semvec/pypi-packages huggingface dataset:
pywa-async 0.0.1
Please install `pywa` instead. It already includes the async version.
License: MIT
Requires Python: >=3.10

# pywa_async

Installing this package will only install the latest version of pywa, which already includes the async support. This package is just a placeholder to prevent takeovers of the name.
Avoid using this package because if pywa gets updated, you will not get the latest version.

## Installation

```sh
pip3 install pywa # not pywa_async!
```

```python

from pywa_async import WhatsApp, types, filters

wa = WhatsApp(...)

async def main():
    await wa.send_message(...)

@wa.on_message(filters.text)
async def hello(_: WhatsApp, msg: types.Message):
    await msg.react("👋")
    await msg.reply(...)
```
goppy 1.1.2
GopPy (Gaussian Online Processes for Python) is a pure Python module providing a Gaussian process implementation which allows 'to efficiently add new data online.
License: MIT
Requires Python: >=3.9
Keywords: Gaussian processes, machine learning, online learning

.. image:: https://github.com/jgosmann/goppy/actions/workflows/ci.yml/badge.svg
  :target: https://github.com/jgosmann/goppy/actions/workflows/ci.yml
  :alt: CI and release pipeline
.. image:: https://codecov.io/gh/jgosmann/goppy/branch/main/graph/badge.svg?token=mkgZs4nds5
  :target: https://codecov.io/gh/jgosmann/goppy
.. image:: https://img.shields.io/pypi/v/goppy
  :target: https://pypi.org/project/goppy/
  :alt: PyPI
.. image:: https://img.shields.io/pypi/pyversions/goppy
  :target: https://pypi.org/project/goppy/
  :alt: PyPI - Python Version
.. image:: https://img.shields.io/pypi/l/goppy
  :target: https://pypi.org/project/goppy/
  :alt: PyPI - License


.. image:: https://github.com/jgosmann/goppy/blob/main/doc/_static/goppy-sm.png
  :alt: GopPy logo

Overview
--------

GopPy (Gaussian Online Processes for Python) is a pure Python module providing
a Gaussian process implementation which allows to add new data efficiently
online. I wrote this module because all other Python implementations I knew did
not support efficient online updates.

The feature list:

* `scikit-learn <http://scikit-learn.org>`_ compatible interface.
* Efficient online updates.
* Prediction of first order derivatives.
* Estimation of the log likelihood and its derivative.
* Well documented.
* `Good test coverage. <https://app.codecov.io/gh/jgosmann/goppy>`_
* MIT license.

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

The documentation can be found at https://goppy.readthedocs.io/en/latest/.

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

You can install GopPy with pip::

    pip install goppy
downloaders 1.0.22
Python package to handle download of multiple types of files.
License: MIT
Requires Python: >=3.8

# Downloaders

![PyPI version](https://badge.fury.io/py/downloaders.svg)
![Downloads](https://pepy.tech/badge/downloaders)
![GitHub Actions](https://github.com/lucacappelletti94/downloaders/actions/workflows/python.yml/badge.svg)

Python package to handle the download of multiple types of files.

## How do I install this package?

As usual, just download it using pip:

```shell
pip install downloaders
```

## Usage examples

```python
from downloaders import BaseDownloader

downloader = BaseDownloader()
urls = [...]
downloader.download(urls)
```

## Troubleshooting

### MacOS multiprocessing nightmare fuel

Cupertino has a gift for us: somehow, under certain specific astral configurations on MacOS (which I have yet to fully understand), multiprocessing will crash with the following error:

```bash
The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec().
Break on __THE_PROCESS_HAS_FORKED_AND_YOU_CANNOT_USE_THIS_COREFOUNDATION_FUNCTIONALITY___YOU_MUST_EXEC__() to debug.
```

Apparently, this can be easily fixed by changing the way multiprocessing spawns processes:

```python
import platform, multiprocessing

if platform.system() == "Darwin":
    multiprocessing.set_start_method('spawn')
```

The aforementioned solution was proposed on [this StackOverflow question](https://stackoverflow.com/questions/30669659/multiproccesing-and-error-the-process-has-forked-and-you-cannot-use-this-corefou).
NP.ENS.KBDD 0.1.0
A package for NP.ENS.KBDD: a nonparametric ensemble knowledge-based and data-driven method for genetic network construction
License: MIT
Requires Python: >=3.6

# NP.ENS.KBDD: a nonparametric ensemble knowledge-based and data-driven method for genetic network construction

Updated: October 26 2024

This repository contains code to reproduce the results of simulation and applications in

Chen-Po Liao, Hung-Ching Chang, Chuhsing Kate Hsiao. "NP.ENS.KBDD: a nonparametric ensemble knowledge-based and data-driven method for genetic network construction" (2024)
NEKBDD 0.2.0
A package for NEKBDD: a nonparametric ensemble knowledge-based data-driven genetic network construction
License: MIT
Requires Python: >=3.6

# NEKBDD: a nonparametric ensemble knowledge-based data-driven genetic network construction

Updated: August 23 2024

This repository contains code to reproduce the results of simulation and applications in

Chen-Po Liao, Hung-Ching Chang, Chuhsing Kate Hsiao. "NEKBDD: a nonparametric ensemble knowledge-based data-driven genetic network construction" (2024)
mkdocs-py-ref-gen 0.1.1
mkdocs plugin to generate reference documentation and summary of python package(s)
License: MIT
Requires Python: <4.0,>=3.9
Keywords: mkdocs, mkdocs-plugin, docstrings, autodoc, documentation, mkdocstrings[python], python

# mkdocs-py-ref-gen

mkdocs plugin to generate reference documentation and summary of python package(s)

It's a wrapper plugin built using [mkdocs-gen-file](https://github.com/oprypin/)

```shell
pip install mkdocs-py-ref-gen
```

## usage

```yaml
plugins:
    - py-ref-gen
        modules:
            - name: "my_module"

```

[Click me](https://leninkhaidem.github.io/mkdocs-python-ref-generator) for full documention
bite-parser 0.2.5
Asynchronous parser taking incremental bites out of your byte input stream.
License: MIT
Requires Python: <4.0,>=3.9
Keywords: asyncio, parser, PEG, incremental, parser expression grammar

.. image:: https://github.com/jgosmann/bite-parser/actions/workflows/ci.yml/badge.svg
  :target: https://github.com/jgosmann/bite-parser/actions/workflows/ci.yml
  :alt: CI and release pipeline
.. image:: https://codecov.io/gh/jgosmann/bite-parser/branch/main/graph/badge.svg?token=O4M05YWNQK
  :target: https://codecov.io/gh/jgosmann/bite-parser
  :alt: Codecov coverage
.. image:: https://img.shields.io/pypi/v/bite-parser
  :target: https://pypi.org/project/bite-parser/
  :alt: PyPI
.. image:: https://img.shields.io/pypi/pyversions/bite-parser
  :target: https://pypi.org/project/bite-parser/
  :alt: PyPI - Python Version
.. image:: https://img.shields.io/pypi/l/bite-parser
  :target: https://pypi.org/project/bite-parser/
  :alt: PyPI - License

Welcome to bite-parser
======================

   Asynchronous parser taking incremental bites out of your byte input stream.

The bite-parser is a parser combinator library for Python.
It is similar to `PyParsing <https://github.com/pyparsing/pyparsing>`_
in that it allows the construction of grammars for parsing
from simple building blocks in pure Python.
This approach is also known as `Parsing Expression Grammar (PEG)
<https://en.wikipedia.org/wiki/Parsing_expression_grammar>`_.
While PyParsing
(and many other Python parsing libraries)
only support string,
bite-parser operates on bytes.
In addition,
bite-parser makes use of `asyncio`
and can asynchronously generate parsed items
from an input stream.

A typical use-case would be the parsing of a network protocol
like IMAP.
In fact,
I wrote this library for the IMAP implementation of my
`dmarc-metrics-exporter <https://github.com/jgosmann/dmarc-metrics-exporter>`_.

.. note::
   I have implemented the fundamental set of parsers,
   which should allow constructing most or all grammars
   recognizable by this type of parser.
   However, many convenience or higher level parsers are not yet implemented.

   Other areas that still need improvement are:

   * Abilitiy to debug the parsing.
   * Better error messages.
   * Performance: Currently, only a basic recursive descent parser is
     implemented which can exhibit exponential worst case performance.
     This could be improved by implementing a packrat parser.

Important links
---------------

* `Documentation <https://jgosmann.github.io/bite-parser/docs/en/main/>`_
* `GitHub repository <https://github.com/jgosmann/bite-parser>`_
count-city-csv 0.1.0
Подсчет клиентов по возрасту и городу
License: MIT

--input-file - входной файл с заказ, в котором id, возраст и город

--output-file - выходной файл, куда будет записан анализ в формате txt

Пример команды: python -m count_city_csv --input-file data/customers.csv --output-file rrr.txt