Add QCEW CSV module, ECEC breakdown, response caching + typed errors

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>

tests/test_qcew.py

@@ -0,0 +1,51 @@
+"""Tests for the QCEW Open Data CSV module.
+
+Offline tests parse a committed fixture (no network). The live test (opt-in via
+`-m live`) hits the real CSV service, which needs no API key and no quota.
+"""
+import os
+
+import pytest
+
+from bls_client import qcew
+
+FIXTURE = os.path.join(os.path.dirname(__file__), "fixtures", "qcew_dc_sample.csv")
+
+
+@pytest.fixture(scope="module")
+def dc_rows():
+    with open(FIXTURE) as f:
+        return qcew.parse_csv(f.read())
+
+
+def test_parse_returns_dict_rows(dc_rows):
+    assert dc_rows and isinstance(dc_rows[0], dict)
+    # core QCEW columns present
+    for col in ("area_fips", "own_code", "industry_code", "annual_avg_emplvl", "annual_avg_wkly_wage"):
+        assert col in dc_rows[0]
+
+
+def test_all_rows_are_dc_all_industries(dc_rows):
+    assert all(r["area_fips"] == "11000" for r in dc_rows)
+    assert all(r["industry_code"] == "10" for r in dc_rows)
+
+
+def test_filter_by_ownership(dc_rows):
+    # ownership name resolves to its code, and total (own_code 0) exists
+    total = qcew.filter_rows(dc_rows, own_code="total")
+    assert len(total) == 1
+    assert int(total[0]["annual_avg_emplvl"]) > 0
+
+
+def test_ownership_name_mapping():
+    assert qcew.OWNERSHIP["private"] == "5"
+    assert qcew.OWNERSHIP["federal"] == "1"
+
+
+@pytest.mark.live
+def test_live_area_fetch():
+    rows = qcew.area("11000", 2024, "a")          # DC annual, no key / no quota
+    assert len(rows) > 100
+    private_total = qcew.filter_rows(rows, own_code="private", industry_code="10", agglvl_code="51")
+    assert len(private_total) == 1
+    assert int(private_total[0]["annual_avg_emplvl"]) > 100_000   # DC private ~525k