Add MinIO object storage + LONGBINARY blob extractor (migration step 4)
deploy/jorgecuadros-minio.stack.yml: S3-compatible object storage (MinIO) for the platform's document blobs, deployed to the cubex Swarm with the same statefulness rules as the DB stack (named volume, pinned to the labeled node). Parametrized for dev/prod as two stacks (dev API 9100/console 9101, prod 9000/9001). Dev deployed + bucket jorgecuadros-documents created. migration/blob_extract.py: re-reads the LONGBINARY columns via mdb-export -b hex (staging used -b strip), carves the embedded file out of the Access OLE wrapper by locating its magic bytes (JPEG/PNG/PDF/GIF/TIFF) and trimming trailing OLE junk, uploads to MinIO, and writes service_documents / policy_documents pointer rows. Row->parent alignment uses mdb-export's deterministic order (== staged _row_num) for policies and numer_id for properties. Idempotent (truncate doc tables + overwrite by deterministic key); --limit/--tables for test passes. Validated on a limited pass: carved blobs are valid JPEGs (ffd8ff..ffd9) correctly linked to their policies. requirements.txt: add boto3. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Claude Opus 4.8
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"""
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Migration plan step 4: extract LONGBINARY document blobs to object storage.
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The Access LONGBINARY columns hold scanned utility bills / IDs / policy docs
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wrapped in an Access OLE Object container (a "\\x15\\x1c...Pres..." header +
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optional DIB preview, then the real embedded file). Staging used
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`mdb-export -b strip` (blobs dropped); this re-reads each table with
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`-b hex`, carves the embedded file out of the OLE wrapper by locating its
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magic bytes, uploads it to MinIO (S3), and writes a *_documents row pointing
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at it (MySQL keeps only the pointer + metadata, per the plan).
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Row alignment: `mdb-export` order is deterministic and identical to the order
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load_staging used, so a row's position == its staged `_row_num`. Policy docs
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resolve to a policy by (legacySourceTable, legacyId=row position); property
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docs resolve by DATMEX numer_id -> propertyId.
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Idempotent: truncates the *_documents tables for the selected models and
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re-uploads under deterministic keys (overwrite). Use --limit N for a small
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test pass, --tables to restrict.
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Run: ./.venv/bin/python blob_extract.py --env dev [--limit N] [--tables datmex,mult]
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"""
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from __future__ import annotations
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import argparse
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import csv
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import subprocess
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import sys
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import uuid
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from pathlib import Path
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import boto3
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from botocore.config import Config
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from dbenv import connect, load_env
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from extract import sanitize_column_name as san
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csv.field_size_limit(300_000_000)
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SOURCE_ROOT = Path.home() / "Downloads" / "JorgeCuadros-Legacy"
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# (key, access_file, access_table, staged_table_name, blob_cols, model)
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SOURCES = [
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dict(key="datmex", file="UTILITIES.accdb", table="DATMEX", staged="DATMEX",
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blobs=["doc_1", "doc_2"], model="service"),
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dict(key="mult", file="SEGUROS 16_be.mdb", table="MULT", staged="mult",
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blobs=["foto1", "docs_1", "docs_2"], model="policy"),
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dict(key="autos_ampl", file="SEGUROS 16_be.mdb", table="TABLA AUTOS AMPL",
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staged="tabla_autos_ampl", blobs=["foto1", "docs_1", "docs_2"], model="policy"),
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]
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# magic -> (ext, content-type). Order = priority when several appear.
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MAGICS = [
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(b"\xff\xd8\xff", "jpg", "image/jpeg"),
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(b"\x89PNG\r\n\x1a\n", "png", "image/png"),
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(b"%PDF", "pdf", "application/pdf"),
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(b"GIF8", "gif", "image/gif"),
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(b"II*\x00", "tif", "image/tiff"),
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(b"MM\x00*", "tif", "image/tiff"),
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]
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def carve(b: bytes):
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"""Locate the embedded file inside the OLE wrapper and return
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(bytes, ext, content_type) or None if no known type is present."""
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best = None
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for sig, ext, ct in MAGICS:
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i = b.find(sig)
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if i >= 0 and (best is None or i < best[0]):
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best = (i, ext, ct)
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if best is None:
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return None
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i, ext, ct = best
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data = b[i:]
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# trim trailing OLE junk after the real end marker where we know it
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if ext == "jpg":
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e = data.rfind(b"\xff\xd9")
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if e >= 0:
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data = data[: e + 2]
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elif ext == "png":
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e = data.rfind(b"IEND\xaeB`\x82")
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if e >= 0:
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data = data[: e + 8]
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return data, ext, ct
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--env", default="dev")
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ap.add_argument("--limit", type=int, default=0, help="max rows per table (0 = all); test with a small N")
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ap.add_argument("--tables", default="", help="comma list of source keys to run (default all)")
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args = ap.parse_args()
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only = set(x.strip() for x in args.tables.split(",") if x.strip())
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sources = [s for s in SOURCES if not only or s["key"] in only]
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env = load_env(args.env)
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s3 = boto3.client(
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"s3", endpoint_url=env["S3_ENDPOINT"],
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aws_access_key_id=env["MINIO_ROOT_USER"], aws_secret_access_key=env["MINIO_ROOT_PASSWORD"],
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config=Config(signature_version="s3v4"), region_name="us-east-1")
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bucket = env["S3_BUCKET"]
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conn = connect(args.env)
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cur = conn.cursor()
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# parent lookups
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cur.execute("SELECT legacyId, id FROM properties WHERE legacySourceTable='DATMEX'")
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prop_by_numer = {}
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for lid, pid in cur.fetchall():
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prop_by_numer.setdefault(lid, pid) # first property per numer_id
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cur.execute("SELECT legacySourceTable, legacyId, id FROM policies")
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pol_by_row = {(t, l): i for t, l, i in cur.fetchall()}
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# fresh rebuild of the doc tables we're loading (unless a limited test pass)
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if not args.limit:
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cur.execute("SET FOREIGN_KEY_CHECKS=0")
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if any(s["model"] == "service" for s in sources):
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cur.execute("TRUNCATE TABLE service_documents")
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if any(s["model"] == "policy" for s in sources):
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cur.execute("TRUNCATE TABLE policy_documents")
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cur.execute("SET FOREIGN_KEY_CHECKS=1")
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conn.commit()
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svc_rows, pol_rows = [], []
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stats = {}
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for src in sources:
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path = SOURCE_ROOT / src["file"]
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want = {c: None for c in src["blobs"]}
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uploaded = skipped_noparent = no_magic = empty = 0
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p = subprocess.Popen(["mdb-export", "-b", "hex", str(path), src["table"]],
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stdout=subprocess.PIPE, text=True, encoding="utf-8",
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errors="replace", bufsize=1)
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rdr = csv.reader(p.stdout)
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hdr = next(rdr)
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sh = [san(c) for c in hdr]
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idx = {c: sh.index(c) for c in src["blobs"] if c in sh}
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numer_idx = sh.index("numer_id") if "numer_id" in sh else None
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for ri, row in enumerate(rdr):
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if args.limit and ri >= args.limit:
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break
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# resolve parent
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if src["model"] == "service":
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numer = (row[numer_idx].strip() if numer_idx is not None and numer_idx < len(row) else "")
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if numer.endswith(".0"):
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numer = numer[:-2]
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parent = prop_by_numer.get(numer)
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else:
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parent = pol_by_row.get((src["staged"], str(ri)))
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for col, ci in idx.items():
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h = row[ci].strip() if ci < len(row) else ""
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if len(h) < 16:
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empty += 1
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continue
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if not parent:
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skipped_noparent += 1
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continue
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try:
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raw = bytes.fromhex(h)
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except ValueError:
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continue
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out = carve(raw)
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if out is None:
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no_magic += 1
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continue
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data, ext, ct = out
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prefix = "service" if src["model"] == "service" else "policy"
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key = f"{prefix}/{parent}/{src['staged']}_{ri}_{col}.{ext}"
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s3.put_object(Bucket=bucket, Key=key, Body=data, ContentType=ct)
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dtype = col.upper()
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if src["model"] == "service":
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svc_rows.append((str(uuid.uuid4()), parent, dtype, key))
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else:
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pol_rows.append((str(uuid.uuid4()), parent, dtype, key, col))
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uploaded += 1
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p.stdout.close(); p.wait()
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stats[src["key"]] = dict(uploaded=uploaded, no_parent=skipped_noparent,
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no_magic=no_magic, empty_cells=empty)
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print(f" [{src['key']}] uploaded={uploaded} no_parent={skipped_noparent} "
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f"no_magic={no_magic}")
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if svc_rows:
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cur.executemany("INSERT INTO service_documents (id,propertyId,documentType,storageKey) "
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"VALUES (%s,%s,%s,%s)", svc_rows)
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if pol_rows:
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cur.executemany("INSERT INTO policy_documents (id,policyId,documentType,storageKey,originalColumn) "
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"VALUES (%s,%s,%s,%s,%s)", pol_rows)
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conn.commit()
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cur.execute("SELECT COUNT(*) FROM service_documents"); ns = cur.fetchone()[0]
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cur.execute("SELECT COUNT(*) FROM policy_documents"); npd = cur.fetchone()[0]
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print("=== Blob extraction complete ===")
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for k, v in stats.items():
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print(f" {k}: {v}")
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print(f" -> service_documents rows total: {ns}")
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print(f" -> policy_documents rows total : {npd}")
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conn.close()
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if __name__ == "__main__":
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main()
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@@ -4,6 +4,7 @@ pandas>=2.2
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pyarrow>=15.0
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sqlalchemy>=2.0
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pymysql>=1.1
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boto3>=1.34 # S3/MinIO client for blob_extract.py (migration step 4)
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# Windows-only, historical — the DAO/COM object catalog (catalog_objects.py)
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# was already run on Windows and its output is committed (objects.json). Not
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