semvec/pypi-packages huggingface dataset:
aioface 0.0.2
aioface is a powerful and simple asynchronous framework for the Facebook Messenger API written in Python 3.7.
License: MIT
Requires Python: >=3.7

# aioface

aioface is a powerful and simple asynchronous framework for the Facebook Messenger API written in Python 3.7.

## Installation

```console
$ pip install aioface
```

## Examples

### Echo bot

```Python
from aioface import Bot, Dispatcher, BaseStorage, FacebookRequest


dispatcher = Dispatcher(BaseStorage())
bot = Bot(webhook_token='your_webhook_token',
          page_token='your_page_token',
          dispatcher=dispatcher)


@dispatcher.message_handler()
async def echo_handler(fb_request: FacebookRequest):
    await fb_request.send_message(message=fb_request.message_text)
    
    
if __name__ == '__main__':
    bot.run()
```
datasetsmanager 0.0.2
Datasets Manager
License: MIT
Requires Python: >=3.6.0

# Introduction 
TODO: Give a short introduction of your project. Let this section explain the objectives or the motivation behind this project. 

# Getting Started
TODO: Guide users through getting your code up and running on their own system. In this section you can talk about:
1.	Installation process
2.	Software dependencies
3.	Latest releases
4.	API references

# Build and Test
TODO: Describe and show how to build your code and run the tests. 

# Contribute
TODO: Explain how other users and developers can contribute to make your code better. 

If you want to learn more about creating good readme files then refer the following [guidelines](https://docs.microsoft.com/en-us/azure/devops/repos/git/create-a-readme?view=azure-devops). You can also seek inspiration from the below readme files:
- [ASP.NET Core](https://github.com/aspnet/Home)
- [Visual Studio Code](https://github.com/Microsoft/vscode)
- [Chakra Core](https://github.com/Microsoft/ChakraCore)
wc-utils 0.0.22
Utilities for whole-cell modeling
License: MIT
Keywords: whole-cell modeling

|PyPI package| |Documentation| |Test results| |Test coverage| |Code
analysis| |License| |Analytics|

Whole-cell modeling utilities
=============================

This package contains utilities that are useful to multiple whole-cell
(WC) software components.

Installation
------------

1. Install the third-party dependencies listed below. Detailed
   installation instructions are available in `An Introduction to
   Whole-Cell
   Modeling <http://docs.karrlab.org/intro_to_wc_modeling/master/0.0.1/installation.html>`__.

   -  `ChemAxon Marvin <https://chemaxon.com/products/marvin>`__:
      optional to calculate major protonation states
   -  `Java <https://www.java.com>`__ >= 1.8
   -  `Git <https://git-scm.com/>`__
   -  `OpenBabel <http://openbabel.org>`__: optional to calculate
      chemical formulae
   -  `Pip <https://pip.pypa.io>`__ >= 18.0
   -  `Python <https://www.python.org>`__ >= 3.6

2. To use Marvin to calculate major protonation states, set
   ``JAVA_HOME`` to the path to your Java virtual machine (JVM)
   ``export JAVA_HOME=/usr/lib/jvm/default-java``

3. To use Marvin to calculate major protonation states, add Marvin to
   the Java class path
   ``export CLASSPATH=$CLASSPATH:/opt/chemaxon/marvinsuite/lib/MarvinBeans.jar``

4. Install this package

   -  Install the latest release from PyPI ``pip install wc_utils[all]``

   -  Install the latest revision from GitHub
      ``pip install git+https://github.com/KarrLab/pkg_utils.git#egg=pkg_utils[all]   pip install git+https://github.com/KarrLab/wc_utils.git#egg=wc_utils[all]``

Example usage
-------------

Documentation
-------------

Please see the `API documentation <http://docs.karrlab.org/wc_utils>`__.

License
-------

The build utilities are released under the `MIT license <LICENSE>`__.

Development team
----------------

This package was developed by the `Karr Lab <http://www.karrlab.org>`__
at the Icahn School of Medicine at Mount Sinai in New York, USA.

-  Arthur Goldberg
-  Jonathan Karr

Questions and comments
----------------------

Please contact the `Karr Lab <http://www.karrlab.org>`__ with any
questions or comments.

.. |PyPI package| image:: https://img.shields.io/pypi/v/wc_utils.svg
   :target: https://pypi.python.org/pypi/wc_utils
.. |Documentation| image:: https://readthedocs.org/projects/wc-utils/badge/?version=latest
   :target: http://docs.karrlab.org/wc_utils
.. |Test results| image:: https://circleci.com/gh/KarrLab/wc_utils.svg?style=shield
   :target: https://circleci.com/gh/KarrLab/wc_utils
.. |Test coverage| image:: https://coveralls.io/repos/github/KarrLab/wc_utils/badge.svg
   :target: https://coveralls.io/github/KarrLab/wc_utils
.. |Code analysis| image:: https://api.codeclimate.com/v1/badges/8139298cdbc1e32dcde4/maintainability
   :target: https://codeclimate.com/github/KarrLab/wc_utils
.. |License| image:: https://img.shields.io/github/license/KarrLab/wc_utils.svg
   :target: LICENSE
.. |Analytics| image:: https://ga-beacon.appspot.com/UA-86759801-1/wc_utils/README.md?pixel
paten 0.1.3
paten
License: MIT
Requires Python: >=3.7
Keywords: azure,azure functions

# Paten

[![pytest](https://github.com/gsy0911/paten/workflows/pytest/badge.svg)](https://github.com/gsy0911/paten/actions?query=workflow%3Apytest)
[![codecov](https://codecov.io/gh/gsy0911/paten/branch/master/graph/badge.svg)](https://codecov.io/gh/gsy0911/paten)
[![PythonVersion](https://img.shields.io/badge/python-3.7|3.8-blue.svg)](https://www.python.org/downloads/release/python-377/)
[![PiPY](https://img.shields.io/badge/pypi-0.1.3-blue.svg)](https://pypi.org/project/paten/)


Paten is a framework for azure functions written in Python. Paten provides:

* A command line tool for creating, building, deploying azure functions.
* A decorator based API integrated with in/out bindings.

## install

install `paten` package.

```shell script
$ pip install paten
```

In addition, `Azure CLI` and `Azure Functions Core Tools` are required. 
See below to install the libraries.

* [Azure CLI](https://docs.microsoft.com/ja-jp/cli/azure/install-azure-cli?view=azure-cli-latest)
* [Azure Functions Core Tools](https://docs.microsoft.com/ja-jp/azure/azure-functions/functions-run-local?tabs=macos%2Cpython%2Cbash)

## preparation

Before deploying to Azure, `az login` is required.

```shell script
$ az login

You have logged in. Now let us find all the subscriptions to which you have access...
```

## Quickstart

In your project directory, type below.
Directory {function_app_name} and example python scripts are created.

```shell script
$ paten new-app {function_app_name}
```

Then, modify `app.py`, like below.

```python
import azure.functions as func
from paten import Paten

app = Paten('{function_app_name}')


@app.http_trigger('req', methods=['GET'], route='/')
@app.out_http()
def example_http_function(req: func.HttpRequest) -> func.HttpResponse:
    name = req.params.get('name')
    
    # response
    return func.HttpResponse(name)

```

Before deploying to azure functions, you can test your functions on local with the command below.

```shell script
$ paten local
```

Finally, to deploy to azure functions, type below in the directory `{function_app_name}`.
The files are generated in `./{function_app_name}/.paten` and your function app is deployed to azure.

```shell script
$ paten deploy
```

## support bindings

| services | trigger | in | out | 
|:--:|:--:|:--:|:--:|
| http | O | - | O |
| blob | O | X | X |
| queue | O | X | 0 |
| timer | O | - | - |
 
* O: supported
* X: not supported yet
* -: officially not supported
inipec-scraper 0.0.2
Web scraper that take a TAX Code and return the PEC address of the company
License: MIT
Requires Python: >=3.6

# inipec-scraper

Inipec-scaper is a simple scraper project that take a TAX Code of a company and return the PEC address 
of it

### Tech

inipec-scraper uses a number of open source projects to work properly:

* [pip]==20.2.2
* [beautifulsoup4]~=4.9.1
* [mechanize]~=0.4.5
* [pymongo]~=3.11.0
* [dnspython]~=2.0.0
* [python_dotenv]~=0.14.0
* [setuptools]~=50.3.0

And inipec-scraper itself is open source with a [public repository](https://github.com/riccardopaltrinieri/inipec-scraper)
on GitHub.
 
### Installation

inipec-scraper requires [python 3.7](https://https://www.python.org/) to run.

How to install it
```sh
$ pip install inipec-scraper==0.0.1
```
How to run it with a simple [tkinter] gui
```sh
$ python3 inipec-scraper.py
```
You can also use only the scraper code with
```sh
$ cd .\inipec-scraper\modules
$ python3 scraper.py
```

License
----

MIT
nuditychk 0.2.4
Nudity detection with re-trained Tensorflow MobileNet Model http://nudity.canaydogan.net
License: MIT
Requires Python: >=3
Keywords: nude,nudity,detection,pornographic,inappropriate content

nudity
=======
.. image:: https://travis-ci.org/canaydogan/nudity.svg?branch=master
    :target: https://travis-ci.org/canaydogan/nudity
    :alt: Build status

About
-----
Nudity detection with re-trained Tensorflow MobileNet Model. Accuracy is 92.2% based on my dataset.

Installation
------------
.. code-block:: sh

    $ pip install nudity


Requirements
------------
* Python3.5+

Usage
-----
via command-line

.. code-block:: sh


    $ nudity --image=IMAGE_FILE

via Python Module

.. code-block:: python

    from nudity import Nudity
    nudity = Nudity();
    print(nudity.has('/file/path/example.jpg'))
    # gives you True or False

    print(nudity.score('/file/path/example.jpg'))
    # gives you nudity score 0 - 1