impact-radius 1.1.0

AST call graph analyzer — what breaks if I change this file?

blast-radius

What breaks if I change this file?

blast-radius builds an incremental AST call graph for your Python project and answers the question instantly. It indexes imports and symbol definitions into SQLite (SHA-256 cached — only changed files are re-indexed) and resolves transitive dependents in milliseconds.

pip install impact-radius

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Quickstart

# Build the graph (incremental — only re-indexes changed files)
impact-radius --build

# What breaks if I change src/utils.py?
impact-radius --query src/utils.py

# Output a Mermaid diagram (renders in GitHub READMEs / PRs)
impact-radius --query src/utils.py --mermaid

# Watch mode — auto-rebuild on every save
impact-radius --watch

# Raw JSON output (pipe to jq, scripts, CI)
impact-radius --query src/utils.py --json

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Terminal output (with Rich)

src/utils.py  ⚡ GOD NODE
├── 📄 src/api/routes.py
├── 📄 src/models/user.py
├── 🧪 tests/test_utils.py
└── 🧪 tests/test_api.py
  14 file(s) affected · in-degree 47 · 2 test file(s)

Install Rich for colored output:

pip install impact-radius[rich]

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Mermaid diagram (renders in GitHub)

from blast_radius import build_graph, get_blast_radius, to_mermaid

build_graph()
result = get_blast_radius("src/utils.py")
print(to_mermaid(result))

Paste the output into any GitHub issue, PR, or README:

graph TD
    utils_py["src/utils.py"]
    utils_py --> routes_py["src/api/routes.py"]
    utils_py --> user_py["src/models/user.py"]
    utils_py --> test_utils_py["tests/test_utils.py"]
    style test_utils_py fill:#22c55e,color:#fff
    %% total affected: 3 | in-degree: 0

---

Python API

from blast_radius import build_graph, get_blast_radius, to_mermaid, watch

# Build the import graph (incremental — re-indexes only changed files)
n = build_graph()
print(f"{n} files indexed")

# Query blast radius
result = get_blast_radius("src/mymodule.py")
print(result["total_affected"])   # int
print(result["direct_dependents"])  # list of file paths
print(result["test_files"])         # files that start with tests/

# Mermaid output
diagram = to_mermaid(result)

# Watch mode (blocking — runs until Ctrl+C)
watch(interval=2.0)

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Configuration

All paths are configurable — no hardcoded assumptions:

# Scan only specific directories
impact-radius --build --scan src tests

# Use a custom DB path (useful in CI)
impact-radius --build --db /tmp/my-graph.db

# Adjust watch poll interval
impact-radius --watch --interval 1.0

Or via Python API:

from pathlib import Path
build_graph(scan_dirs=["src", "tests"], db_path=Path("/tmp/my-graph.db"))
get_blast_radius("src/utils.py", db_path=Path("/tmp/my-graph.db"))

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GitHub Action — comment blast radius on PRs

# .github/workflows/blast-radius.yml
name: Blast Radius
on: [pull_request]

jobs:
  blast-radius:
    runs-on: ubuntu-latest
    permissions:
      pull-requests: write
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with: {python-version: "3.11"}
      - run: pip install impact-radius
      - name: Compute blast radius
        id: br
        run: |
          impact-radius --build
          echo "mermaid<<EOF" >> $GITHUB_OUTPUT
          impact-radius --query "${{ github.event.pull_request.head.sha }}" --mermaid >> $GITHUB_OUTPUT
          echo "EOF" >> $GITHUB_OUTPUT
      - uses: marocchino/sticky-pull-request-comment@v2
        with:
          message: |
            ## Blast Radius

            ${{ steps.br.outputs.mermaid }}

---

Graphify god-node detection (optional)

If you have graphify installed and have run graphify update . in your repo, blast-radius will enrich results with transitive centrality data and flag god nodes (files imported by 30+ modules):

result = get_blast_radius("src/core.py")
if result.get("graphify", {}).get("god_node"):
    print("WARNING: this is a god node — change it carefully")

---

Installation

# Core (no dependencies)
pip install impact-radius

# With Rich colored output
pip install impact-radius[rich]

# With watchdog file watching (faster than polling)
pip install impact-radius[watch]

# Everything
pip install impact-radius[all]

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Part of the LexiPro Sovereign OS

blast-radius is extracted from LexiPro — a local-first agentic OS where it powers the pre-edit safety gate: before any agent touches a kernel file, get_blast_radius() checks if it's a god node. Agents touching files with in-degree ≥ 30 must acquire a hard mutex first.

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Known Limitations

Limitation	Impact	Mitigation
Static analysis only	Dynamic imports (__import__, importlib) flagged but not graph-traversed	Check result["dynamic_import_warning"] in results; manually verify dynamic targets
Python only	No cross-language analysis	Pair with language-specific tools for polyglot repos
Import aliases not resolved	import numpy as np; np.something won't resolve symbol-level deps	Structural file-level deps still captured
__all__ not parsed for re-exports	Re-exported symbols via __all__ look like dead ends	Treat re-export files as high-blast-radius by convention
No runtime import analysis	Conditional imports (if TYPE_CHECKING) count as live deps	Use --type-checking-only flag (planned) to filter

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Comparison: impact-radius vs. alternatives

Feature	impact-radius	pydeps	importlab	modulegraph
Transitive blast radius query	Yes	No	Partial	No
Incremental SQLite cache	Yes (SHA-256)	No	No	No
God-node detection	Yes	No	No	No
Mermaid diagram output	Yes	No	No	No
File-watch mode	Yes	No	No	No
Dynamic import detection	Yes (flagged)	No	Partial	No
CLI + Python API	Both	CLI only	Python only	Python only
Install size	Minimal	Medium	Minimal	Medium

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Performance

Project size	Index build	Blast radius query
50 files	~0.3s	<1ms
500 files	~2s	<5ms
5,000 files	~18s	<20ms

After the initial build, incremental re-index only processes changed files. Query time is independent of project size — SQLite index lookup is O(log n).

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License

MIT — see LICENSE.

Built by Broken Arrow Entertainment LLC · Sovereign Intelligence Systems Group

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OS Integration — God-Node Gate

blast-radius wires into pre-edit safety gates to enforce a hard stop before any agent touches a high-centrality file. This is the v9.6 integration pattern used in the LexiPro Sovereign OS:

# tool_hook_pipeline.py — _hook_guardian_path_guard (v9.6)
from blast_radius import get_blast_radius, rebuild_if_stale

async def pre_edit_gate(file_path: str) -> dict:
    rebuild_if_stale(max_age_seconds=300)
    br = get_blast_radius(file_path)

    # Hard block — god-node writes require explicit mutex acquisition
    if br.get("graphify", {}).get("god_node"):
        in_deg = br["graphify"]["in_degree_sum"]
        return {
            "allowed": False,
            "error": (
                f"GOD_NODE_PROTECTED: {file_path} has in_degree_sum={in_deg}. "
                f"Acquire hard mutex before editing god-node files."
            ),
        }

    # High blast radius — warn + emit contention pheromone
    if br["total_affected"] >= 10:
        emit_contention_pheromone(file_path, strength=br["total_affected"] / 50.0)

    return {"allowed": True, "warning": f"{br['total_affected']} dependents affected"}

God-node threshold: files with in_degree_sum >= 30 (via Graphify) require explicit mutex acquisition before any write. Without Graphify, the gate still warns on total_affected >= 10.

Pheromone broadcast: high-blast-radius edits emit a WRITE_CONTENTION signal to the NeuralBus so other agents observe the contested resource and can defer non-critical writes.

Run graphify update . in your repo root to generate graphify-out/graph.json and enable god-node detection.