Dave Boyd
4fe734381e
Repair every dead series-ID encoding (library now 82/82 query helpers
return live data, verified against the BLS API):
- JOLTS: 21-char format (was 18) — add state/area/sizeclass fields
- OES: national area code 0000000 (was invalid 0000400)
- ECI: correct owner/component/estimate encoding, default unadjusted (CIU)
- Productivity: 4-digit sector + 4-digit measure codes (was 2+3)
- QCEW: 13-char timeseries-API form (ENUUS00010510 / ENU{fips}00010{own}10)
- PPI: repoint finished-goods -> final demand (WPUFD4); keep alias
- ECEC: drop fabricated health-insurance/retirement helpers; add total benefits
- wages SOC: software developers 151132 -> 151252 (2018 SOC)
Tooling/docs:
- config reads BLS_API_KEY env var (takes precedence; config.py gitignored)
- add requirements.txt
- rewrite README as project front door + coverage table + limitations
- correct JOLTS/OES tables in series_id_formats.md, USAGE.md, dataset explorer
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
167 lines
6.8 KiB
Markdown
167 lines
6.8 KiB
Markdown
# BLS Data Library
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A small, dependency-light Python library for pulling U.S. Bureau of Labor Statistics
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(BLS) time series — unemployment, payrolls, inflation, wages, job openings, and
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productivity — with pre-built series-ID helpers so you never have to hand-encode a
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series ID.
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```python
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from bls_client import BLSClient
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from bls_client.queries import employment, prices
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client = BLSClient(API_KEY)
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# Latest national nonfarm payrolls
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client.fetch_latest(employment.nonfarm_payrolls(), years=1)
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# A labeled CPI dashboard in one call
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client.fetch_named(prices.cpi_dashboard(), 2024, 2025)
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```
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All 82 zero-argument query helpers are verified against the live API.
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---
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## Install
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```bash
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pip install -r requirements.txt # just `requests`
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```
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## Configure your API key
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Register for a free key (instant, no approval): https://data.bls.gov/registrationEngine/
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The free v2 key allows 500 queries/day, 50 series/query, 20 years/query.
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```bash
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cp config.example.py config.py
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export BLS_API_KEY="your-key" # preferred — config.py reads this env var
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```
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`config.py` is gitignored; the env var takes precedence over anything written in the file.
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You can also pass the key directly: `BLSClient("your-key")`.
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## Quick start
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```bash
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python3 examples/basic_pull.py # payrolls, CPI dashboard, DC-region unemployment
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python3 examples/custom_series.py # building custom series IDs
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```
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---
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## What's in the box
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```
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bls_client/
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├── client.py BLSClient — batching, named fetches, catalog metadata, row flattening
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├── series.py low-level series-ID builders (LAUS, CES, CPI, PPI, OES, JOLTS, ECI, QCEW, productivity)
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└── queries/
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├── employment.py payrolls, unemployment (LAUS), JOLTS, QCEW
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├── prices.py CPI, PPI, average prices, import/export prices
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├── wages.py OES occupational wages, ECI, ECEC
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└── productivity.py major-sector productivity & costs
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```
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`BLSClient` highlights:
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- `fetch(ids, start, end)` — auto-batches >50 series, returns `{series_id: {data, catalog}}`
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- `fetch_latest(ids, years=N)` — most recent N years
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- `fetch_named({label: id})` — returns results keyed by your labels
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- `latest_obs(series)` / `to_rows(results)` — convenience for the most recent value / CSV-ready rows
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See **[USAGE.md](USAGE.md)** for the full API and **[series_id_formats.md](series_id_formats.md)**
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for the series-ID decode tables.
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---
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## Coverage
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| Survey | Helpers | Notes |
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|---|---|---|
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| LAUS — local area unemployment | state / metro / county rates, DC-region dashboard | ✅ |
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| CES — payroll employment | national by supersector; state/metro | ✅ |
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| CPS — household survey | national unemployment rate, participation | ✅ |
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| JOLTS — job openings & turnover | openings/hires/quits/layoffs, dashboard | ✅ |
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| CPI — consumer prices | all-items, core, food, energy, gasoline, …; dashboard | ✅ |
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| PPI — producer prices | all commodities, final demand, food, energy | ✅ |
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| OES — occupational wages | employment + wage percentiles by SOC; 15 common occupations | ✅ |
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| ECI — employment cost index | total comp / wages / benefits × civilian/private/gov | ✅ |
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| ECEC — employer cost levels | total compensation, total benefits | ✅ (totals only) |
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| Productivity & costs | output/hr, ULC, comp, hours × business/nonfarm/manufacturing | ✅ |
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| QCEW — quarterly census | national & state private totals | ⚠️ totals only via this API |
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## Known limitations / what "complete" would add
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- **QCEW** is only partially served by the BLS *timeseries* API used here (national and
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state-level totals work). County- and industry-level QCEW detail requires the separate
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**QCEW Open Data API** (CSV: `https://data.bls.gov/cew/data/api/...`). Not yet wired up.
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- **ECEC benefit subcomponents** (health insurance, retirement & savings, etc.) need
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specific benefit-subcell codes from the ECEC component list; only the compensation and
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benefits totals are currently exposed.
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- **No caching / rate-limit handling.** Repeated runs spend against the 500/day quota; a
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small on-disk cache and a friendly error on `REQUEST_NOT_PROCESSED` (quota hit) would help.
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- **No packaging.** Importable in-tree but not `pip install`-able; add a `pyproject.toml`
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to ship it as a real package.
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- **No automated tests.** A pytest suite asserting builder outputs against known-good IDs
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(and a live smoke test behind a marker) would lock the series-ID encodings in place.
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---
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## Appendix: BLS API reference
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Reference material for working directly with the API (the library wraps all of this).
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### API versions
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| Feature | v1 (no key) | v2 (registered) |
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|---------------------------|-------------|-----------------|
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| Daily query limit | 25 | 500 |
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| Series per query | 25 | 50 |
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| Years of history | 10 | 20 |
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| Net/percent changes | No | Yes |
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| Series descriptions | No | Yes |
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| Calculations | No | Yes |
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### Endpoints
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```
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GET /v2/surveys # all survey codes and names (see surveys.json)
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GET /v2/surveys/{abbr} # one survey
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GET /v2/timeseries/popular?survey={abbr} # 25 most-requested series IDs for a survey
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POST /v2/timeseries/data/ # the time-series data endpoint
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```
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Base URL: `https://api.bls.gov/publicAPI/v2`
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**POST body (registered, all v2 features):**
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```json
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{
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"seriesid": ["LAUST110000000000003", "CES0000000001"],
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"startyear": "2020", "endyear": "2025",
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"registrationkey": "YOUR_KEY",
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"catalog": true, "calculations": true, "annualaverage": true
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}
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```
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**Period codes:** monthly `M01`–`M12` (`M13` = annual avg); quarterly `Q01`–`Q04` (`Q05` = annual avg); annual `A01`.
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**Status codes:** `REQUEST_SUCCEEDED`, `REQUEST_FAILED`, `REQUEST_NOT_PROCESSED` (often = daily quota hit).
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**Footnote codes:** `R` revised, `P` preliminary, `X`/`N` unavailable.
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A full real response is saved in `api_response_example.json`.
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### Bulk flat files
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Base: `https://download.bls.gov/pub/time.series/` — each survey folder has
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`{prefix}.series` (master list), `{prefix}.data.*` (observations), and `{prefix}.{dimension}`
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decode tables (area, industry, measure). Tab-delimited; handy for bulk PostgreSQL ingest.
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Key prefixes: `la/` LAUS, `ce/` CES, `sm/` state-metro, `en/` QCEW, `oe/` OES, `jt/` JOLTS,
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`cu/` CPI-U, `wp/` PPI.
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### Other files in this repo
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- `series_id_formats.md` — series-ID decode tables for each survey
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- `qcew_field_schema.md` — QCEW quarterly/annual CSV field layouts
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- `surveys.json` — complete survey list from the API
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- `bls_dataset_explorer.py` / `.html` — browsable survey catalog
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- `dc_md_va_unemployment.py` / `generate_report.py` — example report generators
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