Backs the previously-dead header date-picker and Filters button with
an actual scoped query. getDashboard() takes optional dateFrom/dateTo/
warehouseId: received (renamed from receivedToday) is the only
activity counter and respects the date range, defaulting to today when
omitted; the 10 status-backlog counters respect warehouseId only;
totalWarehouses/emptyContainers/importTrains/exportTrains stay global
since nothing ties them to a specific warehouse in the schema. Adds a
warehouse Select + date-range picker to the dashboard header, with a
caption spelling out what is and isn't scoped.
Backoffice: new tab on the booking detail page (?tab=additional-charges,
already linked from the row menu) with an Add Charge modal — Save draft or
Send to customer.
Portal: charges panel on the booking detail page, Pay now per charge via
the existing OTP/CBE-bill payment flow.
Also fixes: GET /bookings/:id/additional-charges was returning DRAFT
charges to the customer (hidden client-side only) — now filtered
server-side per caller.
New freight.additional_charge table, independent of BookingClearanceCharge
(unbounded per booking, free-text reason). Draft -> send issues an invoice
and notifies the customer in-app/SMS/email; settles via the standard
.invoice.paid event. Adds the Additional charges row-menu entry
next to Cancel booking, permission-gated.
Not included: the Additional Payments tab UI, add-charge modal, portal pay
flow.
seed-occ-july-2026 loads the OCC plan and operated figures the operations
reports were built against, so the plan-versus-actual tables have real
numbers to check.
tmp-ops-plan, tmp-ops-verify, tmp-mkdb and tmp-ops-reconcile were
scratch: written to reconcile those figures while the reports were being
built, and superseded by the seed above.
`source` named the subsystem and `sourceId` was a raw UUID, so the list
could not say which record an invoice belonged to, and search matched
only the invoice number and that UUID — nobody types a UUID.
Every source except a shipping-line credit hangs off a booking, directly
or through the warehouse/first-mile/last-mile record, so the list read
now resolves each row to a booking reference, GRN or shipping line and
sends it as `sourceRef`. Search spans the same ground plus the customer
name, with the raw sourceId still matchable so a pasted UUID keeps
working.
plannedValueExpr matched a target only when its period_type and
period_start equalled the report's bucket exactly, so a monthly plan
vanished the moment you viewed by quarter, by year, or by day. The plan
column simply went empty and the implement rate read 0%.
plannedRowsSql replaces it with a derived table: each target is spread
evenly over the days it covers, then re-gathered into whichever bucket
the report shows. Three monthly targets add up to a quarter exactly, a
daily view gets a thirty-first of the month, and a week straddling a
month boundary draws proportionally on both. The even spread is an
assumption and the only one available — a monthly figure says nothing
about which days inside it were busier — so PLAN_GRANULARITY_NOTE says so
in each report's description.
The share is clipped to the user's date filter as well as to the bucket,
or filtering to July and viewing by year would sit a whole year's plan
next to one month's work. Reports FULL OUTER JOIN it so a category that
was planned but never ran still publishes, at 0% — dropping the row would
hide a total miss, which is the one thing a plan-versus-actual table is
for.
The OCC report plans a station lane per cargo type — Nagad–Mojo container
and Nagad–Mojo fertilizer are separate numbers — but a target's identity
was period + metric + dimension + dimensionKey, so the two collided on
one slot. `cargo_category` is now part of the row and of the uniqueness
check; it stays null for cargo_category and container_class targets,
whose dimensionKey already carries the category.
The config grid showed raw codes (VOLUME_TONS, cargo_category, a yard
code). The list read now sends readable twins alongside the stored codes,
which stay exactly as they are because the reports join on them — the
same shape YardDistancesService uses. Labels resolve per dimension rather
than from one merged map: CONTAINER_EXPORT exists in both vocabularies
and reads differently in each, and merging them gave every cargo-category
row the container-class wording.
Bookings, contracts and train schedules all validated originYardId /
destinationYardId (originStationId / destinationStationId) as a single
@IsUUID and matched with `=`, so a list could be narrowed to exactly one
lane. The filter bar can now ask for several stations per end, and each
end independently, which needs the same on the server.
@IdListParam() is the shared transform: one id, a comma-separated list,
or a repeated query param, always landing as a string[]. It yields
undefined rather than [] when nothing usable is left — a repository that
branches on `?.length` can then never hand TypeORM an empty array, which
compiles to the syntax error IN (). It stays backwards compatible with
the single-value form, so existing deep links and saved views are
unaffected.
Matching moves to IN (:...ids) — for contracts inside the two existing
EXISTS subqueries, which keeps meaning "has a route from one of these
origins" AND "has a route to one of these destinations", not necessarily
the same route. All three statements were EXPLAIN-validated against
edr_dev.
Extends the warehouse dashboard with 3 metrics the screenshot target
needed but the backend didn't expose: emptyContainers (AVAILABLE
containers — closest proxy, no literal EMPTY status exists),
importTrains (reuses the import arrival queue definition), and
exportTrains (reuses the Djibouti export arrival queue definition) via
SchedulingReadFacade. Reorders the frontend metric grid to match and
fixes the Empty Containers card linking to a route that doesn't exist.
Rows-per-page was capped at 100 in three independent places: @Max on
PaginationQueryDto, the same @Max repeated on ListWagonsQueryDto (which does
not extend the base), and MAX_PAGE_SIZE in pagination.util. The first two
reject with a 400, the third silently truncates, so a larger page size had to
be lifted in all three or the endpoints that opted in would refuse it --
train schedules, routes, locomotives, wagons, audit, rule engine, built
trains, batch board and the rest.
No service overrides maxPageSize, so the util constant is the effective cap
everywhere it is reached.
Adds a spec pinning the three together: 500 validates, 501 rejects, and the
util returns take: 500 rather than truncating. A fourth copy of the number
lives in the backoffice data-table footer and is noted there.
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.
New endpoints:
POST invoices/eims/bulk-register { invoiceIds: [...] } — trigger
POST eims/webhook/bulk-register — MoR's callback
Fundamentally different shape from single register: bulkRegister
answers only {conversationId, status:202} immediately: MoR processes
the array asynchronously and pushes the real per-invoice results
(a mix of accepted/rejected in one array, per the collection's own
examples) to a webhook configured out of band. So this ships as two
halves that don't share a call stack — EimsBulkRegistrationService.
registerBulk() reserves a contiguous block of counters (durable
reservation, same doctrine as single register, extended to N items)
and submits; handleBulkCallback(), invoked by the new
EimsWebhookController whenever MoR gets around to it, settles.
New EimsSystemState.inFlightConversationId is the bulk equivalent of
inFlightInvoiceId — a whole batch outstanding, not one invoice — and
the two markers block each other since they share the same counter
sequence. The conversation id isn't known until MoR's 202 arrives, so
reservation stamps a locally-generated placeholder first (same
commit-before-the-network-call reasoning as single register), then
swaps it for MoR's real id right after — the only value the callback
can actually use to find the batch again.
Only the first invoice in a bulk batch chains via PreviousIrn — every
other item gets an empty string, matching the collection's own
two-invoice example exactly (MoR doesn't expect a batch to chain to
IRNs that don't exist yet at submission time).
Webhook has no auth (MoR has no JWT to send) — the conversation id
embedded in the payload is what stands between this and a forged
callback: an item only ever touches an invoice actually holding that
exact id, and an unknown id is logged and ignored, never applied.
Migration 3580000000000: eims_system_state.in_flight_conversation_id,
invoices.eims_bulk_conversation_id (tags which batch an invoice was
submitted in, so a stuck batch — webhook never arrived — can be found
and reconciled by conversation id). Applied to dev DB and recorded in
freight.migrations directly (idempotent IF NOT EXISTS DDL).
Not live-testable from this sandbox (no route to MoR's real gateway).
Signing the whole array as one envelope, the way single /v1/register
was confirmed live to need despite the collection's raw example
showing no envelope, is the reasonable extension of that confirmed
behavior, not a blind guess — but it has not itself been exercised
against the real gateway. Left for the first live bulk attempt to
confirm, same as every other MoR-facing assumption this integration
has made.
- Add migration for consolidation approvals table and status enum
- Create ConsolidationApprovalService to handle approval logic
- Implement repository for managing consolidation approvals
- Add entity for consolidation approval with necessary fields
- Develop frontend components for displaying and managing consolidation approvals
- Create tests for consolidation approval service to ensure correct behavior
- Add migration for consolidation approvals table and status enum
- Create ConsolidationApprovalService to handle approval logic
- Implement repository for managing consolidation approvals
- Add entity for consolidation approval with necessary fields
- Develop frontend components for displaying and managing consolidation approvals
- Create tests for consolidation approval service to ensure correct behavior
