statcast-bigquery 0.3.1

Statcast → BigQuery: idempotent ingestion + LLM-friendly docs + Baseball Savant verification

statcast-bigquery

Idempotent Statcast → BigQuery ingestion, with first-class documentation for SQL/LLM agents and round-trip validation against Baseball Savant.

Install

pip install statcast-bigquery

Quickstart

gcloud auth application-default login
statcast-bigquery sync \
    --start 2024-04-01 --end 2024-10-31 \
    --table myproject.mydataset.statcast_pitches

Backfill

Backfill historical seasons in resumable chunks:

statcast-bigquery sync \
    --start 2015-04-01 --end 2026-05-11 \
    --chunk-by year --resume \
    --table myproject.mydataset.statcast_pitches

--resume skips chunks already recorded as success in <dataset>._statcast_ingest_runs. Override with --runs-table if you want the run log in a sidecar dataset. Re-running with the same --chunk-by is safe; switching --chunk-by year → month between runs will re-process (chunks must match exactly to skip).

Documentation

statcast-bigquery docs --format llm > STATCAST_FOR_LLMS.md

Seed your data dictionary

If you maintain a data_dictionary table (one row per column with business definitions, tags, lineage), you can seed it directly:

statcast-bigquery docs --format dictionary --apply \
    --dataset mydataset --table myproject.mydataset.statcast_pitches \
    --dictionary-table myproject.shared_ops.data_dictionary

Atomically replaces rows for (dataset, table) only; other entries in the dictionary table are untouched. Required target schema:

dataset, table, column, dtype, description, business_definition,
owner, tags ARRAY<STRING>, source_system, upstream_lineage_json,
created_at TIMESTAMP, updated_at TIMESTAMP

Verification

statcast-bigquery verify \
    --source baseball-savant \
    --aggregation player-season \
    --metric all --season 2024 \
    --table myproject.mydataset.statcast_pitches

MIT licensed. This software does not include or distribute MLB data.