semvec/pypi-packages huggingface dataset:
numpy-partition 1.18.9
SQL PARTITION BY and window functions for NumPy

# Split numpy arrays into partitions by one or multiple columns and apply window function to each partition.


This module tries to replicate `select window_function() over (partition by ... order by ...) ...` functionality, commonly found in SQL databases.

The following window functions are available out of the box: `row_number()`, `top()`, `avg()`. 


## Usage examples:

```
    >>> from partition import apply_over_partition
    >>> from partition.window import row_number, top, avg

    >>> data = np.array([[1,1,3], [2,2,3], [1,1,4]], dtype=np.float32)
    >>> partition_by_col_indexes = (0, 1)
    >>> value_col_indexes = (2,)
    >>> value_ordering = (-1,)  # descending order
    >>> f = avg
    >>> f_kwargs = dict(vcol=2, top_n=2)
    >>> apply_over_partition(data=data, partition_by_col_indexes=partition_by_col_indexes, value_col_indexes=value_col_indexes, value_ordering=value_ordering, f=f, f_kwargs=f_kwargs)
    array([3.5, 3. , 3.5])

    >>> f = avg
    >>> f_kwargs = dict(vcol=2, top_n=1)
    >>> apply_over_partition(data=data, partition_by_col_indexes=partition_by_col_indexes, value_col_indexes=value_col_indexes, value_ordering=value_ordering, f=f, f_kwargs=f_kwargs)
    array([4., 3., 4.])

    >>> f = row_number
    >>> f_kwargs = dict()
    >>> apply_over_partition(data=data, partition_by_col_indexes=partition_by_col_indexes, value_col_indexes=value_col_indexes, value_ordering=value_ordering, f=f, f_kwargs=f_kwargs)
    array([1, 0, 0])

    >>> f = top
    >>> f_kwargs = dict(n=1)
    >>> apply_over_partition(data=data, partition_by_col_indexes=partition_by_col_indexes, value_col_indexes=value_col_indexes, value_ordering=value_ordering, f=f, f_kwargs=f_kwargs)
    array([False,  True,  True])

```
mozart 1.0.3
Nice API for developers who like music™
Requires Python: >=3.6.0
Keywords: music,api,mozart

# MusicAPI
![GitHub](https://img.shields.io/github/license/kushao1267/MusicAPI.svg)
![Build](https://travis-ci.org/kushao1267/MusicAPI.svg?branch=master)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mozart.svg)
[![codecov](https://codecov.io/gh/kushao1267/MusicAPI/branch/master/graph/badge.svg)](https://codecov.io/gh/kushao1267/MusicAPI)

## About
MusicAPI当前仅支持`Python3.5`及以上.

它提供了国内许多音乐的API，支持通过`music_id`和`音乐链接`两种方式来获取歌曲信息及下载链接（版权、会员的除外）。
使用者可以很容易地添加其他音乐类的API。

目前已支持的音乐有:
- [x] 网易云音乐
- [x] QQ音乐
- [x] 虾米音乐
- [ ] 喜马拉雅
- [ ] 百度音乐
- [ ] 酷狗音乐

注: 该仓库仅可用于学习和交流实验用途，若用于商业用途，与本人无关。


## Install
推荐方式
```
pip install mozart
```

其他方式:
```
git clone git@github.com:kushao1267/MusicAPI.git
python setup.py install
```


## Usage
在MusicAPI目录下:

1.使用music_id访问

```
$ python -m mozart -n netease -l http://music.163.com/song/1358275974/\?userid\=1769873017
[Music]
singer:李子璇
song:豆你玩
cover:http://p1.music.126.net/326BBneDl4izrTBF8vJJxA==/109951163993105848.jpg
download_url:http://m10.music.126.net/20190419145523/620fa37967fa54ab80c9987dbaba8e4a/ymusic/045d/0e5d/0553/37a1dc7beb972befb40629f085a5eb39.mp3
```

2.使用music share url访问

```
$ python -m mozart -n netease -m 1358275974
[Music]
singer:李子璇
song:豆你玩
cover:http://p2.music.126.net/326BBneDl4izrTBF8vJJxA==/109951163993105848.jpg
download_url:http://m10.music.126.net/20190419145641/41f171066b22d8e496b63ff67c6ca429/ymusic/045d/0e5d/0553/37a1dc7beb972befb40629f085a5eb39.mp3
```

## License
[MIT License](https://github.com/kushao1267/facade/blob/master/LICENSE)
cizsle 0.0a7
Cisco ZTP Server LE
Keywords: cisco ztp ios-xe catalyst

----------------------------
cizsle | Cisco ZTP Server LE
----------------------------

*Zero-Touch Provisioning (ZTP) Server for Cisco Network Devices*

.. image:: https://travis-ci.org/CiscoDevNet/cizsle.svg?branch=master
    :target: https://travis-ci.org/CiscoDevNet/cizsle
.. image:: https://readthedocs.org/projects/cizsle/badge/?version=latest
    :target: https://cizsle.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status
.. image:: https://codecov.io/gh/CiscoDevNet/cizsle/branch/master/graph/badge.svg
    :target: https://codecov.io/gh/CiscoDevNet/cizsle

------------------------------------------------------------------------------------------------------------------------

The goal of this project is to develop a Zero Touch Provisioning (ZTP) Server to simplify and accelerate deployment of
Cisco networking devices.

Project Targets
---------------

- Developed in Python
- Deployed in Docker containers

Key Features
------------

- Support ZTP on IOS XE, IOS XR, and NXOS devices
- Template and scripted device configurations
- Software image upgrades
- Topology validation
- Intuitive web UI and concise CLI