.. _minimal-working-example: Minimal Working Example ======================= The following is a quick guide for creating and running a simple pipeline to extract Call metrics for daily and night epochs of one participant monitored on the US East coast. #. Make sure your database connection credentials in ``.env`` are correct. See step 1 of :ref:`Usage Section `. #. Create at least one participant file ``p01`` under ``data/external/``. See step 2 of :ref:`Usage Section `. #. Make sure your Conda (python) environment is active. See step 6 of :ref:`install-page`. #. Replace the contents of the ``Snakefile`` with the following snippet :: configfile: "config.yaml" include: "rules/renv.snakefile" include: "rules/preprocessing.snakefile" include: "rules/features.snakefile" include: "rules/reports.snakefile" rule all: input: expand("data/processed/{pid}/call_{call_type}_{day_segment}.csv", pid=config["PIDS"], call_type=config["CALLS"]["TYPES"], day_segment = config["CALLS"]["DAY_SEGMENTS"]), #. Modify the following settings in the ``config.yaml`` file with the values shown below (leave all other settings as they are) :: SENSORS: [calls] FITBIT_TABLE: [] FITBIT_SENSORS: [] PIDS: [p01] DAY_SEGMENTS: &day_segments [daily, night] TIMEZONE: &timezone America/New_York DATABASE_GROUP: &database_group MY_GROUP For more information on the ``calls`` sensor see :ref:`call-sensor-doc` #. Run the following command to execute RAPIDS :: snakemake -j1 #. Daily and night call metrics will be found in files under the ``data/processed/p01/`` directory.