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https://github.com/gbessoni/seobuild-onpage.git
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Greg BessoniandClaude Opus 4.6
ae47fcccba
GEO framework that writes pages ranking on Google AND getting cited by LLMs. 500-token chunk architecture, Reddit Test quality gates, verification tags, Not For You blocks, information gain enforcement. Data layer: DataForSEO, GSC, Ahrefs MCP, SEMRush MCP. 21 files, all tests passing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
126 lines
4.0 KiB
Python
126 lines
4.0 KiB
Python
"""Tests for serp_analyze module."""
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import sys
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import os
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import json
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from pathlib import Path
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# Add scripts dir to path
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sys.path.insert(
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0, str(Path(__file__).parent.parent / "scripts")
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)
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from lib.serp_analyze import analyze_serp, detect_intent
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def load_fixture(name: str):
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fixtures_dir = Path(__file__).parent.parent / "fixtures"
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with open(fixtures_dir / name) as f:
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return json.load(f)
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def test_detect_intent_commercial():
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assert detect_intent("best project management tools", [], {}) == "commercial"
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assert detect_intent("X vs Y comparison", [], {}) == "commercial"
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assert detect_intent("slack alternatives", [], {}) == "commercial"
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def test_detect_intent_informational():
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assert detect_intent("how to park at JFK", [], {}) == "informational"
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assert detect_intent("what is SEO", [], {}) == "informational"
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assert detect_intent("python tutorial for beginners", [], {}) == "informational"
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def test_detect_intent_transactional():
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assert detect_intent("buy parking pass JFK", [], {}) == "transactional"
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assert detect_intent("JFK parking coupon discount", [], {}) == "transactional"
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assert detect_intent("cheap parking near me", [], {}) == "transactional"
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def test_detect_intent_navigational():
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assert detect_intent("JFK airport official website", [], {}) == "navigational"
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assert detect_intent("parkingaccess.com login", [], {}) == "navigational"
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def test_analyze_serp_with_fixtures():
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serp_data = load_fixture("serp_sample.json")
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# Build content_data from the fixture's embedded word_count/headings
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content_data = []
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for item in serp_data.get("organic", []):
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if item.get("word_count"):
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content_data.append({
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"word_count": item["word_count"],
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"headings": item.get("headings", []),
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})
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else:
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content_data.append(None)
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analysis = analyze_serp(serp_data, content_data, "airport parking JFK")
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assert analysis["keyword"] == "airport parking JFK"
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assert analysis["intent"] in (
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"informational", "commercial", "transactional", "navigational"
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)
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# Word count stats should reflect fixture data
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wc = analysis["word_count_stats"]
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assert wc["min"] > 0
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assert wc["max"] >= wc["min"]
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assert wc["median"] > 0
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assert wc["recommended_min"] > 0
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assert wc["recommended_max"] > wc["recommended_min"]
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# PAA should come through
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assert len(analysis["paa_questions"]) > 0
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# Topic frequency should have entries from headings
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assert len(analysis["topic_frequency"]) > 0
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# Heading patterns should be populated
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hp = analysis["heading_patterns"]
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assert hp["avg_h2_count"] > 0
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def test_analyze_serp_empty():
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"""Handle empty SERP data gracefully."""
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analysis = analyze_serp(
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{"organic": [], "paa": [], "featured_snippet": None},
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[],
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"nonexistent keyword",
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)
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assert analysis["keyword"] == "nonexistent keyword"
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assert analysis["word_count_stats"] == {}
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assert analysis["competitors_analyzed"] == 0
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def test_analyze_serp_partial_content():
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"""Handle mix of parsed and failed content parses."""
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serp_data = {
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"organic": [
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{"position": 1, "url": "https://a.com", "title": "A", "description": ""},
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{"position": 2, "url": "https://b.com", "title": "B", "description": ""},
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],
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"paa": ["Question 1?"],
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"featured_snippet": None,
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}
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content_data = [
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{"word_count": 2000, "headings": ["H1: Title", "H2: Section One", "H2: Section Two"]},
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None, # failed parse
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]
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analysis = analyze_serp(serp_data, content_data, "test keyword")
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assert analysis["competitors_analyzed"] == 1
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assert analysis["word_count_stats"]["median"] == 2000
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if __name__ == "__main__":
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test_detect_intent_commercial()
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test_detect_intent_informational()
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test_detect_intent_transactional()
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test_detect_intent_navigational()
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test_analyze_serp_with_fixtures()
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test_analyze_serp_empty()
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test_analyze_serp_partial_content()
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print("All tests passed.")
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