semvec/pypi-packages huggingface dataset:
enddiscord 1.0.1
A Python wrapper for the Discord API
License: MIT
Requires Python: >=3.5.3

discord.py
==========

.. image:: https://discord.com/api/guilds/336642139381301249/embed.png
   :target: https://discord.gg/r3sSKJJ
   :alt: Discord server invite
.. image:: https://img.shields.io/pypi/v/discord.py.svg
   :target: https://pypi.python.org/pypi/discord.py
   :alt: PyPI version info
.. image:: https://img.shields.io/pypi/pyversions/discord.py.svg
   :target: https://pypi.python.org/pypi/discord.py
   :alt: PyPI supported Python versions

A modern, easy to use, feature-rich, and async ready API wrapper for Discord written in Python.

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

- Modern Pythonic API using ``async`` and ``await``.
- Proper rate limit handling.
- 100% coverage of the supported Discord API.
- Optimised in both speed and memory.

Installing
----------

**Python 3.5.3 or higher is required**

To install the library without full voice support, you can just run the following command:

.. code:: sh

    # Linux/macOS
    python3 -m pip install -U discord.py

    # Windows
    py -3 -m pip install -U discord.py

Otherwise to get voice support you should run the following command:

.. code:: sh

    # Linux/macOS
    python3 -m pip install -U "discord.py[voice]"

    # Windows
    py -3 -m pip install -U discord.py[voice]


To install the development version, do the following:

.. code:: sh

    $ git clone https://github.com/Rapptz/discord.py
    $ cd discord.py
    $ python3 -m pip install -U .[voice]


Optional Packages
~~~~~~~~~~~~~~~~~~

* PyNaCl (for voice support)

Please note that on Linux installing voice you must install the following packages via your favourite package manager (e.g. ``apt``, ``dnf``, etc) before running the above commands:

* libffi-dev (or ``libffi-devel`` on some systems)
* python-dev (e.g. ``python3.6-dev`` for Python 3.6)

Quick Example
--------------

.. code:: py

    import discord

    class MyClient(discord.Client):
        async def on_ready(self):
            print('Logged on as', self.user)

        async def on_message(self, message):
            # don't respond to ourselves
            if message.author == self.user:
                return

            if message.content == 'ping':
                await message.channel.send('pong')

    client = MyClient()
    client.run('token')

Bot Example
~~~~~~~~~~~~~

.. code:: py

    import discord
    from discord.ext import commands

    bot = commands.Bot(command_prefix='>')

    @bot.command()
    async def ping(ctx):
        await ctx.send('pong')

    bot.run('token')

You can find more examples in the examples directory.

Links
------

- `Documentation <https://discordpy.readthedocs.io/en/latest/index.html>`_
- `Official Discord Server <https://discord.gg/r3sSKJJ>`_
- `Discord API <https://discord.gg/discord-api>`_
simulai 0.0.1
SimulAI - Simulation + Artificial Intelligence
License: MIT
Keywords: simulai,simulation,artificial intelligence,decision sciences,optimization

[![Documentation Status](https://readthedocs.org/projects/simulai/badge/?version=latest)](https://simulai.readthedocs.io/en/latest/?badge=latest)
[![Build Status](https://travis-ci.com/carosaav/SimulAI.svg?branch=master)](https://travis-ci.com/carosaav/SimulAI)
[![Coverage Status](https://coveralls.io/repos/github/carosaav/SimulAI/badge.svg?branch=master)](
https://coveralls.io/github/carosaav/SimulAI?branch=master)
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
[![Python 3.7+](https://img.shields.io/badge/Python-3.7+-blue.svg)](https://www.python.org/downloads/release/python-370/)
[![Windows](https://img.shields.io/badge/OS-Windows-blue.svg)](https://www.microsoft.com/windows)
[![https://github.com/leliel12/diseno_sci_sfw](https://img.shields.io/badge/DiSoftCompCi-FAMAF-ffda00)](https://github.com/leliel12/diseno_sci_sfw)

![logo](https://github.com/carosaav/SimulAI/blob/master/docs/_static/logo_long.png)

_It is a library that facilitates the use of Artificial Intelligence (AI) techniques for the optimization of variables derived from the Simulation of Flexible Manufacturing Systems (FMS). The objective is to improve the decision-making process in organizations, making it more efficient and safe._

## Development 🔨

_Initially the work will focus on the integration of Tecnomatix Plant Simulation software with diverse methods of optimization, which will be submitted to a process of improvement throughout the Doctorate stage in development._

_In the future, it is expected to achieve a library of greater accessibility, allowing the application in various simulation software, as required by the user._

OS Windows, Tecnomatix Plant Simulation version 15.0 and pywin32 library are currently required for its operation.

## Authors 👥

* **Perez Colo Ivo** - [@ivoperezcolo](https://github.com/IvoPerezColo)
* **Pirozzo Bernardo** - [@bermpirozzo](https://github.com/BerMPirozzo)
* **Saavedra Sueldo Carolina** - [@carosaav](https://github.com/carosaav)
osmon 0.1.5
Simple cli system monitor made for fun.
License: MIT

# osmon

Are You tired of having to one of these speedtest websites every time you want to check you internet connection?
We've got solution designed specially for You!
<br>
Introducing... osmon!
<br>
Minimal weight and easy in use system monitor.

### Installation

```bash

pip3 install osmon

```
### Examples

If You get stuck:

```bash

$ osmon -h
usage: osmon [-h] [--cpu] [--gpu] [--ram] [--down] [--up] [--ping] [--net] [--all]

Get some stats.

optional arguments:
  -h, --help  show this help message and exit
  --cpu, -c   Check CPU parameters
  --gpu, -g   Check GPU parameters
  --ram, -r   Check RAM paramters
  --down, -d  Check download speed
  --up, -u    Check upload speed
  --ping, -p  Check download speed
  --net, -n   Check all network parameters
  --all, -a   Check all possible parameters

```

To get output off all possible measurements run:


```bash

$ osmon -a

CPU usage: 2.1%
Usage by Threads: 12
1  -  [3.3%]
2  -  [2.5%]
3  -  [3.3%]
4  -  [1.7%]
5  -  [1.6%]
6  -  [0.0%]
7  -  [0.0%]
8  -  [1.6%]
9  -  [2.5%]
10  -  [0.0%]
11  -  [3.3%]
12  -  [4.1%]
VRAM:
1  -  [592]MB Used
GPU Usage: 
 [1]
RAM usage: 27.2%
Available: 72.8%
Retrieving speedtest.net configuration...
Testing from Skynet sp. z o.o. ($IP)...
Retrieving speedtest.net server list...
Selecting best server based on ping...
Hosted by Orange Polska S.A. (Warsaw) [14.84 km]: 3.898 ms
Testing download speed................................................................................
Download: 495.75 Mbit/s
Testing upload speed......................................................................................................
Upload: 60.53 Mbit/s


```

### Why?
To gather Your data.
And but mostly to learn new things and have fun.
apipt 0.1.1
Install Python packages by apt
License: MIT
Requires Python: >=3.6
Keywords: apipt

# apipt
`APIPT` is a package which installs Python packages by `apt` if possible, otherwise using `pip`.

[It's better to use `apt`](https://stackoverflow.com/questions/6874527).

## Example
Say there are a few packages we want to install:

Python packages that can be install by `apt`:
* numpy
* requests

Python packages that can't:
* fastai
* tensorflow

Normal packages:
* bind9
* curl

Let's run `apipt install numpy requests fastai tensorflow bind9 curl`:

```shell script
root@Ubuntu ~# apipt install numpy requests fastai tensorflow bind9 curl
Running: apt install python3-numpy python3-requests bind9 curl
Press any key if no [y/N] prompt.

...

After this operation, 27.0 MB of additional disk space will be used.
Do you want to continue? [Y/n] Y

...

Running: pip install fastai tensorflow
Press any key if no [y/N] prompt.


Collecting fastai
...
```

Like what is shown above, `apipt` automatically divide those package into two group. 

For one group, it calls `apt install python3-numpy python3-requests bind9 curl`, and for another, `pip install fastai tensorflow`.
stock-market 0.4.1
A library that gather stock market historical OHLC data.
License: MIT
Requires Python: >=3.6
Keywords: klsescreener

# stock-market
A library that gather stock market historical OHLC data.

# klsescreener

## To get klsescreener dashboard
```
>>> from stock_market.screeners import klsescreener
>>> klsescreener.api.KlseScreener.stocks_screener()
             Name    Code                                    Category  ...  MCap.(M)       Indicators  Unnamed: 15
0       DIGI  [s]    6947     Telecommunications & Media, Main Market  ...  32421.75              NaN           >>
1       MGRC  [s]    0155                     Health Care, Ace Market  ...     64.69              YoY           >>
2         CARLSBG    2836   Consumer Products & Services, Main Market  ...   7117.81              NaN           >>
3    CHINAETF-USD  0829EB                             ETF-Equity, ETF  ...      0.62              NaN           >>
4    LAGENDA  [s]    7179                       Property, Main Market  ...    575.35          QoQ YoY           >>
..            ...     ...                                         ...  ...       ...              ...          ...
977    HUAAN  [s]    2739                         Energy, Main Market  ...    137.79              NaN           >>
978    SEERS  [s]   03009   Consumer Products & Services, Leap Market  ...     25.76             RQoQ           >>
979           M&G    5078     Transportation & Logistics, Main Market  ...     65.15  RQoQ RYoY RTopQ           >>
980  BRAHIMS  [s]    9474   Consumer Products & Services, Main Market  ...     69.70              YoY           >>
981  HHGROUP  [s]    0175  Industrial Products & Services, Ace Market  ...     13.45              NaN           >>

[982 rows x 16 columns]
```

## To export klsescreener dashboard to Excel file
```
>>> from stock_market.screeners import klsescreener
>>> filepath = 'klsescreener.xlsx'
>>> klsescreener.api.export_stocks_screener_to_excel(filepath)
```

# bursamalaysia

## To export securities equities keyindicator PDF
```
>>> from stock_market.screeners import bursamalaysia
>>> bursamalaysia.api.export_securities_equities_keyindicators_pdf('2020-12-31')
```

## To export securities equities PDF
```
>>> from stock_market.screeners import bursamalaysia
>>> bursamalaysia.api.export_securities_equities_pdf('2020-12-31')
```

## To export indices
```
>>> from stock_market.screeners import bursamalaysia
>>> bursamalaysia.api.export_indices_data('0200I')
```

## To export equities
```
>>> from stock_market.screeners import bursamalaysia
>>> bursamalaysia.api.export_equities_data('1818')
```

=============
Release Notes
=============

0.0.1 (2020-10-26)
====================================================
- New Features:
    - Initial release on PyPI

- Changes to Existing Features:
    - Initial project

- Bug Fixes:
    - None
azutils 0.1.2
Utilities for Azure
License: MIT
Requires Python: >=3.6
Keywords: azure,databricks

# azutils

[![PythonVersion](https://img.shields.io/badge/python-3.6|3.7|3.8-blue.svg)](https://www.python.org/downloads/release/python-377/)
[![PiPY](https://img.shields.io/pypi/v/azutils.svg)](https://pypi.org/project/azutils/)


`azutils` is to provide convenient Python functions for Azure Services.

* Databricks,
* Azure Batch ?

## install

```bash
$ pip install azutils
```

## usage

* for `Databricks`

```python
from azutils.databricks import DatabricksClient
token = "..."

dc = DatabricksClient(token=token)

# list cluster
cluster_list = dc.clusters_list()

for cluster in cluster_list:
    print(cluster)

# * cluster_name: some-cluster
#   * cluster_id: XXXX-XXXXXX-xxxxxxx
#   * spark_version: 7.1.x-scala2.12
#   * driver_node_type: Standard_DS12_v2
#   * node_type: Standard_DS3_v2
#   * cost: 96.208 + 79.408 * NUM [YEN/HOUR]

cluster_id = "XXXX-XXXXXX-xxxxxxx"
print(dc.cluster_cost(cluster_id=cluster_id, start_time="2020-10-01", end_time="2020-10-31"))


# display cluster usage with `seaborn`
cluster_id_1 = "XXXX-XXXXXX-xxxxxx1"
cluster_id_2 = "XXXX-XXXXXX-xxxxxx2"
dc.cluster_running_time_as_sns(cluster_id=[cluster_id_1, cluster_id_2])

```