semvec/pypi-packages huggingface dataset:
datarush 0.10.0
No-code data pipelines
Requires Python: >=3.11

# DataRush

DataRush is a no-code data pipeline framework that allows you to quickly build, execute, and manage data workflows through a visual interface or programmatic API.
## Key Features
- **Visual Interface**: Web-based UI built with Streamlit for building pipelines
- **Template System**: Reusable, versioned pipeline configurations
- **Rich Operation Library**: 30+ built-in operations for data processing
- **Custom Operations**: Extensible framework for implementing your own data operations
- **Multiple Execution Modes**: UI, CLI, and programmatic execution
- **Cloud Integration**: Native S3 support for data sources and sinks
- **Jinja2 Templating**: Dynamic, parametrizable pipelines with powerful template expressions


## Quick Start

- **[Getting Started](docs/GettingStarted.md)** - Get up and running with DataRush in minutes
- **[Configuration](docs/Configuration.md)** - Learn about environment variables and settings

## Core Concepts

- **[Operations](docs/Operations.md)** - Complete guide to all available data operations
- **[Operation Model Types](docs/OperationModelTypes.md)** - Reference for supported field types and UI elements
- **[Templates](docs/Templates.md)** - How to create and use reusable data pipeline templates

## Advanced Topics

- **[Advanced Usage](docs/AdvancedUsage.md)** - Jinja2 templating, custom operations, and advanced features
AGRemapUtils 1.0.5
Utility library for the Anime Game Remap (AGRemap) project
Requires Python: >=3.6

# AG Remap's Utilities

[![PyPI - Version](https://img.shields.io/pypi/v/AGRemapUtils?style=for-the-badge)](https://pypi.org/project/AGRemapUtils/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/AGRemapUtils?style=for-the-badge)](https://pypi.org/project/AGRemapUtils/)
[![Pepy Total Downloads](https://img.shields.io/pepy/dt/AGRemapUtils?style=for-the-badge)](https://pypi.org/project/AGRemapUtils/)

Common utility functions/classes used by different tools in the [AGRemap](https://github.com/nhok0169/Anime-Game-Remap) project
tex2image 0.1.6
A simple python library for converting latex snippets to images.
Requires Python: >=3.9

# tex2image

[![Documentation Status](https://readthedocs.org/projects/tex2image/badge/?version=latest)](https://tex2image.readthedocs.io/en/latest/?badge=latest)
[![PyPI Version](https://img.shields.io/pypi/v/tex2image.svg)](https://pypi.python.org/pypi/tex2image)

This is a simple library to generate images from tex snippets.

It uses the [standalone](https://ctan.org/pkg/standalone) latex package to
produce PDFs that are already set to an appropriate size, and then uses
[poppler](https://poppler.freedesktop.org/) to convert the PDF to an image.
You must make sure that `pdflatex` and `pdftoppm` are available for python to
execute.
turbojpeg-rpi 0.0.3
Python bindungs for libjpeg-turbo using pybind11
Requires Python: >=3.7

# turbojpeg-python

Python bindings for libjpeg-turbo using pybind11. It's using Version 3 of the TurboJPEG C API.

It implements the three functions `transform`, `compress` and `decompress`. For more details see the function docstrings or the TurboJPEG C API docs <https://rawcdn.githack.com/libjpeg-turbo/libjpeg-turbo/main/doc/html/group___turbo_j_p_e_g.html>

## Install

- `pip install turbojpeg`

## Example

Rotate JPEG file losslessly by 90 degrees.

```python
import turbojpeg

with open("image.jpg", "rb") as fr:
    img_data = fr.read()

# lossless rotation. fails if lossless rotation is not possible
# for example when the image dimensions are not multiples of 16
img_data_rot = turbojpeg.transform(img_data, op=turbojpeg.OP.ROT90)

with open("image-rotated.jpg", "xb") as fw:
    fw.write(img_data_rot)
```

Save random image as JPEG with arithmetic coding.

```python
import numpy as np
import turbojpeg
arr = np.random.randint(0, 256, (256, 256, 3), dtype=np.uint8)  # random color image
quality = 90
result = turbojpeg.compress(arr, quality, turbojpeg.SAMP.Y420, arithmetic=True)
with open("arithmetic.jpg", "xb") as fw:
    fw.write(result)
```

## Build

The Python `setup.py` expects the `libjpeg-turbo` binaries in `libjpeg-turbo-build`. You can either build it yourself or download precompiled binaries. For more details see <https://github.com/libjpeg-turbo/libjpeg-turbo/blob/main/BUILDING.md>.

GitHub actions CI builds wheels for Windows 32 and 64-bit, manylinux 64-bit, musllinux 64-bit and MacOS 64-bit. 32-bit Linux builds fail due some weird NASM error. Not all wheels are tested, since some of the test dependencies are not available for all platforms.

## Run tests

`python -m unittest discover -s tests`