Metadata-Version: 2.1
Name: mltraq
Version: 0.0.60
Summary: Open source experiment tracking API with ML performance analysis.
Home-page: https://mltraq.com/
License: BSD-3
Author: Michele Dallachiesa
Author-email: michele.dallachiesa@sigforge.com
Requires-Python: >=3.8.0,<3.11
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Provides-Extra: complete
Provides-Extra: dask
Provides-Extra: pgsql
Requires-Dist: cloudpickle (>=2.2.0,<3.0.0)
Requires-Dist: colorama (>=0.4.6,<0.5.0)
Requires-Dist: dask[complete] (>=2022.11.0,<2023.0.0); extra == "dask" or extra == "complete"
Requires-Dist: ipywidgets (>=8.0.2,<9.0.0); extra == "complete"
Requires-Dist: joblib (>=1.1.1,<2.0.0)
Requires-Dist: pandas (>=1.4.4,<2.0.0)
Requires-Dist: psycopg2-binary (>=2.9.5,<3.0.0); extra == "pgsql"
Requires-Dist: scikit-learn (>=1.1.3,<2.0.0); extra == "complete"
Requires-Dist: sqlalchemy (>=1.4.44,<2.0.0)
Requires-Dist: sqlalchemy-utils (>=0.38.3,<0.39.0)
Requires-Dist: tabulate (>=0.9.0,<0.10.0); extra == "complete"
Requires-Dist: tqdm (>=4.64.1,<5.0.0)
Requires-Dist: ulid-py (>=1.1.0,<2.0.0)
Project-URL: Repository, https://github.com/elehcimd/mltraq
Description-Content-Type: text/markdown

<p align="center">
<img width="33%" height="33%" src="https://mltraq.com/assets/img/logo-black.svg" alt="MLTRAQ Logo">
</p>

<p align="center">
<img src="https://www.mltraq.com/assets/img/badges/test.svg" alt="Test">
<img src="https://www.mltraq.com/assets/img/badges/coverage.svg" alt="Coverage">
<img src="https://www.mltraq.com/assets/img/badges/python.svg" alt="Python">
<img src="https://www.mltraq.com/assets/img/badges/pypi.svg" alt="PyPi">
<img src="https://www.mltraq.com/assets/img/badges/license.svg" alt="License">
<img src="https://www.mltraq.com/assets/img/badges/code-style.svg" alt="Code style">
</p>

---

Open source **experiment tracking API** with **ML performance analysis** to build better models faster, facilitating collaboration and transparency within the team and with stakeholders.

---

* **Documentation**: [https://www.mltraq.com](https://www.mltraq.com)
* **Source code**: [https://github.com/elehcimd/mltraq](https://github.com/elehcimd/mltraq)

---

## Key features

* **Fast and efficient**: start tracking experiments with a few lines of code.
* **Distributed**: work on experiments independently and upstream them for sharing.
* **Accessible**: Storage on SQL tables accessible with SQL, Pandas and Python API.
* **Structured types**: track Numpy arrays, Pandas dataframes, and series.
* **Parallel execution**: define and execute experiment pipelines with parameter grids.
* **Light checkpointing**: save time by reloading and continuing your experiments anywhere.
* **Steps library**: enjoy pre-built steps for tracking, testing, analysis and reporting.

## Requirements

* **Python >=3.8**
* **SQLAlchemy**, **Pandas**, and **Joblib** (installed as dependencies)

## Installation

```
pip install mltraq
```

## License

This project is licensed under the terms of the [BSD 3-Clause License](https://mltraq.com/license).


