semvec/pypi-packages huggingface dataset:
ctao-datapipe 0.3.2
CTAO Data Processing Pipeline Software
Requires Python: >=3.12

# CTAO Data Processing Pipeline Subsystem

This package provides the software and workflow definitions for the [CTAO][1]
_Data Processing and Preservation System_ (DPPS) **Data Processing Pipeline**
subsystem (DataPipe). It is responsible for transforming raw (DL0) observed and
simulated data products produced by the observatory into "science-ready" data
products (DL3), including reconstructed event lists and instrumental response
functions.

- [Documentation][2]
- [Code Repository][3]
- [PyPI: ctao-datapipe](https://pypi.org/project/ctao-datapipe/)

[1]: https://www.ctao.org "CTAO website"
[2]: http://cta-computing.gitlab-pages.cta-observatory.org/dpps/datapipe/datapipe/latest/ "DataPipe documentation"
[3]: https://gitlab.cta-observatory.org/cta-computing/dpps/datapipe/datapipe "DataPipe code"
logie 0.2.3
로그 활용 패키지
Requires Python: >=3.7

# Install
```bash
pip install logie
```

# 개요

Python 기본 logging 모듈을 사용할 때마다 매번 formatter, handler, 파일 분리 등을 설정하는 과정을 생략하고자 편의성 함수로 그 과정을 압축하여 제공하는 로그 생성 유틸성 라이브러리

# Features

| 함수명                                                       | 목적                                     |
| ------------------------------------------------------------ | ---------------------------------------- |
| [get_logger](https://github.com/Kim-YoonHyun/logie/blob/master/docs/get_logger.md) | log 생성                                 |
| [log_sort](https://github.com/Kim-YoonHyun/logie/blob/master/docs/log_sort.md) | 생성된 rollover .log 파일 폴더 트리 정리 |

# version

## ver 0.2.2
- docsutils 추가

## ver 0.2.0
- 코드 내부 @log 주석의 내용을 추출하고 이를 md로 바꾸는 로깅 프로세스를 수행하는 sourceutils 추가

## ver 0.1.7
- rollover 시 생성되는 log 파일을 특정 기간 기준 삭제하는 함수 log_del 추가

## ver 0.1.7.1 

- docs 추가

## ver 0.1.7.2 
- log_path 설정 안할시 자동으로 작업 디렉토리가 되도록 수정

## ver 0.1.7.3

- log_del 에 print 추가
- README.md 내용 갱신

## ver 0.1.6
- log 생성시 log_id 를 반드시 지정하도록 변경
- log handler 를 중복 생성하지 않도록 설정하여 log 기록 중첩을 방지
## ver 0.1.5 
- log 찍을 시 console display 추가
log 생성용 모듈
fast-scaffold 0.2.0
CLI para gerar scaffolding de projetos FastAPI
Requires Python: >=3.10
Keywords: fastapi, cli, scaffold, scaffolding, code-generator, typer, backend, api

# fast-scaffold 🚀

CLI to generate **FastAPI project scaffolding** in a fast, standardized, and extensible way.

`fast-scaffold` creates the initial structure of a FastAPI project using Mako templates, allowing for easy evolution into multiple types of scaffolds in the future.

---

## ✨ Features

- 📦 Simple and fast CLI
- ⚡ Generate FastAPI projects in seconds
- 🧱 Template-based structure (Mako)
- 🧩 Easy to extend for new scaffolds
- 🐍 Compatible with Python 3.10+

---

## 📦 Installation

### Using pipx (recommended for CLIs)

```bash
pipx install fast-scaffold
```

Or using pip:

```bash
pip install fast-scaffold
```

## 🚀 Quick Start

Create a new FastAPI project:

```bash
fast-scaffold project init my-api
```

This will generate the project structure in the current directory:

```text
my-api/
├── pyproject.toml
├── README.md
└── app/
    └── main.py
```

## 🧠 How it works

fast-scaffold utilizes Mako templates located within the package:

```text
fast_scaffold/
└── templates/
    └── project/
        ├── pyproject.toml.mako
        ├── README.md.mako
        └── app/
            └── main.py.mako
```

## 🛠️ Local Development

Clone the repository and install the dependencies:

```bash
poetry install
```

Run the CLI locally:

```bash
poetry run fast-scaffold project init my-api
```

## 📄 Requirements

* Python >= 3.10
* Poetry (for development)
* pipx (recommended for global use)


## 🤝 Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

##📜 License

MIT License
vilovskiy 0.1.0
Simplified Telegram reporting library for Telethon
Requires Python: >=3.7
Keywords: telegram, telethon, report, moderation, vilovskiy, botnet, telegrambotnet

# Vilovskiy 📨

Упрощенная библиотека для отправки жалоб в Telegram через Telethon.

## Установка

```bash
pip install vilovskiy
adtf 1.1.1
ADTF python module
Requires Python: >=3.9

ADTF Python Package
===================

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

### Binary Packages

Binary packages are provided for Linux (x86_64 and aarch64) and Windows (x86_64) for Python versions 3.9 and up.

```bash
pip install adtf
```

### Building from the source distribution

If you cannot obtain a binary package for your platform/python version you can build the package from source.
You therefore need:

- a working C/C++ compiler toolchain,
- an installed **ADTF runtime package** and an installed **ADTF sdk package** (both at least version `3.21.0`).

#### Linux

```bash
adtf_sdk_DIR="<path to your ADTF sdk package>" adtf_runtime_DIR="<path to your ADTF runtime package>" pip install adtf
```

#### Windows

```cmd.exe
cmd /C (set adtf_sdk_DIR="<path to your ADTF sdk package>" && set adtf_runtime_DIR="<path to your ADTF runtime package>" && pip install adtf)
```

Python Modules
-------

This package provides the following modules:

- [adtf](doc/adtf_python_module.md)
- [adtf_file](doc/adtf_file_python_module.md)

ADTF File Plugins
-------

This packlage provides the following ADTF File plugins:

- [adtf_file_python_processor](doc/adtf_file_python_processor.md)

License
-------

This package uses the [MPL-2.0](LICENSE.md) license.

Release Notes
-------------

The release notes can be found at [RELEASENOTES.md](RELEASENOTES.md).
pylhc 0.8.3
An accelerator physics script collection for the OMC team at CERN.
Requires Python: >=3.10

# <img src="https://raw.githubusercontent.com/pylhc/pylhc.github.io/master/docs/assets/logos/OMC_logo.svg" height="28" alt="omc3 logo"> PyLHC Tools

[![Tests](https://github.com/pylhc/PyLHC/actions/workflows/coverage.yml/badge.svg?branch=master)](https://github.com/pylhc/PyLHC/actions/workflows/coverage.yml)
[![GitHub last commit](https://img.shields.io/github/last-commit/pylhc/PyLHC.svg?style=popout)](https://github.com/pylhc/PyLHC/)
[![PyPI Version](https://img.shields.io/pypi/v/PyLHC?label=PyPI&logo=pypi)](https://pypi.org/project/PyLHC/)
[![GitHub release](https://img.shields.io/github/release/pylhc/PyLHC.svg?style=popout)](https://github.com/pylhc/PyLHC/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.5643602.svg)](https://doi.org/10.5281/zenodo.5643602)

This package provides tools for particle accelerator physics complementing the optics measurement analysis tools of the [omc3 package](https://github.com/pylhc/omc3).
It is a collection of useful scripts for the Optics Measurements and Corrections team (OMC) at CERN, with functionality for data analysis, corrections calculation, simulations management and machine information extraction.

## Documentation

- Autogenerated docs via `Sphinx` can be found at <https://pylhc.github.io/PyLHC/>.
- General documentation of the OMC-Team is located at <https://pylhc.github.io/>

## Installing

This package is `Python 3.7+` compatible, and can be installed through `pip`:

```bash
python -m pip install pylhc
```

After installing, scripts can be run with either `python -m pylhc.SCRIPT --FLAG ARGUMENT` or by calling the Python files directly.

For development purposes, we recommend creating a new virtual environment and installing from VCS in editable mode with all extra dependencies:

```bash
git clone https://github.com/pylhc/pylhc
python -m pip install --editable "pylhc[all]"
```

**Note:** Some scripts access functionality only available on the CERN Technical Network.
To use those, you should make sure to install the relevant extra dependencies with `python -m pip install "pylhc[cern]"`.

## Functionality

- `Forced DA Analysis` - Script to analyze forced DA. ([**forced_da_analysis.py**](pylhc/forced_da_analysis.py))
- `Machine Settings Info` - Prints an overview over the machine settings at a given time. ([**machine_settings_info.py**](pylhc/machine_settings_info.py))
- `KickGroup Information` - Get information about KickGroups. ([**kickgroups.py**](pylhc/kickgroups.py))
- `BSRT Logger` and `BSRT Analysis` - Saves data coming straight from LHC BSRT FESA class and allows subsequent analysis. ([**bsrt_logger.py**](pylhc/bsrt_logger.py) & [**bsrt_analysis.py**](pylhc/bsrt_analysis.py) )
- `BPM Calibration Factors` - Compute the BPM calibration factors using ballistic optics. Two methods are available: using the beta function and using the dispersion. ([**bpm_calibration.py**](pylhc/bpm_calibration.py))

## License

This project is licensed under the `MIT` License - see the [LICENSE](LICENSE) file for details.
yoco 1.3.0
Minimalistic YAML-based configuration system
Requires Python: >=3.8

# YOCO
[![PyPI Release](https://github.com/roym899/yoco/actions/workflows/publish_release.yaml/badge.svg)](https://github.com/roym899/yoco/actions/workflows/publish_release.yaml) [![PyTest](https://github.com/roym899/yoco/actions/workflows/pytest.yaml/badge.svg)](https://github.com/roym899/yoco/actions/workflows/pytest.yaml) [![Docs](https://github.com/roym899/yoco/actions/workflows/build_docs.yaml/badge.svg)](https://github.com/roym899/yoco/actions/workflows/build_docs.yaml)

YOCO is a minimalistic YAML-based configuration system for Python.
Visit the [YOCO documentation](https://roym899.github.io/yoco/) for detailed usage instructions and API reference.


## Installation
```bash
pip install yoco
```

## Development
- Use `pip install -e .` to install the package in editable mode
- Use `pip install -r requirements-dev.txt` to install dev tools
- Use `pytest -rf --cov=yoco --cov-report term-missing tests/` to run tests and check code coverage
- Use `mkdocs serve --livereload` to test docs locally