36678cd00d
Phase 1 - Foundation: - Add pytest, pyproject.toml, requirements-dev.txt - 593 smoke tests (324 syntax + 269 argparse --help) for all Python scripts - Harden CI: remove || true from compileall, expand to all 9 directories, add pytest step Phase 2 - Calculator unit tests: - RICE prioritizer: formula, prioritization, portfolio analysis, roadmap - DCF valuation: WACC, cash flow projections, terminal value, sensitivity - Financial ratios: profitability, liquidity, leverage, efficiency, valuation - Campaign ROI: metrics, benchmarks, portfolio summary - Funnel analyzer: stage metrics, bottleneck detection, segment comparison - OKR tracker: numeric/percentage/milestone/boolean KR scoring, status Phase 3 - Parser and compliance tests: - SEO checker: HTML parsing, scoring, heading hierarchy, alt text, word count - Commit linter: conventional commit regex, lint report, file input - GDPR compliance: pattern detection, file scanning, project analysis Phase 4 - Integration tests: - 671 skill integrity tests: frontmatter, H1 headings, scripts dirs, references Bug fixes found by tests: - Fix duplicate --reason argparse arg in document_version_control.py https://claude.ai/code/session_01MsVmZoAsPvLv7rAGDBGTbL
102 lines
3.6 KiB
Python
102 lines
3.6 KiB
Python
"""Unit tests for the Funnel Analyzer."""
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import sys
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import os
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import pytest
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sys.path.insert(0, os.path.join(
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os.path.dirname(__file__), "..", "marketing-skill", "campaign-analytics", "scripts"
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))
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from funnel_analyzer import analyze_funnel, compare_segments, safe_divide
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class TestAnalyzeFunnel:
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def test_basic_funnel(self):
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stages = ["Visit", "Signup", "Activate", "Pay"]
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counts = [10000, 5000, 2000, 500]
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result = analyze_funnel(stages, counts)
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assert result["total_entries"] == 10000
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assert result["total_conversions"] == 500
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assert result["total_lost"] == 9500
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assert result["overall_conversion_rate"] == 5.0
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def test_stage_metrics_count(self):
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stages = ["A", "B", "C"]
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counts = [1000, 500, 100]
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result = analyze_funnel(stages, counts)
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assert len(result["stage_metrics"]) == 3
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def test_conversion_rates(self):
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stages = ["Visit", "Signup", "Pay"]
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counts = [1000, 500, 250]
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result = analyze_funnel(stages, counts)
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# Visit -> Signup: 500/1000 = 50%
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assert result["stage_metrics"][1]["conversion_rate"] == 50.0
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# Signup -> Pay: 250/500 = 50%
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assert result["stage_metrics"][2]["conversion_rate"] == 50.0
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def test_dropoff_detection(self):
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stages = ["A", "B", "C"]
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counts = [1000, 200, 100]
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result = analyze_funnel(stages, counts)
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# Biggest absolute drop: A->B (800)
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assert result["bottleneck_absolute"]["dropoff_count"] == 800
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assert "A -> B" in result["bottleneck_absolute"]["transition"]
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def test_relative_bottleneck(self):
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stages = ["A", "B", "C"]
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counts = [1000, 900, 100]
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result = analyze_funnel(stages, counts)
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# A->B: dropoff_rate = 10%, B->C: dropoff_rate = 88.89%
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assert "B -> C" in result["bottleneck_relative"]["transition"]
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def test_cumulative_conversion(self):
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stages = ["A", "B", "C"]
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counts = [1000, 500, 200]
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result = analyze_funnel(stages, counts)
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assert result["stage_metrics"][0]["cumulative_conversion"] == 100.0
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assert result["stage_metrics"][1]["cumulative_conversion"] == 50.0
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assert result["stage_metrics"][2]["cumulative_conversion"] == 20.0
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def test_single_stage(self):
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result = analyze_funnel(["Only"], [500])
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assert result["overall_conversion_rate"] == 100.0
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assert result["total_entries"] == 500
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assert result["total_lost"] == 0
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def test_mismatched_lengths_raises(self):
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with pytest.raises(ValueError, match="must match"):
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analyze_funnel(["A", "B"], [100])
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def test_empty_stages_raises(self):
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with pytest.raises(ValueError, match="at least one"):
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analyze_funnel([], [])
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def test_no_dropoff(self):
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stages = ["A", "B"]
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counts = [100, 100]
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result = analyze_funnel(stages, counts)
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assert result["stage_metrics"][1]["conversion_rate"] == 100.0
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assert result["stage_metrics"][1]["dropoff_count"] == 0
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class TestCompareSegments:
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def test_ranks_segments(self):
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stages = ["Visit", "Signup", "Pay"]
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segments = {
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"mobile": {"counts": [1000, 300, 50]},
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"desktop": {"counts": [1000, 600, 200]},
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}
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result = compare_segments(segments, stages)
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# Desktop has better overall conversion (20% vs 5%)
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assert result["rankings"][0]["segment"] == "desktop"
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def test_mismatched_segment_counts_raises(self):
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with pytest.raises(ValueError, match="counts"):
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compare_segments({"bad": {"counts": [100, 50]}}, ["A", "B", "C"])
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