test(scanner): unit tests for github_trending_scanner
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Rockachopa
2026-04-26 11:21:02 +00:00
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#!/usr/bin/env python3
"""Tests for github_trending_scanner.py — pure function validation.
Tests the feature inference, extraction, and output formatting logic
without relying on external GitHub API calls.
"""
import json
import sys
import tempfile
from pathlib import Path
# Add scripts dir to path for import
sys.path.insert(0, str(Path(__file__).resolve().parent))
from github_trending_scanner import (
extract_repo_features,
infer_features,
save_trending,
)
def test_infer_features_from_description():
"""Feature inference extracts capabilities from description text."""
desc = "A local, quantized LLM framework for fine-tuning and agent-based RAG with vision."
topics = ["ai", "llm"]
features = infer_features(desc, topics)
# Should include relevant capabilities (case-insensitive comparison)
expected_lower = {"fine-tuning", "local/offline", "quantized models", "agent framework", "vision", "retrieval/rag"}
actual_lower = set(f.lower() for f in features)
assert expected_lower.issubset(actual_lower), f"Missing features. Expected subset of {expected_lower}, got {actual_lower}"
print("PASS: infer_features_from_description")
def test_infer_features_from_topics_only():
"""Topics alone can drive feature detection."""
desc = ""
topics = ["computer-vision", "speech", "pytorch"]
features = infer_features(desc, topics)
# Non-generic topics should appear as features (topics preserved as-is)
assert "computer-vision" in features, f"Expected 'computer-vision' in {features}"
assert "speech" in features, f"Expected 'speech' in {features}"
# Generic topics (pytorch) may be filtered
print(f"PASS: infer_features_from_topics_only → {features}")
def test_extract_repo_features_produces_valid_structure():
"""extract_repo_features returns all required fields."""
mock_repo = {
"full_name": "example/repo",
"description": "An example repository",
"stargazers_count": 1234,
"forks_count": 56,
"open_issues_count": 7,
"language": "Python",
"topics": ["ai", "llm"],
"html_url": "https://github.com/example/repo",
"created_at": "2025-01-01T00:00:00Z",
"updated_at": "2026-01-01T00:00:00Z",
}
result = extract_repo_features(mock_repo)
assert result["name"] == "example/repo"
assert result["description"] == "An example repository"
assert result["stars"] == 1234
assert isinstance(result["key_features"], list)
assert "scanned_at" in result
assert result["url"] == "https://github.com/example/repo"
print("PASS: extract_repo_features_structure")
def test_save_trending_creates_dated_json():
"""save_trending writes a valid JSON file with the expected schema."""
repos = [
{
"name": "test/repo",
"description": "Test repository",
"stars": 999,
"language": "Python",
"topics": ["test"],
"key_features": ["testing"],
"scanned_at": "2026-04-26T00:00:00+00:00",
}
]
with tempfile.TemporaryDirectory() as tmp:
output_file = save_trending(repos, output_dir=tmp)
path = Path(output_file)
assert path.exists(), f"Output file not created: {output_file}"
with open(path) as f:
data = json.load(f)
assert "scanned_at" in data
assert data["count"] == 1
assert isinstance(data["repos"], list)
assert data["repos"][0]["name"] == "test/repo"
print(f"PASS: save_trending → {output_file}")
def test_save_trending_respects_output_dir_creation():
"""Output directory is created if it doesn't exist."""
repos = []
with tempfile.TemporaryDirectory() as tmp:
nested = Path(tmp) / "nested" / "trending"
assert not nested.exists()
output_file = save_trending(repos, output_dir=str(nested))
assert nested.exists()
assert Path(output_file).exists()
print("PASS: output_dir_creation")
if __name__ == "__main__":
test_infer_features_from_description()
test_infer_features_from_topics_only()
test_extract_repo_features_produces_valid_structure()
test_save_trending_creates_dated_json()
test_save_trending_respects_output_dir_creation()
print("\nAll github_trending_scanner tests passed.")