semvec/pypi-packages huggingface dataset:
lapyrinth 1.17.1
A program capable of creating mazes with many different algorithms and solving them with different pathfinders.
Requires Python: >=3.10
Keywords: maze, pathfinding, algorithm, labyrinth, pathfinder, maze generator

This Mazer Maker Solver made entirely in Python is a program where you can generate maze with many different algorithm and solving them with different pathfinders. Nothing more, nothing less. More info at https://github.com/Pietot/Lapyrinth
good-dev 0.1.1
Add your description here
Requires Python: >=3.12.8

# good-dev

Development tools and CLI utilities for managing good-* packages.

## Installation

```bash
pip install good-dev
```

## Features

### Dependency Explorer

good-dev includes a comprehensive dependency exploration toolset to help you discover functionality within your existing dependencies before adding new ones.

#### Commands

**Tree View**
```bash
# Show dependency tree for a specific package
good-dev packages tree requests --max-depth 3

# Show dependency tree for current project
good-dev packages tree
```

**Search Dependencies**
```bash
# Search for functionality across all dependencies
good-dev packages search "json" --type function

# Search in a specific package
good-dev packages search "parse" --package urllib3 --type class
```

**API Discovery**
```bash
# List all APIs exported by a package
good-dev packages api requests

# Filter APIs by pattern
good-dev packages api json --filter "dump"
```

**Community Explorer**
```bash
# Find packages that share dependencies
good-dev packages community fastapi pydantic --min-overlap 2

# Discover packages in the data science ecosystem
good-dev packages community pandas numpy --limit 20
```

### Configuration Management

```bash
# Manage application configuration
good-dev config set my_key my_value
good-dev config get my_key
```

### Package Analysis

```bash
# Get reverse dependencies for packages
good-dev packages reverse-dependencies requests typer
```

### Run Utilities

```bash
# Execute arbitrary Python functions
good-dev run path.to.module:function --arg1 value1
```

## Development

This package is part of the good-libraries monorepo. To contribute:

1. Clone the repository
2. Navigate to `libs/good-dev`
3. Install dependencies with `uv sync`
4. Run tests with `uv run pytest`

## Dependencies

- `typer`: CLI framework
- `rich`: Beautiful terminal formatting
- `httpx`: HTTP client
- `cashews`: Caching library
- `loguru`: Logging
- And more...
upwork-cli 0.1.0
Automate and streamline your Upwork freelancer workflow using the Upwork API.
Requires Python: >=3.9
Keywords: api, developer, freelancer, python, upwork, upwork-api, upwork-python

<div align="center">
  <img src="assets/upwork.svg" alt="BitByteLab Logo" height="100">
 

**Upwork API Automation Toolkit for Freelancers**  
Automate and streamline your Upwork freelancer workflow using the Upwork API directly from the terminal.

[![Release](https://img.shields.io/github/v/tag/rsmahmud/upwork-cli)](https://github.com/rsmahmud/upwork-cli/tag)
[![Platforms](https://img.shields.io/badge/platform-windows%20%7C%20macOS%20%7C%20linux-blue)]()
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE)
[![Python](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://www.python.org/)
[![PyPI](https://img.shields.io/badge/PyPI-upwork-cli-lightgrey.svg)](https://pypi.org/project/upwork-cli)

</div>

Upwork API Automation Toolkit for Freelancers
=============================================

This Python package helps Upwork freelancers automate their daily workflows using the official Upwork API. It is designed to boost efficiency and reduce manual effort by providing programmable access to common tasks and events on the platform.

Features:
- Fetch and display public reviews from your Upwork profile for your personal portfolio
- Set up real-time alerts for:
  - New messages from clients with active contracts
  - Invitations to interview
  - General inbox messages
- Periodically scan job posts using custom filter logic and notify you with relevant links
- Retrieve and monitor personal data such as:
  - Earnings
  - Work diary
- Automate common actions via the command line

Whether you're an experienced freelancer or just starting out, this tool helps you stay responsive, informed, and efficient — all while remaining compliant with Upwork’s terms of service.

---
Setup Requirement
=================

1. Get an API Key from upwork https://www.upwork.com/developer/keys/apply
2. Set an environment variable `export UPWORK_API_KEY=<your-upwork-api-key>`
2. Set an environment variable `export UPWORK_API_SECRET=<your-upwork-api-secret>`
3. Install this package from pypi `pip install upwork-cli`

---
Usage
=====

`upwork-cli` or `upcli` can be used to run this tool from terminal.

use `upcli --help` to view the available options and commands.

---
## 🧪 Project Structure

<pre>
<!-- dir-tree-start -->
📁 upwork-cli/
├── 📁 src/
│   └── 📁 upwork_cli/
│       ├── __init__.py
│       ├── __main__.py
│       ├── __init__.py
├── 📁 examples/
│   └── sample_usage.py
├── 📁 tests/
│   └── test.py
├── ⚙️ .env
├── 🚫 .gitignore
├── 📃 LICENSE
├── 📃 LICENSE.txt
├── ⚙️ pyproject.toml
├── 📝 README.md
└── ⚙️ ruff.toml
<!-- dir-tree-end -->
</pre>

---

## 📄 License

Licensed under the [MIT License](LICENSE).

---

## 🤝 Contributing

- Open an issue for ideas, bugs, or suggestions.
- Pull requests are welcome!

---

## 🔗 Links

- 📦 [PyPI](https://pypi.org/project/upwork-cli)
- 🛠️ [Issues](https://github.com/rsmahmud/upwork-cli/issues)
- ⭐ [Star on GitHub](https://github.com/rsmahmud/upwork-cli)

---
taktkit 0.1.0
Style and asset kit for Flask/Django projects with a focus on visual agility

# 📦 Taktkit

**Taktkit** is a lightweight JavaScript toolkit to build beautiful, data-driven dashboards with minimal configuration. Designed for flexibility and fast integration, Taktkit provides a set of utilities to render charts, handle JSON datasets, and build responsive visualizations for agile metrics, product tracking, or general analytics.

---

## 🚀 Features

- 📊 Render bar, pie, and line charts with zero boilerplate
- 🎨 Custom color support per category/year/status
- 📁 Load data directly from JSON embedded in `<script>` tags or fetched dynamically
- 🔍 Smart support for dashboards with filters
- 🧩 Modular and framework-agnostic (no dependencies)
- 🌐 Works with Flask, Django, Express, static HTML, etc.

---

## 📁 Installation

Include via link tag:
```html
<link rel="stylesheet" href="taktkit/css/taktkit.min.css">

Include via script tag:

```html
<script type="module" src="taktkit/js/taktkit.min.js"></script>
megakino 0.6.1
A Megakino Downloader!
Requires Python: >=3.8

# Megakino Downloader

## Description
I created this tool to download and watch several movies or series from megakino.video!
This tool can download your favorite movies and series directly and you can also watch them with your friends
with Syncplay! 

## Instruction
Just run this command to install the tool!
(Make sure you have python installed!)
```shell
pip install megakino
```
To start the menu type:
```shell
megakino
```
Also you have one option right now for specifying a path:
```shell
megakino --path "E:\Videos"
```

## Dependencies/Credits
1. **[yt-dlp](https://pypi.org/project/yt-dlp/)** for downloading
2. **[requests](https://pypi.org/project/requests/)** for fetching html pages
3. **[bs4](https://pypi.org/project/beautifulsoup4/)** for searching in these pages
4. **[fake_useragent](https://pypi.org/project/fake_useragent/)** for dynamic generated user-agents
5. **[windows-curses](https://pypi.org/project/windows-curses/)** for the windows version of curses
6. **[mpv](https://github.com/mpv-player/mpv.git)** for playing video content (Needs to be installed)
7. **[syncplay](https://github.com/Syncplay/syncplay.git)** for syncing videos for friends (Needs to be installed)

## ⚠️ Disclaimer
I provide this tool for educational and informational purposes only.
You are solely responsible for how you use it.
Any actions taken using this tool are entirely your own responsibility.
I do not condone or support illegal use.

## Support 
If you need any help you can open an issue or contact me via discord ``Tmaster055``!
vspyplugin 1.4.5
Package for simplifying writing VapourSynth "plugins" in python.
Requires Python: >=3.12

# vs-pyplugin

### Package for simplifying writing VapourSynth "plugins" in python.

<br>

Backends wrapper classes and helper functions for python plugins.

Original concept this is inspired from is by [WolframRhodium](https://github.com/WolframRhodium/muvsfunc/tree/master/Collections).

For support you can check out the [JET Discord server](https://discord.gg/XTpc6Fa9eB). <br><br>

## How to install

Install `vspyplugin` with the following command:

```sh
pip install vspyplugin
```

Or if you want the latest git version, install it with this command:

```sh
pip install git+https://github.com/Jaded-Encoding-Thaumaturgy/vs-pyplugin.git
```
py-pane 0.11.3
A modern dataclass & data conversion library, focused on speed and expressiveness.
Requires Python: >=3.9
Keywords: dataclass, validation, parsing, conversion

# pane

`pane` is a modern Python library for dataclasses and data conversion, aiming
for speed and expressiveness.

[![][ci-badge]][ci-url] [![][commit-badge]][commit-url] [![][pypi-badge]][pypi-url] [![][docs-stable-badge]][docs-stable-url] [![][docs-dev-badge]][docs-dev-url]

`pane` draws heavy inspiration from [Pydantic][pydantic] (among others), but its goals
are quite different. For example, `pane` has first-class conversion to and from
all JSON datatypes, not just mappings (and no '__root__' hacks necessary).
In this sense `pane` is a library for general data conversion & validation,
while Pydantic is a dataclass-first library. In addition, `pane` is stricter
than Pydantic in several cases. For instance, `pane` [will not attempt to coerce
`3.14` or `"3"` to an integer](https://github.com/pydantic/pydantic/issues/578).

`pane` is designed to be used to create complex declarative configuration languages
in formats like JSON, TOML, and YAML. This requires full support for complex, nested
types like `t.Union[int, t.Tuple[int, str], list[int]]`. It also requires
useful error messages:

```python
>>> pane.convert('fail', t.Union[int, t.Tuple[int, str], list[int]])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "pane/convert.py", line 489, in convert
    return from_data(data, ty)
           ^^^^^^^^^^^^^^^^^^^
  File "pane/convert.py", line 484, in from_data
    return converter.convert(val)
           ^^^^^^^^^^^^^^^^^^^^^^
  File "pane/convert.py", line 128, in convert
    raise ConvertError(node)
pane.convert.ConvertError: Expected one of:
- an int
- tuple of length 2
- sequence
Instead got `fail` of type `str`
```

## Features

`pane` is a work in progress. The following is a roadmap of features:

| Feature                      | State   |
| :--------------------------- | :----   |
| Basic type conversions       | Done    |
| Numeric array types (numpy)  | Done    |
| Sum & product type support   | Done    |
| Tagged unions                | Partial |
| 'Flattened' fields           | Planned |
| Basic dataclasses            | Done    |
| Dataclass helpers            | Partial |
| Generic & inherited dataclasses | Done |
| Parameter aliases & renaming | Done    |
| Arbitrary validation logic   | Done    |
| Schema import/export         | Not planned |

[pydantic]: https://github.com/pydantic/pydantic
[ci-badge]: https://github.com/hexane360/pane/workflows/Tests/badge.svg
[ci-url]: https://github.com/hexane360/pane/actions?query=workflow%3ATests
[docs-dev-badge]: https://img.shields.io/badge/docs-dev-blue
[docs-dev-url]: https://hexane360.github.io/pane/dev/
[docs-stable-badge]: https://img.shields.io/badge/docs-stable-blue
[docs-stable-url]: https://hexane360.github.io/pane/latest/
[commit-badge]: https://img.shields.io/github/last-commit/hexane360/pane
[commit-url]: https://github.com/hexane360/pane/commits
[pypi-badge]: https://badge.fury.io/py/py-pane.svg
[pypi-url]: https://pypi.org/project/py-pane/
whatshap 2.8
phase genomic variants using DNA sequencing reads
Requires Python: >=3.9

.. image:: https://img.shields.io/pypi/v/whatshap.svg?branch=main
    :target: https://pypi.python.org/pypi/whatshap

.. image:: https://github.com/whatshap/whatshap/workflows/CI/badge.svg

.. image:: https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg
    :target: http://bioconda.github.io/recipes/whatshap/README.html

|

.. image:: https://github.com/whatshap/whatshap/raw/main/logo/whatshap_logo.png

|

WhatsHap
========

WhatsHap is a software for phasing genomic variants using DNA sequencing
reads, also called *read-based phasing* or *haplotype assembly*. It is
especially suitable for long reads, but works also well with short reads.


Features
========

  * Very accurate results (Martin et al.,
    `WhatsHap: fast and accurate read-based phasing <https://doi.org/10.1101/085050>`_)
  * Works well with Illumina, PacBio, Oxford Nanopore and other types of reads
  * It phases SNVs, indels and even “complex” variants (such as ``TCG`` → ``AGAA``)
  * Pedigree phasing mode uses reads from related individuals (such as trios)
    to improve results and to reduce coverage requirements
    (Garg et al., `Read-Based Phasing of Related Individuals <https://doi.org/10.1093/bioinformatics/btw276>`_).
  * WhatsHap is easy to install
  * It is easy to use: Pass in a VCF and one or more BAM files, get out a phased VCF.
    Supports multi-sample VCFs.
  * It produces standard-compliant VCF output by default
  * If desired, get output that is compatible with ReadBackedPhasing
  * Open Source (MIT license)


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

* We recommend you start with this book chapter for a concise introduction:
  `Read-Based Phasing and Analysis of Phased Variants with WhatsHap <https://doi.org/10.1007/978-1-0716-2819-5_8>`_
* `WhatsHap documentation online <https://whatshap.readthedocs.io/>`_
* `GitHub repository <https://github.com/whatshap/whatshap/>`_


Issue tracker
-------------
Please do not hesitate to use our `issue tracker <https://github.com/whatshap/whatshap/issues>`_ for bug reports and feature requests.
image-processing-by-rogergomes 0.0.2
primeiro-projeto
Requires Python: >=3.8

# package_name

Description. 
The package package_name is used to:
	Processing:
		-Histogram matching 
		-Structural Similarity
	Utils:
		-Read Image
		-Save Image
		-Plot Image
		-Plot Result
		-Plot Histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install package_name
```

## Usage

```python
from package_name.module1_name import file1_name
file1_name.my_function()
```

## Author
RogerGomes

## License
[MIT](https://choosealicense.com/licenses/mit/)
edea 0.8.4
KiCAD file format parser and tools
Requires Python: <4,>=3.11

# edea python library

The core python library and command line interface for the EDeA project.

## Documentation
[latest docs](https://edea-dev.gitlab.io/edea/latest/)

## Getting started
[Getting started](https://edea-dev.gitlab.io/edea/latest/getting_started.html)


## CHANGELOG
[CHANGELOG](https://edea-dev.gitlab.io/edea/latest/changelog.html)

## Developer documentation
[Developer docs](https://edea-dev.gitlab.io/edea/latest/dev.html)
Ligare.database 0.5.1
Libraries for working with databases.
Requires Python: >=3.10

# `Ligare.database`

Libraries for working with databases.

# SQLite Support

SQLite support is built into `Ligare.database`.

# PostgreSQL Support

Install `Ligare.database[postgres]` for production use or `Ligare.database[postgres-binary]` if your machine cannot compile [psycopg2](https://pypi.org/project/psycopg2/).