CMS Hospitals Assessment

Downloads all CSV datasets tagged with theme "Hospitals" from the CMS provider-data metastore, converts CSV headers to snake_case, and tracks state so daily re-runs only download what's changed.

Run

pip install -r requirements.txt
python cms_hospitals_sync.py

Outputs CSVs to ./output/{identifier}.csv and tracks per-dataset modified dates in ./state.json. Design notes

• Incremental loads via per-dataset modified comparison (not a global last-run timestamp). Self-healing: delete state.json for a clean rebuild; delete a single key to force one dataset to re-pull.
• Parallelism via ThreadPoolExecutor (I/O-bound work; threads are the right tool). Capped at 4 workers — CMS rate-limits aggressive parallel requests.
• Atomic writes: download → .download, transform → .tmp, then os.replace to final path. Same pattern for state.json
• Streamed downloads with iter_content (auto-handles gzip Content-Encoding).
• Header transformation only: data rows pass through unchanged via csv.reader/csv.writer, so memory use is constant regardless of file size.
• Failure isolation: one dataset's exception doesn't abort the rest; state only updates for successful downloads, so failures auto-retry on the next run.

Scheduling

Daily at 02:00 UTC:

**Linux cron

0 2 * * * /usr/bin/python3 /path/to/cms_hospitals_sync.py >> /var/log/cms_sync.log 2>&1

Windows Task Scheduler — Action: Start a program; Program: python.exe; Arguments: C:\path\to\cms_hospitals_sync.py.

xit codes

• 0 — all datasets succeeded, unchanged, or had no CSV distribution
• 1 — one or more downloads failed after retries (logged; next run retries them)

Sample output

contains three transformed CSVs from a real run medicare_spend_national.csv,asc_quality_measures_national.csv, oas_surgiacal_centersss_.csv, plus the resulting state.json. Headers are snake_case; data is byte-for-byte from CMS.