feat: APV JSON ingest + risk summary CLI

.github/workflows/dependabot-label.yml

@@ -1,9 +1,14 @@
 name: dependabot metadata and labels
-on: pull_request_target
+on:
+  pull_request_target:
+    types: [opened, synchronize, reopened, labeled]
 jobs:
   label:
+    if: github.actor == 'dependabot[bot]'
     runs-on: ubuntu-latest
     steps:
       - uses: dependabot/fetch-metadata@v2
         with:
           github-token: "${{ secrets.GITHUB_TOKEN }}"
+      - name: noop
+        run: echo "labels applied (if any)"

examples/sample_apv.json

@@ -1,5 +1,7 @@
-[
-  {"file":"app.py","predicted_risk":"high","reason":"Sensitive API call in diff"},
-  {"file":"utils.py","predicted_risk":"medium","reason":"Input validation weakened"},
-  {"file":"README.md","predicted_risk":"low","reason":"Docs-only change"}
-]
+{
+  "findings": [
+    {"severity": "HIGH", "title": "dangerous pattern"},
+    {"severity": "MEDIUM", "title": "needs review"},
+    {"severity": "LOW", "title": "style"}
+  ]
+}

pyproject.toml

@@ -21,8 +21,6 @@ mypy = "^1.11"
 [tool.ruff]
 target-version = "py311"
 line-length = 100
-select = ["E","F","I","W","UP"]
-ignore = ["E203"]
 
 [tool.black]
 line-length = 100
@@ -31,3 +29,7 @@ target-version = ["py311"]
 [tool.mypy]
 python_version = "3.11"
 strict = true
+
+[tool.ruff.lint]
+select = ["E","F","I","UP"]
+ignore = []

src/diff_risk_dashboard/__main__.py

@@ -1,3 +1,3 @@
 from .cli import main
-if __name__ == "__main__":
-    main()
+
+raise SystemExit(main())

src/diff_risk_dashboard/cli.py

@@ -1,22 +1,41 @@
 from __future__ import annotations
+
 import argparse
-from rich.console import Console
-from rich.table import Table
-from .core import summarize_apv_json
-
-def main() -> None:
-    parser = argparse.ArgumentParser(description="Diff Risk Dashboard (CLI)")
-    parser.add_argument("json_path", help="Path to ai-patch-verifier JSON report")
-    args = parser.parse_args()
-
-    summary = summarize_apv_json(args.json_path)
-    console = Console()
-    table = Table(title="PR Risk Exposure")
-    table.add_column("Severity", justify="left")
-    table.add_column("Count", justify="right")
-
-    for sev in ["high", "medium", "low"]:
-        table.add_row(sev.capitalize(), str(summary["by_severity"][sev]))
-
-    console.print(table)
-    console.print(f"[bold]Total findings:[/bold] {summary['total']}")
+import json
+import sys
+from pathlib import Path
+
+from .core import Summary, summarize
+
+
+def _print_table(summary: Summary) -> None:
+    bs = summary["by_severity"]
+    rows = [
+        ("CRITICAL", bs["CRITICAL"]),
+        ("HIGH", bs["HIGH"]),
+        ("MEDIUM", bs["MEDIUM"]),
+        ("LOW", bs["LOW"]),
+        ("INFO", bs["INFO"]),
+    ]
+    print("\n=== Diff Risk Summary ===")
+    print(f"Total findings: {summary['total']}")
+    print("Severity counts:")
+    w = max(len(r[0]) for r in rows)
+    for name, cnt in rows:
+        print(f"  {name:<{w}} : {cnt}")
+    print(f"Worst severity : {summary['worst']}")
+    print(f"Risk level     : {summary['risk_level']}\n")
+
+
+def main(argv: list[str] | None = None) -> int:
+    p = argparse.ArgumentParser(description="Diff Risk Dashboard (APV JSON -> summary)")
+    p.add_argument("apv_json", help="Path to ai-patch-verifier JSON")
+    args = p.parse_args(argv)
+    data = json.loads(Path(args.apv_json).read_text(encoding="utf-8"))
+    sm = summarize(data)
+    _print_table(sm)
+    return 2 if sm["risk_level"] == "red" else (1 if sm["risk_level"] == "yellow" else 0)
+
+
+if __name__ == "__main__":
+    sys.exit(main())

src/diff_risk_dashboard/core.py

@@ -1,25 +1,118 @@
 from __future__ import annotations
-from typing import Dict, Any
+
 import json
-from collections import Counter
-
-def summarize_apv_json(path: str) -> Dict[str, Any]:
-    '''
-    Expect a JSON array or object containing findings with a 'predicted_risk'
-    field in {'low','medium','high'} (interface compatible with ai-patch-verifier output).
-    '''
-    with open(path, "r", encoding="utf-8") as f:
-        data = json.load(f)
-
-    items = data if isinstance(data, list) else data.get("findings", [])
-    risks = [str(i.get("predicted_risk", "")).lower() for i in items]
-    counts = Counter(risks)
-    total = sum(counts.values())
-    return {
-        "total": total,
-        "by_severity": {
-            "high": counts.get("high", 0),
-            "medium": counts.get("medium", 0),
-            "low": counts.get("low", 0),
-        },
+from collections.abc import Iterable
+from pathlib import Path
+from typing import Any, Literal, TypedDict, cast
+
+Severity = Literal["CRITICAL", "HIGH", "MEDIUM", "LOW", "INFO"]
+
+
+class Finding(TypedDict, total=False):
+    severity: str
+    predicted_risk: str
+    title: str
+    score: float
+
+
+class Summary(TypedDict):
+    total: int
+    by_severity: dict[str, int]  # incluye claves lower y UPPER
+    worst: Severity
+    risk_level: Literal["red", "yellow", "green"]
+
+
+_SEV_ORDER: dict[Severity, int] = {
+    "CRITICAL": 4,
+    "HIGH": 3,
+    "MEDIUM": 2,
+    "LOW": 1,
+    "INFO": 0,
+}
+
+
+def _norm_sev(s: str | None) -> Severity:
+    if not s:
+        return "INFO"
+    s = s.strip().upper()
+    if s in _SEV_ORDER:
+        return s  # type: ignore[return-value]
+    if s in {"CRIT"}:
+        return "CRITICAL"
+    if s in {"MED", "MODERATE"}:
+        return "MEDIUM"
+    if s in {"WARN", "WARNING"}:
+        return "LOW"
+    return "INFO"
+
+
+def _extract_raw_sev(f: Finding) -> str | None:
+    return f.get("severity") or f.get("predicted_risk")
+
+
+def _iter_findings(obj: Any) -> Iterable[Finding]:
+    if isinstance(obj, dict):
+        cand = obj.get("findings", obj.get("results", []))
+        if isinstance(cand, list):
+            for x in cand:
+                if isinstance(x, dict):
+                    yield cast(Finding, x)
+        return
+    if isinstance(obj, list):
+        for x in obj:
+            if isinstance(x, dict):
+                yield cast(Finding, x)
+
+
+def summarize(obj: Any) -> Summary:
+    counts_uc: dict[Severity, int] = {"CRITICAL": 0, "HIGH": 0, "MEDIUM": 0, "LOW": 0, "INFO": 0}
+    total = 0
+    for f in _iter_findings(obj):
+        sev = _norm_sev(_extract_raw_sev(f))
+        counts_uc[sev] += 1
+        total += 1
+
+    worst: Severity = "INFO"
+    if counts_uc["CRITICAL"] > 0:
+        worst = "CRITICAL"
+    elif counts_uc["HIGH"] > 0:
+        worst = "HIGH"
+    elif counts_uc["MEDIUM"] > 0:
+        worst = "MEDIUM"
+    elif counts_uc["LOW"] > 0:
+        worst = "LOW"
+
+    if worst in {"CRITICAL", "HIGH"}:
+        risk: Literal["red", "yellow", "green"] = "red"
+    elif worst == "MEDIUM":
+        risk = "yellow"
+    else:
+        risk = "green"
+
+    by_lc = {
+        "critical": counts_uc["CRITICAL"],
+        "high": counts_uc["HIGH"],
+        "medium": counts_uc["MEDIUM"],
+        "low": counts_uc["LOW"],
+        "info": counts_uc["INFO"],
+    }
+    by_uc = {
+        "CRITICAL": counts_uc["CRITICAL"],
+        "HIGH": counts_uc["HIGH"],
+        "MEDIUM": counts_uc["MEDIUM"],
+        "LOW": counts_uc["LOW"],
+        "INFO": counts_uc["INFO"],
     }
+    by_sev: dict[str, int] = {**by_lc, **by_uc}
+    return {"total": total, "by_severity": by_sev, "worst": worst, "risk_level": risk}
+
+
+def summarize_apv_json(text_or_path: str | bytes) -> Summary:
+    """Acepta JSON (str/bytes) o ruta a archivo JSON."""
+    if isinstance(text_or_path, bytes):
+        payload = text_or_path.decode("utf-8", errors="strict")
+    else:
+        p = Path(text_or_path)
+        payload = p.read_text(encoding="utf-8") if p.exists() else text_or_path
+    data = json.loads(payload)
+    return summarize(data)

tests/test_core.py

@@ -0,0 +1,17 @@
+from diff_risk_dashboard.core import summarize
+
+
+def test_summarize_counts_and_worst():
+    data = {
+        "findings": [
+            {"severity": "LOW"},
+            {"severity": "MEDIUM"},
+            {"severity": "HIGH"},
+            {"severity": "INFO"},
+        ]
+    }
+    s = summarize(data)
+    assert s["total"] == 4
+    assert s["by_severity"]["HIGH"] == 1
+    assert s["worst"] == "HIGH"
+    assert s["risk_level"] == "red"

tests/test_smoke.py

@@ -1,4 +1,6 @@
 from diff_risk_dashboard.core import summarize_apv_json
+
+
 def test_summary_counts(tmp_path):
     sample = tmp_path / "s.json"
     sample.write_text(