Add legacy database structural reference for non-Windows machines
docs/LEGACY_DATABASES.md documents all three source Access databases (every table, column, type, and known data-quality quirk) generated from a live read of the real files, so no Windows/Access driver is needed to understand their structure going forward. New migration/ tooling: catalog_schema.py connects to the real files and walks every table (including excluded scratch tables); render_catalog_md.py renders that into the doc's appendix. Raw output checked in at migration/catalog.json so the doc can be regenerated without touching Access again.
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@@ -37,6 +37,7 @@ infrastructure decisions below.
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- `C:\Users\ricar\Downloads\Jorge\SEGUROS 16.mdb` — insurance frontend shell, **empty**, all data is in `_be`
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- `C:\Users\ricar\Downloads\Jorge\SEGUROS 16_be.mdb` — insurance backend, 64 tables, ~882MB
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- `C:\Users\ricar\Downloads\Jorge\SCOTHIA.mdb` — office's own Scotiabank checking register ("chequera"), 7 tables, ~3MB
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- **Full structural reference for all three, usable without Windows or the original files:** [`docs/LEGACY_DATABASES.md`](docs/LEGACY_DATABASES.md) — every table, every column with type/nullability, the cross-reference keys between the three databases, and every known data-quality quirk (the UTF-16 decode bug, the corrupted `MULT` row, near-duplicate snapshot tables, etc.), all generated from a live read of the real files via `migration/catalog_schema.py`. Regenerate it if the source files change; the raw JSON it's built from is checked in at `migration/catalog.json`.
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- `C:\Users\ricar\Downloads\jorgecuadros_app.sql` and `jorgecuadros_app (1).sql` — MySQL dumps of the customer-portal's **tracking/analytics** sidecar DB (`browse_tracking`, `devices` push-tokens, `task_tracking`) from `mysql.freakma.com`. **Not** the portal's real data DB — see open item #1 below.
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**Old internal app (reference-only, not being built on):**
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"""
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Generates a complete structural catalog of every table in the legacy Access
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source files (including excluded/scratch tables, for documentation
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completeness) and writes it as JSON.
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This is the source data for docs/LEGACY_DATABASES.md. Re-run this any time
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the source .accdb/.mdb files change, then regenerate the doc from the JSON.
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Must run on a Windows machine with the Microsoft Access Database Engine
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ODBC driver installed (pyodbc can't reach Access files otherwise) — see
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docs/LEGACY_DATABASES.md for why non-Windows machines can't do this step
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themselves and have to work from this catalog / the staged Parquet output
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instead.
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Usage:
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python catalog_schema.py --output catalog.json
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"""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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import extract
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from config import SOURCES
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def get_access_type_labels(cnxn, table_name: str) -> dict[str, str] | None:
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"""Best-effort: cursor.columns() gives real Access type names/sizes
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(VARCHAR(255), DOUBLE, LONGCHAR, LONGBINARY, COUNTER, BIT, CURRENCY...)
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but decode-errors on a subset of tables (see extract.py). Returns None
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on failure so the caller can fall back to pandas-inferred dtypes."""
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try:
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cursor = cnxn.cursor()
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labels = {}
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for col in cursor.columns(table=table_name):
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size = col.column_size
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labels[col.column_name] = f"{col.type_name}({size})" if size else col.type_name
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return labels
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except Exception:
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return None
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def catalog_source(source_name: str, source_cfg: dict) -> dict:
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path = source_cfg["path"]
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result = {"path": str(path), "tables": {}}
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if not Path(path).exists():
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result["error"] = "file not found"
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return result
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cnxn = extract.connect(path)
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tables = extract.list_tables(cnxn)
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for table_name in tables:
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entry = {"excluded": table_name in source_cfg["exclude"]}
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access_types = get_access_type_labels(cnxn, table_name)
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try:
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df = extract.read_table(cnxn, table_name)
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except Exception as exc: # noqa: BLE001
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entry["error"] = str(exc)
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result["tables"][table_name] = entry
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continue
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original_columns = df.attrs.get("original_columns", list(df.columns))
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columns = []
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for orig_name, sanitized_name in zip(original_columns, df.columns):
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dtype = str(df[sanitized_name].dtype)
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has_nulls = bool(df[sanitized_name].isna().any()) if len(df) else None
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type_label = None
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if access_types is not None:
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type_label = access_types.get(orig_name)
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columns.append(
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{
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"name": orig_name,
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"access_type": type_label,
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"pandas_dtype": dtype,
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"nullable": has_nulls,
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}
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)
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entry["row_count"] = len(df)
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entry["column_count"] = len(columns)
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entry["columns"] = columns
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entry["access_type_metadata_available"] = access_types is not None
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result["tables"][table_name] = entry
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return result
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def main() -> None:
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("--output", type=Path, default=Path("catalog.json"))
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args = parser.parse_args()
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catalog = {}
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for source_name, source_cfg in SOURCES.items():
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print(f"Cataloging {source_name}...")
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catalog[source_name] = catalog_source(source_name, source_cfg)
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args.output.write_text(json.dumps(catalog, indent=2, default=str), encoding="utf-8")
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print(f"Wrote {args.output}")
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if __name__ == "__main__":
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main()
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@@ -0,0 +1,98 @@
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"""
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Renders catalog.json (from catalog_schema.py) into a Markdown appendix:
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one section per source file, one subsection per table, with a column
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table. Excluded (scratch/template/report) tables are marked and collapsed
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to a one-liner rather than a full column dump, since they carry no data
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worth documenting column-by-column.
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Usage:
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python render_catalog_md.py catalog.json --output appendix.md
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"""
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from __future__ import annotations
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import argparse
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import json
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from pathlib import Path
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SOURCE_TITLES = {
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"utilities": "UTILITIES.accdb",
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"seguros": "SEGUROS 16_be.mdb",
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"scothia": "SCOTHIA.mdb",
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}
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def render_table(name: str, entry: dict) -> str:
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lines = [f"#### `{name}`"]
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if entry.get("excluded"):
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lines.append("")
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lines.append(f"**Excluded from migration** — {entry.get('row_count', '?')} rows. Not detailed here; see the exclusion rationale table above.")
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lines.append("")
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return "\n".join(lines)
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if "error" in entry:
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lines.append("")
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lines.append(f"**Could not read this table:** `{entry['error']}`")
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lines.append("")
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return "\n".join(lines)
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lines.append("")
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lines.append(f"Rows: {entry['row_count']} | Columns: {entry['column_count']}")
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lines.append("")
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lines.append("| Column | Type | Nullable |")
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lines.append("|---|---|---|")
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for col in entry["columns"]:
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type_label = col["access_type"] or f"_(inferred: {col['pandas_dtype']})_"
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nullable = "yes" if col["nullable"] else ("no" if col["nullable"] is False else "—")
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col_name = col["name"].replace("|", "\\|")
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lines.append(f"| `{col_name}` | {type_label} | {nullable} |")
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lines.append("")
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return "\n".join(lines)
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def render_source(source_name: str, source_data: dict) -> str:
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title = SOURCE_TITLES.get(source_name, source_name)
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lines = [f"### {title}", ""]
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tables = source_data["tables"]
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included = sorted(t for t, e in tables.items() if not e.get("excluded"))
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excluded = sorted(t for t, e in tables.items() if e.get("excluded"))
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lines.append(f"{len(tables)} tables total — {len(included)} included in migration, {len(excluded)} excluded (scratch/template/report tables).")
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lines.append("")
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for table_name in included:
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lines.append(render_table(table_name, tables[table_name]))
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if excluded:
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lines.append("#### Excluded tables")
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lines.append("")
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lines.append("| Table | Rows |")
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lines.append("|---|---|")
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for table_name in excluded:
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entry = tables[table_name]
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lines.append(f"| `{table_name}` | {entry.get('row_count', '?')} |")
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lines.append("")
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return "\n".join(lines)
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def main() -> None:
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument("catalog", type=Path)
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parser.add_argument("--output", type=Path, default=Path("appendix.md"))
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args = parser.parse_args()
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catalog = json.loads(args.catalog.read_text(encoding="utf-8"))
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sections = ["## Appendix: full table catalog", "", "Generated by `migration/catalog_schema.py` + `migration/render_catalog_md.py`. Regenerate after any change to the source files.", ""]
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for source_name in ["utilities", "seguros", "scothia"]:
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sections.append(render_source(source_name, catalog[source_name]))
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args.output.write_text("\n".join(sections), encoding="utf-8")
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print(f"Wrote {args.output}")
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if __name__ == "__main__":
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main()
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