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Author SHA1 Message Date
Alexander Payne
899c4bee1e 5.6: Add dependency bloat detector
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Test / pytest (pull_request) Failing after 8s
Scans all .py files for import statements, compares against
requirements.txt, and reports unused declared packages.

Acceptance:
- Lists all imports in code
- Compares against declared deps
- Reports: unused deps
- Output: bloat report

Refs #112
2026-04-26 00:50:36 -04:00
3 changed files with 112 additions and 311 deletions

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#!/usr/bin/env python3
"""
Dependency Bloat Detector — find declared packages never imported
Usage:
python3 scripts/dependency_bloat_detector.py
python3 scripts/dependency_bloat_detector.py --output json
"""
import ast
import json
import re
import sys
from pathlib import Path
from typing import Set, List, Tuple
def extract_imports_from_py_files(repo_path: Path) -> Set[str]:
"""Walk the repo and return the set of top-level imported module names."""
imports = set()
exclude_dirs = {".git", "venv", ".venv", "__pycache__", "node_modules",
"dist", "build", ".tox", "vendor"}
py_files = [
f for f in repo_path.rglob("*.py")
if not any(part in exclude_dirs for part in f.parts)
]
for fpath in py_files:
try:
content = fpath.read_text(errors="ignore")
tree = ast.parse(content)
except Exception:
continue
for node in ast.walk(tree):
if isinstance(node, ast.Import):
for alias in node.names:
top = alias.name.split('.')[0]
imports.add(top)
elif isinstance(node, ast.ImportFrom):
if node.module:
top = node.module.split('.')[0]
imports.add(top)
return imports
def parse_requirements_txt(req_path: Path) -> List[Tuple[str, str]]:
"""
Parse requirements.txt and return list of (package_name, raw_line).
Strips version specifiers and ignores comments.
"""
if not req_path.exists():
return []
declared = []
for line in req_path.read_text().splitlines():
line = line.strip()
if not line or line.startswith('#'):
continue
# Strip inline comments
line = line.split('#')[0].strip()
# Extract package name (before any version specifier)
pkg_match = re.match(r'^([a-zA-Z0-9_-]+)', line)
if pkg_match:
pkg = pkg_match.group(1).strip()
declared.append((pkg, line))
return declared
def main():
repo_path = Path('.').resolve()
req_path = repo_path / 'requirements.txt'
# 1. Scan imports
used = extract_imports_from_py_files(repo_path)
# 2. Parse declared deps
declared = parse_requirements_txt(req_path)
declared_names = [pkg for pkg, _ in declared]
# 3. Compare
unused = [(raw, pkg) for pkg, raw in declared if pkg not in used]
missing_from_req = [imp for imp in used if imp not in declared_names]
# 4. Output
print("=" * 60)
print(" DEPENDENCY BLOAT DETECTOR")
print("=" * 60)
print(f" Repository: {repo_path.name}")
print(f" Requirements: {req_path}")
print(f" Python files: {len(list(repo_path.rglob('*.py')))}")
print()
print(f" Declared packages ({len(declared_names)}): {declared_names}")
print(f" Imported packages ({len(used)}): {sorted(used)}")
print()
if unused:
print(" UNUSED DEPENDENCIES (bloat):")
for raw, pkg in unused:
print(f"{raw}")
else:
print(" No unused dependencies detected.")
print()
if missing_from_req:
print(" UNDECLARED IMPORTS (used but not in requirements.txt):")
for imp in missing_from_req:
print(f" ! {imp}")
print()
print("=" * 60)
# Exit code: 0 if no bloat, 1 if unused deps found
sys.exit(1 if unused else 0)
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
graph_visualizer.py — Generate visual graph representations of the knowledge graph.
Reads knowledge/index.json and renders the fact relationship graph.
Supports ASCII terminal output and DOT export for Graphviz.
Usage:
python3 scripts/graph_visualizer.py # ASCII, all nodes
python3 scripts/graph_visualizer.py --format dot # DOT output
python3 scripts/graph_visualizer.py --seed root --max-depth 2
python3 scripts/graph_visualizer.py --filter-domain hermes-agent
python3 scripts/graph_visualizer.py --filter-category pitfall
Acceptance: [x] Subgraph extraction [x] ASCII rendering [x] DOT export [x] Configurable depth/filter
"""
import argparse
import json
import sys
from collections import defaultdict, deque
from pathlib import Path
from typing import Optional
def load_index(index_path: Path):
with open(index_path) as f:
return json.load(f)
def build_adjacency(facts):
adj = defaultdict(list)
all_ids = {f['id'] for f in facts if 'id' in f}
for f in facts:
fid = f.get('id')
if not fid:
continue
for rel in f.get('related', []):
if rel in all_ids:
adj[fid].append(rel)
return dict(adj)
def build_reverse_adjacency(adj):
rev = defaultdict(list)
for src, targets in adj.items():
for tgt in targets:
rev[tgt].append(src)
return dict(rev)
def extract_subgraph(
facts,
adj,
rev_adj,
seeds=None,
max_depth=None,
filter_domain=None,
filter_category=None,
):
filtered_nodes = set()
for f in facts:
fid = f.get('id')
if not fid:
continue
if filter_domain and f.get('domain') != filter_domain:
continue
if filter_category and f.get('category') != filter_category:
continue
filtered_nodes.add(fid)
if seeds is None:
return filtered_nodes if filtered_nodes else {f['id'] for f in facts if 'id' in f}
valid_seeds = [s for s in seeds if s in filtered_nodes]
if not valid_seeds:
return set()
visited = set()
queue = deque([(s, 0) for s in valid_seeds])
while queue:
node, depth = queue.popleft()
if node in visited or node not in filtered_nodes:
continue
visited.add(node)
if max_depth is not None and depth >= max_depth:
continue
for neighbor in adj.get(node, []):
if neighbor in filtered_nodes and neighbor not in visited:
queue.append((neighbor, depth + 1))
for neighbor in rev_adj.get(node, []):
if neighbor in filtered_nodes and neighbor not in visited:
queue.append((neighbor, depth + 1))
return visited
def build_fact_map(facts):
return {f['id']: f for f in facts if 'id' in f and 'fact' in f}
def render_ascii(subgraph_ids, adj, fact_map):
lines = []
visited = set()
inorder = []
from collections import deque
queue = deque()
inbound = defaultdict(int)
for src in subgraph_ids:
for tgt in adj.get(src, []):
if tgt in subgraph_ids:
inbound[tgt] += 1
roots = [n for n in sorted(subgraph_ids) if inbound.get(n, 0) == 0]
if not roots:
roots = sorted(subgraph_ids)
for root in roots:
queue.append((root, 0, None))
while queue:
node, depth, parent_label = queue.popleft()
if node in visited:
continue
visited.add(node)
fact = fact_map.get(node, {})
label = fact.get('fact', str(node))[:80]
category = fact.get('category', 'fact')
domain = fact.get('domain', 'global')
node_label = domain + '/' + category + ': ' + label
if parent_label is None:
lines.append(f"{' ' * depth}┌─ {node_label}")
else:
lines.append(f"{' ' * depth}├─ {node_label}")
children = [c for c in adj.get(node, []) if c in subgraph_ids]
for i, child in enumerate(children):
queue.append((child, depth + 1, node))
if len(visited) < len(subgraph_ids):
lines.append("\n[Disconnected nodes — not in traversal order:]")
for n in sorted(subgraph_ids - visited):
fact = fact_map.get(n, {})
label = fact.get('fact', n)[:60]
lines.append(f" {n}{label}")
return "\n".join(lines)
def render_dot(subgraph_ids, adj, fact_map):
lines = ["digraph knowledge_graph {", " rankdir=LR;"]
cat_colors = {
'fact': '#3498db',
'pitfall': '#e74c3c',
'pattern': '#2ecc71',
'tool-quirk': '#f39c12',
'question': '#9b59b6',
}
for nid in sorted(subgraph_ids):
fact = fact_map.get(nid, {})
category = fact.get('category', 'fact')
domain = fact.get('domain', 'global')
label = fact.get('fact', nid).replace('"', '\\"')[:80]
fillcolor = cat_colors.get(category, '#666666')
lines.append(f' "{nid}" [label="{domain}\\n{category}\\n{label}", fillcolor="{fillcolor}", style=filled, shape=box];')
lines.append("")
for src in sorted(subgraph_ids):
for tgt in adj.get(src, []):
if tgt in subgraph_ids:
lines.append(f' "{src}" -> "{tgt}";')
lines.append("}")
return "\n".join(lines)
def main():
parser = argparse.ArgumentParser(description="Visualize the knowledge graph (ASCII terminal or DOT for Graphviz).")
parser.add_argument("--index", type=Path, default=Path(__file__).parent.parent / "knowledge" / "index.json",
help="Path to knowledge/index.json")
parser.add_argument("--format", choices=["ascii", "dot"], default="ascii",
help="Output format (default: ascii)")
parser.add_argument("--output", "-o", type=Path, help="Write output to file (default: stdout)")
parser.add_argument("--seed", help="Starting fact ID (comma-sep). Omit to render full graph.")
parser.add_argument("--max-depth", type=int, help="Max traversal depth from seed nodes (requires --seed).")
parser.add_argument("--filter-domain", help="Only include facts from this domain.")
parser.add_argument("--filter-category", help="Only include facts of this category.")
args = parser.parse_args()
index = load_index(args.index)
facts = index.get('facts', [])
adj = build_adjacency(facts)
rev_adj = build_reverse_adjacency(adj)
fact_map = build_fact_map(facts)
seeds = args.seed.split(',') if args.seed else None
subgraph_ids = extract_subgraph(facts=facts, adj=adj, rev_adj=rev_adj, seeds=seeds,
max_depth=args.max_depth,
filter_domain=args.filter_domain,
filter_category=args.filter_category)
if not subgraph_ids:
print("No nodes match the specified filters.", file=sys.stderr)
sys.exit(1)
if args.format == "ascii":
output = render_ascii(subgraph_ids, adj, fact_map)
else:
output = render_dot(subgraph_ids, adj, fact_map)
if args.output:
args.output.write_text(output)
print(f"Written: {args.output}", file=sys.stderr)
else:
print(output)
if __name__ == "__main__":
main()

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#!/usr/bin/env python3
"""
Tests for graph_visualizer.py — smoke test + subgraph logic.
Run: python3 scripts/test_graph_visualizer.py
"""
import json, sys, tempfile
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent))
import graph_visualizer as gv
def make_index(facts, tmp_dir):
p = tmp_dir / "index.json"
p.write_text(json.dumps({"version": 1, "total_facts": len(facts), "facts": facts}, indent=2))
return p
def test_build_adjacency_simple():
facts = [{"id": "a", "related": ["b", "c"]}, {"id": "b", "related": ["c"]}, {"id": "c", "related": []}]
adj = gv.build_adjacency(facts)
assert adj == {"a": ["b", "c"], "b": ["c"]}
print(" PASS: build_adjacency simple")
def test_build_adjacency_unknown_nodes():
facts = [{"id": "a", "related": ["x", "b"]}, {"id": "b", "related": []}]
adj = gv.build_adjacency(facts)
assert adj == {"a": ["b"]}
print(" PASS: build_adjacency filters unknown nodes")
def test_extract_subgraph_seed_only():
facts = [{"id": "a", "domain": "t", "category": "f"}, {"id": "b", "domain": "t", "category": "f"}, {"id": "c", "domain": "t", "category": "f"}]
adj = {"a": ["b"], "b": ["c"], "c": []}
rev_adj = gv.build_reverse_adjacency(adj)
sub = gv.extract_subgraph(facts, adj, rev_adj, seeds=["a"])
assert sub == {"a", "b", "c"}, f"got {sub}"
print(" PASS: extract_subgraph with seed returns full reachable set")
def test_extract_subgraph_with_depth():
facts = [{"id": "a", "domain": "t", "category": "f"}, {"id": "b", "domain": "t", "category": "f"}, {"id": "c", "domain": "t", "category": "f"}, {"id": "d", "domain": "t", "category": "f"}]
adj = {"a": ["b"], "b": ["c"], "c": ["d"], "d": []}
rev_adj = gv.build_reverse_adjacency(adj)
sub = gv.extract_subgraph(facts, adj, rev_adj, seeds=["a"], max_depth=2)
assert sub == {"a", "b", "c"}
print(" PASS: extract_subgraph depth=2 includes up to depth 2")
def test_extract_subgraph_filter_domain():
facts = [{"id": "a", "domain": "alpha", "category": "f"}, {"id": "b", "domain": "beta", "category": "f"}, {"id": "c", "domain": "alpha", "category": "f"}]
sub = gv.extract_subgraph(facts, {}, {}, filter_domain="alpha")
assert sub == {"a", "c"}
print(" PASS: filter_domain works")
def test_extract_subgraph_filter_category():
facts = [{"id": "a", "domain": "g", "category": "pitfall"}, {"id": "b", "domain": "g", "category": "fact"}, {"id": "c", "domain": "g", "category": "pitfall"}]
sub = gv.extract_subgraph(facts, {}, {}, filter_category="pitfall")
assert sub == {"a", "c"}
print(" PASS: filter_category works")
def test_render_ascii_simple_chain():
facts = [{"id": "a", "fact": "A", "domain": "t", "category": "f"}, {"id": "b", "fact": "B", "domain": "t", "category": "f"}, {"id": "c", "fact": "C", "domain": "t", "category": "f"}]
adj = {"a": ["b"], "b": ["c"]}
fact_map = gv.build_fact_map(facts)
out = gv.render_ascii({"a", "b", "c"}, adj, fact_map)
assert "A" in out and "B" in out and "C" in out
print(" PASS: render_ascii simple chain")
def test_render_dot_simple():
facts = [{"id": "x", "fact": "node x", "domain": "d1", "category": "fact"}, {"id": "y", "fact": "node y", "domain": "d2", "category": "pitfall"}]
adj = {"x": ["y"]}
fact_map = gv.build_fact_map(facts)
out = gv.render_dot({"x", "y"}, adj, fact_map)
assert 'digraph knowledge_graph' in out and '"x"' in out and '"y"' in out and '->' in out
assert '#3498db' in out and '#e74c3c' in out
print(" PASS: render_dot basic structure and colors")
def main():
print("\n=== graph_visualizer test suite ===\n")
passed = failed = 0
tests = [test_build_adjacency_simple, test_build_adjacency_unknown_nodes, test_extract_subgraph_seed_only, test_extract_subgraph_with_depth,
test_extract_subgraph_filter_domain, test_extract_subgraph_filter_category,
test_render_ascii_simple_chain, test_render_dot_simple]
for test in tests:
try:
test()
passed += 1
except AssertionError as e:
print(f" FAIL: {test.__name__}{e}")
failed += 1
except Exception as e:
print(f" ERROR: {test.__name__}{e}")
failed += 1
print(f"\n=== Results: {passed}/{passed+failed} passed, {failed} failed ===")
return failed == 0
if __name__ == "__main__":
sys.exit(0 if main() else 1)