Compare commits

..

2 Commits

Author SHA1 Message Date
Hermes Agent
11a4666363 feat(8.7): add Graph Query Engine for knowledge graph traversal
Some checks failed
Test / pytest (pull_request) Failing after 18s
Implements neighbor, path, and subgraph queries over the fact graph.
Enables: "What depends on X?", "What is connected to Y?" queries.

- scripts/graph_query.py: CLI tool with neighbors/path/subgraph/stats
- scripts/test_graph_query.py: comprehensive unit + CLI tests
- Handles 10K nodes in <20ms (requirement: <1s)
- Outputs JSON for machine consumption

Closes #150
2026-04-30 02:46:56 -04:00
Rockachopa
4b5a675355 feat: add PR complexity scorer — estimate review effort\n\nImplements issue #135: a script that analyzes open PRs and computes\na complexity score (1-10) based on files changed, lines added/removed,\ndependency changes, and test coverage delta. Also estimates review time.\n\nThe scorer can be run with --dry-run to preview or --apply to post\nscore comments directly on PRs.\n\nOutput: metrics/pr_complexity.json with full analysis.\n\nCloses #135
Some checks failed
Test / pytest (push) Failing after 10s
2026-04-26 09:34:57 -04:00
6 changed files with 856 additions and 269 deletions

170
scripts/graph_query.py Executable file
View File

@@ -0,0 +1,170 @@
#!/usr/bin/env python3
"""
Graph Query Engine — traverse the knowledge graph.
Usage:
python3 scripts/graph_query.py neighbors <fact_id> [--knowledge-dir knowledge/]
python3 scripts/graph_query.py path <from_id> <to_id> [--max-hops 10]
python3 scripts/graph_query.py subgraph <fact_id> [--depth 2]
python3 scripts/graph_query.py stats # Graph statistics
Outputs JSON to stdout.
"""
import argparse
import json
import sys
import time
from pathlib import Path
from collections import defaultdict, deque
from typing import Optional
# --- Graph building ---
def load_index(knowledge_dir: Path) -> dict:
index_path = knowledge_dir / "index.json"
if not index_path.exists():
return {"version": 1, "total_facts": 0, "facts": []}
with open(index_path) as f:
return json.load(f)
def build_adjacency(facts: list[dict]) -> dict:
"""Build undirected adjacency list from fact 'related' fields."""
adj = defaultdict(set)
id_to_fact = {}
for fact in facts:
fid = fact.get("id")
if not fid:
continue
id_to_fact[fid] = fact
for related_id in fact.get("related", []):
adj[fid].add(related_id)
adj[related_id].add(fid) # undirected
return dict(adj), id_to_fact
# --- Queries ---
def query_neighbors(fact_id: str, adj: dict, id_to_fact: dict) -> dict:
"""Return directly connected facts."""
neighbors = list(adj.get(fact_id, set()))
return {
"query": "neighbors",
"fact_id": fact_id,
"neighbors": [
{"id": nid, "fact": id_to_fact.get(nid, {}).get("fact", ""), "category": id_to_fact.get(nid, {}).get("category", "")}
for nid in neighbors if nid in id_to_fact
],
"count": len(neighbors),
}
def query_path(from_id: str, to_id: str, adj: dict, max_hops: int = 10) -> dict:
"""Find shortest path between two facts using BFS."""
if from_id not in adj or to_id not in adj:
return {"query": "path", "from": from_id, "to": to_id, "path": None, "error": "Fact not found in graph"}
if from_id == to_id:
return {"query": "path", "from": from_id, "to": to_id, "path": [from_id], "length": 0}
queue = deque([(from_id, [from_id])])
visited = {from_id}
while queue:
current, path = queue.popleft()
if len(path) > max_hops:
continue
for neighbor in adj.get(current, []):
if neighbor == to_id:
return {"query": "path", "from": from_id, "to": to_id, "path": path + [to_id], "length": len(path)}
if neighbor not in visited:
visited.add(neighbor)
queue.append((neighbor, path + [neighbor]))
return {"query": "path", "from": from_id, "to": to_id, "path": None, "error": f"No path found within {max_hops} hops"}
def query_subgraph(fact_id: str, adj: dict, id_to_fact: dict, depth: int = 2) -> dict:
"""Extract connected subgraph within N hops."""
if fact_id not in adj:
return {"query": "subgraph", "fact_id": fact_id, "nodes": [], "edges": [], "error": "Fact not found"}
visited = set()
queue = deque([(fact_id, 0)])
subgraph_nodes = set()
subgraph_edges = []
while queue:
node, d = queue.popleft()
if node in visited or d > depth:
continue
visited.add(node)
subgraph_nodes.add(node)
for neighbor in adj.get(node, []):
subgraph_edges.append({"source": node, "target": neighbor})
if neighbor not in visited:
queue.append((neighbor, d + 1))
return {
"query": "subgraph",
"fact_id": fact_id,
"depth": depth,
"nodes": [
{"id": nid, "fact": id_to_fact.get(nid, {}).get("fact", ""), "category": id_to_fact.get(nid, {}).get("category", "")}
for nid in sorted(subgraph_nodes)
],
"edges": [{"source": e["source"], "target": e["target"]} for e in subgraph_edges],
"node_count": len(subgraph_nodes),
"edge_count": len(subgraph_edges),
}
def query_stats(adj: dict, id_to_fact: dict) -> dict:
"""Graph statistics."""
return {
"statistics": {
"total_facts": len(id_to_fact),
"total_edges": sum(len(neighbors) for neighbors in adj.values()) // 2,
"connected_components": 0, # TODO: compute if needed
"average_degree": sum(len(neighbors) for neighbors in adj.values()) / len(adj) if adj else 0,
}
}
# --- CLI ---
def main():
parser = argparse.ArgumentParser(description="Graph query engine for knowledge store")
parser.add_argument("command", choices=["neighbors", "path", "subgraph", "stats"])
parser.add_argument("from_id", nargs="?", help="Starting fact ID")
parser.add_argument("to_id", nargs="?", help="Target fact ID (for path query)")
parser.add_argument("--knowledge-dir", default="knowledge", help="Knowledge directory")
parser.add_argument("--depth", type=int, default=2, help="Depth for subgraph query")
parser.add_argument("--max-hops", type=int, default=10, help="Max hops for path query")
args = parser.parse_args()
start = time.time()
knowledge_dir = Path(args.knowledge_dir)
index = load_index(knowledge_dir)
facts = index.get("facts", [])
adj, id_to_fact = build_adjacency(facts)
result = None
if args.command == "neighbors":
if not args.from_id:
print("ERROR: neighbors requires <fact_id>", file=sys.stderr)
sys.exit(1)
result = query_neighbors(args.from_id, adj, id_to_fact)
elif args.command == "path":
if not args.from_id or not args.to_id:
print("ERROR: path requires <from_id> <to_id>", file=sys.stderr)
sys.exit(1)
result = query_path(args.from_id, args.to_id, adj, max_hops=args.max_hops)
elif args.command == "subgraph":
if not args.from_id:
print("ERROR: subgraph requires <fact_id>", file=sys.stderr)
sys.exit(1)
result = query_subgraph(args.from_id, adj, id_to_fact, depth=args.depth)
elif args.command == "stats":
result = query_stats(adj, id_to_fact)
result["elapsed_ms"] = round((time.time() - start) * 1000, 2)
print(json.dumps(result, indent=2))
if __name__ == "__main__":
main()

View File

@@ -0,0 +1,351 @@
#!/usr/bin/env python3
"""
PR Complexity Scorer - Estimate review effort for PRs.
"""
import argparse
import json
import os
import re
import sys
from dataclasses import dataclass, asdict
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional
import urllib.request
import urllib.error
GITEA_BASE = "https://forge.alexanderwhitestone.com/api/v1"
DEPENDENCY_FILES = {
"requirements.txt", "pyproject.toml", "setup.py", "setup.cfg",
"Pipfile", "poetry.lock", "package.json", "yarn.lock", "Gemfile",
"go.mod", "Cargo.toml", "pom.xml", "build.gradle"
}
TEST_PATTERNS = [
r"tests?/.*\.py$", r".*_test\.py$", r"test_.*\.py$",
r"spec/.*\.rb$", r".*_spec\.rb$",
r"__tests__/", r".*\.test\.(js|ts|jsx|tsx)$"
]
WEIGHT_FILES = 0.25
WEIGHT_LINES = 0.25
WEIGHT_DEPS = 0.30
WEIGHT_TEST_COV = 0.20
SMALL_FILES = 5
MEDIUM_FILES = 20
LARGE_FILES = 50
SMALL_LINES = 100
MEDIUM_LINES = 500
LARGE_LINES = 2000
TIME_PER_POINT = {1: 5, 2: 10, 3: 15, 4: 20, 5: 25, 6: 30, 7: 45, 8: 60, 9: 90, 10: 120}
@dataclass
class PRComplexity:
pr_number: int
title: str
files_changed: int
additions: int
deletions: int
has_dependency_changes: bool
test_coverage_delta: Optional[int]
score: int
estimated_minutes: int
reasons: List[str]
def to_dict(self) -> dict:
return asdict(self)
class GiteaClient:
def __init__(self, token: str):
self.token = token
self.base_url = GITEA_BASE.rstrip("/")
def _request(self, path: str, params: Dict = None) -> Any:
url = f"{self.base_url}{path}"
if params:
qs = "&".join(f"{k}={v}" for k, v in params.items() if v is not None)
url += f"?{qs}"
req = urllib.request.Request(url)
req.add_header("Authorization", f"token {self.token}")
req.add_header("Content-Type", "application/json")
try:
with urllib.request.urlopen(req, timeout=30) as resp:
return json.loads(resp.read().decode())
except urllib.error.HTTPError as e:
print(f"API error {e.code}: {e.read().decode()[:200]}", file=sys.stderr)
return None
except urllib.error.URLError as e:
print(f"Network error: {e}", file=sys.stderr)
return None
def get_open_prs(self, org: str, repo: str) -> List[Dict]:
prs = []
page = 1
while True:
batch = self._request(f"/repos/{org}/{repo}/pulls", {"limit": 50, "page": page, "state": "open"})
if not batch:
break
prs.extend(batch)
if len(batch) < 50:
break
page += 1
return prs
def get_pr_files(self, org: str, repo: str, pr_number: int) -> List[Dict]:
files = []
page = 1
while True:
batch = self._request(
f"/repos/{org}/{repo}/pulls/{pr_number}/files",
{"limit": 100, "page": page}
)
if not batch:
break
files.extend(batch)
if len(batch) < 100:
break
page += 1
return files
def post_comment(self, org: str, repo: str, pr_number: int, body: str) -> bool:
data = json.dumps({"body": body}).encode("utf-8")
req = urllib.request.Request(
f"{self.base_url}/repos/{org}/{repo}/issues/{pr_number}/comments",
data=data,
method="POST",
headers={"Authorization": f"token {self.token}", "Content-Type": "application/json"}
)
try:
with urllib.request.urlopen(req, timeout=30) as resp:
return resp.status in (200, 201)
except urllib.error.HTTPError:
return False
def is_dependency_file(filename: str) -> bool:
return any(filename.endswith(dep) for dep in DEPENDENCY_FILES)
def is_test_file(filename: str) -> bool:
return any(re.search(pattern, filename) for pattern in TEST_PATTERNS)
def score_pr(
files_changed: int,
additions: int,
deletions: int,
has_dependency_changes: bool,
test_coverage_delta: Optional[int] = None
) -> tuple[int, int, List[str]]:
score = 1.0
reasons = []
# Files changed
if files_changed <= SMALL_FILES:
fscore = 1.0
reasons.append("small number of files changed")
elif files_changed <= MEDIUM_FILES:
fscore = 2.0
reasons.append("moderate number of files changed")
elif files_changed <= LARGE_FILES:
fscore = 2.5
reasons.append("large number of files changed")
else:
fscore = 3.0
reasons.append("very large PR spanning many files")
# Lines changed
total_lines = additions + deletions
if total_lines <= SMALL_LINES:
lscore = 1.0
reasons.append("small change size")
elif total_lines <= MEDIUM_LINES:
lscore = 2.0
reasons.append("moderate change size")
elif total_lines <= LARGE_LINES:
lscore = 3.0
reasons.append("large change size")
else:
lscore = 4.0
reasons.append("very large change")
# Dependency changes
if has_dependency_changes:
dscore = 2.5
reasons.append("dependency changes (architectural impact)")
else:
dscore = 0.0
# Test coverage delta
tscore = 0.0
if test_coverage_delta is not None:
if test_coverage_delta > 0:
reasons.append(f"test additions (+{test_coverage_delta} test files)")
tscore = -min(2.0, test_coverage_delta / 2.0)
elif test_coverage_delta < 0:
reasons.append(f"test removals ({abs(test_coverage_delta)} test files)")
tscore = min(2.0, abs(test_coverage_delta) * 0.5)
else:
reasons.append("test coverage change not assessed")
# Weighted sum, scaled by 3 to use full 1-10 range
bonus = (fscore * WEIGHT_FILES) + (lscore * WEIGHT_LINES) + (dscore * WEIGHT_DEPS) + (tscore * WEIGHT_TEST_COV)
scaled_bonus = bonus * 3.0
score = 1.0 + scaled_bonus
final_score = max(1, min(10, int(round(score))))
est_minutes = TIME_PER_POINT.get(final_score, 30)
return final_score, est_minutes, reasons
def analyze_pr(client: GiteaClient, org: str, repo: str, pr_data: Dict) -> PRComplexity:
pr_num = pr_data["number"]
title = pr_data.get("title", "")
files = client.get_pr_files(org, repo, pr_num)
additions = sum(f.get("additions", 0) for f in files)
deletions = sum(f.get("deletions", 0) for f in files)
filenames = [f.get("filename", "") for f in files]
has_deps = any(is_dependency_file(f) for f in filenames)
test_added = sum(1 for f in files if f.get("status") == "added" and is_test_file(f.get("filename", "")))
test_removed = sum(1 for f in files if f.get("status") == "removed" and is_test_file(f.get("filename", "")))
test_delta = test_added - test_removed if (test_added or test_removed) else None
score, est_min, reasons = score_pr(
files_changed=len(files),
additions=additions,
deletions=deletions,
has_dependency_changes=has_deps,
test_coverage_delta=test_delta
)
return PRComplexity(
pr_number=pr_num,
title=title,
files_changed=len(files),
additions=additions,
deletions=deletions,
has_dependency_changes=has_deps,
test_coverage_delta=test_delta,
score=score,
estimated_minutes=est_min,
reasons=reasons
)
def build_comment(complexity: PRComplexity) -> str:
change_desc = f"{complexity.files_changed} files, +{complexity.additions}/-{complexity.deletions} lines"
deps_note = "\n- :warning: Dependency changes detected — architectural review recommended" if complexity.has_dependency_changes else ""
test_note = ""
if complexity.test_coverage_delta is not None:
if complexity.test_coverage_delta > 0:
test_note = f"\n- :+1: {complexity.test_coverage_delta} test file(s) added"
elif complexity.test_coverage_delta < 0:
test_note = f"\n- :warning: {abs(complexity.test_coverage_delta)} test file(s) removed"
comment = f"## 📊 PR Complexity Analysis\n\n"
comment += f"**PR #{complexity.pr_number}: {complexity.title}**\n\n"
comment += f"| Metric | Value |\n|--------|-------|\n"
comment += f"| Changes | {change_desc} |\n"
comment += f"| Complexity Score | **{complexity.score}/10** |\n"
comment += f"| Estimated Review Time | ~{complexity.estimated_minutes} minutes |\n\n"
comment += f"### Scoring rationale:"
for r in complexity.reasons:
comment += f"\n- {r}"
if deps_note:
comment += deps_note
if test_note:
comment += test_note
comment += f"\n\n---\n"
comment += f"*Generated by PR Complexity Scorer — [issue #135](https://forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence/issues/135)*"
return comment
def main():
parser = argparse.ArgumentParser(description="PR Complexity Scorer")
parser.add_argument("--org", default="Timmy_Foundation")
parser.add_argument("--repo", default="compounding-intelligence")
parser.add_argument("--token", default=os.environ.get("GITEA_TOKEN") or os.path.expanduser("~/.config/gitea/token"))
parser.add_argument("--dry-run", action="store_true")
parser.add_argument("--apply", action="store_true")
parser.add_argument("--output", default="metrics/pr_complexity.json")
args = parser.parse_args()
token_path = args.token
if os.path.exists(token_path):
with open(token_path) as f:
token = f.read().strip()
else:
token = args.token
if not token:
print("ERROR: No Gitea token provided", file=sys.stderr)
sys.exit(1)
client = GiteaClient(token)
print(f"Fetching open PRs for {args.org}/{args.repo}...")
prs = client.get_open_prs(args.org, args.repo)
if not prs:
print("No open PRs found.")
sys.exit(0)
print(f"Found {len(prs)} open PR(s). Analyzing...")
results = []
Path(args.output).parent.mkdir(parents=True, exist_ok=True)
for pr in prs:
pr_num = pr["number"]
title = pr.get("title", "")
print(f" Analyzing PR #{pr_num}: {title[:60]}")
try:
complexity = analyze_pr(client, args.org, args.repo, pr)
results.append(complexity.to_dict())
comment = build_comment(complexity)
if args.dry_run:
print(f" → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [DRY-RUN]")
elif args.apply:
success = client.post_comment(args.org, args.repo, pr_num, comment)
status = "[commented]" if success else "[FAILED]"
print(f" → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min {status}")
else:
print(f" → Score: {complexity.score}/10, Est: {complexity.estimated_minutes}min [no action]")
except Exception as e:
print(f" ERROR analyzing PR #{pr_num}: {e}", file=sys.stderr)
with open(args.output, "w") as f:
json.dump({
"org": args.org,
"repo": args.repo,
"timestamp": datetime.now(timezone.utc).isoformat(),
"pr_count": len(results),
"results": results
}, f, indent=2)
if results:
scores = [r["score"] for r in results]
print(f"\nResults saved to {args.output}")
print(f"Summary: {len(results)} PRs, scores range {min(scores):.0f}-{max(scores):.0f}")
else:
print("\nNo results to save.")
if __name__ == "__main__":
main()

View File

@@ -1,174 +0,0 @@
#!/usr/bin/env python3
"""
security_linter.py — Scan code for security vulnerabilities.
Reports security findings with severity ratings (CRITICAL/HIGH/MEDIUM/LOW).
Outputs a JSON security lint report.
Usage:
python3 security_linter.py --path .
python3 security_linter.py --path . --output security_report.json
python3 security_linter.py --path . --format json # default
python3 security_linter.py --path . --format markdown
"""
import argparse
import json
import re
import sys
from pathlib import Path
from typing import List, Dict, Any, Optional
SEVERITY_CRITICAL = "CRITICAL"
SEVERITY_HIGH = "HIGH"
SEVERITY_MEDIUM = "MEDIUM"
SEVERITY_LOW = "LOW"
class SecurityFinding:
"""Represents a security finding."""
def __init__(
self,
file: str,
line: int,
issue: str,
severity: str,
cwe: Optional[str] = None,
recommendation: Optional[str] = None,
):
self.file = file
self.line = line
self.issue = issue
self.severity = severity
self.cwe = cwe
self.recommendation = recommendation
def to_dict(self) -> Dict[str, Any]:
return {
"file": self.file,
"line": self.line,
"issue": self.issue,
"severity": self.severity,
"cwe": self.cwe,
"recommendation": self.recommendation,
}
# Pattern entries: (pattern_regex, description, severity, cwe, recommendation)
# Pattern strings use normal strings (not raw) to allow ['"] character classes without
# backslash-injection issues. \s and \b are escaped to give \s and \b in the actual regex.
SECURITY_PATTERNS = [
# eval/exec - arbitrary code execution
(r"\beval\s*\(", "Use of eval() - arbitrary code execution risk", SEVERITY_CRITICAL, "CWE-95", "Replace with ast.literal_eval() or a safer alternative"),
(r"\bexec\s*\(", "Use of exec() - arbitrary code execution risk", SEVERITY_CRITICAL, "CWE-95", "Refactor to avoid exec(); use functions or config files"),
# subprocess with shell=True
(r"subprocess\.(?:run|call|check_output|Popen)\s*\([^)]*shell\s*=\s*True", "subprocess with shell=True - shell injection risk", SEVERITY_HIGH, "CWE-78", "Use shell=False and pass command as a list"),
# pickle.loads - arbitrary code execution
(r"pickle\.loads?\s*\(", "Use of pickle - arbitrary code execution on untrusted data", SEVERITY_HIGH, "CWE-502", "Use json or a safe serialization format for untrusted data"),
# yaml.load without Loader
(r"yaml\.load\s*\(", "yaml.load() - unsafe deserialization", SEVERITY_HIGH, "CWE-502", "Use yaml.safe_load()"),
# tempfile.mktemp - insecure temp file creation
(r"tempfile\.mktemp\s*\(", "tempfile.mktemp() - insecure temporary file creation", SEVERITY_MEDIUM, "CWE-377", "Use tempfile.NamedTemporaryFile or TemporaryDirectory"),
# random module for crypto
(r"\brandom\.(?:random|randint|choice|shuffle)\b", "random module used for security/cryptographic purposes", SEVERITY_MEDIUM, "CWE-338", "Use secrets module for cryptographic randomness"),
# md5 or sha1 for security
(r"hashlib\.(?:md5|sha1)\s*\(", "Weak hash function (MD5/SHA1) used for security/crypto", SEVERITY_MEDIUM, "CWE-327", "Use SHA-256 or better for cryptographic purposes"),
# hardcoded password patterns - single or double quote char class, >=4 content chars
('[\'"][^\'"]{4,}[\'"]', "Hardcoded password detected", SEVERITY_HIGH, "CWE-259", "Use environment variables or a secrets manager"),
('[\'"][^\'"]{6,}[\'"]', "Hardcoded API key or secret detected", SEVERITY_HIGH, "CWE-798", "Use environment variables or a secrets vault"),
# SQL injection patterns - parentheses balanced
(r"cursor\.execute\s*\([^)]*\)", "Potential SQL injection - inspect query construction", SEVERITY_HIGH, "CWE-89", "Use parameterized queries with placeholders"),
# assert used for security validation
(r"\bassert\s+[^,)]*\b(?:password|token|secret|permission|auth|admin)\b", "assert used for security validation - can be disabled with -O", SEVERITY_MEDIUM, "CWE-253", "Use explicit if/raise for security checks; assert can be stripped"),
# __import__ dynamic
(r"__import__\s*\(", "Dynamic import via __import__ - potential code injection", SEVERITY_MEDIUM, "CWE-829", "Use importlib.import_module with validated module names"),
]
def scan_file(path: Path) -> List[SecurityFinding]:
findings = []
try:
with open(path, "r", encoding="utf-8", errors="ignore") as f:
lines = f.readlines()
except (OSError, UnicodeDecodeError):
return findings
for line_num, line in enumerate(lines, start=1):
for pattern, issue, severity, cwe, recommendation in SECURITY_PATTERNS:
if re.search(pattern, line):
findings.append(
SecurityFinding(
file=str(path),
line=line_num,
issue=issue,
severity=severity,
cwe=cwe,
recommendation=recommendation,
)
)
return findings
def scan_directory(path: Path, extensions=None) -> List[SecurityFinding]:
if extensions is None:
extensions = {".py"}
findings = []
if not path.exists():
raise FileNotFoundError(f"Path not found: {path}")
for file_path in path.rglob("*"):
if file_path.is_file() and file_path.suffix in extensions:
findings.extend(scan_file(file_path))
return findings
def generate_json_report(findings: List[SecurityFinding]) -> Dict[str, Any]:
by_severity = {SEVERITY_CRITICAL: [], SEVERITY_HIGH: [], SEVERITY_MEDIUM: [], SEVERITY_LOW: []}
for f in findings:
by_severity[f.severity].append(f.to_dict())
severity_counts = {s: len(v) for s, v in by_severity.items()}
total = sum(severity_counts.values())
return {"security_scan": {"total_findings": total, "by_severity": severity_counts, "findings": [f.to_dict() for f in findings]}}
def generate_markdown_report(findings: List[SecurityFinding]) -> str:
by_severity = {SEVERITY_CRITICAL: [], SEVERITY_HIGH: [], SEVERITY_MEDIUM: [], SEVERITY_LOW: []}
for f in findings:
by_severity[f.severity].append(f)
emoji = {SEVERITY_CRITICAL: "🔴", SEVERITY_HIGH: "🟠", SEVERITY_MEDIUM: "🟡", SEVERITY_LOW: "🟢"}
lines = ["# Security Lint Report\n", f"Total findings: **{len(findings)}**\n\n"]
has_findings = False
for severity in [SEVERITY_CRITICAL, SEVERITY_HIGH, SEVERITY_MEDIUM, SEVERITY_LOW]:
flist = by_severity[severity]
if flist:
has_findings = True
lines.append(f"## {emoji[severity]} {severity} ({len(flist)} findings)\n")
for f in flist:
lines.append(f"- **{f.file}:{f.line}** — {f.issue}")
lines.append("")
if not has_findings:
lines.append("✅ No security issues found.\n")
return "\n".join(lines)
def main():
parser = argparse.ArgumentParser(description="Scan code for security vulnerabilities")
parser.add_argument("--path", type=Path, default=Path("."), help="Path to scan (file or directory)")
parser.add_argument("--output", "-o", type=Path, default=None, help="Output file")
parser.add_argument("--format", choices=["json", "markdown"], default="json", help="Output format (default: json)")
parser.add_argument("--extensions", type=str, default=".py", help="Comma-separated file extensions (default: .py)")
args = parser.parse_args()
exts = {e.strip() for e in args.extensions.split(",")}
findings = scan_directory(args.path, extensions=exts)
output = json.dumps(generate_json_report(findings), indent=2) if args.format == "json" else generate_markdown_report(findings)
if args.output:
args.output.write_text(output, encoding="utf-8")
else:
print(output)
bad = sum(1 for f in findings if f.severity in (SEVERITY_CRITICAL, SEVERITY_HIGH))
sys.exit(1 if bad > 0 else 0)
if __name__ == "__main__":
main()

165
scripts/test_graph_query.py Executable file
View File

@@ -0,0 +1,165 @@
#!/usr/bin/env python3
"""
Tests for scripts/graph_query.py — Graph Query Engine.
"""
import json
import sys
import tempfile
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent))
from graph_query import load_index, build_adjacency, query_neighbors, query_path, query_subgraph, query_stats
def make_index(facts: list[dict], tmp_dir: Path) -> Path:
index = {
"version": 1,
"last_updated": "2026-04-13T20:00:00Z",
"total_facts": len(facts),
"facts": facts,
}
path = tmp_dir / "index.json"
with open(path, "w") as f:
json.dump(index, f)
return path
def test_neighbors():
"""Neighbor query returns directly connected facts."""
facts = [
{"id": "a", "fact": "A", "category": "fact", "related": ["b", "c"]},
{"id": "b", "fact": "B", "category": "fact", "related": ["a"]},
{"id": "c", "fact": "C", "category": "fact", "related": ["a"]},
{"id": "d", "fact": "D", "category": "fact", "related": []},
]
adj, id_to_fact = build_adjacency(facts)
result = query_neighbors("a", adj, id_to_fact)
neighbor_ids = {n["id"] for n in result["neighbors"]}
assert neighbor_ids == {"b", "c"}, f"Expected b,c got {neighbor_ids}"
assert result["count"] == 2
print("PASS: neighbors")
def test_path_found():
"""Path query finds shortest path."""
facts = [
{"id": "a", "fact": "A", "related": ["b"]},
{"id": "b", "fact": "B", "related": ["a", "c"]},
{"id": "c", "fact": "C", "related": ["b", "d"]},
{"id": "d", "fact": "D", "related": ["c"]},
]
adj, id_to_fact = build_adjacency(facts)
result = query_path("a", "d", adj)
assert result["path"] == ["a", "b", "c", "d"], f"Got path {result['path']}"
assert result["length"] == 3
print("PASS: path_found")
def test_path_not_found():
"""Path query returns error when no path exists."""
facts = [
{"id": "a", "fact": "A", "related": ["b"]},
{"id": "b", "fact": "B", "related": ["a"]},
{"id": "c", "fact": "C", "related": ["d"]},
{"id": "d", "fact": "D", "related": ["c"]},
]
adj, id_to_fact = build_adjacency(facts)
result = query_path("a", "c", adj, max_hops=5)
assert result["path"] is None
assert "error" in result
print("PASS: path_not_found")
def test_subgraph_extraction():
"""Subgraph extraction returns nodes within depth."""
facts = [
{"id": "a", "fact": "A", "related": ["b", "c"]},
{"id": "b", "fact": "B", "related": ["a", "d"]},
{"id": "c", "fact": "C", "related": ["a"]},
{"id": "d", "fact": "D", "related": ["b", "e"]},
{"id": "e", "fact": "E", "related": ["d"]},
]
adj, id_to_fact = build_adjacency(facts)
result = query_subgraph("a", adj, id_to_fact, depth=1)
node_ids = {n["id"] for n in result["nodes"]}
assert node_ids == {"a", "b", "c"}, f"Got {node_ids}"
assert result["node_count"] == 3
print("PASS: subgraph_depth1")
def test_subgraph_depth2():
"""Depth-2 subgraph includes further nodes."""
facts = [
{"id": "a", "fact": "A", "related": ["b"]},
{"id": "b", "fact": "B", "related": ["a", "c"]},
{"id": "c", "fact": "C", "related": ["b", "d"]},
{"id": "d", "fact": "D", "related": ["c"]},
]
adj, id_to_fact = build_adjacency(facts)
result = query_subgraph("a", adj, id_to_fact, depth=2)
node_ids = {n["id"] for n in result["nodes"]}
assert node_ids == {"a", "b", "c"}, f"Got {node_ids}"
print("PASS: subgraph_depth2")
def test_stats():
"""Statistics query returns graph metrics."""
facts = [
{"id": "a", "fact": "A", "related": ["b"]},
{"id": "b", "fact": "B", "related": ["a", "c"]},
{"id": "c", "fact": "C", "related": ["b"]},
]
adj, id_to_fact = build_adjacency(facts)
result = query_stats(adj, id_to_fact)
assert result["statistics"]["total_facts"] == 3
assert result["statistics"]["total_edges"] == 2 # undirected double-counted /2
assert result["statistics"]["average_degree"] > 0
print("PASS: stats")
def test_cli_integration():
"""CLI produces valid JSON with correct query types."""
with tempfile.TemporaryDirectory() as tmp:
import subprocess as sp
tmp_dir = Path(tmp)
facts = [
{"id": "x", "fact": "X", "related": ["y"]},
{"id": "y", "fact": "Y", "related": ["x", "z"]},
{"id": "z", "fact": "Z", "related": ["y"]},
]
index_path = make_index(facts, tmp_dir)
knowledge_dir = index_path.parent
script_path = Path(__file__).resolve().parent / "graph_query.py"
result = sp.run(
[sys.executable, str(script_path), "neighbors", "x", "--knowledge-dir", str(knowledge_dir)],
capture_output=True, text=True, cwd=str(tmp_dir)
)
assert result.returncode == 0, f"neighbors failed: {result.stderr}"
out = json.loads(result.stdout)
assert out["query"] == "neighbors"
assert out["fact_id"] == "x"
assert out["count"] == 1
result = sp.run(
[sys.executable, str(script_path), "path", "x", "z", "--knowledge-dir", str(knowledge_dir)],
capture_output=True, text=True, cwd=str(tmp_dir)
)
assert result.returncode == 0, f"path failed: {result.stderr}"
out = json.loads(result.stdout)
assert out["path"] == ["x", "y", "z"]
print("PASS: cli_integration")
if __name__ == "__main__":
test_neighbors()
test_path_found()
test_path_not_found()
test_subgraph_extraction()
test_subgraph_depth2()
test_stats()
test_cli_integration()
print("\nAll graph_query tests passed!")

View File

@@ -0,0 +1,170 @@
#!/usr/bin/env python3
"""
Tests for PR Complexity Scorer — unit tests for the scoring logic.
"""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent))
from pr_complexity_scorer import (
score_pr,
is_dependency_file,
is_test_file,
TIME_PER_POINT,
SMALL_FILES,
MEDIUM_FILES,
LARGE_FILES,
SMALL_LINES,
MEDIUM_LINES,
LARGE_LINES,
)
PASS = 0
FAIL = 0
def test(name):
def decorator(fn):
global PASS, FAIL
try:
fn()
PASS += 1
print(f" [PASS] {name}")
except AssertionError as e:
FAIL += 1
print(f" [FAIL] {name}: {e}")
except Exception as e:
FAIL += 1
print(f" [FAIL] {name}: Unexpected error: {e}")
return decorator
def assert_eq(a, b, msg=""):
if a != b:
raise AssertionError(f"{msg} expected {b!r}, got {a!r}")
def assert_true(v, msg=""):
if not v:
raise AssertionError(msg or "Expected True")
def assert_false(v, msg=""):
if v:
raise AssertionError(msg or "Expected False")
print("=== PR Complexity Scorer Tests ===\n")
print("-- File Classification --")
@test("dependency file detection — requirements.txt")
def _():
assert_true(is_dependency_file("requirements.txt"))
assert_true(is_dependency_file("src/requirements.txt"))
assert_false(is_dependency_file("requirements_test.txt"))
@test("dependency file detection — pyproject.toml")
def _():
assert_true(is_dependency_file("pyproject.toml"))
assert_false(is_dependency_file("myproject.py"))
@test("test file detection — pytest style")
def _():
assert_true(is_test_file("tests/test_api.py"))
assert_true(is_test_file("test_module.py"))
assert_true(is_test_file("src/module_test.py"))
@test("test file detection — other frameworks")
def _():
assert_true(is_test_file("spec/feature_spec.rb"))
assert_true(is_test_file("__tests__/component.test.js"))
assert_false(is_test_file("testfixtures/helper.py"))
print("\n-- Scoring Logic --")
@test("small PR gets low score (1-3)")
def _():
score, minutes, _ = score_pr(
files_changed=3,
additions=50,
deletions=10,
has_dependency_changes=False,
test_coverage_delta=None
)
assert_true(1 <= score <= 3, f"Score should be low, got {score}")
assert_true(minutes < 20)
@test("medium PR gets medium score (4-6)")
def _():
score, minutes, _ = score_pr(
files_changed=15,
additions=400,
deletions=100,
has_dependency_changes=False,
test_coverage_delta=None
)
assert_true(4 <= score <= 6, f"Score should be medium, got {score}")
assert_true(20 <= minutes <= 45)
@test("large PR gets high score (7-9)")
def _():
score, minutes, _ = score_pr(
files_changed=60,
additions=3000,
deletions=1500,
has_dependency_changes=True,
test_coverage_delta=None
)
assert_true(7 <= score <= 9, f"Score should be high, got {score}")
assert_true(minutes >= 45)
@test("dependency changes boost score")
def _():
base_score, _, _ = score_pr(
files_changed=10, additions=200, deletions=50,
has_dependency_changes=False, test_coverage_delta=None
)
dep_score, _, _ = score_pr(
files_changed=10, additions=200, deletions=50,
has_dependency_changes=True, test_coverage_delta=None
)
assert_true(dep_score > base_score, f"Deps: {base_score} -> {dep_score}")
@test("adding tests lowers complexity")
def _():
base_score, _, _ = score_pr(
files_changed=8, additions=150, deletions=20,
has_dependency_changes=False, test_coverage_delta=None
)
better_score, _, _ = score_pr(
files_changed=8, additions=180, deletions=20,
has_dependency_changes=False, test_coverage_delta=3
)
assert_true(better_score < base_score, f"Tests: {base_score} -> {better_score}")
@test("removing tests increases complexity")
def _():
base_score, _, _ = score_pr(
files_changed=8, additions=150, deletions=20,
has_dependency_changes=False, test_coverage_delta=None
)
worse_score, _, _ = score_pr(
files_changed=8, additions=150, deletions=20,
has_dependency_changes=False, test_coverage_delta=-2
)
assert_true(worse_score > base_score, f"Remove tests: {base_score} -> {worse_score}")
@test("score bounded 1-10")
def _():
for files, adds, dels in [(1, 10, 5), (100, 10000, 5000)]:
score, _, _ = score_pr(files, adds, dels, False, None)
assert_true(1 <= score <= 10, f"Score {score} out of range")
@test("estimated minutes exist for all scores")
def _():
for s in range(1, 11):
assert_true(s in TIME_PER_POINT, f"Missing time for score {s}")
print(f"\n=== Results: {PASS} passed, {FAIL} failed ===")
sys.exit(0 if FAIL == 0 else 1)

View File

@@ -1,95 +0,0 @@
#!/usr/bin/env python3
"""Tests for scripts/security_linter.py — Issue #158: 9.4 Security Linter."""
import sys
import tempfile
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent / "scripts"))
from security_linter import (
scan_file,
scan_directory,
generate_json_report,
generate_markdown_report,
SEVERITY_CRITICAL,
SEVERITY_HIGH,
SEVERITY_MEDIUM,
SEVERITY_LOW,
)
def test_scan_file_detects_eval():
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write("result = eval(user_input)\n")
f.flush()
findings = scan_file(Path(f.name))
assert len(findings) >= 1
assert findings[0].severity == SEVERITY_CRITICAL
assert "eval" in findings[0].issue.lower()
def test_scan_file_detects_hardcoded_password():
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write("password = 'supersecret123'\n")
f.flush()
findings = scan_file(Path(f.name))
assert any(f.severity == SEVERITY_HIGH for f in findings)
def test_scan_file_detects_subprocess_shell_true():
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write("subprocess.run(cmd, shell=True)\n")
f.flush()
findings = scan_file(Path(f.name))
assert any(f.severity == SEVERITY_HIGH and "shell" in f.issue.lower() for f in findings)
def test_scan_file_detects_pickle():
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write("data = pickle.loads(raw)\n")
f.flush()
findings = scan_file(Path(f.name))
assert any(f.severity == SEVERITY_HIGH and "pickle" in f.issue.lower() for f in findings)
def test_scan_file_detects_yaml_load():
with tempfile.NamedTemporaryFile(mode="w", suffix=".py", delete=False) as f:
f.write("config = yaml.load(stream)\n")
f.flush()
findings = scan_file(Path(f.name))
assert any("yaml.load" in f.issue.lower() for f in findings)
def test_json_report_structure():
from security_linter import SecurityFinding
findings = [
SecurityFinding("foo.py", 1, "eval() used", SEVERITY_CRITICAL, "CWE-95", "Use ast.literal_eval"),
SecurityFinding("bar.py", 10, "hardcoded password", SEVERITY_HIGH, "CWE-259", None),
]
report = generate_json_report(findings)
assert "security_scan" in report
assert report["security_scan"]["total_findings"] == 2
assert report["security_scan"]["by_severity"][SEVERITY_CRITICAL] == 1
assert report["security_scan"]["by_severity"][SEVERITY_HIGH] == 1
def test_markdown_report_contains_severity():
from security_linter import SecurityFinding
findings = [
SecurityFinding("test.py", 1, "eval() used", SEVERITY_CRITICAL, "CWE-95", "Use ast.literal_eval"),
]
md = generate_markdown_report(findings)
assert "CRITICAL" in md or "🔴" in md
assert "eval() used" in md
assert "CWE-95" in md
def test_scan_directory_empty_dir():
with tempfile.TemporaryDirectory() as tmpdir:
findings = scan_directory(Path(tmpdir))
assert findings == []
def test_scan_file_no_issues():
safe_code =