semvec/pypi-packages huggingface dataset:
py-utlx 2.2.0
Python utilities.
Requires Python: <4.0.0,>=3.10.0
Keywords: py-utlx, utlx, util, utils

py-utlx
=======

Python utilities.

Overview
========

TBD...

`PyPI record`_.

`Documentation`_.

Usage
-----

TBD...

Installation
============

Prerequisites:

+ Python 3.10 or higher

  * https://www.python.org/

+ pip

  * https://pypi.org/project/pip/

To install run:

  .. parsed-literal::

    python -m pip install --upgrade |package|

Development
===========

Prerequisites:

+ Development is strictly based on *nox*. To install it run::

    python -m pip install --upgrade nox

Visit `Development page`_.

Installation from sources:

clone the sources:

  .. parsed-literal::

    git clone |respository| |package|

and run:

  .. parsed-literal::

    python -m pip install ./|package|

or on development mode:

  .. parsed-literal::

    python -m pip install --editable ./|package|

License
=======

  | |copyright|
  | Licensed under the zlib/libpng License
  | https://opensource.org/license/zlib
  | Please refer to the accompanying LICENSE file.

Authors
=======

* Adam Karpierz <adam@karpierz.net>

Sponsoring
==========

| If you would like to sponsor the development of this project, your contribution
  is greatly appreciated.
| As I am now retired, any support helps me dedicate more time to maintaining and
  improving this work.

`Donate`_

.. |package| replace:: py-utlx
.. |package_bold| replace:: **py-utlx**
.. |copyright| replace:: Copyright (c) 2004-2026 Adam Karpierz
.. |respository| replace:: https://github.com/karpierz/py-utlx
.. _Development page: https://github.com/karpierz/py-utlx
.. _PyPI record: https://pypi.org/project/py-utlx/
.. _Documentation: https://karpierz.github.io/py-utlx/
.. _Donate: https://www.paypal.com/donate/?hosted_button_id=FX8L7CJUGLW7S
must-gather-parser 0.5.0
Asynchronous (multi) must-gather parsing library.
Requires Python: >=3.11

# must-gather-parser

[![Python Version](https://img.shields.io/pypi/pyversions/must-gather-parser.svg)](https://pypi.org/project/must-gather-parser/)
![publish workflow](https://github.com/gmeghnag/must-gather-parser/actions/workflows/publish.yml/badge.svg) 
![version](https://img.shields.io/pypi/v/must-gather-parser?label=version&color=green)

Asynchronous (multi) must-gather parsing library.

## INSTALL
```
pip install must-gather-parser
```

---

This module uses [**PyYAML**](https://github.com/yaml/pyyaml) for parsing YAML files.

For **significantly better performance**, PyYAML should be installed **with [libyaml](https://github.com/yaml/libyaml) support**.  
When available, PyYAML automatically uses its C-based loader, resulting in much faster YAML processing.

#### `libyaml` installation
```
# Debian / Ubuntu
sudo apt install libyaml-dev
```
```
# macOS
brew install libyaml
```
```
# Fedora
sudo dnf install libyaml-devel
```

## USAGE
```python
import asyncio
from must_gather_parser import MustGather
import json

must_gather = MustGather()

async def main():
    try:
        await must_gather.use("/home/must-gather.local.1972254135986597168")
        x = await must_gather.get_resources(resource_kind_plural="pods", group="core", all_namespaces=True)
        print(json.dumps(x))
    except:
        must_gather.close()


if __name__ == "__main__":
    asyncio.run(main())
```
django-plans 2.1.3
Pluggable django app for managing pricing plans with quotas and accounts expiration
Requires Python: >=3.9

Welcome to django-plans
=======================


.. image:: https://codecov.io/gh/django-getpaid/django-plans/branch/master/graph/badge.svg?token=oEyv7odqUW
   :target: https://codecov.io/gh/django-getpaid/django-plans

Django-plans is a pluggable app for managing pricing plans with quotas and accounts expiration.

Features currently supported:

* Multiple plans,
* Support for user custom plans.
* Flexible model for parametrizing plans (quota).
* Customizable billing periods (plan pricing),
* Order total calculation using customizable taxation policy (e.g. in EU calculating VAT based on seller/buyer countries and VIES)
* Invoicing,
* Account expiratons + E-mail remainders.

Documentation: https://django-plans.readthedocs.org/

Master branch: Support for Django 4.2 - 5.2, support for Python 3.9 - 3.13

.. image:: docs/source/_static/images/django-plans-1.png

.. image:: docs/source/_static/images/django-plans-2.png

.. image:: docs/source/_static/images/django-plans-3.png



License
-------

Django Plans is licensed and distributed under MIT licesne..
tripp 1.1.2
Trajectory Iterative pKa Predictor
Requires Python: <3.10,>=3.9

# TrIPP: Trajectory Iterative pKa Predictor


TrIPP (Trajectory Iterative pKa Predictor) is a Python tool to monitor and analyse changes in the pKa of ionisable residues during Molecular Dynamics simulations of proteins.

TrIPP uses [PROPKA 3](https://github.com/jensengroup/propka) or [pKAI](https://github.com/bayer-science-for-a-better-life/pKAI), which are licensed under
the GNU Lesser General Public License (LGPL) and MIT License, respectively. PROPKA and pKAI are not included in this repository
but are required to run the software. See the PROPKA or pKAI repository for their license terms. 

## Prerequisites

This project has been developed and tested with Python (version 3.9). To make sure you have the right version available on your machine, run the following command: 

```sh
$ python --version
Python 3.9
```

The Visualization class in TrIPP requires a working installation of PyMOL (https://www.pymol.org/) on your machine.

## Table of contents

- [Project Name](#project-name)
  - [Prerequisites](#prerequisites)
  - [Table of contents](#table-of-contents)
  - [Installation](#installation)
  - [Workflow](#workflow)
  - [Development](#development)
  - [Authors](#authors)
  - [License](#license)

## Installation
The recommended way to install TrIPP is via PyPI.
You may want to create a virtual environment before installing the package.
```sh
conda create -n tripp python=3.9 setuptools=75 ipykernel
conda activate tripp
pip install tripp
```

(Optional) You can test the installation with the following:
```sh
git clone https://github.com/fornililab/TrIPP.git
cd TrIPP/tests/
pytest -s test_Installation.py
```
Note that you will be prompted for the path of the PyMOL executable when testing the Visualization class.
You may type `skip` to bypass the Visualization class test.

Mac: /Applications/PyMOL.app/Contents/MacOS/MacPyMOL or `which pymol` (depending on how PyMOL has been installed)

Linux: which pymol

Windows: where pymol

### Workflow

Please start the conda environement for TrIPP
```sh
conda activate tripp
```
then follow the [tripp_tutorial](tutorial/tripp_tutorial.ipynb) for a comprehensive workflow.

Running the full tutorial on a Macbook Pro (M2 Pro) using 12 cores requires about 6 minutes (2 trajectories, 3087 frames, 1960 atoms).

### Development

Tests for each function are a work in progress.
Users who modifiy the code should pass all tests inside the [tests](tests/) directory.

### Authors

* **Christos Matsingos** - [chmatsingos](https://github.com/chmatsingos)
* **Ka Fu Man** [mkf30](https://github.com/mkf30)
* **Arianna Fornili** [fornililab](https://github.com/fornililab)

### Citation

If you publish results produced with TrIPP or develop methods based on TrIPP, please cite the following paper:

Matsingos, C.; Man, K. F.; Fornili, A. TrIPP: A Trajectory Iterative pKa Predictor. Bioinformatics 2026, btag063. https://doi.org/10.1093/bioinformatics/btag063.



### License

Copyright (C) 2024 Christos Matsingos, Ka Fu Man and Arianna Fornili  
TrIPP is licensed under **GPL-3.0**
wuji-sdk 0.6.0
Wuji SDK: Python package for automatic device discovery and real-time data streaming with Wuji devices.
Requires Python: >=3.10
Keywords: wuji, sdk, robotics

# wuji-sdk

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE) [![Release](https://img.shields.io/github/v/release/wuji-technology/wuji-sdk)](https://github.com/wuji-technology/wuji-sdk/releases) ![Coverage](https://raw.githubusercontent.com/wuji-technology/wuji-sdk/badges/coverage.svg)

Python SDK for Wuji series devices. Provides automatic device discovery, connection management, and real-time data streaming for Wuji Glove and other Wuji peripherals. Features type-safe semantic API with native async/await and callback-based subscription support.

**Get started with [Quick Start](#quick-start). For detailed documentation, please refer to [Wuji Docs Center](https://docs.wuji.tech/docs/en/wuji-glove/latest/).**

## Repository Structure

```text
├── examples/                      # Example scripts demonstrating SDK usage patterns
│   ├── 0.subscribe_callback.py
│   └── 1.subscribe_async.py
├── CHANGELOG.md                   # Version history and release notes
├── LICENSE                        # MIT license file
└── README.md
```

## Quick Start

### Installation

```bash
pip install wuji-sdk
```

### Running

```python
import time
from wuji_sdk import SdkManager

manager = SdkManager.instance()
glove = manager.auto_connect(device_name="glove")

sub = glove.tactile().subscribe_with_callback(
    callback=lambda frame: print(f"Max pressure: {max(frame.data):.2f}")
)

time.sleep(10)
sub.close()
```

## Contact

For any questions, please contact [support@wuji.tech](mailto:support@wuji.tech).
bl-odoo 0.3.3
A command-line tool for managing Odoo dependencies.
Requires Python: >=3.9

# bl

## Why BL

Because `ak` is a bit slow and I was tired of waiting around

## Install

`pipx install bl-odoo`

## Usage

### Build

```bl build -c <path_to_spec.yaml> -z <path_to_frozen.yaml> -j <concurrency>```

#### Params
* `path_to_spec.yaml` should be the path to your spec (default: spec.yaml)
* `path_to_frozen.yaml` should be the path to your spec (default: frozen.yaml)
* `concurrency` number of module clone simultaneously (default: 28)

#### How it looks
<img width="1683" height="756" alt="bl_build" src="https://github.com/user-attachments/assets/22fc1565-3a54-4f57-9b85-a11263b9b536" />

### Freeze

```bl freeze -c <path_to_spec.yaml> -z <path_to_frozen.yaml> -j <concurrency>```

#### Params
* `path_to_spec.yaml` should be the path to your spec (default: spec.yaml)
* `path_to_frozen.yaml` should be the path to your spec (default: frozen.yaml)
* `concurrency` number of module clone simultaneously (default: 28)

## Odoo is taking a really long time to clone

Yes !

You can add a locales entry to your odoo repo in `spec.yaml` like so:
```
odoo:
  modules:
    - account
    ...
  remotes:
    odoo: https://github.com/odoo/odoo
  merges:
    - odoo 14.0
  locales:
    - fr
    - en
```
It will only download the french and english translation instead of all of them
- without locales: 849MB and 40 seconds fresh build
- with locales fr, en: 169MB and 27 seconds fresh build

## Benchmarks

### Ak benchmarks
#### Fresh install
<img width="1462" height="347" alt="ak_bench_cold" src="https://github.com/user-attachments/assets/e29cd3d9-831c-43c1-8f29-e040ebee5740" />

#### Already cloned once
<img width="1419" height="356" alt="ak_bench_hot" src="https://github.com/user-attachments/assets/47b5756e-efe1-4272-82b7-e160f73af1be" />

### Bl benchmarks
#### Fresh install
<img width="1335" height="343" alt="bl_bench_cold" src="https://github.com/user-attachments/assets/a64ba1c4-17bd-4017-acfd-5749df505f50" />

#### Already cloned once
<img width="1373" height="342" alt="bl_bench_hot" src="https://github.com/user-attachments/assets/b11e60c2-368b-496c-bc88-f5a765f44bfe" />

### Results
|Type| AK | BL |
|----|----|----|
|Cold| ~100s | 2 - 10x faster |
|Hot| 3-20s | 2 - 10x faster |
chatterbot-corpus 1.3.2
A machine readable multilingual dialog corpus.
Requires Python: <4.0,>=3.9
Keywords: chatterbot, dialog, language, corpus

# ChatterBot Language Training Corpus

[![Package Version](https://img.shields.io/pypi/v/chatterbot-corpus.svg)](https://pypi.python.org/pypi/chatterbot-corpus/)

These modules are used to quickly train ChatterBot to respond to various inputs in different languages.
Although much of ChatterBot is designed to be language independent, it is still useful to have these
training sets available to prime a fresh database and make the variety of responses that a bot can yield
much more diverse.

All training data contained within this corpus is user contributed.

## Documentation

Documentation is available at:
http://corpus.chatterbot.us/

## Content Quality

We strive for factual correctness, proper grammar, and spelling in all corpus content. However, as this is a community-contributed project, there may be occasional mistakes or inaccuracies. If you find any errors or would like to contribute improvements, please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines on how to help.

If you are interested in contributing support for a new language please create a pull request. Additions are welcomed!

# Create your own Corpus Training data

Chatterbot is a very flexible and dynamic chatbot that you easily can create your own training data and structure.

Create or copy an existing .yml file and put that file in a existing or a new directory you created under `chatterbot_corpus\data\<NEW DIRECTORY>`
Edit that file with any text editor that you like to work with.

In the beginning of the file you set one or two categories.
```
categories:
- myown
- my own categories
````

Then can you start your actual training conversation data.

```
conversations:
- - Hello
  - Hello
- - Hi
  - Hello
```

# Unit Testing

> “A true professional does not waste the time and money of other people by handing over software that is not reasonably free of obvious bugs; that has not undergone minimal unit testing; that does not meet the specifications and requirements; that is gold-plated with unnecessary features; or that looks like junk.”
> 
> – Daniel Read

```bash
python -Wonce -m unittest discover -s tests -v
```