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HF Data Library · Econ Data Library · more to come
FULL-COVERAGE ingest of the U.S. BLS flat files (time.series database). Source: https://download.bls.gov/pub/time.series/ -- one folder per survey (ap, ce, cu, ln, jt, wp, pr, la, ...). For each survey we download every `<survey>.data.N.*` file (the observations) plus `<survey>.series` (series…
U.S. Bureau of Labor Statistics. Retrieved from https://www.bls.gov. Compiled and redistributed by the Elkassabgi Data Library.
Processing: Retrieved from the official source, normalized to a long {series_key, obs_date, value} schema (period-start dates), de-duplicated, and stored as zstd Parquet. Compiled and redistributed by the Elkassabgi Data Library.
FULL-COVERAGE ingest of the U.S. BLS flat files (time.series database). Source: https://download.bls.gov/pub/time.series/ -- one folder per survey (ap, ce, cu, ln, jt, wp, pr, la, ...). For each survey we download every `<survey>.data.N.*` file (the observations) plus `<survey>.series` (series metadata) and parse ALL series. GROUPED storage (mirrors jobs/ingest_eurostat.py / ingest_sec_edgar.py): ONE Parquet per survey -> data/clean_full/bls/<survey>.parquet with a `series_id` column inside. Columns: series_id, obs_date, value, period, footnote. Memory is bounded: data files are streamed to disk, then parsed line-by-line and flushed to the Parquet writer in row-group batches (never the whole survey in RAM). License: us-public-domain (configs/sources.yaml). BLS data-file row (tab-separated, has a header line): series_id <tab> year <tab> period <tab> value <tab> footnote_codes period codes: M01..M12 monthly, M13 annual avg, Q01..Q04 quarterly, Q05 annual avg, S01/S02 semiannual, S03 semiannual annual avg, A01 annual. Usage: python jobs/ingest_bls.py --probe # validate parser on small surveys python jobs/ingest_bls.py --only pr,jl # one/few surveys python jobs/ingest_bls.py # full run (all 67 surveys) python jobs/ingest_bls.py --skip-download # reuse already-downloaded raw files
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