customers, contracts, invoices, payments, train schedules, and locomotives /
trains / wagons via the fleet page's config.
FilterBar pages pass controls.params into the children slot. The four pages
still on ad-hoc filtering pass their own hand-built filter object instead,
which is why ExportButton takes plain params rather than a UseFilters — it
would otherwise have been blocked behind migrating those pages. FleetResource
serves seven slugs from config, so it gets an optional exportKey there and
renders nothing for the four slugs with no dataset yet.
Auditing each page's real filter keys against the dataset declarations turned
up three gaps where an on-screen filter would have silently not applied to the
export: invoices sends a singular "status" (the dataset only had the
multiselect "statuses"), contracts sends paymentCurrency, serviceTypeId and
route origin/destination, and train schedules sends freightType. Added all of
them — contract routes filter through EXISTS on contract_routes since they are
one-to-many, and train-schedule freightType through EXISTS on the bookings
aboard, matching the list service.
Verified in the browser: the button renders on each page, and the invoices
dialog follows that page's own filter object — selecting Paid moves the count
from 126 to 100, which matches the database. Filter pass-through checked
against the database for invoices, payments, wagons, contracts and train
schedules.
customers, contracts, invoices, payments, train-schedules, locomotives,
trains and wagons. 319 fields across the nine datasets, all reusing the
existing engine — no change to export.types.ts was needed, which is the
result the bookings-first phase was meant to test.
Per-dataset notes worth keeping:
- trains resolves route, stations and current yard, which the list endpoint
never loads — the UI shows raw FK uuids there today.
- wagons reads tare/payload/length off wagon_types (they are not on the
wagon), and reproduces the service's attachStatusDates() as correlated
subqueries. wagon_status_logs stores from_status/to_status, not status.
- payments applies no soft-delete guard: freight.payments has neither
deleted_at nor updated_at, so the usual predicate is a 42703. Failure
columns are failer_code/failer_message. payment_refunds stores MINOR
units, so refundedTotal divides by 100.
- train-schedules derives freightType from the bookings aboard rather than
a column, matching the list service.
- customers stays one row per company; profiles, bookings and invoice
totals aggregate in subqueries. Verified no row multiplication: trains,
customers and contracts each return exactly their counted row count while
selecting one-to-many aggregate fields.
EXPLAIN-validated against the database: every dataset's widest query, its
count query, and all 319 fields individually. That run caught five columns
typed varchar rather than timestamp (companies.date_registered,
renewal_date, renewed_from, renewed_to and invoices.eims_ack_date), which
were being pushed through to_char and would have 500'd the moment anyone
ticked them; they now export verbatim.
All nine count endpoints verified equal to SELECT count(*) on their table.
Adds a parallel export system the reports module can also draw on. A dataset
describes a table's exportable fields — including related-entity detail the
list page never shows — and the engine assembles a query from whichever fields
the caller picked.
GET /exports catalog (metadata only; select/requires never ship)
GET /exports/:key/count exact row count + per-format caps
GET /exports/:key/download csv | xlsx | pdf
Two invariants carry the design:
- Every lazy join is a LEFT join, and ExportJoin has no 'kind' field to make
anything else expressible. An inner join added because a checkbox was ticked
would change the rowset, so two exports of the same filters would disagree on
their row count.
- Because of that, the count cannot depend on field selection, so /count runs
base + alwaysJoin only and is exact rather than an estimate. Verified: count
and the delivered file both report 223 rows.
One-to-many relations (a booking's containers) aggregate in a correlated
subquery rather than joining, so a row can never multiply.
Export rides each dataset's existing view permission — no new permission keys
and no seeder change. Sensitive columns are simply never declared as fields:
raw gateway payloads, signature blobs, error dumps, raw jsonb snapshots,
internal user UUIDs and review notes are all absent by construction.
bookings ships 77 fields across 10 groups. scripts/validate-export-datasets.ts
EXPLAINs every dataset's widest query, its count query, and each field on its
own against the real database — the per-field pass is what catches a field
referencing a join it forgot to declare, which otherwise only fails when that
one field is picked alone.
The export path used one number for two different things: the format's hard
row cap, and the caller's explicit 'give me the first N rows'. Because
resolveExportCap() returned min(requested, formatCap) and runAll() then threw
when the result reached it, picking 'Records: First 100' in the export dialog
400'd on any report with more than 100 rows — the user asked to be truncated
and got an error instead.
Splits them: formatRowCap() is the hard, non-caller-controllable ceiling that
still throws when exceeded (a silently short file hides missing rows), while
resolveRowLimit() is the deliberate truncation and is honoured by slicing.
Verified against a 223-row dataset: limit=5 now returns 5 rows, and no limit
returns all 223.
Completes the writer extraction whose other half landed in fb21ad154.
reports.controller now builds a TabularDoc and calls TabularExportService,
so report-export.service.ts and report-export-request.util.ts are dead and
removed — HEAD was carrying both copies with the controller still on the old
one.
Reports gain CSV for free, and the PDF path now passes buildTabularFallbackPdf
as its fallback: previously it passed none, so a box without Chromium silently
returned PdfRenderService's ~900-character generic text dump instead of a
table. Adds a spec covering the CSV writer's quoting of embedded commas and
double quotes — the reason this uses ExcelJS's csv writer rather than a
hand-rolled join.
