CARP Analytics Python

carp-analytics-python is a Python library for working with CARP study data. It focuses on streaming JSON records, participant lookup, schema discovery, export, parquet conversion, and optional plotting.

Quick Start

from carp import CarpStudy

study = CarpStudy("sleep-data/phase-1-1/data-streams.json")
print(study.records.count())
print(study.participants.summary_rows()[0])

Main API

CarpStudy is the primary entrypoint.

from carp import CarpStudy

study = CarpStudy([
    "sleep-data/phase-1-1/data-streams.json",
    "sleep-data/phase-2-1/data-streams.json",
])

study.schema.scan()
study.export.export_json("output.json", data_type="dk.cachet.carp.stepcount")
study.frames.convert_to_parquet("output_parquet")
study.participant("alice@example.com").info()

CLI

carp schema sleep-data/phase-1-1/data-streams.json
carp count sleep-data/phase-1-1/data-streams.json
carp participants sleep-data/phase-1-1/data-streams.json
carp export sleep-data/phase-1-1/data-streams.json -o output.json -t dk.cachet.carp.stepcount
carp group sleep-data/phase-1-1/data-streams.json -o grouped_output
carp convert sleep-data/phase-1-1/data-streams.json -o output_parquet

Documentation

The docs are built with Sphinx, autodoc, and napoleon.

python -m pip install sphinx sphinx-rtd-theme
sphinx-build -b html docs docs/_build/html

Examples

python examples/main.py sleep-data/phase-1-1/data-streams.json
python examples/disc.py sleep-data/phase-1-1/data-streams.json

Optional Dependencies

pandas and pyarrow enable dataframe and parquet support. folium enables plotting.