# packages/matching

Job posting similarity, dedupe clustering, and keyword coverage for the
jobhunt-platform v1.1 agency duplicate detection feature (ADR-0003).

## Modules

### similarity.py
- `normalize_employer(name)` -- lowercase, strip agency/legal suffixes (AB, Consulting, etc.), remove punctuation.
- `title_score(a, b)` -- rapidfuzz token_set_ratio on job titles (0-100).
- `employer_match(a, b)` -- True if normalized employer names are equal.
- `desc_score(a, b, max_chars=2000)` -- token_set_ratio on first 2000 chars of descriptions.

### dedupe.py
- `cluster(postings: list[dict]) -> dict[str, list[str]]` -- group postings into duplicate clusters.

Clustering rule (per ADR-0003):
- Same employer (normalized) **OR**
- Title similarity >= 85 **AND** description similarity >= 80

Uses union-find for transitive grouping.  Clusters are sorted by descending
max pairwise score (`c1` = tightest cluster).

### keywords.py
- `extract_keywords(text, top_n=30)` -- frequency-based keyword extraction with Swedish + English stopword removal.
- `coverage(cv_text, posting_text)` -- computes keyword coverage of a CV against a job posting.

Multiword tech terms like "fast api" are collapsed to "fastapi" so they survive as single keywords.

## Installation (uv)

```bash
cd packages/matching
uv venv && source .venv/bin/activate
uv pip install -e ".[dev]"
pytest
```

## License
MIT