PyDPEET 0.3.1

Python package to read, unify, and convert battery measurement data from arbitrary battery cyclers to Parquet files. This package also provides functions to process, evaluate, and visualise the standardised data.

PyDPEET - Fast and Easy Battery Data Unification, Processing, and Analysis

Contact

Feel free to open an issue on GitHub or use our email for direct enquiries: [e-mail].

Project Goals

PyDPEET is a Python package developed to handle battery measurement data from various cyclers and other measurement devices by

• converting input data into a standardised format using Pandas data frames,
• allowing users to merge multiple single tests into test series of one cell, and multiple test series into multi-cell measurement campaigns, and
• adding sequence info either by automatically synthesising from an existing schedule or automatically analysing in case of unknown measurement procedure.

Standardised data can then be analysed using various functions which add additional data columns to a data frame:

• power, energy, capacity,
• inner resistance,
• state of charge (SOC), state of health (SOH),
• OCV points, DVA and ICA,
• and more...

Processed data can be exported to highly efficient Parquet files to be stored and re-imported later -- or to CSV or XLSX formats to maintain legacy workflows.

Citing PyDPEET

Documentation

GitHub Pages

• PyDPEET homepage
• Installation
• API reference
• Examples
• Developer Guide

Installation

For Users

Please refer to the installation guide at our GitHub Pages.

For Developers

Please refer to the developer guide at our GitHub Pages.

Current Status

Roadmap

Contributing to PyDPEET

Reporting Issues

Request for Data Conversion

Development Guidelines

Please refer to the developer guide at our GitHub Pages.