BI-Vital Python Library

bivital is the official tool-chain for working with BI-Vital data in Python.
It stream-lines everything from project setup to labelling and makes your workflows reproducible – whether you prefer a quick CLI call or an interactive Jupyter notebook.

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✨ Main capabilities

Area	What you can do
Project management	Create a clean on-disk project folder tree for multi-series studies (bvtool project)
Data import	Import raw CSV records from the hard drive or directly from the BI-Vital hardware and sort them automatically by device ID. (bvtool data)
Series handling	Group measurements into logical blocks – perfect for cross-day sessions (bvtool series)
Label workflow	Attach time-stamped labels (activities, events, anomalies) via CLI or notebook helpers (bvtool label)
CLI everywhere	One Swiss-army-knife command: bvtool – ideal for scripts & head-less servers
Notebook ready	Native pandas/numpy objects make it easy to pass data to your own ML pipeline or use other libraries such as Neurokit2

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🐍 Installation

The package is published on PyPI: PyPI - bivital.
Please refer to the README in the repository for detailed installation notes.

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▶️ Usage

The full user manual can be found in the official Python library repository.

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💡 Examples

Hands-on notebooks live in the src/bivital/example/ folder of the
official repository — perfect to copy-paste and adapt to your own project:

Example	What it shows
basic_example.ipynb	Create a project, import BI-Vital CSV data, and plot ECG + heart rate.
data_and_label_interpolate_example.ipynb	Demonstrates attaching labels and performing time-aligned interpolation of signals + labels.
time_index_handling_example.ipynb	Shows advanced handling of time indices when working with multi-series data.

→ Browse them at py_bivital/examples