Dave Boyd
9e2c55c568
Item 1 — QCEW county/industry detail: - new bls_client/qcew.py: thin client over the QCEW Open Data CSV service (area/industry/size slices; no API key, no quota), with filter_rows helper - covers the county/industry detail the timeseries API can't reach Item 2 — ECEC benefit breakdown: - new series.ecec() builder from the authoritative cm.estimate decode table - real helpers: wages, total benefits, paid leave, supplemental pay, health insurance, retirement & savings, legally required + ecec_dashboard() - FIX: ecec_total_benefits was CMU1036... (education/health industries only); correct all-civilian total benefits is CMU1030000000000D Item 3 — caching + typed errors: - bls_client/cache.py FileCache (on-disk, TTL); BLSClient(cache=True), queries_used counter (cache hits don't spend quota) - bls_client/errors.py: BLSError / BLSQuotaError / BLSRequestError; quota exhaustion now raises a clear BLSQuotaError instead of a generic RuntimeError Tests: 119 offline (+24) incl. ECEC goldens, QCEW fixture parse, cache/quota behavior; live smoke extended to ECEC + QCEW. Helper sweep: 96/96 live. README: caching/QCEW usage, updated coverage + limitations. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
196 lines
7.9 KiB
Markdown
196 lines
7.9 KiB
Markdown
# BLS Data Library
|
||
|
||
A small, dependency-light Python library for pulling U.S. Bureau of Labor Statistics
|
||
(BLS) time series — unemployment, payrolls, inflation, wages, job openings, and
|
||
productivity — with pre-built series-ID helpers so you never have to hand-encode a
|
||
series ID.
|
||
|
||
```python
|
||
from bls_client import BLSClient
|
||
from bls_client.queries import employment, prices
|
||
|
||
client = BLSClient(API_KEY)
|
||
|
||
# Latest national nonfarm payrolls
|
||
client.fetch_latest(employment.nonfarm_payrolls(), years=1)
|
||
|
||
# A labeled CPI dashboard in one call
|
||
client.fetch_named(prices.cpi_dashboard(), 2024, 2025)
|
||
```
|
||
|
||
All 82 zero-argument query helpers are verified against the live API.
|
||
|
||
---
|
||
|
||
## Install
|
||
|
||
```bash
|
||
pip install -r requirements.txt # just `requests`
|
||
# or install the package itself (editable):
|
||
pip install -e .
|
||
```
|
||
|
||
## Configure your API key
|
||
|
||
Register for a free key (instant, no approval): https://data.bls.gov/registrationEngine/
|
||
The free v2 key allows 500 queries/day, 50 series/query, 20 years/query.
|
||
|
||
```bash
|
||
cp config.example.py config.py
|
||
export BLS_API_KEY="your-key" # preferred — config.py reads this env var
|
||
```
|
||
|
||
`config.py` is gitignored; the env var takes precedence over anything written in the file.
|
||
You can also pass the key directly: `BLSClient("your-key")`.
|
||
|
||
## Quick start
|
||
|
||
```bash
|
||
python3 examples/basic_pull.py # payrolls, CPI dashboard, DC-region unemployment
|
||
python3 examples/custom_series.py # building custom series IDs
|
||
```
|
||
|
||
## Tests
|
||
|
||
```bash
|
||
pip install -e ".[dev]" # pytest
|
||
pytest # offline: 95 tests locking the series-ID encodings
|
||
pytest -m live # also hit the live API (needs network + BLS_API_KEY)
|
||
```
|
||
|
||
---
|
||
|
||
## What's in the box
|
||
|
||
```
|
||
bls_client/
|
||
├── client.py BLSClient — batching, caching, named fetches, catalog metadata, row flattening
|
||
├── series.py low-level series-ID builders (LAUS, CES, CPI, PPI, OES, JOLTS, ECI, ECEC, QCEW, productivity)
|
||
├── qcew.py QCEW Open Data CSV client (county/industry detail; no key, no quota)
|
||
├── cache.py on-disk response cache (FileCache)
|
||
├── errors.py BLSError / BLSQuotaError / BLSRequestError
|
||
└── queries/
|
||
├── employment.py payrolls, unemployment (LAUS), JOLTS, QCEW totals
|
||
├── prices.py CPI, PPI, average prices, import/export prices
|
||
├── wages.py OES occupational wages, ECI, ECEC breakdown
|
||
└── productivity.py major-sector productivity & costs
|
||
```
|
||
|
||
`BLSClient` highlights:
|
||
- `fetch(ids, start, end)` — auto-batches >50 series, returns `{series_id: {data, catalog}}`
|
||
- `fetch_latest(ids, years=N)` — most recent N years
|
||
- `fetch_named({label: id})` — returns results keyed by your labels
|
||
- `latest_obs(series)` / `to_rows(results)` — convenience for the most recent value / CSV-ready rows
|
||
|
||
See **[USAGE.md](USAGE.md)** for the full API and **[series_id_formats.md](series_id_formats.md)**
|
||
for the series-ID decode tables.
|
||
|
||
---
|
||
|
||
## Coverage
|
||
|
||
| Survey | Helpers | Notes |
|
||
|---|---|---|
|
||
| LAUS — local area unemployment | state / metro / county rates, DC-region dashboard | ✅ |
|
||
| CES — payroll employment | national by supersector; state/metro | ✅ |
|
||
| CPS — household survey | national unemployment rate, participation | ✅ |
|
||
| JOLTS — job openings & turnover | openings/hires/quits/layoffs, dashboard | ✅ |
|
||
| CPI — consumer prices | all-items, core, food, energy, gasoline, …; dashboard | ✅ |
|
||
| PPI — producer prices | all commodities, final demand, food, energy | ✅ |
|
||
| OES — occupational wages | employment + wage percentiles by SOC; 15 common occupations | ✅ |
|
||
| ECI — employment cost index | total comp / wages / benefits × civilian/private/gov | ✅ |
|
||
| ECEC — employer cost levels | full breakdown: comp, wages, benefits, paid leave, supplemental, health insurance, retirement, legally-required | ✅ |
|
||
| Productivity & costs | output/hr, ULC, comp, hours × business/nonfarm/manufacturing | ✅ |
|
||
| QCEW — quarterly census | national/state totals (timeseries) **plus** full county/industry detail via the CSV module (`bls_client.qcew`) | ✅ |
|
||
|
||
## Caching & quota handling
|
||
|
||
```python
|
||
client = BLSClient(API_KEY, cache=True) # on-disk cache at ~/.cache/bls (1-day TTL)
|
||
client.fetch(...) # repeated identical requests don't re-spend quota
|
||
client.queries_used # network calls made this session (cache hits excluded)
|
||
```
|
||
|
||
A blown daily quota raises `BLSQuotaError` (vs `BLSRequestError` for a bad request), so
|
||
"am I throttled or is my series ID wrong?" is no longer ambiguous.
|
||
|
||
## QCEW county/industry detail
|
||
|
||
The timeseries helpers give QCEW national/state totals; the `qcew` module reaches the full
|
||
county- and industry-level detail via BLS's separate CSV service (no key, no quota):
|
||
|
||
```python
|
||
from bls_client import qcew
|
||
rows = qcew.area("11000", 2024, "a") # everything for DC, annual
|
||
dc_private = qcew.filter_rows(rows, own_code="private", industry_code="10", agglvl_code="51")
|
||
hospitals = qcew.industry("622", 2024, "a") # one NAICS across all areas
|
||
```
|
||
|
||
## Known limitations
|
||
|
||
- **No automatic retry/backoff** on transient network errors (a `requests` failure surfaces
|
||
directly). Caching mitigates repeat load but there's no rate-limit pacing.
|
||
- **Coverage is the headline cut** of each survey, not an exhaustive mirror — e.g. CES is
|
||
national supersectors + a couple of states; CPI is the common items; OES ships 15 named
|
||
occupations (any SOC works via `occupation_*`). Broaden the helper dicts as needed.
|
||
|
||
---
|
||
|
||
## Appendix: BLS API reference
|
||
|
||
Reference material for working directly with the API (the library wraps all of this).
|
||
|
||
### API versions
|
||
|
||
| Feature | v1 (no key) | v2 (registered) |
|
||
|---------------------------|-------------|-----------------|
|
||
| Daily query limit | 25 | 500 |
|
||
| Series per query | 25 | 50 |
|
||
| Years of history | 10 | 20 |
|
||
| Net/percent changes | No | Yes |
|
||
| Series descriptions | No | Yes |
|
||
| Calculations | No | Yes |
|
||
|
||
### Endpoints
|
||
|
||
```
|
||
GET /v2/surveys # all survey codes and names (see surveys.json)
|
||
GET /v2/surveys/{abbr} # one survey
|
||
GET /v2/timeseries/popular?survey={abbr} # 25 most-requested series IDs for a survey
|
||
POST /v2/timeseries/data/ # the time-series data endpoint
|
||
```
|
||
|
||
Base URL: `https://api.bls.gov/publicAPI/v2`
|
||
|
||
**POST body (registered, all v2 features):**
|
||
```json
|
||
{
|
||
"seriesid": ["LAUST110000000000003", "CES0000000001"],
|
||
"startyear": "2020", "endyear": "2025",
|
||
"registrationkey": "YOUR_KEY",
|
||
"catalog": true, "calculations": true, "annualaverage": true
|
||
}
|
||
```
|
||
|
||
**Period codes:** monthly `M01`–`M12` (`M13` = annual avg); quarterly `Q01`–`Q04` (`Q05` = annual avg); annual `A01`.
|
||
**Status codes:** `REQUEST_SUCCEEDED`, `REQUEST_FAILED`, `REQUEST_NOT_PROCESSED` (often = daily quota hit).
|
||
**Footnote codes:** `R` revised, `P` preliminary, `X`/`N` unavailable.
|
||
|
||
A full real response is saved in `api_response_example.json`.
|
||
|
||
### Bulk flat files
|
||
|
||
Base: `https://download.bls.gov/pub/time.series/` — each survey folder has
|
||
`{prefix}.series` (master list), `{prefix}.data.*` (observations), and `{prefix}.{dimension}`
|
||
decode tables (area, industry, measure). Tab-delimited; handy for bulk PostgreSQL ingest.
|
||
Key prefixes: `la/` LAUS, `ce/` CES, `sm/` state-metro, `en/` QCEW, `oe/` OES, `jt/` JOLTS,
|
||
`cu/` CPI-U, `wp/` PPI.
|
||
|
||
### Other files in this repo
|
||
|
||
- `series_id_formats.md` — series-ID decode tables for each survey
|
||
- `qcew_field_schema.md` — QCEW quarterly/annual CSV field layouts
|
||
- `surveys.json` — complete survey list from the API
|
||
- `bls_dataset_explorer.py` / `.html` — browsable survey catalog
|
||
- `dc_md_va_unemployment.py` / `generate_report.py` — example report generators
|