144 customers owned zero properties, zero policies and zero transactions —
the legacy DATGRAL row exists but nothing in either business line ever
attached to it. They padded the staff customer list with rows that can't be
acted on. 27 were also nameless (dead ID slots); the other 117 have real
names and sometimes contact details, and read as never-activated prospects
or lapsed clients rather than junk. Removing both sets is a deliberate call.
Implemented as a separate step rather than a filter inside
transform_customers.py: emptiness is only knowable after properties, policies
and transactions have loaded, and deciding it there would mean re-deriving
each downstream transform's source-matching logic against the staged Parquet.
Runs after transform_transactions.py in run_all.py.
Safe by construction — a customer with no rows in any of the three tables has
nothing pointing at it, so the delete cannot orphan anything; only its own
customer_legacy_refs go with it. The step asserts zero orphans afterwards.
Every pruned customer is written to output/pruned_customers.csv with its
legacy provenance before the delete, and --dry-run reports without touching
anything. Nothing is unrecoverable: the Access sources are untouched and a
pipeline run without this step brings them all back.
Verified: full run_all.py pass ends at 1538 customers (from 1682), with
1519 properties / 2378 policies / 45861 transactions all intact and zero
orphans. 17 nameless customers remain, all of which carry real records.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The 44 customers with no recoverable name render as "(SIN NOMBRE)", and
ordering the list by name alone floated all of them to the top — "(" sorts
before every letter — so the first two screens of the customer browser were
nothing but placeholders. Small number, worst possible position.
Adds customers.nameMissing, set by the transform and used as the primary sort
key so those records land at the end of the list. Denormalized rather than
computed in the query because the list is paginated in SQL, so the ordering
has to be expressible as a column.
Applied to the dev DB as an ALTER + UPDATE in place (no truncate), so the
existing loaded data and its FKs were left alone.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
DATGRAL.NOMBRE is blank on 266 legacy rows (140 utilities, 126 insurance),
which surfaced in the UI as 257 customers literally named "(SIN NOMBRE)".
The blank is real — those cells are empty in the Access files, not lost in
extraction — but the rows mostly are not junk: 176 of the 257 carry a
property, a policy, or transactions.
The old PHP importer handled this by skipping blank-name rows outright
(jorgecuadros-intra-webapp/src/tools/customerAdapter.php:47,81). That was
worse than it looks: every other adapter resolved its customer FK through
the customer_mapping table those skipped rows never entered, so their
properties and policies were silently dropped (customerServiceAdapter.php:45)
and their transactions were written against customer_id 0
(customerBalanceAdapter.php:52). So: recover the name instead of skipping.
Names come from the secondary tables that still carry them, most trustworthy
first — UTILSEG (the office's own hand-maintained name <-> id cross-reference
spanning both lines), then the billing runs (IVA 2015, COBRO3) and the policy
rows' NOMBRE ASEG (MULT, M EMPR, INCENDIO). A linked customer can also borrow
the name its insurance record resolved to. Result: 213 of 257 recovered, 44
still genuinely nameless anywhere in the source.
customers.nameSource records which table each recovered name came from, so a
reconstructed name is never mistaken for one that was really on the record —
the list tags it "nombre recuperado", the detail header names the source, and
a still-unnamed customer renders muted italic instead of as a normal name.
Also fixes run_all.py: transform_properties and transform_policies truncate
service_documents/policy_documents, but blob_extract.py was not in the step
list, so a full re-run left the uploaded MinIO objects with no rows pointing
at them. Hit exactly that while reloading for this change.
Verified end-to-end: full pipeline re-run against dev reproduces every prior
count (1682 customers, 1519 properties, 2378 policies, 45861 transactions,
22354 bank rows, 70 documents) with zero orphans, and both apps build clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
First real frontend feature against the live Customer module API.
- login/ — session login form posting to /auth/login with credentials
included; the session cookie is what every subsequent request rides on.
- clientes/ — customer list with search and the cross-line stats header
(customers, utilities/insurance split, both-lines count).
- clientes/[id]/ — unified detail view: identity, properties + services,
policies, and transaction history for one customer, which is the whole
point of the migration (one record spanning both business lines).
- components/AppShell.tsx, lib/{api,labels,types}.ts — shared fetch wrapper
(always credentials: "include"), Spanish label maps for the enum values
the API returns, and the API response types.
- globals.css + layout.tsx — Spanish-first document (lang="es"), the type
scale, and the design tokens the pages share. Fonts load via <link> so an
offline build still renders on the system fallback stacks.
- page.tsx now redirects / to /clientes.
Also fixes pnpm-workspace.yaml: the allowBuilds map held pnpm's literal
placeholder text ("set this to true or false"), which made every install
fail with ERR_PNPM_IGNORED_BUILDS. Since pnpm 11 auto-installs before
running a script, that broke `pnpm start:dev` outright. Set the values to
true and dropped the superseded onlyBuiltDependencies list.
Verified: both apps build clean, and login -> /auth/me -> /customers/stats
round-trips against the dev database (1682 customers, 526 on both lines).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Adds the unified Customer API against the migrated data:
- customers.service: list (search across name/email/phone/city/legacy id,
business-line filter, pagination + per-row _count flags), detail (identity +
legacyRefs + properties/services/trust + policies with installments/vehicles/
drivers/beneficiaries/claims/docs + recent transactions + a per-domain/
currency ledger summary), and stats.
- customers.controller: GET /customers, /customers/:id, /customers/stats,
guarded by AuthenticatedGuard. Registered in AppModule.
- Fix LocalAuthGuard to call super.logIn so a session is actually established
(login previously succeeded but persisted no session -> 403 afterwards).
- apps/api/scripts/seed-user.mjs: idempotent Argon2 admin seed.
Tooling: adopt pnpm as the package manager (machine npm is a pnpm shim that
ignores the workspaces field). Add pnpm-workspace.yaml (+ onlyBuiltDependencies
for argon2/prisma/nest native builds), switch the api's @jorgecuadros/database
dep to workspace:*, add @types/passport, track pnpm-lock.yaml, drop the stale
package-lock.json.
Verified end-to-end against the dev DB: login sets a session cookie; stats
returns 1682 customers / 526 both-lines / 45861 transactions; search + detail
return the full cross-line customer view (properties+services AND policies AND
a unified transaction statement).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
DATMEX's scanned bills are in the ILUZ/IAGUA/IPREDIAL/ITEL invoice-image OLE
columns (typed ELECTRIC_BILL/WATER_BILL/PROPERTY_TAX_BILL/PHONE_BILL), not
doc_1/doc_2 (which are empty). Add them to the extractor with meaningful
document types.
Data finding: the LONGBINARY columns are almost entirely unpopulated — only 3
DATMEX blob cells across 1520 rows, and 67 policy blobs (MULT/TABLA AUTOS
AMPL foto/docs). The large .accdb/.mdb file sizes are Access bloat, not
documents. Final: 70 documents in MinIO (~290 MB), 3 service_documents +
67 policy_documents, 0 orphans, storageKeys resolve.
Migration steps 1-4 (staging, reconciliation, transform+load, documents) are
complete; RESUME.md updated. Next: the Customer module (API/web).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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>
migration/transform_transactions.py unions every cash/billing ledger into
`transactions` per the reconciliation rules: both EFECTIVO tables (no folio
de-dup, near-disjoint), all three billing tables (disjoint periods), the FM3
fee stream (amount = fee+tax+multa), IVA 2015 (nominal date), and insurance
EFECTIVO (domain INSURANCE). Also loads the type_transactions (EN/ES) and
exchange_rates lookups. Customer FK resolves through customer_legacy_refs;
rows with no resolvable customer/date are skipped and counted.
Loaded (dev): 45861 transactions (UTILITY 45566 / INSURANCE 295, 0 orphans),
79 type_transactions, 2301 exchange_rates.
migration/transform_bank.py loads SCOTHIA DATOS I/E into bank_transactions as
signed amounts (income +, expense -) and TABLA RAMODOS into
business_line_categories. Deliberately customer-independent (office's own
checking account). Loaded (dev): 22354 bank_transactions (net +899,375.77),
66 categories; categoryId left null (concept->ramo classifier is future work).
run_all.py: pipeline now customers -> properties -> policies -> transactions
-> bank, all idempotent. Verified full end-to-end run against dev.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
migration/transform_policies.py folds every insurance Access table into one
`policies` table (policy_types discriminator) plus child tables, via a
per-table declarative mapping that absorbs the column-name variance
(num_id/numer_id, no_poliza/poliza, p_neta/prima_neta/prima1). Any source
column not explicitly modeled — the type-specific coverage amounts — is
preserved verbatim in coveragesJson, so consolidation loses nothing.
Unpivots the hardcoded repeated slots: 4 payment installments (c_1er_pago +
pago_subsec x3), up to 3 vehicles (auto tables + MCA2), up to 3 named
insured drivers (MCA2 + LICENCIAS). Also loads BENEF -> policy_beneficiaries
(by policy number), DATOS -> claims, AJUSTADORES(+ATLAS) -> adjusters, and
builds policy_types + insurance_providers lookups.
Loaded/validated (dev): 2378 policies (AUTO 1307 / MULT 760 / LICENCIAS 306 /
M_EMPR 5; 10 skipped for unresolved customer FK, 0 orphans), 4678
installments, 1110 vehicles, 513 drivers, 126 beneficiaries, 1 claim, 15
providers, 17 adjusters — all child FKs verified 0 orphans. Spot-checked a
customer carrying both a utility property and MULT policies (the unified
cross-line view).
run_all.py: add policies to the ordered pipeline. Customer FK resolves
through insurance customer_legacy_refs, so this runs after customers.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
migration/transform_properties.py loads properties, property_services and
trust_accounts from staged DATMEX/PROFILE, resolving each property's customer
FK through customer_legacy_refs. Services are derived from DATMEX's own
account/route/meter fields (the authoritative data); PROFILE flags — merged
best-effort on (numer_id,casa,direccion), which matched 1519/1519 — only
refine each service's `active`. Trust accounts are 1:1 from DATMEX trust
fields; TRUSTVENCE (overlapping) deferred to reconciliation; blobs are step 4.
Loaded/validated (dev): 1519 properties (0 orphans, 1 blank id skipped),
3486 services (ELECTRIC 1118 / PROPERTY_TAX 939 / WATER 859 / GAS 335 /
OTHER 115 / FEDERAL_ZONE 76 / CABLE 41 / ALARM 3), 553 trust accounts —
counts track the PROFILE enrollment flags.
Reproducibility (asked: dev must be redoable in prod):
- migration/dbenv.py: single DB-target source = deploy/.env.<env>'s
DATABASE_URL; connect(env) + env_arg() (--env, default dev).
- transform_customers.py / transform_properties.py now take --env instead of
hardcoding .env.dev.
- migration/run_all.py: runs every step in dependency order against --env
(optional --stage re-extracts from Access first). Reproducing dev->prod is
`run_all.py --env prod` after deploying the prod stack + prisma db push.
All steps are idempotent (truncate+rebuild); re-run yields identical counts.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
migration/transform_customers.py builds `customers` + `customer_legacy_refs`
from staged DATGRAL, implementing the reconciliation rules: utilities DATGRAL
is the customer master; insurance DATGRAL folds in via its num_util
cross-reference (matches enrich the master with the ID-document fields
utilities lacks); COBRO3 excluded as a charge batch. Every legacy row gets a
provenance ref, so the load is auditable and idempotent (truncate+rebuild).
Loaded and validated against the dev DB (192.168.4.212:3307):
1682 customers (1172 utilities master + 510 insurance-only)
2242 legacy refs (1172 utilities + 1070 insurance) — 0 orphans
560 insurance rows linked via num_util, 0 broken cross-refs
542 merged identities spanning both business lines
Spot-checked a merged customer: single record carrying utilities fee +
insurance passport/ID enriched in, both provenance refs present.
RESUME.md: mark customers done, record dev-DB infra + the pnpm/npm caveat.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
deploy/jorgecuadros-db.stack.yml: canonical internal MySQL for the platform,
targeting the Portainer local endpoint on cubex (3-node Swarm). Parametrized
(MYSQL_PORT / MYSQL_SERVER_ID) so one file deploys both environments as two
stacks with Swarm-namespaced volumes:
dev -> jorgecuadros-dev-db :3307 server-id 11
prod -> jorgecuadros-prod-db :3306 server-id 1 (replication source)
Swarm-correct: named volume (no bind mount), pinned to one node via
node.labels.jorgecuadros_db==true (cubex labeled), binlog+GTID enabled from
the start so prod can be the VPS replication source without reconfigure.
Dev deployed and verified: MySQL 8.4.10 reachable at 192.168.4.212:3307,
gtid_mode ON, database jorgecuadros present. Secrets live in gitignored
deploy/.env.dev, injected via Portainer stack env at deploy time.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add migration/reconcile.py (reads staged Parquet) and the generated
migration/RECONCILIATION.md. Naive full-row matching across the suspected
"duplicate" groups gives a misleading ~0 overlap, so each group is probed on
a deliberate business key instead. The evidence overturns all three of the
plan's original assumptions:
- EFECTIVO vs EFECTIVO_BACKUP: NOT a live/backup pair. `folio` is a per-table
sequential number that collides (12,363 shared folio numbers, every one a
different transaction); real business-key (cl,fecha,monto,conepto) overlap
is 2. Near-disjoint ledgers (BACKUP ~2017-2022, EFECTIVO recent). Rule:
migrate both, keyed by (source_table, folio) provenance, no folio de-dup,
don't drop BACKUP. FM3 tables are a separate fee/tax/multa stream.
- datos2 vs FEE ANUAL vs fee15: disjoint billing runs from different periods
(2025-26 / 2018 / 2017), zero real-identity overlap. Rule: union all three,
no de-dup; keep datos2.due_date.
- DATGRAL vs COBRO3: COBRO3.fee is a constant 75 (a charge batch), not a
filtered customer snapshot; every num_id already in DATGRAL. Rule: DATGRAL
is the sole customer master, COBRO3 contributes zero customers.
Also flags monedas currency variants (PESOS/Pesos/DOLLARS) for normalization
at transform time.
Update PLAN.md (migration step 2 outcome + corrected inventory bullets) and
RESUME.md (queue: reconciliation done, transform+load next).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
macOS has no Access ODBC driver, so the pyodbc-based extract.py could not
run. Rewrite it to shell out to mdbtools (mdb-tables/mdb-export) while
keeping the public interface (connect/list_tables/read_table/
sanitize_column_name) unchanged, so load_staging.py and config.py are
untouched. connect() now returns the file path as the handle (mdbtools has
no persistent connection).
Behavior details:
- -b strip drops LONGBINARY/OLE bytes so blobs never corrupt the CSV
(documents are extracted separately in migration step 4).
- ISO date/datetime output (-D/-T); staging read as text (dtype=str),
only empty fields treated as null (keep_default_na=False) so literal
"NA"/"NULL" data strings survive.
- mdbtools reads deleted/corrupted records mdbtools omits rather than
aborting, so the old per-row skip loop is no longer needed.
Verified end-to-end: full staging load reproduces the original Windows
run (82 tables, 0 errors) with exact row counts (datos2 16000, EFECTIVO
13697, DATGRAL 1172/1070, DATMEX 1520) and recovers all 764 MULT rows
(the pyodbc path lost 1 to HY109 corruption). Accented-column tables
(PROPANO) read cleanly.
requirements.txt: drop pyodbc/pywin32 (Windows-only), keep pandas/pyarrow/
sqlalchemy/pymysql; document the Windows-only DAO catalog as historical.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Project moved Windows -> macOS, retiring the pyodbc + Access ODBC driver
extraction path in favor of mdbtools (verified against the real files).
Record the four now-locked decisions and the resolved utility_dbo blocker.
- PLAN.md: rework migration step 1 for mdbtools; replace "Open decisions"
with locked Decisions (extraction=mdbtools, i18n=Spanish-first,
CI=Gitea Actions, utility_dbo=available); update Status for the macOS
move + portal DB in hand; finalize sync steps against real utility_dbo.
- RESUME.md: rewrite next-steps as a locked execution queue.
- migration/config.py: point SOURCE_ROOT at ~/Downloads/JorgeCuadros-Legacy.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
ODBC only exposes Tables and non-hidden SELECT queries, so this used
DAO COM automation (migration/catalog_objects.py, requires pywin32)
to catalog Reports, Forms, and full Query SQL text across all four
files instead.
Key finding: SEGUROS 16.mdb, previously noted as having zero data
tables, turns out to hold all 212 Reports/149 Forms/857 Queries for
the insurance line - SEGUROS 16_be.mdb is confirmed pure data storage
with zero saved objects. The renewal-notice reports also reveal a
RENEW/RENEW2/RENEW3 multi-notice reminder cycle not visible in the
table schema.
docs/LEGACY_DATABASES_OBJECTS.md documents all of this with the full
751 real queries' SQL text (business logic: billing math, year-
rollover batches, duplicate/delinquency detection). Raw output at
migration/objects.json. Cross-linked from RESUME.md and the existing
table-only LEGACY_DATABASES.md.
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.
Next.js + NestJS + Prisma (MySQL) monorepo replacing the legacy PHP
internal app. Includes a session-based auth module with Argon2 password
hashing and global input validation (replacing the old app's SQL
injection and plaintext password comparison), the full target Prisma
schema for customers/insurance/utilities/shared ledger/bank register,
Docker Compose + Dockerfiles, and an Access-to-staging migration
pipeline (migration/) already run against the real source databases.
See PLAN.md and RESUME.md for the full architecture and session history.
rmancinasandClaude Opus 4.8