semvec/pypi-packages huggingface dataset:
sharedkernel 2.4.1
sharekernel is a shared package between all python projects

# SharedKernel
this is a shared kernel package

# Change Log
### Version 2.4.1
- Fix file validation
### Version 2.4.0
- Implement file validation
### Version 2.3.0
- Implement multipart uploader for S3
### Version 2.2.7
- add presigned url in s3 uploader
### Version 2.2.6
- implement api key
### Version 2.2.5
- add org_token to user_info Object
### Version 2.2.4
- make pagination response default values to None
### Version 2.2.3
- add paginate to mongo repository
### Version 2.2.2
- update on audit logging queries
- added is_audit to update_one parameters
### Version 2.2.1
- fixbug requirements
### Version 2.2.0
- implement Audit logging
### Version 2.1.2
- Update pydantic parse_object with model_validate
### Version 2.1.0
- Implement persian string normalizer
### Version 2.0.3
- Fix boto3 version
### Version 2.0.2
- Fix FastApi dependency
### Version 2.0.1
- Fix minor bugs
### Version 2.0.0
- Update pydantic version
- Delete vector databases
- Implement JsonStringModel
### Version 1.9.0
- Implement DataFormatConverter
### Version 1.8.0
- Implement persian number normalizer
### Version 1.7.3
- Add optional folder name for s3 uploader to save the file in
### Version 1.7.2
- Fix bug of to_diff_persian_date_time_string
### Version 1.7.1
- Update BaseDocument initial values
### Version 1.7.0
- Implement S3 Uploader
### Version 1.6.10
- Add updated_on to BaseDocument
- Update phonenumber normalizer
### Version 1.6.9
- Delete milvus
### Version 1.6.8
- Fix Date Converter Bug
### Version 1.6.7
- Fix bug and remove additional features
### Version 1.6.6
- Fix bug of phonenumber normalizer
### Version 1.6.5
- Update on the JWTBearer (Save decoded token in request state)
### Version 1.6.4
- Update normlizer package
### Version 1.6.3
- Fix minor bug in phone normalizer
### Version 1.6.2
- Minor update: normalize function name
### Version 1.6.1
- Minor update normalize functions
### Version 1.6
- Add phone number normalizer
### Version 1.5.2
- Add created_on to base_document
### Version 1.5.1
- fix mongo repository bug
### Version 1.5.0
- implement date converter
  -  example: فردا - دیروز - یک ماه قبل
### Version 1.4.5
- upgrade fastapi version
### Version 1.4.4
- Fix regex masking bugs
### Version 1.4.3
- Fix collection bug in MongoGenericRepository
### Version 1.4.2
- Fix minor bugs
### Version 1.4.1
- Fix minor bug in MongoGenericRepository
### Version 1.4.0
- Implement date convertor for jalali and georgian
### Version 1.3.0
- Implement Sentry For Log Exceptions
### Version 1.2.0
- Implement Regex Masking
# Create Package
    python3 -m pip install --upgrade build
    python3 -m build
    python3 -m pip install --upgrade twine
    python3 -m twine upload dist/*

# Pypi
pip install sharedkernel
gbdc 0.3.4
Extension Module for GBD

# GBDC: Global Benchmark Database, C++ Extension Module

[![Build-Test](https://github.com/Udopia/gbdc/actions/workflows/build_test.yml/badge.svg?branch=master)](https://github.com/Udopia/gbdc/actions/workflows/build_test.yml)

[GBDC](https://github.com/Udopia/gbdc) provides efficient implementations of functions for benchmark instance identification, instance feature extraction and instance transformation.
GBDC provides a command-line tool as well as the Python package `gbdc`.
The Python package `gbdc` is used by [Global Benchmark Database](https://github.com/Udopia/gbd).

## [Documentation](https://udopia.github.io/gbdc/doc/Index.html)

GBDC provides benchmark instance identifiers, feature extractors, and instance transformers for several problem domains, including propositional satisfiability (SAT) and optimization (MaxSAT), as well as Pseudo-Boolean Optimization (PBO).
A description of the supported domains, feature extractors, and instance transformers can be found in the [documentation](https://udopia.github.io/gbdc/doc/Index.html).

## Installation from PyPI
* Pre-built distributions for Linux and MacOS.
* Requires at least Python 3.8.0 (3.10.0 for Apple Silicon).
* Installation via `pip install gbdc`

## Installation from Source

* GBDC uses `libarchive` for reading from a large variety of compressed formats (in some systems provided by the package `libarchive-dev`).
* Some GBDC functions use an [IPASIR](https://github.com/biotomas/ipasir) SAT Solver. GBDC's build-system pulls the external SAT Solver [CaDiCaL](http://fmv.jku.at/cadical/) by A. Biere (MIT licensed).

### Steps:
1. **Install Dependencies** (libarchive, pybind, ninja)
   - For Ubuntu: `apt install libarchive-dev pybind11-dev ninja-build`
   - For macOS: `brew install libarchive pybind11 ninja`

2. Run `pip install . --user` in the repository directory.
<!-- #### Shipped Dependencies

* A copy of the command-line argument parser by P. S. Kumar [`argparse.h`](https://github.com/p-ranav/argparse) (MIT licensed) resides in the `lib` folder.

* A copy of the [MD5 hash](https://github.com/CommanderBubble/MD5) implementation by M. Lloyd (MIT licensed) resides in the `lib` folder. -->

<!-- ## Publications

* Gate feature extraction uses our gate recognition algorithm which is described in the following publications:

    * [*Recognition of Nested Gates in CNF Formulas* (SAT 2015, Iser et al.)](https://rdcu.be/czCr1)

    * [*Recognition and Exploitation of Gate Structure in SAT Solving* (2020, Iser)](https://d-nb.info/1209199122/34)

* The Python module `gbdc` is used in our project [GBD Benchmark Database](https://github.com/Udopia/gbd)

    * [*Collaborative Management of Benchmark Instances and their Attributes* (2020, Iser et al.)](https://arxiv.org/pdf/2009.02995.pdf) -->
pdmv-http-client 2.2.1
A HTTP client wrapper to handle authenticated requests to CERN internal applications
Requires Python: >=3.9

# PdmV HTTP Client

This project provides an HTTP client based on [requests](https://github.com/psf/requests) to handle authenticated requests to CERN
internal applications. Furthermore, it includes some clients to ease the interaction with the APIs of
PdmV applications. This version is a refactor of the old [McM Scripts](https://github.com/cms-PdmV/mcm_scripts) project, and it is published at
PyPI to be public available.

### How to use this package

#### Prerequisite

Create an isolated virtual environment using a Python version >= 3.9 like, for instance:

`python3.9 -m venv venv && source ./venv/bin/activate`

#### Development version

If you want to set up a development environment to contribute to this project:

Install `uv` and the required dependencies.

`pip install uv`

Set the current `venv` to use with `uv`:

`export UV_PROJECT_ENVIRONMENT="${VIRTUAL_ENV}"`

Install the packages via: `uv sync`

Run the test suite via:
`uv run pytest -s -vv`

> [!IMPORTANT]
> Make sure your execution environment has a valid Kerberos ticket to consume CERN services!

#### Build package

If you just want to use this package in your own project, install it via:

`pip install pdmv-http-client`

Make sure to remove the `sys.path.append(...)` statement, if you have them in your script, to avoid overloading old versions from CERN AFS.

### Examples

At the `examples/` folder, you will find some scripts explaining how to use the clients and the HTTP client.

### Priority change
* If you want to use priority-changing scripts or do anything else related to cmsweb, you'll have to use voms-proxy:
    * `voms-proxy-init -voms cms`
    * `export X509_USER_PROXY=$(voms-proxy-info --path)`
unforgettable 0.1.1
Unforgettable is a simple cache you can used for tiny repetitive executions.
Requires Python: >=3.11

# Unforgettable - v0.1.1

Unforgettable is a simple cache class you can used for tiny repetitive executions.

It uses a [temp dir](https://docs.python.org/3/library/tempfile.html) for each
execution.
### How to install and use

Install with `uv` or `pip`
```shell
uv add unforgettable
# or
pip unforgettable
```

Setting values:
```python
cache = unforgettable()

cache.set(content=code, cache_id=cache_id=cache_id)
```

Setting values:
```python
cache = unforgettable()

cached_code = cache.get(cache_id=cache_id)
```

Using your own folder for storing longer term cache:
```python
SIMPLE_CACHE_ROOT_DIR = os.getenv("SIMPLE_CACHE_ROOT_DIR", None)
cache = unforgettable(cache_folder=SIMPLE_CACHE_ROOT_DIR)
```

And you can clean the cache with:
```python
unforgettable.clean()
```

### Example of Usage

```python
import requests
from unforgettable import unforgettable

cache = unforgettable()

def my_request():
    url = "https://github.com/bouli/unforgettable"

    url_request_1 = requests_get(url) #no cache yet
    url_request_2 = requests_get(url) #with cache

def requests_get(url):
    cached_code = cache.get(cache_id=url)

    if cached_code is not None:
        print("You are using cached")
        return cached_code

    req = requests.get(url=url, timeout=5)
    if req.status_code != 200:
        return None

    code = req.content
    cache.set(content=code, cache_id=url)
    return code
```

## See Also

- Github: https://github.com/bouli/unforgettable
- PyPI: https://pypi.org/project/unforgettable/

## License
This package is distributed under the [MIT license](https://opensource.org/license/MIT).
enclaves 0.1.0
Add your description here
Requires Python: >=3.11

# enclaves

Initial PyPI package scaffold for `enclaves`, using `uv` for build and publish.

## Local workflow

```bash
uv build
uv publish
```

`uv publish` reads `UV_PUBLISH_TOKEN` automatically.

If your token is stored as `PYPI_TOKEN`, run:

```bash
export UV_PUBLISH_TOKEN="$PYPI_TOKEN"
uv publish
```

## TestPyPI

```bash
uv publish --publish-url https://test.pypi.org/legacy/
```
runtimes 0.1.0
Add your description here
Requires Python: >=3.11

# runtimes

Initial PyPI package scaffold for `runtimes`, using `uv` for build and publish.

## Local workflow

```bash
uv build
uv publish
```

`uv publish` reads `UV_PUBLISH_TOKEN` automatically.

If your token is stored as `PYPI_TOKEN`, run:

```bash
export UV_PUBLISH_TOKEN="$PYPI_TOKEN"
uv publish
```

## TestPyPI

```bash
uv publish --publish-url https://test.pypi.org/legacy/
```
ctk-markdown 0.1.1
Markdown Renderer for customtkinter
Requires Python: >=3.7

# ctk-markdown

![python](https://img.shields.io/badge/python-3.9%2B-blue)
![customtkinter](https://img.shields.io/badge/customtkinter-required-1f6feb)
![status](https://img.shields.io/badge/status-alpha-orange)
![PyPI - License](https://img.shields.io/badge/license-MIT-blue)

`ctk-markdown` is a **CustomTkinter** Markdown renderer based on `CTkTextbox`. It applies rich tags for headings, lists, tables, code blocks, and inline formatting.

## ✨ Features

- Single widget (`CTkMarkdown`) with Markdown rendering
- Headings, lists, blockquotes, tables, and code blocks
- Basic syntax highlighting for Python and JavaScript
- Theme-aware colors for light and dark appearance modes

## 📦 Installation

```bash
pip install ctk-markdown
```

## 🚀 Usage

```python
from ctk_markdown import CTkMarkdown
import customtkinter as ctk

app = ctk.CTk()
frame = ctk.CTkFrame(app)
frame.pack(fill="both", expand=True, padx=16, pady=16)

renderer = CTkMarkdown(frame)
renderer.pack(fill="both", expand=True)
renderer.set_markdown("""# Title\nText with *italic* and **bold**.""")

app.mainloop()
```

## 🧠 How it works

The widget inherits from `CTkTextbox`. Markdown parsing is done line by line and uses Tkinter text tags for styling. Theme colors are applied based on the current CustomTkinter appearance mode.

## 🧪 Run the demo

```bash
python example.py
```

## 🤝 Contributing

Contributions are welcome!

1. Fork the repo
2. Create a feature branch (`feature/my-change`)
3. Commit your changes
4. Open a Pull Request with a clear description

Ideas:
- More language grammars for code highlighting
- Image support
- Clickable links
gomath 0.0.5
A simple package of mathematics(beta test)
Requires Python: >=3.6

<h1 align="center">
gomaths
</h1>


<h2 align="center">
How to install 
</h2>

```python
pip install gomath
```

<h2 align="center">
Exemple
</h2>

```python
from gomath import *

calc = gomath.Calcul()



a = calc.pair(1, 2, 3, 4, 5, 6)

b = calc.multiplication(4, 2)

c = calc.AreaSquarre(2, 4)



print(a, b, c)
```
shells 0.1.0
Add your description here
Requires Python: >=3.11

# shells

Initial PyPI package scaffold for `shells`, using `uv` for build and publish.

## Local workflow

```bash
uv build
uv publish
```

`uv publish` reads `UV_PUBLISH_TOKEN` automatically.

If your token is stored as `PYPI_TOKEN`, run:

```bash
export UV_PUBLISH_TOKEN="$PYPI_TOKEN"
uv publish
```

## TestPyPI

```bash
uv publish --publish-url https://test.pypi.org/legacy/
```
tsccm 0.0.7
TSCCM (Tenable.SC CLI Manager) by LimberDuck

# TSCCM

**TSCCM** *(Tenable.SC CLI Manager)* by LimberDuck is a CLI tool which enables you to perform certain actions on Tenable.SC by (C) Tenable, Inc. via [Tenable.SC API](https://docs.tenable.com/tenablesc/api).

[![pepy - Downloads](https://img.shields.io/pepy/dt/tsccm?logo=PyPI)](https://pepy.tech/projects/tsccm) [![PyPI Downloads](https://static.pepy.tech/badge/tsccm/month)](https://pepy.tech/projects/tsccm)
[![Latest Release version](https://img.shields.io/github/v/release/LimberDuck/tsccm?label=Latest%20release)](https://github.com/LimberDuck/tsccm/releases) 
[![GitHub Release Date](https://img.shields.io/github/release-date/limberduck/tsccm?label=released&logo=GitHub)](https://github.com/LimberDuck/tsccm/releases)
[![License](https://img.shields.io/github/license/LimberDuck/tsccm.svg)](https://github.com/LimberDuck/tsccm/blob/main/LICENSE) [![Repo size](https://img.shields.io/github/repo-size/LimberDuck/tsccm.svg)](https://github.com/LimberDuck/tsccm) [![Code size](https://img.shields.io/github/languages/code-size/LimberDuck/tsccm.svg)](https://github.com/LimberDuck/tsccm) [![Supported platform](https://img.shields.io/badge/platform-windows%20%7C%20macos%20%7C%20linux-lightgrey.svg)](https://github.com/LimberDuck/tsccm)
<!-- [![PyPI - Downloads](https://img.shields.io/pypi/dm/tsccm?logo=PyPI)](https://pypi.org/project/tsccm/) -->


Main features
=============

Initial version of **TSCCM** lets you get Tenable.SC's:
* audit file list
* credential list  
* group list
* policy list
* role list
* active scan list
* scan result list
* server info
  * status
  * licensed IPs
  * version
* users list


How to
======

1. Install
    
    `pip install tsccm`

2. Run

    `tsccm`

Meta
====

Change log
----------

See [CHANGELOG].


Licence
-------

MIT: [LICENSE].


Authors
-------

[Damian Krawczyk] created **TSCCM** *(Tenable.SC CLI Manager)* by LimberDuck.

[Damian Krawczyk]: https://damiankrawczyk.com

[CHANGELOG]: https://github.com/LimberDuck/tsccm/blob/main/CHANGELOG.md
[LICENSE]: https://github.com/LimberDuck/tsccm/blob/main/LICENSE