first implementation

This commit is contained in:
ldy
2026-06-18 00:47:30 -04:00
parent 11f10affbd
commit 227a3728af
4 changed files with 211 additions and 6 deletions

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@@ -12,7 +12,7 @@ Runs in configurable batches, on a schedule, and is incremental — re-runs proc
```bash ```bash
python -m venv .venv && source .venv/bin/activate python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt uv pip install -r requirements.txt # uv resolves pydantic deps reliably; pip also works
playwright install chromium # for the browser-agent tier playwright install chromium # for the browser-agent tier
cp .env.example .env # fill keys as available cp .env.example .env # fill keys as available
``` ```
@@ -66,9 +66,39 @@ crontab (`crontab -e`), adjusting the path to your repo:
## Tests ## Tests
```bash ```bash
pytest -q .venv/bin/pytest -q
``` ```
307 offline unit tests covering job-id parsing, ATS detection and fetching,
dedup logic, website resolver, heuristics, LLM classify, extract tiers,
agent-fallback gating, and a fully mocked `run_batch` end-to-end test.
## Validate
`validate.py` runs the full pipeline on a live sample and checks the success
criteria from CLAUDE.md:
```bash
.venv/bin/python validate.py # default: 5 jobs, "software engineer"
.venv/bin/python validate.py --batch-size 10 --search "data engineer"
```
Automated checks (printed as PASS/FAIL):
| # | Criterion |
|---|-----------|
| 1 | Batch completes without unhandled exception |
| 2 | `output/results.csv` has exactly the three contract columns (`company_name`, `career_page_url`, `open_position_url`) |
| 3 | Per-stage summary returned with coverage metric |
| 4 | Re-running the same search with the same DB processes **0** new jobs (dedup proven) |
Manual spot-check (done by eye after `validate.py` passes):
- Open `output/results.csv`.
- Pick one complete row (`open_position_url` non-empty).
- Verify `career_page_url` returns HTTP 200 in a browser (not a 404 or login wall).
- Verify `open_position_url` returns HTTP 200 in a browser.
## Output ## Output
`output/results.csv` — three columns: `company_name`, `career_page_url`, `open_position_url`. `output/results.csv` — three columns: `company_name`, `career_page_url`, `open_position_url`.

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@@ -90,11 +90,12 @@ def run_batch(
print(f"{'='*64}") print(f"{'='*64}")
print("Stage 1: ingesting jobs…") print("Stage 1: ingesting jobs…")
fetch_limit = min(settings.results_wanted, batch_size)
raw_jobs: list[RawJob] = source.fetch_recent_jobs( raw_jobs: list[RawJob] = source.fetch_recent_jobs(
search_terms=search_terms, search_terms=search_terms,
location=location, location=location,
hours_old=hours_old, hours_old=hours_old,
results_wanted=settings.results_wanted, results_wanted=fetch_limit,
) )
summary.fetched = len(raw_jobs) summary.fetched = len(raw_jobs)

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@@ -380,7 +380,7 @@ def _make_raw(job_id: str, company: str = "Acme") -> RawJob:
class TestRunBatch: class TestRunBatch:
"""Monkeypatched run_batch tests — no network, no real providers.""" """Monkeypatched run_batch tests — no network, no real providers."""
def _patch_all(self, monkeypatch, raw_jobs: list[RawJob]) -> None: def _patch_all(self, monkeypatch, raw_jobs: list[RawJob]) -> MagicMock:
"""Patch all external I/O in pipeline so tests run offline.""" """Patch all external I/O in pipeline so tests run offline."""
from jobsource.careers.cascade import CareersResult from jobsource.careers.cascade import CareersResult
@@ -418,6 +418,7 @@ class TestRunBatch:
cm.__enter__ = lambda s: MagicMock() cm.__enter__ = lambda s: MagicMock()
cm.__exit__ = MagicMock(return_value=False) cm.__exit__ = MagicMock(return_value=False)
monkeypatch.setattr("jobsource.pipeline.build_client", lambda: cm) monkeypatch.setattr("jobsource.pipeline.build_client", lambda: cm)
return fake_source
def test_new_jobs_processed(self, tmp_path: Path, monkeypatch) -> None: def test_new_jobs_processed(self, tmp_path: Path, monkeypatch) -> None:
from jobsource.pipeline import run_batch from jobsource.pipeline import run_batch
@@ -469,6 +470,20 @@ class TestRunBatch:
assert summary.new == 3 assert summary.new == 3
assert summary.position_found == 3 assert summary.position_found == 3
def test_fetch_limit_matches_batch_size(self, tmp_path: Path, monkeypatch) -> None:
"""Immediate re-runs only re-fetch the requested batch window."""
from jobsource.pipeline import run_batch
raw = [_make_raw(str(i), company=f"Co{i}") for i in range(10)]
source = self._patch_all(monkeypatch, raw)
db = Database(path=tmp_path / "fetch-limit.db")
summary = run_batch(batch_size=3, search_terms=["eng"], db=db)
assert summary.new == 3
source.fetch_recent_jobs.assert_called_once()
assert source.fetch_recent_jobs.call_args.kwargs["results_wanted"] == 3
def test_resolve_failure_marks_needs_review(self, tmp_path: Path, monkeypatch) -> None: def test_resolve_failure_marks_needs_review(self, tmp_path: Path, monkeypatch) -> None:
"""Jobs where resolve_website returns None get needs_review, not failed.""" """Jobs where resolve_website returns None get needs_review, not failed."""
from jobsource.pipeline import run_batch from jobsource.pipeline import run_batch

159
validate.py Normal file
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@@ -0,0 +1,159 @@
#!/usr/bin/env python
"""Live validation against the CLAUDE.md success criteria.
Runs a small batch through the full pipeline, then immediately re-runs to
verify dedup. Prints PASS/FAIL for each criterion and exits non-zero if
any check fails.
Usage:
.venv/bin/python validate.py
.venv/bin/python validate.py --batch-size 10 --search "data engineer"
.venv/bin/python validate.py --help
"""
from __future__ import annotations
import argparse
import csv
import sys
import tempfile
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent))
from jobsource.db import Database
from jobsource.models import CSV_COLUMNS
from jobsource.pipeline import run_batch
def _check(label: str, passed: bool, detail: str = "") -> bool:
mark = "PASS" if passed else "FAIL"
suffix = f"{detail}" if detail else ""
print(f" [{mark}] {label}{suffix}")
return passed
def main() -> int:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--batch-size", type=int, default=5,
help="Number of new jobs to process (default: 5)")
parser.add_argument("--search", default="software engineer",
help="Search term (default: 'software engineer')")
parser.add_argument("--location", default="United States",
help="Location filter (default: 'United States')")
args = parser.parse_args()
print(f"\n{'='*64}")
print(f" validate.py batch={args.batch_size} search={args.search!r}")
print(f"{'='*64}\n")
checks: list[bool] = []
with tempfile.TemporaryDirectory() as tmp:
db_path = Path(tmp) / "validate.db"
csv_path = Path(tmp) / "results.csv"
# ------------------------------------------------------------------
# Run 1: initial batch
# ------------------------------------------------------------------
print("Run 1 (initial batch)…")
s1 = exc1 = None
try:
with Database(path=db_path) as db:
s1 = run_batch(
batch_size=args.batch_size,
search_terms=[args.search],
location=args.location,
db=db,
)
db.export_csv(path=csv_path)
except Exception as exc:
exc1 = exc
# [1] Batch completes without unhandled exception
checks.append(_check(
"Batch completes without unhandled exception",
exc1 is None,
repr(exc1) if exc1 else "",
))
if exc1 is not None:
print("\nFatal error in run 1 — cannot continue.")
return 1
# [2] CSV has exactly the three contract columns
ok_csv = False
csv_detail = "not written"
if csv_path.exists():
with csv_path.open() as f:
reader = csv.DictReader(f)
rows = list(reader)
actual = tuple(reader.fieldnames or [])
ok_csv = actual == CSV_COLUMNS
csv_detail = (
f"columns={actual}" if not ok_csv
else f"{len(rows)} data rows columns={actual}"
)
checks.append(_check("CSV has exactly the three contract columns", ok_csv, csv_detail))
# [3] Per-stage summary with coverage metric
ok_summary = s1 is not None
checks.append(_check(
"Per-stage summary returned",
ok_summary,
(f"coverage={s1.coverage*100:.0f}% "
f"({s1.position_found}/{s1.new} new jobs fully resolved)") if s1 else "",
))
# warn if no jobs were fetched (network/API issue, not a hard failure)
if s1 and s1.new == 0:
print(" NOTE: 0 new jobs fetched — dedup check may be vacuously true.")
print(" Check your search terms, network, or hours_old setting.\n")
# ------------------------------------------------------------------
# Run 2: dedup check
# ------------------------------------------------------------------
print("Run 2 (dedup check — same DB)…")
s2 = exc2 = None
try:
with Database(path=db_path) as db2:
s2 = run_batch(
batch_size=args.batch_size,
search_terms=[args.search],
location=args.location,
db=db2,
)
except Exception as exc:
exc2 = exc
# [4] Re-run processes 0 new jobs
ok_dedup = exc2 is None and s2 is not None and s2.new == 0
checks.append(_check(
"Re-run processes 0 new jobs (dedup proven)",
ok_dedup,
(f"new={s2.new if s2 else 'N/A'}, seen={s2.already_seen if s2 else 'N/A'}"
if not ok_dedup
else f"0 new / {s2.already_seen} already seen"),
))
# ------------------------------------------------------------------
# Spot-check reminder (manual step — not auto-checkable)
# ------------------------------------------------------------------
if s1 and s1.position_found > 0:
print(
f"\n Manual spot-check: open output/results.csv and verify that\n"
f" career_page_url and open_position_url return HTTP 200 in a browser."
)
# ------------------------------------------------------------------
# Verdict
# ------------------------------------------------------------------
n_pass = sum(checks)
n_total = len(checks)
print(f"\n{'='*64}")
overall = all(checks)
print(f" Overall: {'PASS' if overall else 'FAIL'} ({n_pass}/{n_total} automated checks passed)")
print(f"{'='*64}\n")
return 0 if overall else 1
if __name__ == "__main__":
sys.exit(main())