018/01/19)
------------------
- forked from pp.core
- switched to fs>2
monkeyrun 0.0.6
MonkeyRunnerTestCase

README
====

- 待完成

适配window和mac系统 > 已完成

对接接口，上传数据 

对接GUI

- 功能

对APP进行滑动点击操作后，收集应用的错误日志及性能数据（cpu,memery）

- 安装

```shell
pip install monkeyrun
```

- 执行

```python
from monkeyrun import run

run.run(device=devices, fpath=fpath, scheme=scheme, activity=activity, m=5)
```

- 参数解释

```markdown
    :param device: the devices of android 设备token
    :param fpath: the path of apk package apk包远程下载地址
    :param scheme: the scheme of your business line scheme地址
    :param activity: the activity of you scheme scheme对应的activity名
    :param d: day 日
    :param h: hour 时
    :param m: minus 分
    :param s: second 秒
```

- APK

将apk文件下载到执行目录，执行结束后删除

- LOG

执行log生成于你的执行目录，log/*.log

- DB

会在执行目录下生成DB文件
autodiffpy 1.2.8
Autodifferentiation software package

# autodiffpy

[![Build Status](https://travis-ci.org/rajayuco/cs207-FinalProject.svg?branch=master)](https://travis-ci.org/rajayuco/cs207-FinalProject.svg?branch=master))

[![Coverage Status](https://coveralls.io/repos/github/rajayuco/cs207-FinalProject/badge.svg?branch=master)](https://coveralls.io/github/rajayuco/cs207-FinalProject?branch=master)

* Group name: rajayuco
* Group number: 6
* Team members: Rachel Moon, Jamila Pegues, Yudi Wang, Cory Williams

Welcome! Thank you for downloading our autodiffpy package. 

Details of our package can be found at: https://github.com/rajayuco/cs207-FinalProject/blob/master/docs/documentation.ipynb

Enjoy autodiffing! :D