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The analytics system must be fully integrated with orders, customers, products, inventory, marketing campaigns, payments, and user activity. Include the following features: - Sales Dashboard: Real-time overview of revenue, orders, average order value (AOV), sales trends, top-selling products, top-performing categories, payment methods, refunds, taxes, and key business KPIs. - Revenue Reports: Analyze revenue by day, week, month, quarter, year, custom date range, product, category, brand, customer, sales channel, and payment method. Support comparison reports and forecast trends. - Customer Analytics: Track customer growth, acquisition sources, new vs. returning customers, customer lifetime value (CLV), purchase frequency, retention rate, churn rate, geographic distribution, demographics (where available), and customer segmentation. - Product Performance: Monitor product views, impressions, add-to-cart rate, sales, conversion rate, revenue, profit margin, inventory turnover, stock availability, return rate, wishlist activity, and best/worst-performing products. - Funnel Analytics: Visualize the complete customer journey, including Landing Page → Product View → Add to Cart → Checkout → Payment → Order Completed. Identify drop-off points and bottlenecks with detailed conversion metrics. - Conversion Rate Analytics: Measure conversion rates across marketing campaigns, traffic sources, devices, browsers, landing pages, categories, products, and checkout stages. Support A/B testing comparison and attribution reporting. - Cohort Analysis: Analyze customer retention and purchasing behavior by signup date, first purchase, acquisition channel, campaign, or custom cohorts. Display repeat purchase trends, retention curves, and revenue contribution over time. Additional requirements: - Interactive dashboards with charts, graphs, heatmaps, and drill-down reports. - Real-time data updates with configurable refresh intervals. - Advanced filtering by date range, location, channel, customer segment, product, category, and campaign. - Export reports in CSV, Excel, and PDF formats. - Schedule automated report generation and email delivery. - Role-based dashboard access and permissions. - Seamless integration with Google Analytics 4, Google Tag Manager, Meta Pixel, Meta Conversions API, and other supported analytics providers. - High-performance queries, data caching, audit logging, and a scalable architecture capable of handling large datasets in production.Add schema fields to catalog, orders, identity Build analytics event spine models and consent-gated ingest Build daily rollup fact tables and roll_up_analytics command Build report API with scopes, caching, audit, exports, schedules Build analytics frontend registry, API client, and live tabs Verify backend tests, typecheck, build, and brow ser **The 7 sub-modules plus export/scheduling/RBAC/caching is far more than one safe pass in this repo (every module here ships with backend + tests + typecheck + build + browser verification). How should I sequence it?**: Phase 1: event spine + Sales & Revenue (Recommended) **Where should the behavioural data (page views, product views, add-to-cart, checkout steps, device/browser/traffic source) come from?**: First-party store in Django (Recommended) **Several requested metrics need new fields on existing models. Which should I add?**: Product cost price (profit margin), Order sales channel, Customer acquisition source / UTM **Which of the operational extras should be in this build?**: CSV + Excel export (Recommended), Scheduled email reports, Granular dashboard permissions, Query caching + audit loggi ng. Close out schema task: generate migrations and snapshot order-item cost at checkout Build the analytics event spine: session/event models plus consent-gated ingest endpoint Wire first-touch attribution into orders and customer records Verify: pytest, ruff, migration check. Which date should a day's revenue be attributed to? The existing dashboard selector counts revenue only for DELIVERED orders, which means "yesterday's revenue" keeps rising for weeks as orders ship — fine for a live tile, wrong for a settled daily fact table. Store both bases side by side (Recommended) Continue whare you stopped..3c:o9,128:T94c,3c:o94c,Looking at the data aggregation logic, the `_rebuild_products` function correctly uses distinct counts for order IDs and sums for units sold. DailyProductFact can include rows for deleted products, which is handled through product key lookups with currency fallbacks. There's a potential edge case where refunded items might reference a product row that doesn't exist in the sold currency table, though this shouldn't occur since items sold that day should have corresponding entries. I'm noticing a possible issue with `MoneySum` 's field type resolution — when multiplying a DecimalField by a PositiveIntegerField, Django may throw a mixed-types error because the inner CombinedExpression doesn't have an explicit output field set. Even though Sum's output_field is defined, the multiplication expression itself needs its own output field resolution during compilation. Wrapping the expression with ExpressionWrapper and explicitly setting output_field to MoneyField should resolve this. Now I'm setting up tests to verify the behavior. I need to handle timezone considerations by using explicit dates and updating created_at via queryset updates since it's auto_now_add. I'm planning helper functions for test setup rather than fixtures — creating orders with configurable placed_at, status, channel, payment method, and line items. I should verify the required fields across Cart, Product, User, Payment, and ReturnRequest models, then write test cases covering sales fact grain calculations, cancelled order exclusions, and customer history logic. Continuing with the remaining test cases: local day boundary handling where orders created near midnight in different timezones land in separate rows, idempotency checks on rebuild operations, refund and recognised basis dating logic, product fact aggregation with distinct viewing sessions, funnel fact deduplication, and rollup failure recording. For the command-line tool, I'm setting up the rebuild window to default to the last seven days inclusive, with explicit --from/--to flags for custom ranges, a --full option for backfilling from the earliest order, validation for errors, and messaging for empty stores. Then I need to set up the analytics session creation with required fields for session_key and last_event_at, and handle the started_at timestamp appropriately. Now I'm writing the conftest.py fixtures.3c:oa,129:T3dff,3c:o3dff,[V0_FILE]python:file="/backend/apps/analytics/tests/test_rollups.py" """What the daily fact tables must guarantee. These tests are deliberately about *contracts*, not coverage. Each one pins a property that, if it broke, would make a dashboard confidently wrong rather than visibly broken — the worst failure mode a reporting system has. """ from __future__ import annotations import datetime as dt from decimal import Decimal import pytest from apps.analytics import rollups from apps.analytics.models import ( AnalyticsRollupRun, DailyFunnelFact, DailyProductFact, DailySalesFact, ) from apps.orders.models import Order from apps.tracking.contracts import CanonicalEvent from .conftest import dhaka DAY = dt.date(2026, 7, 20) @pytest.mark.django_db def test_local_day_bounds_are_half_open_and_dhaka_local(): start, end = rollups.day_bounds(DAY) # 2026-07-20 00:00 Dhaka is 2026-07-19 18:00 UTC. A UTC-day rollup would put # this boundary six hours late and split every evening's trading in two. assert start.isoformat() == "2026-07-19T18:00:00+00:00" assert end.isoformat() == "2026-07-20T18:00:00+00:00" assert end - start == dt.timedelta(days=1) @pytest.mark.django_db def test_late_evening_order_belongs_to_the_local_day_it_was_placed( make_order, customer, product ): make_order(customer, placed_at=dhaka(2026, 7, 20, 23, 30), product=product) make_order(customer, placed_at=dhaka(2026, 7, 21, 0, 30), product=product) rollups.rebuild_day(DAY) rollups.rebuild_day(DAY + dt.timedelta(days=1)) assert DailySalesFact.objects.get(date=DAY).orders_placed == 1 assert DailySalesFact.objects.get(date=DAY + dt.timedelta(days=1)).orders_placed == 1 @pytest.mark.django_db def test_sales_fact_is_grained_by_channel_method_and_currency( make_order, customer, product ): make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, payment_method=Order.PaymentMethod.PREPAID, ) make_order( customer, placed_at=dhaka(2026, 7, 20, 11), product=product, payment_method=Order.PaymentMethod.COD, ) rollups.rebuild_day(DAY) facts = DailySalesFact.objects.filter(date=DAY) assert facts.count() == 2 assert {fact.payment_method for fact in facts} == {"prepaid", "cod"} assert all(fact.orders_placed == 1 for fact in facts) @pytest.mark.django_db def test_order_totals_and_cost_reconcile_with_the_orders_tables( make_order, customer, product ): make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, quantity=2, unit_price="100.00", unit_cost="60.00", discount="30.00", tax="15.00", shipping="20.00", ) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.gross_revenue == Decimal("200.00") assert fact.discount_amount == Decimal("30.00") assert fact.tax_amount == Decimal("15.00") assert fact.shipping_amount == Decimal("20.00") # The identity the whole sales fact rests on: the components must add back up # to what the customer was actually charged. assert ( fact.gross_revenue - fact.discount_amount + fact.tax_amount + fact.shipping_amount == fact.total_amount ) assert fact.units_sold == 2 assert fact.cogs_amount == Decimal("120.00") @pytest.mark.django_db def test_unknown_item_cost_does_not_fabricate_a_zero_margin(make_order, customer, product): make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00", unit_cost=None, ) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) # A NULL cost snapshot means "unknown", and unknown must not silently read as # 100% margin. It sums to zero here, and the report layer is responsible for # showing margin as unavailable rather than inferring it. assert fact.units_sold == 1 assert fact.cogs_amount == Decimal("0.00") @pytest.mark.django_db def test_cancelled_orders_are_counted_but_earn_nothing(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 9), product=product, unit_price="100.00") make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="500.00", status=Order.Status.CANCELLED, ) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.orders_placed == 1 assert fact.total_amount == Decimal("100.00") assert fact.cancelled_orders == 1 assert fact.cancelled_amount == Decimal("500.00") # Cancelled units must not inflate the day's volume either. assert fact.units_sold == 1 @pytest.mark.django_db def test_returning_customer_is_judged_against_full_history_not_the_window( make_order, customer, product ): # Their first order is months before the day being rebuilt. make_order(customer, placed_at=dhaka(2026, 3, 1, 10), product=product) make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.returning_customer_orders == 1 assert fact.new_customer_orders == 0 @pytest.mark.django_db def test_first_ever_order_counts_as_new(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.new_customer_orders == 1 assert fact.returning_customer_orders == 0 @pytest.mark.django_db def test_refund_lands_on_both_the_order_day_and_the_refund_day( make_order, customer, product, refund_order ): order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) refund_order(order, amount="100.00", completed_at=dhaka(2026, 7, 25, 10)) rollups.rebuild_day(DAY) rollups.rebuild_day(dt.date(2026, 7, 25)) placed_day = DailySalesFact.objects.get(date=DAY) refund_day = DailySalesFact.objects.get(date=dt.date(2026, 7, 25)) # Booking basis: the sale's own day is restated, which is what makes an # attribution comparison against that day's ad spend honest. assert placed_day.refunded_amount_on_order_date == Decimal("100.00") assert placed_day.refunded_amount_on_refund_date == Decimal("0.00") # Cash basis: the refund also shows on the day the money actually left. assert refund_day.refunded_amount_on_refund_date == Decimal("100.00") @pytest.mark.django_db def test_recognised_revenue_is_dated_to_delivery_not_placement( make_order, customer, product, deliver_order ): order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) deliver_order(order, dhaka(2026, 7, 28, 15)) rollups.rebuild_day(DAY) rollups.rebuild_day(dt.date(2026, 7, 28)) placed_day = DailySalesFact.objects.get(date=DAY) delivery_day = DailySalesFact.objects.get(date=dt.date(2026, 7, 28)) assert placed_day.total_amount == Decimal("100.00") assert placed_day.delivered_orders == 0 assert placed_day.recognised_revenue == Decimal("0.00") assert delivery_day.delivered_orders == 1 assert delivery_day.recognised_revenue == Decimal("100.00") assert delivery_day.recognised_cogs == Decimal("60.00") # The delivery day did not itself take an order. assert delivery_day.orders_placed == 0 @pytest.mark.django_db def test_rebuild_is_idempotent(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) rollups.rebuild_day(DAY) first = DailySalesFact.objects.get(date=DAY) rollups.rebuild_day(DAY) rollups.rebuild_day(DAY) second = DailySalesFact.objects.get(date=DAY) # Re-running must converge, not accumulate. This is the property that makes # a cron overlap, a manual replay and a bug-fix backfill all safe. assert DailySalesFact.objects.filter(date=DAY).count() == 1 assert second.orders_placed == first.orders_placed == 1 assert second.total_amount == first.total_amount @pytest.mark.django_db def test_rebuild_repairs_a_day_after_the_source_changes(make_order, customer, product): order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) rollups.rebuild_day(DAY) assert DailySalesFact.objects.get(date=DAY).orders_placed == 1 # A late correction: the order is cancelled after the fact was first built. Order.objects.filter(pk=order.pk).update(status=Order.Status.CANCELLED) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.orders_placed == 0 assert fact.cancelled_orders == 1 # --------------------------------------------------------------------------- # Product facts # --------------------------------------------------------------------------- @pytest.mark.django_db def test_product_fact_joins_behaviour_to_sales_on_one_row( make_order, customer, product, make_session, add_event ): session = make_session(started_at=dhaka(2026, 7, 20, 9)) other = make_session(started_at=dhaka(2026, 7, 20, 9, 30)) # One visitor views twice; a second views once. add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9), product=product) add_event( session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9, 5), product=product ) add_event( other, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9, 40), product=product ) add_event( session, CanonicalEvent.ADD_TO_CART, occurred_at=dhaka(2026, 7, 20, 9, 10), product=product ) make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product, quantity=3) rollups.rebuild_day(DAY) fact = DailyProductFact.objects.get(date=DAY, product=product) assert fact.product_views == 3 # Distinct sessions, not raw views: a reload must not make conversion look # worse than it was. assert fact.viewing_sessions == 2 assert fact.add_to_carts == 1 assert fact.units_sold == 3 assert fact.orders_count == 1 assert fact.gross_revenue == Decimal("300.00") @pytest.mark.django_db def test_product_fact_records_views_with_no_sales(product, make_session, add_event): session = make_session(started_at=dhaka(2026, 7, 20, 9)) add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9), product=product) rollups.rebuild_day(DAY) fact = DailyProductFact.objects.get(date=DAY, product=product) # A product that was looked at and not bought is the single most useful row # in the table; it must exist even with no order to hang it on. assert fact.product_views == 1 assert fact.units_sold == 0 assert fact.currency == "BDT" # --------------------------------------------------------------------------- # Funnel facts # --------------------------------------------------------------------------- @pytest.mark.django_db def test_funnel_counts_distinct_sessions_per_stage(product, make_session, add_event): session = make_session(started_at=dhaka(2026, 7, 20, 9), channel="organic", device_type="mobile") add_event(session, CanonicalEvent.PAGE_VIEW, occurred_at=dhaka(2026, 7, 20, 9)) add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9, 2), product=product) # Three cart adds in one visit is still one session reaching the cart step. for minute in (5, 6, 7): add_event( session, CanonicalEvent.ADD_TO_CART, occurred_at=dhaka(2026, 7, 20, 9, minute), product=product, ) rollups.rebuild_day(DAY) fact = DailyFunnelFact.objects.get(date=DAY, channel="organic", device_type="mobile") assert fact.sessions == 1 assert fact.reached_landing == 1 assert fact.reached_product_view == 1 assert fact.reached_add_to_cart == 1 assert fact.reached_checkout == 0 @pytest.mark.django_db def test_funnel_keeps_a_midnight_crossing_journey_in_one_row( make_order, customer, product, make_session, add_event ): session = make_session(started_at=dhaka(2026, 7, 20, 23, 50)) add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 23, 55), product=product) order = make_order(customer, placed_at=dhaka(2026, 7, 21, 0, 5), product=product) add_event(session, CanonicalEvent.PURCHASE, occurred_at=dhaka(2026, 7, 21, 0, 5), order=order) rollups.rebuild_day(DAY) rollups.rebuild_day(DAY + dt.timedelta(days=1)) fact = DailyFunnelFact.objects.get(date=DAY) # Anchored on session start, so the purchase stays attached to the visit that # produced it instead of appearing on the next day with no preceding steps. assert fact.reached_product_view == 1 assert fact.reached_purchase == 1 assert fact.orders_count == 1 assert DailyFunnelFact.objects.filter(date=DAY + dt.timedelta(days=1)).count() == 0 @pytest.mark.django_db def test_duplicate_purchase_events_do_not_double_count_revenue( make_order, customer, product, make_session, add_event ): session = make_session(started_at=dhaka(2026, 7, 20, 9)) order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) # A confirmation-page reload reports the same purchase twice. add_event(session, CanonicalEvent.PURCHASE, occurred_at=dhaka(2026, 7, 20, 10), order=order) add_event(session, CanonicalEvent.PURCHASE, occurred_at=dhaka(2026, 7, 20, 10, 1), order=order) rollups.rebuild_day(DAY) fact = DailyFunnelFact.objects.get(date=DAY) assert fact.orders_count == 1 assert fact.revenue_amount == Decimal("100.00") # --------------------------------------------------------------------------- # Run audit # --------------------------------------------------------------------------- @pytest.mark.django_db def test_successful_range_records_an_audit_row(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) run = rollups.rebuild_range(DAY, DAY + dt.timedelta(days=2), triggered_by="cron") assert run.status == AnalyticsRollupRun.Status.SUCCEEDED assert run.days_processed == 3 assert run.rows_written >= 1 assert run.finished_at is not None assert rollups.last_successful_run() == run @pytest.mark.django_db def test_failure_is_recorded_and_reraised(monkeypatch): def explode(day): raise RuntimeError("source table vanished") monkeypatch.setattr(rollups, "rebuild_day", explode) with pytest.raises(RuntimeError): rollups.rebuild_range(DAY, DAY, triggered_by="cron") run = AnalyticsRollupRun.objects.get() # A job that dies at 3am must be visible as a failure, not as a quiet day. assert run.status == AnalyticsRollupRun.Status.FAILED assert "source table vanished" in run.error_message assert rollups.last_successful_run() is None @pytest.mark.django_db def test_range_rejects_inverted_dates(): with pytest.raises(ValueError): rollups.rebuild_range(DAY, DAY - dt.timedelta(days=1)) @pytest.mark.django_db def test_earliest_activity_date_spans_orders_and_sessions( make_order, customer, product, make_session ): assert rollups.earliest_activity_date() is None make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) make_session(started_at=dhaka(2026, 5, 4, 10)) # The spine and the order history each predate the other in real deployments; # the backfill start has to be the earlier of the two. assert rollups.earliest_activity_date() == dt.date(2026, 5, 4)3c:oa,12a:T3dff,3c:o3dff,[V0_FILE]python:file="/backend/apps/analytics/tests/test_rollups.py" """What the daily fact tables must guarantee. These tests are deliberately about *contracts*, not coverage. Each one pins a property that, if it broke, would make a dashboard confidently wrong rather than visibly broken — the worst failure mode a reporting system has. """ from __future__ import annotations import datetime as dt from decimal import Decimal import pytest from apps.analytics import rollups from apps.analytics.models import ( AnalyticsRollupRun, DailyFunnelFact, DailyProductFact, DailySalesFact, ) from apps.orders.models import Order from apps.tracking.contracts import CanonicalEvent from .conftest import dhaka DAY = dt.date(2026, 7, 20) @pytest.mark.django_db def test_local_day_bounds_are_half_open_and_dhaka_local(): start, end = rollups.day_bounds(DAY) # 2026-07-20 00:00 Dhaka is 2026-07-19 18:00 UTC. A UTC-day rollup would put # this boundary six hours late and split every evening's trading in two. assert start.isoformat() == "2026-07-19T18:00:00+00:00" assert end.isoformat() == "2026-07-20T18:00:00+00:00" assert end - start == dt.timedelta(days=1) @pytest.mark.django_db def test_late_evening_order_belongs_to_the_local_day_it_was_placed( make_order, customer, product ): make_order(customer, placed_at=dhaka(2026, 7, 20, 23, 30), product=product) make_order(customer, placed_at=dhaka(2026, 7, 21, 0, 30), product=product) rollups.rebuild_day(DAY) rollups.rebuild_day(DAY + dt.timedelta(days=1)) assert DailySalesFact.objects.get(date=DAY).orders_placed == 1 assert DailySalesFact.objects.get(date=DAY + dt.timedelta(days=1)).orders_placed == 1 @pytest.mark.django_db def test_sales_fact_is_grained_by_channel_method_and_currency( make_order, customer, product ): make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, payment_method=Order.PaymentMethod.PREPAID, ) make_order( customer, placed_at=dhaka(2026, 7, 20, 11), product=product, payment_method=Order.PaymentMethod.COD, ) rollups.rebuild_day(DAY) facts = DailySalesFact.objects.filter(date=DAY) assert facts.count() == 2 assert {fact.payment_method for fact in facts} == {"prepaid", "cod"} assert all(fact.orders_placed == 1 for fact in facts) @pytest.mark.django_db def test_order_totals_and_cost_reconcile_with_the_orders_tables( make_order, customer, product ): make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, quantity=2, unit_price="100.00", unit_cost="60.00", discount="30.00", tax="15.00", shipping="20.00", ) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.gross_revenue == Decimal("200.00") assert fact.discount_amount == Decimal("30.00") assert fact.tax_amount == Decimal("15.00") assert fact.shipping_amount == Decimal("20.00") # The identity the whole sales fact rests on: the components must add back up # to what the customer was actually charged. assert ( fact.gross_revenue - fact.discount_amount + fact.tax_amount + fact.shipping_amount == fact.total_amount ) assert fact.units_sold == 2 assert fact.cogs_amount == Decimal("120.00") @pytest.mark.django_db def test_unknown_item_cost_does_not_fabricate_a_zero_margin(make_order, customer, product): make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00", unit_cost=None, ) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) # A NULL cost snapshot means "unknown", and unknown must not silently read as # 100% margin. It sums to zero here, and the report layer is responsible for # showing margin as unavailable rather than inferring it. assert fact.units_sold == 1 assert fact.cogs_amount == Decimal("0.00") @pytest.mark.django_db def test_cancelled_orders_are_counted_but_earn_nothing(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 9), product=product, unit_price="100.00") make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="500.00", status=Order.Status.CANCELLED, ) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.orders_placed == 1 assert fact.total_amount == Decimal("100.00") assert fact.cancelled_orders == 1 assert fact.cancelled_amount == Decimal("500.00") # Cancelled units must not inflate the day's volume either. assert fact.units_sold == 1 @pytest.mark.django_db def test_returning_customer_is_judged_against_full_history_not_the_window( make_order, customer, product ): # Their first order is months before the day being rebuilt. make_order(customer, placed_at=dhaka(2026, 3, 1, 10), product=product) make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.returning_customer_orders == 1 assert fact.new_customer_orders == 0 @pytest.mark.django_db def test_first_ever_order_counts_as_new(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.new_customer_orders == 1 assert fact.returning_customer_orders == 0 @pytest.mark.django_db def test_refund_lands_on_both_the_order_day_and_the_refund_day( make_order, customer, product, refund_order ): order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) refund_order(order, amount="100.00", completed_at=dhaka(2026, 7, 25, 10)) rollups.rebuild_day(DAY) rollups.rebuild_day(dt.date(2026, 7, 25)) placed_day = DailySalesFact.objects.get(date=DAY) refund_day = DailySalesFact.objects.get(date=dt.date(2026, 7, 25)) # Booking basis: the sale's own day is restated, which is what makes an # attribution comparison against that day's ad spend honest. assert placed_day.refunded_amount_on_order_date == Decimal("100.00") assert placed_day.refunded_amount_on_refund_date == Decimal("0.00") # Cash basis: the refund also shows on the day the money actually left. assert refund_day.refunded_amount_on_refund_date == Decimal("100.00") @pytest.mark.django_db def test_recognised_revenue_is_dated_to_delivery_not_placement( make_order, customer, product, deliver_order ): order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) deliver_order(order, dhaka(2026, 7, 28, 15)) rollups.rebuild_day(DAY) rollups.rebuild_day(dt.date(2026, 7, 28)) placed_day = DailySalesFact.objects.get(date=DAY) delivery_day = DailySalesFact.objects.get(date=dt.date(2026, 7, 28)) assert placed_day.total_amount == Decimal("100.00") assert placed_day.delivered_orders == 0 assert placed_day.recognised_revenue == Decimal("0.00") assert delivery_day.delivered_orders == 1 assert delivery_day.recognised_revenue == Decimal("100.00") assert delivery_day.recognised_cogs == Decimal("60.00") # The delivery day did not itself take an order. assert delivery_day.orders_placed == 0 @pytest.mark.django_db def test_rebuild_is_idempotent(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) rollups.rebuild_day(DAY) first = DailySalesFact.objects.get(date=DAY) rollups.rebuild_day(DAY) rollups.rebuild_day(DAY) second = DailySalesFact.objects.get(date=DAY) # Re-running must converge, not accumulate. This is the property that makes # a cron overlap, a manual replay and a bug-fix backfill all safe. assert DailySalesFact.objects.filter(date=DAY).count() == 1 assert second.orders_placed == first.orders_placed == 1 assert second.total_amount == first.total_amount @pytest.mark.django_db def test_rebuild_repairs_a_day_after_the_source_changes(make_order, customer, product): order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) rollups.rebuild_day(DAY) assert DailySalesFact.objects.get(date=DAY).orders_placed == 1 # A late correction: the order is cancelled after the fact was first built. Order.objects.filter(pk=order.pk).update(status=Order.Status.CANCELLED) rollups.rebuild_day(DAY) fact = DailySalesFact.objects.get(date=DAY) assert fact.orders_placed == 0 assert fact.cancelled_orders == 1 # --------------------------------------------------------------------------- # Product facts # --------------------------------------------------------------------------- @pytest.mark.django_db def test_product_fact_joins_behaviour_to_sales_on_one_row( make_order, customer, product, make_session, add_event ): session = make_session(started_at=dhaka(2026, 7, 20, 9)) other = make_session(started_at=dhaka(2026, 7, 20, 9, 30)) # One visitor views twice; a second views once. add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9), product=product) add_event( session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9, 5), product=product ) add_event( other, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9, 40), product=product ) add_event( session, CanonicalEvent.ADD_TO_CART, occurred_at=dhaka(2026, 7, 20, 9, 10), product=product ) make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product, quantity=3) rollups.rebuild_day(DAY) fact = DailyProductFact.objects.get(date=DAY, product=product) assert fact.product_views == 3 # Distinct sessions, not raw views: a reload must not make conversion look # worse than it was. assert fact.viewing_sessions == 2 assert fact.add_to_carts == 1 assert fact.units_sold == 3 assert fact.orders_count == 1 assert fact.gross_revenue == Decimal("300.00") @pytest.mark.django_db def test_product_fact_records_views_with_no_sales(product, make_session, add_event): session = make_session(started_at=dhaka(2026, 7, 20, 9)) add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9), product=product) rollups.rebuild_day(DAY) fact = DailyProductFact.objects.get(date=DAY, product=product) # A product that was looked at and not bought is the single most useful row # in the table; it must exist even with no order to hang it on. assert fact.product_views == 1 assert fact.units_sold == 0 assert fact.currency == "BDT" # --------------------------------------------------------------------------- # Funnel facts # --------------------------------------------------------------------------- @pytest.mark.django_db def test_funnel_counts_distinct_sessions_per_stage(product, make_session, add_event): session = make_session(started_at=dhaka(2026, 7, 20, 9), channel="organic", device_type="mobile") add_event(session, CanonicalEvent.PAGE_VIEW, occurred_at=dhaka(2026, 7, 20, 9)) add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 9, 2), product=product) # Three cart adds in one visit is still one session reaching the cart step. for minute in (5, 6, 7): add_event( session, CanonicalEvent.ADD_TO_CART, occurred_at=dhaka(2026, 7, 20, 9, minute), product=product, ) rollups.rebuild_day(DAY) fact = DailyFunnelFact.objects.get(date=DAY, channel="organic", device_type="mobile") assert fact.sessions == 1 assert fact.reached_landing == 1 assert fact.reached_product_view == 1 assert fact.reached_add_to_cart == 1 assert fact.reached_checkout == 0 @pytest.mark.django_db def test_funnel_keeps_a_midnight_crossing_journey_in_one_row( make_order, customer, product, make_session, add_event ): session = make_session(started_at=dhaka(2026, 7, 20, 23, 50)) add_event(session, CanonicalEvent.VIEW_ITEM, occurred_at=dhaka(2026, 7, 20, 23, 55), product=product) order = make_order(customer, placed_at=dhaka(2026, 7, 21, 0, 5), product=product) add_event(session, CanonicalEvent.PURCHASE, occurred_at=dhaka(2026, 7, 21, 0, 5), order=order) rollups.rebuild_day(DAY) rollups.rebuild_day(DAY + dt.timedelta(days=1)) fact = DailyFunnelFact.objects.get(date=DAY) # Anchored on session start, so the purchase stays attached to the visit that # produced it instead of appearing on the next day with no preceding steps. assert fact.reached_product_view == 1 assert fact.reached_purchase == 1 assert fact.orders_count == 1 assert DailyFunnelFact.objects.filter(date=DAY + dt.timedelta(days=1)).count() == 0 @pytest.mark.django_db def test_duplicate_purchase_events_do_not_double_count_revenue( make_order, customer, product, make_session, add_event ): session = make_session(started_at=dhaka(2026, 7, 20, 9)) order = make_order( customer, placed_at=dhaka(2026, 7, 20, 10), product=product, unit_price="100.00" ) # A confirmation-page reload reports the same purchase twice. add_event(session, CanonicalEvent.PURCHASE, occurred_at=dhaka(2026, 7, 20, 10), order=order) add_event(session, CanonicalEvent.PURCHASE, occurred_at=dhaka(2026, 7, 20, 10, 1), order=order) rollups.rebuild_day(DAY) fact = DailyFunnelFact.objects.get(date=DAY) assert fact.orders_count == 1 assert fact.revenue_amount == Decimal("100.00") # --------------------------------------------------------------------------- # Run audit # --------------------------------------------------------------------------- @pytest.mark.django_db def test_successful_range_records_an_audit_row(make_order, customer, product): make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) run = rollups.rebuild_range(DAY, DAY + dt.timedelta(days=2), triggered_by="cron") assert run.status == AnalyticsRollupRun.Status.SUCCEEDED assert run.days_processed == 3 assert run.rows_written >= 1 assert run.finished_at is not None assert rollups.last_successful_run() == run @pytest.mark.django_db def test_failure_is_recorded_and_reraised(monkeypatch): def explode(day): raise RuntimeError("source table vanished") monkeypatch.setattr(rollups, "rebuild_day", explode) with pytest.raises(RuntimeError): rollups.rebuild_range(DAY, DAY, triggered_by="cron") run = AnalyticsRollupRun.objects.get() # A job that dies at 3am must be visible as a failure, not as a quiet day. assert run.status == AnalyticsRollupRun.Status.FAILED assert "source table vanished" in run.error_message assert rollups.last_successful_run() is None @pytest.mark.django_db def test_range_rejects_inverted_dates(): with pytest.raises(ValueError): rollups.rebuild_range(DAY, DAY - dt.timedelta(days=1)) @pytest.mark.django_db def test_earliest_activity_date_spans_orders_and_sessions( make_order, customer, product, make_session ): assert rollups.earliest_activity_date() is None make_order(customer, placed_at=dhaka(2026, 7, 20, 10), product=product) make_session(started_at=dhaka(2026, 5, 4, 10)) # The spine and the order history each predate the other in real deployments; # the backfill start has to be the earlier of the two. assert rollups.earliest_activity_date() == dt.date(2026, 5, 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apps/notifications/management/commands/process_notifications.py"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"4hCzeX7PNaLVrWnG"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"26:class ReturnRequest(models.Model):\n27: class Status(models.TextChoices):\n36: class Reason(models.TextChoices):\n54: status = models.CharField(max_length=20, choices=Status.choices, default=Status.REQUESTED)\n61: requested_amount = mo\n\n...\n\nadd_argument(\"--limit\", type=int, default=100)\n\n def handle(self, *args, **options):\n count = process_delivery_jobs(limit=max(1, options[\"limit\"]))\n self.stdout.write(self.style.SUCCESS(f\"Processed {count} notification job(s).\"))\n"},"id":"2RuvWCB8E0uZGHCi"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785511797151,"finishedAt":1785511797411,"lastPartSentAt":1785511797411,"taskNameActive":null,"id":"MOQaXKpe2q4loDRv","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":0,"thought":"I need to check the contracts.py file for STAGE_ORDER and FunnelStage definitions, then verify the tracking contracts for canonical event names like VIEW_ITEM_LIST, before generating the migration."}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785511798356,"finishedAt":1785511800400,"lastPartSentAt":1785511800075,"taskNameActive":"Checking contracts","taskNameComplete":"Checked contracts","toolCallId":"toolu_01GBktqNMmLkiRANx9PBaRec","agentTurnId":"turn_wqG3fzxinY7siweB","filePath":null,"id":"FvMW8T7yVPyvCCv9","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && grep -n \"STAGE_ORDER\\|class FunnelStage\\|LANDING\\|PRODUCT_VIEW\\|ADD_TO_CART\\|CHECKOUT\\|PAYMENT\\|PURCHASE\\|NONE\" apps/analytics/contracts.py | head -40 && echo \"=== canonical ===\" && grep -n \"VIEW_ITEM\\|ADD_TO_CART\\|REMOVE_FROM_CART\\|ADD_TO_WISHLIST\\|PURCHASE\" apps/tracking/contracts.py | head -20"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"d4jYxgTU1J7Ydrsk"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"46: CanonicalEvent.ADD_TO_CART,\n49: CanonicalEvent.BEGIN_CHECKOUT,\n51: CanonicalEvent.ADD_PAYMENT_INFO,\n52: CanonicalEvent.PURCHASE,\n61:class FunnelStage(models.TextChoices):\n64: Ordering matters: ``STAGE_ORDER`` below is what a fu\n\n...\n\n \"ViewContent\",\n98: CanonicalEvent.ADD_TO_CART: \"AddToCart\",\n99: CanonicalEvent.ADD_TO_WISHLIST: \"AddToWishlist\",\n102: CanonicalEvent.PURCHASE: \"Purchase\",\n109:MONETARY_EVENTS = frozenset({CanonicalEvent.PURCHASE, CanonicalEvent.REFUND})\n"},"id":"6ugy1Dzc0BoeEP7y"}]}}],["p",{},["text",{},"Now let me generate the migration for the fact tables."]],["AssistantMessageContentPart",{"part":{"createdAt":1785511804823,"finishedAt":1785511806166,"lastPartSentAt":1785511806015,"taskNameActive":"Generating migration","taskNameComplete":"Generated 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Django management command with env loaded from .env.production.generated."},"id":"LPMkJ6h4Ssuc9Ukg"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"\n\nShell `source` cannot parse values containing spaces (the PEM key), so this\nloader reads the file directly and execs ma\n\n...\n\nviron[key.strip()] = value\n\n\nif __name__ == \"__main__\":\n load_env()\n/usr/local/bin/uv\nbin\ninclude\nlib\nlib64\npyvenv.cfg\n"},"id":"hfUp5BuBv6LYrjlV"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785511814820,"finishedAt":1785511816611,"lastPartSentAt":1785511816445,"taskNameActive":"Generating migration","taskNameComplete":"Generated migration","toolCallId":"toolu_01SkedGeadhostwNBud94TSQ","agentTurnId":"turn_i1BZQPbMaUcVAF7I","filePath":null,"id":"r3mIcVFkA6uAJAgC","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && .venv/bin/python manage.py makemigrations analytics 2>&1 | tail -25"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"JH0B9DimltCppvK2"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"Migrations for 'analytics':\n apps/analytics/migrations/0002_analyticsrolluprun_dailyfunnelfact_dailysalesfact_and_more.py\n + Create model AnalyticsRollupRun\n + Create model DailyFunnelFact\n + Create model DailySalesFact\n + Create model D"},"id":"aPxIloiuFUMxiEtr"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"ailyProductFact\n"},"id":"xztD3QxDslI0ZsZB"}]}}],["AssistantMessageContentPart",{"part":{"type":"task-coding-v1","id":"block-b_6w8RSNK1OK9","parts":[{"type":"code-project","isVersioned":false,"isSourceless":false,"changedFiles":[{"fileName":"backend/apps/analytics/migrations/0002_analyticsrolluprun_dailyfunnelfact_dailysalesfact_and_more.py","baseName":"0002_analyticsrolluprun_dailyfunnelfact_dailysalesfact_and_more.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false}],"source":"[V0_FILE]py:file=\"backend/apps/analytics/migrations/0002_analyticsrolluprun_dailyfunnelfact_dailysalesfact_and_more.py\" \nGENERATING","latestDeploymentInfo":"$122:1:1","lastDeployedAt":"2026-07-31T15:39:38.854Z","sourceVersionKey":"v_1_3s2l5_s3","needsBlockSource":true,"isAllImages":false,"blockId":"b_6w8RSNK1OK9","meta":{"taskNameActive":"Applying changes","taskNameComplete":"Applied 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Let me write out the command implementation."}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785511822332,"finishedAt":1785511823469,"lastPartSentAt":1785511823290,"taskNameActive":"Checking command dir","taskNameComplete":"Checked command dir","toolCallId":"toolu_014yqS6DmPyjHTRCRX78eHKH","agentTurnId":"turn_PSPaFPfWaO8RCb5y","filePath":null,"id":"KjR02p8a6VM13nG7","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && ls apps/analytics && cat apps/catalog/management/commands/backfill_units_sold.py"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"hXiKdzjr6wYaGFxr"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"__init__.py\n__pycache__\napps.py\nattribution.py\ncontracts.py\nmigrations\nmodels.py\nrollups.py\nselectors.py\nserializers.py\nservices.py\ntests\nurls.py\nviews.py\n\"\"\"Repair ``Product.units_sold`` from the delivered order history.\n\nRun after deploying the cou"},"id":"c8IKGQXbYfywkrIk"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"nter for the first time, after a bulk order import,\nor any time popularity ordering looks wrong. The command is idempoten\n\n...\n\nduct(s).\")\n )\n else:\n self.stdout.write(\"All products already in sync; nothing to correct.\")\n"},"id":"F79HYxuCXAOnR13v"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785511828838,"finishedAt":1785511830016,"lastPartSentAt":1785511830016,"taskNameActive":null,"id":"nCB0OQDT9mjgb1f0","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":1,"thought":"I'm adding helper functions to rollups.py for the re-windowing logic, including a constant for the default window duration, a function to resolve window boundaries based on various parameters, and a function to find the earliest activity date across orders and analytics sessions."}]}}],["AssistantMessageContentPart",{"part":{"type":"task-coding-v1","id":"block-b_DaSLVPE0HdD","parts":[{"type":"code-project","isVersioned":false,"isSourceless":false,"changedFiles":[{"fileName":"/backend/apps/analytics/rollups.py","baseName":"rollups.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false}],"source":"[V0_FILE]py:file=\"/backend/apps/analytics/rollups.py\" \nGENERATING","latestDeploymentInfo":"$122:2:1","lastDeployedAt":"2026-07-31T15:39:38.854Z","sourceVersionKey":"v_1_ed0pi_s3","needsBlockSource":true,"isAllImages":false,"blockId":"b_DaSLVPE0HdD","meta":{"taskNameActive":"Adding window helpers","taskNameComplete":"Added window helpers","type":"code-project","id":"Code"},"closed":true,"lang":"typescriptreact"}],"createdAt":0,"finishedAt":1,"lastPartSentAt":1,"taskNameActive":"Adding window helpers","taskNameComplete":"Added window 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Let me look at how existing order tests handle this."}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785511891125,"finishedAt":1785511892858,"lastPartSentAt":1785511892630,"taskNameActive":"Finding order test helpers","taskNameComplete":"Found order test helpers","toolCallId":"toolu_01F1YqVcqP2JtZdZafHLWWEW","agentTurnId":"turn_ERQnLcFkn9TRTVfF","filePath":null,"id":"j4FqjmsbDLN9l2vx","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && ls apps/*/tests/factories.py apps/shared_kernel/testing* conftest.py 2>/dev/null; find . -name conftest.py -not -path \"./.venv/*\" | head; echo \"=== order model ===\" && sed -n 80,140p apps/orders/models.py && sed -n 200,245p apps/orders/models.py"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"mYPYIGYMXQrUR4Qu"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"apps/affiliates/tests/factories.py\napps/promotions/tests/factories.py\napps/referrals/tests/factories.py\n./apps/fraud/tests/conftest.py\n./apps/inventory/tests/conftest.py\n./apps/media/tests/conftest.py\n./apps/payments/tests/conftest.py\n./apps/returns/"},"id":"5CZ3TnHXyTn50Ck7"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"tests/conftest.py\n./apps/reviews/tests/conftest.py\n./apps/tracking/tests/conftest.py\n=== order model ===\n READY_FO\n\n...\n\nbetween SQLite (dev) and PostgreSQL (prod). 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Fixing before writing tests."]],["AssistantMessageContentPart",{"part":{"createdAt":1785511947839,"finishedAt":1785511948464,"lastPartSentAt":1785511948382,"taskNameActive":"Reading rollups aggregates","taskNameComplete":"Read rollups aggregates","toolCallId":"toolu_01SxTB1LoqGzf7MqQXdjhAaN","agentTurnId":"turn_AroCg9ZOZ9d7VplR","filePath":null,"id":"wFJ36GD8wwnYF0rg","type":"task-read-file-v1","parts":[{"type":"reading-file","filePath":"/vercel/share/v0-project/backend/apps/analytics/rollups.py"},{"type":"reading-file","filePath":"/vercel/share/v0-project/backend/apps/analytics/rollups.py","offset":127,"limit":130}]}}],["p",{},["text",{},"Now let me fix each aggregation queryset to clear default 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I need to be careful about how I construct the order timestamps—using rollups.today_local() and making sure the placed_at timestamp is timezone-aware.\n\nFor the --full flag test, I'll create an order from 10 days ago and verify that after running with --full, a fact exists for that date and run.from_date matches that date."}]}}],["AssistantMessageContentPart",{"part":{"type":"task-coding-v1","id":"block-b_3qEyEuXAdTD","parts":[{"type":"code-project","isVersioned":true,"isSourceless":false,"changedFiles":[{"fileName":"backend/apps/analytics/migrations/0002_analyticsrolluprun_dailyfunnelfact_dailysalesfact_and_more.py","baseName":"0002_analyticsrolluprun_dailyfunnelfact_dailysalesfact_and_more.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false},{"fileName":"/backend/apps/analytics/rollups.py","baseName":"rollups.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false},{"fileName":"backend/apps/analytics/management/__init__.py","baseName":"__init__.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false},{"fileName":"backend/apps/analytics/management/commands/__init__.py","baseName":"__init__.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false},{"fileName":"/backend/apps/analytics/management/commands/roll_up_analytics.py","baseName":"roll_up_analytics.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false},{"fileName":"/backend/apps/analytics/tests/conftest.py","baseName":"conftest.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false},{"fileName":"/backend/apps/analytics/tests/test_rollups.py","baseName":"test_rollups.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false},{"fileName":"/backend/apps/analytics/tests/test_rollup_command.py","baseName":"test_rollup_command.py","isActive":false,"isTerminated":false,"isDeleted":false,"isMoved":false}],"source":"[V0_FILE]py:file=\"/backend/apps/analytics/tests/test_rollup_command.py\" \nGENERATING","latestDeploymentInfo":"$122:31:1","lastDeployedAt":"2026-07-31T15:39:38.854Z","sourceVersionKey":"v_1_e5t7g_s3","needsBlockSource":true,"isAllImages":false,"blockId":"b_3qEyEuXAdTD","meta":{"taskNameActive":"Writing command tests","taskNameComplete":"Wrote command tests","type":"code-project","id":"Code"},"closed":true,"lang":"typescriptreact"}],"createdAt":0,"finishedAt":1,"lastPartSentAt":1,"taskNameActive":"Writing command tests","taskNameComplete":"Wrote command tests"},"id":"block-b_3qEyEuXAdTD"}],["AssistantMessageContentPart",{"part":{"createdAt":1785512359758,"finishedAt":1785512374070,"lastPartSentAt":1785512373614,"taskNameActive":"Running command tests","taskNameComplete":"Ran command tests","toolCallId":"toolu_01Qx8GJgJsjDpqsm4xnJ73vr","agentTurnId":"turn_E6oAiVcrpC6ZnXXZ","filePath":null,"id":"f4ThOYvHF541xkmk","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && .venv/bin/python -m pytest apps/analytics -q 2>&1 | tail -30"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"6LHZqKYxYNoS7cmd"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"........................................................................ 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After that, I'll run the full test suite, ruff checks, and verify the migration."}]}}],["p",{},["text",{},"All 87 analytics tests pass. Now let me generate the migration for the fact tables."]],["AssistantMessageContentPart",{"part":{"createdAt":1785512389582,"finishedAt":1785512392133,"lastPartSentAt":1785512391989,"taskNameActive":"Generating migration","taskNameComplete":"Generated migration","toolCallId":"toolu_01UJVPVW6kgkAxF8kiZZbrTz","agentTurnId":"turn_JaWHZ1RRnti2k3CM","filePath":null,"id":"t6NaHrmMi78yT4y9","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && ls apps/analytics/migrations/ && .venv/bin/python manage.py makemigrations analytics 2>&1 | tail -25"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"CE1YCATPuvdzRDc7"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"0001_initial.py\n0002_analyticsrolluprun_dailyfunnelfact_dailysalesfact_and_more.py\n__init__.py\n__pycache__\n"},"id":"L5e1CH4UBsD6Xx3Y"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"No changes detected in app 'analytics'\n"},"id":"2ozcpRm2zRWbINiQ"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785512396149,"finishedAt":1785512396586,"lastPartSentAt":1785512396586,"taskNameActive":null,"id":"n8AD1jUt3ZhMRJ4r","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":0,"thought":"The migration is already in place and current, so now I'm running the full test suite along with ruff checks and verifying there are no pending migrations."}]}}],["p",{},["text",{},"Migration already in place and in sync. Now full verification across the whole backend."]],["AssistantMessageContentPart",{"part":{"createdAt":1785512397190,"finishedAt":1785512399410,"lastPartSentAt":1785512399218,"taskNameActive":"Verifying backend","taskNameComplete":"Verified backend","toolCallId":"toolu_01CnqSUnH2EXvypjoCSCqgwy","agentTurnId":"turn_2MtKi13233ZGgzPs","filePath":null,"id":"UhMZHbmoX37lAPDa","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && echo \"=== ruff ===\" && .venv/bin/ruff check apps 2>&1 | tail -20 && echo \"=== ruff format ===\" && .venv/bin/ruff format --check apps 2>&1 | tail -10 && echo \"=== migration check ===\" && .venv/bin/python manage.py makemigrations --check --dry-run 2>&1 | tail -10"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"sJDceHzfnO2Clk0W"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"=== ruff ===\napps/tracking/tests/test_api.py:224:101: E501 Line too long (108 > 100)\n |\n223 | def test_seeding_creates_the_placeholder_rows_for_an_environment(admin_client):\n224 | response = admin_client.post(f\"{ADMIN_TRACKING}configuratio\n\n...\n\nat: apps/tracking/tests/test_api.py\nWould reformat: apps/tracking/tests/test_forwarding.py\nWould reformat: apps/tracking/tests/test_services.py\n83 files would be reformatted, 289 files already formatted\n=== migration check ===\nNo changes detected\n"},"id":"XiiAMmJFrt5ZaW1T"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785512404538,"finishedAt":1785512405847,"lastPartSentAt":1785512405847,"taskNameActive":null,"id":"Ck1Tqmk9xngPhZeO","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":1,"thought":"Ruff is reporting a lot of pre-existing errors across the repo, but my installed version (0.8.4) might differ from what the project specifies, which could be causing spurious differences. I should check the pinned ruff version in the dev requirements to make sure I'm using the right one and then scope my checks to just my changes."}]}}],["p",{},["text",{},"Ruff flags 106 issues repo-wide, but I installed ruff myself — let me check the pinned version and scope to my files."]],["AssistantMessageContentPart",{"part":{"createdAt":1785512405956,"finishedAt":1785512407672,"lastPartSentAt":1785512407455,"taskNameActive":"Checking ruff config","taskNameComplete":"Checked ruff config","toolCallId":"toolu_011bGkg6QbNVSa9w5Vm3wNcv","agentTurnId":"turn_xyODKFKy4ffOvbhY","filePath":null,"id":"YsroMu4bAqC8odFT","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && cat requirements/dev.txt 2>/dev/null; echo \"=== ruff cfg ===\"; grep -n -A25 \"\\[tool.ruff\" pyproject.toml"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"NjeINo0v1OJFlfdG"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"-r base.txt\n\n# Local development & test tooling (TDD — see execution rules).\npytest==8.3.4\npytest-django==4.9.0\npytest-cov==6.0.0\nruff==0.8.4\nmypy==1.13.0\n=== ruff cfg ===\n31:[tool.ruff]\n32-line-length = 100\n33-target-version = \"py310\"\n34-extend-excl"},"id":"is01hAYoa6wNFQko"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"ude = [\n35- \"**/migrations/*\",\n36- \"staticfiles\",\n37-]\n38-\n39:[tool.ruff.lint]\n40-# Pragmatic, high-signal rule set\n\n...\n\nese modules use dynamic TextChoices\n103-# and class-configured DRF serializers that mypy cannot model without the plugin.\n"},"id":"ihUSiSUV22I6UVo5"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785512411802,"finishedAt":1785512412584,"lastPartSentAt":1785512412584,"taskNameActive":null,"id":"rOOL3faF7s511XeC","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":1,"thought":"Ruff version checks out at 0.8.4, and while the repo has 106 pre-existing lint errors I'm not responsible for, I notice formatting isn't enforced here since 83 files are unformatted. I should focus on linting just the files I modified."}]}}],["p",{},["text",{},"Ruff version matches the pin. The 106 errors and format diffs are pre-existing repo-wide — let me scope the gate to the files I actually touched."]],["AssistantMessageContentPart",{"part":{"createdAt":1785512413649,"finishedAt":1785512414758,"lastPartSentAt":1785512414613,"taskNameActive":"Linting my files","taskNameComplete":"Linted my files","toolCallId":"toolu_01GLvntzgju7x88H9t9a4zcs","agentTurnId":"turn_uzjrRp4rI3bUyHJv","filePath":null,"id":"PaCT4ovLf4qRFFsK","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && .venv/bin/ruff check apps/analytics 2>&1 | tail -30"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"gfeXQuboNq70UXgh"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"319 | @pytest.mark.django_db\n320 | def test_funnel_counts_distinct_sessions_per_stage(product, make_session, add_event):\n321 | session = make_session(started_at=dhaka(2026, 7, 20, 9), channel=\"organic\", device_type=\"mobile\")\n | "},"id":"X0GD12x4PddflVri"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":" ^ E501\n322 | add_event(session, \n\n...\n\n), order=order)\n |\n\nFound 5 errors.\nNo fixes available (1 hidden fix can be enabled with the `--unsafe-fixes` option).\n"},"id":"U1p8pD9oKKzcyy8j"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785512417706,"finishedAt":1785512417907,"lastPartSentAt":1785512417907,"taskNameActive":null,"id":"E1yEta4gJUGARksL","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":0,"thought":"I've got 5 E501 line length violations in my test file that I need to track down and fix."}]}}],["p",{},["text",{},"Five long lines in my test file. Let me see all of them."]],["AssistantMessageContentPart",{"part":{"createdAt":1785512418322,"finishedAt":1785512420917,"lastPartSentAt":1785512420747,"taskNameActive":"Listing long lines","taskNameComplete":"Listed long lines","toolCallId":"toolu_01WWYJsXcp65CSoc2agFM7P1","agentTurnId":"turn_ELAJQnAwVV47GN9C","filePath":null,"id":"PxqucttFnatsaIel","type":"task-subtask-v1","parts":[{"type":"subtask-started","data":{"subtaskType":"bash","command":"cd /vercel/share/v0-project/backend && .venv/bin/ruff check apps/analytics --output-format=concise 2>&1"}},{"type":"subtask-log","data":{"logType":"created-terminal"},"id":"wNcKMReKuz7KNWJw"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"apps/analytics/services.py:143:12: UP038 Use `X | Y` in `isinstance` call instead of `(X, Y)`\napps/analytics/tests/test_rollups.py:280:101: E501 Line too long (102 > 100)\napps/analytics/tests/test_rollups.py:321:101: E501 Line too long (101 > 100)\nap"},"id":"qSHXa5jSpbObZrZO"},{"type":"subtask-log","data":{"logType":"poll-terminal-output","delta":"ps/analytics/tests/test_rollups.py:323:101: E501 Line too long (103 > 100)\napps/analytics/tests/test_rollups.py:348:101: \n\n...\n\ne too long (105 > 100)\nFound 5 errors.\nNo fixes available (1 hidden fix can be enabled with the `--unsafe-fixes` option).\n"},"id":"4PkMXkydwPXhQeM5"}]}}],["AssistantMessageContentPart",{"part":{"createdAt":1785512425909,"finishedAt":1785512427436,"lastPartSentAt":1785512427436,"taskNameActive":null,"id":"priJYzZX8CwqPtlB","type":"task-thinking-v1","parts":[{"type":"thinking-end","duration":2,"thought":"I'm noticing an UP038 error in services.py that I didn't modify in this session, so it's likely pre-existing from the repo's 106 known issues. 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