epidatpy 0.5.1

A programmatic interface to Delphi's Epidata API.

epidatpy

The Python client for the Delphi Epidata API.

Install

Install with the following commands:

# Latest dev version
pip install "git+https://github.com/cmu-delphi/epidatpy.git#egg=epidatpy"

# PyPI version (not yet available)
pip install epidatpy

Usage

from epidatpy import CovidcastEpidata, EpiDataContext, EpiRange

# All calls using the `epidata` object will now be cached for 7 days
epidata = EpiDataContext(use_cache=True, cache_max_age_days=7)

# Obtain a DataFrame of the most up-to-date version of the smoothed covid-like illness (CLI)
# signal from the COVID-19 Trends and Impact survey for the US
epidata.pub_covidcast(
    data_source="jhu-csse",
    signals="confirmed_cumulative_num",
    geo_type="nation",
    time_type="day",
    geo_values="us",
    time_values=EpiRange(20210405, 20210410),
).df()

CAST API (snapshot / archive)

The CAST API exposes versioned signals (NSSP, pophive, NWSS, ...). Use epidata_snapshot for a single as-of view, epidata_archive for the full report-time history, or epidata to dispatch between them.

from epidatpy import EpiDataContext, EpiRange

epidata = EpiDataContext()

# Source-level metadata (signals, geo_types, available date ranges).
epidata.epidata_meta(source="nssp")

# Latest snapshot of a signal (omit `snapshot_date` to fetch the newest version).
epidata.epidata_snapshot(
    source="nssp",
    signals="pct_ed_visits_influenza",
    geo_type="state",
    geo_values="ca,ny",
    reference_time=EpiRange("2025-01-01", "2025-06-01"),
).df()

# Full report-time history, filtered to report_times on or before 2025-10-16.
epidata.epidata_archive(
    source="nssp",
    signals="pct_ed_visits_influenza",
    geo_type="state",
    report_time="<2025-10-16",
).df()

# Router: pass `report_time` (or `snapshot_date="*"`) for archive, `snapshot_date` for snapshot.
epidata.epidata(
    source="nssp",
    signals="pct_ed_visits_influenza",
    geo_type="state",
    report_time=EpiRange("2025-01-01", "2025-10-16"),
).df()

geo_values, reference_time, and an EpiRange report_time lower bound are filtered locally after the request.

Development

The following commands are available for developers:

make install        # setup venv, install dependencies and local package
make test           # run unit tests
make format         # format code
make lint           # check linting
make doc            # build docs
make doc-preview    # preview docs in browser
make release        # build distribution packages
make upload         # upload the current version to pypi
make clean          # clean build and docs artifacts

Release Process

dev is the only long-lived branch; each release line lives on a rel-X.Y branch. Everything is driven by the create_release workflow, run with a bump of major, minor, or patch:

• major / minor: bumps the version on dev, cuts a new rel-X.Y branch at that commit, and tags vX.Y.0.
• patch (hotfix): bumps the patch version on an existing rel-X.Y branch and tags vX.Y.Z. Land the fix on that branch first (commit directly or cherry-pick from dev); set release_branch to pick the branch (defaults to the line matching dev's version).

Either way the workflow creates a GitHub release with auto-generated notes. Pushing the vX.Y.Z tag then triggers pypi_publish (build + upload to PyPI) and documentation (docs rebuild). Because publishing is a separate workflow keyed off the tag rather than a step inside create_release, a failed PyPI upload can be re-run against the existing tag via the pypi_publish workflow's Run workflow button — without redoing the release cut.