Metadata-Version: 2.1
Name: sedpack
Version: 0.0.5
Summary: General ML dataset package
Author: Elie Bursztein, Karel Král, Jean-Michel Picod
License: Apache License 2.0
Project-URL: Homepage, https://security-and-privacy-group-research.googlesource.com/sedpack_prototype
Project-URL: Bug Tracker, https://security-and-privacy-group-research.googlesource.com/sedpack_prototype
Keywords: machine learning,dataset
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Framework :: Jupyter
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: aiofiles
Requires-Dist: asyncstdlib
Requires-Dist: flatbuffers
Requires-Dist: lz4
Requires-Dist: numpy
Requires-Dist: perfcounters
Requires-Dist: pydantic
Requires-Dist: pytest
Requires-Dist: pytest-asyncio
Requires-Dist: schema
Requires-Dist: semver
Requires-Dist: tabulate
Requires-Dist: tensorflow
Requires-Dist: termcolor
Requires-Dist: tqdm

# Dataset library prototype

Sedpack: scalable and efficient data packing

This is a prototype of a dataset library. Mainly refactored from the [SCAAML](https://github.com/google/scaaml) project.

## Available components

- TODO

## Install

### Dependencies

To use this library you need to have a working version of [TensorFlow 2.x](https://www.tensorflow.org/install) and a version of Python >=3.8.

### Dataset install

#### Development install

1. Clone the repository: `git clone https://security-and-privacy-group-research.googlesource.com/dataset_lib_prototype`
2. Install dependencies: `python3 -m pip install --require-hashes -r requirements.txt`
3. Install the package in development mode: `python3 -m pip install --editable .` (short `pip install -e .` or legacy `python setup.py develop`)

### Update dependencies

Make sure to have: `sudo apt install python3 python3-pip python3-venv` and
activated the virtual environment.

Install requirements: `pip install --require-hashes -r base-tooling-requirements.txt`

Update: `pip-compile requirements.in --generate-hashes --upgrade` and commit requirements.txt.

#### Package install

`pip install TODO(package name)`

### Tutorial

TODO provide instructions how to use this package.

## Disclaimer

This is not an official Google product.
