pyr0ball
02e004ee5c
- scripts/resume_optimizer.py: full pipeline (extract_jd_signals → prioritize_gaps → rewrite_for_ats → hallucination_check) - scripts/db.py: add optimized_resume + ats_gap_report columns + save_optimized_resume / get_optimized_resume helpers - tests/test_resume_optimizer.py: 17 unit tests; patches at source module (scripts.llm_router.LLMRouter), not consumer Tier gate: gap report is free; full LLM rewrite is paid+.
288 lines
11 KiB
Python
288 lines
11 KiB
Python
# tests/test_resume_optimizer.py
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"""Tests for scripts/resume_optimizer.py"""
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import json
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import pytest
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from unittest.mock import MagicMock, patch
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# ── Fixtures ─────────────────────────────────────────────────────────────────
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SAMPLE_RESUME = {
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"name": "Alex Rivera",
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"email": "alex@example.com",
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"phone": "555-1234",
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"career_summary": "Experienced Customer Success Manager with a track record of growth.",
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"skills": ["Salesforce", "Python", "customer success"],
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"experience": [
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{
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"title": "Customer Success Manager",
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"company": "Acme Corp",
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"start_date": "2021",
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"end_date": "present",
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"bullets": [
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"Managed a portfolio of 120 enterprise accounts.",
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"Reduced churn by 18% through proactive outreach.",
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],
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},
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{
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"title": "Support Engineer",
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"company": "Beta Inc",
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"start_date": "2018",
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"end_date": "2021",
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"bullets": ["Resolved escalations for top-tier clients."],
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},
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],
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"education": [
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{
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"degree": "B.S.",
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"field": "Computer Science",
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"institution": "State University",
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"graduation_year": "2018",
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}
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],
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"achievements": [],
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}
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SAMPLE_JD = (
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"We are looking for a Customer Success Manager with Gainsight, cross-functional "
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"leadership experience, and strong stakeholder management skills. AWS knowledge a plus."
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)
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# ── extract_jd_signals ────────────────────────────────────────────────────────
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def test_extract_jd_signals_returns_list():
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"""extract_jd_signals returns a list even when LLM and TF-IDF both fail."""
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from scripts.resume_optimizer import extract_jd_signals
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with patch("scripts.llm_router.LLMRouter") as MockRouter:
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MockRouter.return_value.complete.side_effect = Exception("no LLM")
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result = extract_jd_signals(SAMPLE_JD, resume_text="Python developer")
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assert isinstance(result, list)
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def test_extract_jd_signals_llm_path_parses_json_array():
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"""extract_jd_signals merges LLM-extracted signals with TF-IDF gaps."""
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from scripts.resume_optimizer import extract_jd_signals
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llm_response = '["Gainsight", "cross-functional leadership", "stakeholder management"]'
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with patch("scripts.llm_router.LLMRouter") as MockRouter:
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MockRouter.return_value.complete.return_value = llm_response
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result = extract_jd_signals(SAMPLE_JD)
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assert "Gainsight" in result
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assert "cross-functional leadership" in result
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def test_extract_jd_signals_deduplicates():
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"""extract_jd_signals deduplicates terms across LLM and TF-IDF sources."""
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from scripts.resume_optimizer import extract_jd_signals
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llm_response = '["Python", "AWS", "Python"]'
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with patch("scripts.llm_router.LLMRouter") as MockRouter:
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MockRouter.return_value.complete.return_value = llm_response
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result = extract_jd_signals(SAMPLE_JD)
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assert result.count("Python") == 1
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def test_extract_jd_signals_handles_malformed_llm_json():
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"""extract_jd_signals falls back gracefully when LLM returns non-JSON."""
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from scripts.resume_optimizer import extract_jd_signals
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with patch("scripts.llm_router.LLMRouter") as MockRouter:
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MockRouter.return_value.complete.return_value = "Here are some keywords: Gainsight, AWS"
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result = extract_jd_signals(SAMPLE_JD)
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# Should still return a list (may be empty if TF-IDF also silent)
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assert isinstance(result, list)
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# ── prioritize_gaps ───────────────────────────────────────────────────────────
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def test_prioritize_gaps_skips_existing_terms():
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"""prioritize_gaps excludes terms already present in the resume."""
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from scripts.resume_optimizer import prioritize_gaps
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# "Salesforce" is already in SAMPLE_RESUME skills
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result = prioritize_gaps(["Salesforce", "Gainsight"], SAMPLE_RESUME)
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terms = [r["term"] for r in result]
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assert "Salesforce" not in terms
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assert "Gainsight" in terms
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def test_prioritize_gaps_routes_tech_terms_to_skills():
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"""prioritize_gaps maps known tech keywords to the skills section at priority 1."""
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from scripts.resume_optimizer import prioritize_gaps
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result = prioritize_gaps(["AWS", "Docker"], SAMPLE_RESUME)
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by_term = {r["term"]: r for r in result}
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assert by_term["AWS"]["section"] == "skills"
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assert by_term["AWS"]["priority"] == 1
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assert by_term["Docker"]["section"] == "skills"
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def test_prioritize_gaps_routes_leadership_terms_to_summary():
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"""prioritize_gaps maps leadership/executive signals to the summary section."""
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from scripts.resume_optimizer import prioritize_gaps
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result = prioritize_gaps(["cross-functional", "stakeholder"], SAMPLE_RESUME)
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by_term = {r["term"]: r for r in result}
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assert by_term["cross-functional"]["section"] == "summary"
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assert by_term["stakeholder"]["section"] == "summary"
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def test_prioritize_gaps_multi_word_routes_to_experience():
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"""Multi-word phrases not in skills/summary lists go to experience at priority 2."""
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from scripts.resume_optimizer import prioritize_gaps
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result = prioritize_gaps(["proactive client engagement"], SAMPLE_RESUME)
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assert result[0]["section"] == "experience"
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assert result[0]["priority"] == 2
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def test_prioritize_gaps_single_word_is_lowest_priority():
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"""Single generic words not in any list go to experience at priority 3."""
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from scripts.resume_optimizer import prioritize_gaps
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result = prioritize_gaps(["innovation"], SAMPLE_RESUME)
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assert result[0]["priority"] == 3
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def test_prioritize_gaps_sorted_by_priority():
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"""prioritize_gaps output is sorted ascending by priority (1 first)."""
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from scripts.resume_optimizer import prioritize_gaps
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gaps = ["innovation", "AWS", "cross-functional", "managed service contracts"]
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result = prioritize_gaps(gaps, SAMPLE_RESUME)
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priorities = [r["priority"] for r in result]
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assert priorities == sorted(priorities)
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# ── hallucination_check ───────────────────────────────────────────────────────
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def test_hallucination_check_passes_unchanged_resume():
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"""hallucination_check returns True when rewrite has no new employers or institutions."""
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from scripts.resume_optimizer import hallucination_check
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# Shallow rewrite: same structure
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rewritten = {
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**SAMPLE_RESUME,
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"career_summary": "Dynamic CSM with cross-functional stakeholder management experience.",
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}
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assert hallucination_check(SAMPLE_RESUME, rewritten) is True
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def test_hallucination_check_fails_on_new_employer():
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"""hallucination_check returns False when a new company is introduced."""
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from scripts.resume_optimizer import hallucination_check
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fabricated_entry = {
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"title": "VP of Customer Success",
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"company": "Fabricated Corp",
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"start_date": "2019",
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"end_date": "2021",
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"bullets": ["Led a team of 30."],
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}
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rewritten = dict(SAMPLE_RESUME)
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rewritten["experience"] = SAMPLE_RESUME["experience"] + [fabricated_entry]
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assert hallucination_check(SAMPLE_RESUME, rewritten) is False
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def test_hallucination_check_fails_on_new_institution():
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"""hallucination_check returns False when a new educational institution appears."""
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from scripts.resume_optimizer import hallucination_check
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rewritten = dict(SAMPLE_RESUME)
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rewritten["education"] = [
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*SAMPLE_RESUME["education"],
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{"degree": "M.S.", "field": "Data Science", "institution": "MIT", "graduation_year": "2020"},
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]
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assert hallucination_check(SAMPLE_RESUME, rewritten) is False
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# ── render_resume_text ────────────────────────────────────────────────────────
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def test_render_resume_text_contains_all_sections():
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"""render_resume_text produces plain text containing all resume sections."""
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from scripts.resume_optimizer import render_resume_text
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text = render_resume_text(SAMPLE_RESUME)
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assert "Alex Rivera" in text
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assert "SUMMARY" in text
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assert "EXPERIENCE" in text
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assert "Customer Success Manager" in text
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assert "Acme Corp" in text
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assert "EDUCATION" in text
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assert "State University" in text
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assert "SKILLS" in text
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assert "Salesforce" in text
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def test_render_resume_text_omits_empty_sections():
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"""render_resume_text skips sections that have no content."""
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from scripts.resume_optimizer import render_resume_text
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sparse = {
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"name": "Jordan Lee",
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"email": "",
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"phone": "",
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"career_summary": "",
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"skills": [],
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"experience": [],
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"education": [],
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"achievements": [],
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}
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text = render_resume_text(sparse)
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assert "EXPERIENCE" not in text
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assert "SKILLS" not in text
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# ── db integration ────────────────────────────────────────────────────────────
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def test_save_and_get_optimized_resume(tmp_path):
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"""save_optimized_resume persists and get_optimized_resume retrieves the data."""
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from scripts.db import init_db, save_optimized_resume, get_optimized_resume
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db_path = tmp_path / "test.db"
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init_db(db_path)
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# Insert a minimal job to satisfy FK
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import sqlite3
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conn = sqlite3.connect(db_path)
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conn.execute(
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"INSERT INTO jobs (id, title, company, url, source, status) VALUES (1, 'CSM', 'Acme', 'http://x.com', 'test', 'approved')"
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)
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conn.commit()
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conn.close()
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gap_report = json.dumps([{"term": "Gainsight", "section": "skills", "priority": 1, "rationale": "test"}])
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save_optimized_resume(db_path, job_id=1, text="Rewritten resume text.", gap_report=gap_report)
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result = get_optimized_resume(db_path, job_id=1)
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assert result["optimized_resume"] == "Rewritten resume text."
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parsed = json.loads(result["ats_gap_report"])
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assert parsed[0]["term"] == "Gainsight"
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def test_get_optimized_resume_returns_empty_for_missing(tmp_path):
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"""get_optimized_resume returns empty strings when no record exists."""
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from scripts.db import init_db, get_optimized_resume
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db_path = tmp_path / "test.db"
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init_db(db_path)
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result = get_optimized_resume(db_path, job_id=999)
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assert result["optimized_resume"] == ""
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assert result["ats_gap_report"] == ""
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