feat: AR-House initial commit

2026-07-03 12:24:58 -04:00
commit 047c05287a
216 changed files with 127552 additions and 0 deletions
@@ -0,0 +1,110 @@
+"""Full pipeline run: Miami-Dade Clerk scraper → deals.db → auto-classify.
+
+Reports:
+- Total deals scraped (today + N days ahead)
+- Deals new / updated / errors
+- Classifications by status (potential_winner / maybe / pass / red_flag)
+- Sample of top 5 deals by classification_score
+"""
+from __future__ import annotations
+import io, sys, time
+from pathlib import Path
+
+sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding="utf-8", errors="replace")
+ROOT = Path(__file__).resolve().parent.parent
+sys.path.insert(0, str(ROOT))
+
+
+def main() -> int:
+    print("=" * 70)
+    print("Miami-Dade Clerk FULL PIPELINE (scrape + persist + classify)")
+    print("=" * 70)
+
+    from scrapers.miami_dade_clerk import run_scraper_to_db
+    from deals_db import init_db, list_deals, count_deals_by_status
+    init_db()
+
+    def log(m: str) -> None:
+        print(f"  {m}")
+
+    t0 = time.perf_counter()
+    summary = run_scraper_to_db(
+        days_ahead=14,
+        days_back=0,
+        auto_classify=True,
+        status_cb=log,
+        # max_dates not set → full 15 days
+    )
+    elapsed = time.perf_counter() - t0
+
+    print()
+    print("=" * 70)
+    print(f"PIPELINE SUMMARY (elapsed {elapsed:.0f}s = {elapsed/60:.1f} min)")
+    print("=" * 70)
+    for k, v in summary.items():
+        if k == "errors":
+            print(f"  {k}: ({len(v)} items)")
+            for e in v[:5]:
+                print(f"    - {e}")
+        else:
+            print(f"  {k}: {v}")
+
+    # Show count breakdown
+    print()
+    print("--- deals.db counts by status ---")
+    counts = count_deals_by_status()
+    for s, n in sorted(counts.items()):
+        print(f"  {s}: {n}")
+
+    # Show top 5 by classification score
+    print()
+    print("--- TOP 5 by classification_score ---")
+    top = list_deals(
+        classification=None,
+        source="miami_dade_clerk",
+        limit=200,
+        order_by="classification_score DESC NULLS LAST",
+    )[:5]
+    for i, d in enumerate(top, 1):
+        score = d.get("classification_score")
+        cls = d.get("classification_status")
+        strategy = d.get("classification_strategy")
+        addr = (d.get("address") or "(no address)")[:60]
+        sb = d.get("starting_bid")
+        sb_str = f"${sb:,.0f}" if sb else "Hidden/None"
+        av = d.get("estimated_arv")
+        av_str = f"${av:,.0f}" if av else "N/A"
+        fj = d.get("final_judgment_amount")
+        fj_str = f"${fj:,.0f}" if fj else "N/A"
+        reasons_raw = d.get("classification_reasons", "[]")
+        import json as _json
+        try:
+            reasons = _json.loads(reasons_raw) if reasons_raw else []
+        except Exception:
+            reasons = []
+        print(f"\n  [{i}] score={score} status={cls} strategy={strategy}")
+        print(f"      Case: {d.get('case_number')} | Type: {d.get('deal_type')}")
+        print(f"      Address: {addr}")
+        print(f"      Starting bid: {sb_str} | Assessed: {av_str} | Final Judgment: {fj_str}")
+        print(f"      Reasons:")
+        for r in reasons[:4]:
+            print(f"        - {r}")
+
+    # Show classifications by status
+    print()
+    print("--- Classifications by status (Miami-Dade only) ---")
+    by_class = {}
+    all_md = list_deals(source="miami_dade_clerk", limit=500)
+    for d in all_md:
+        cs = d.get("classification_status") or "(unclassified)"
+        by_class[cs] = by_class.get(cs, 0) + 1
+    for cs, n in sorted(by_class.items()):
+        print(f"  {cs}: {n}")
+
+    print()
+    print(f"✅ B1.4 COMPLETE — {summary['deals_new']} new deals persisted + classified")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())