cd1c99d5e0
Major parity push against the original SPA's bundle-level feature set (non-architectural items — separate Forecast / ProjectType / TimeLog views and AI Chat remain TBD). Backend (40/40 tests, +7): - merge.py splits booked hours by booking status: active vs soft. Active set: Active, Active Booked, Fully Booked, Partially Booked. Soft set: Soft Booking, Soft Booked, Soft-Booked. Unknown statuses default to active so they're not silently dropped. Existing `bookedHours` field is preserved as the sum for back-compat. - compute_totals(): rolls KPIs across the filtered summary — totalBooked, activeBooked, softBooked, totalLogged, totalBillable, totalLeave, totalProjects (distinct projectName/projectNumber), activePeople (distinct employees with logged>0), allocated, allocatedNetOfLeave. - breakdown_by_project(): drills into a single period+employee (or whole-period) and returns per-project logged + booked hours. - New /api/utilisation/breakdown endpoint. /api/utilisation/summary response gains `totals` and accepts `period=week|month`. - New schemas: UtilisationTotals, BreakdownResponse, plus activeBookedHours / softBookedHours on UtilisationSummaryRow. Frontend (typecheck/lint/build clean): - KpiTiles component shows Total Booked / Logged / Billable, Total projects, Active People (logged), Active bookings, Avg/person/week or /month, Allocated (net of leave), Period covered. - PeriodToggle (Per day / Per week / Per month). Day is rendered disabled with an explanatory tooltip — backend only accepts week/ month. - HourBreakdown drill-down panel: per-project logged + booked rows, shown when a chart bar is clicked; "Upload a time log to see logged breakdown" empty-state when no upload yet. - MonthlyUtilisation: ComposedChart with stacked Active/Soft booked bars + forecast Line overlay driven by the existing showForecast toggle. onPeriodClick wired into HourBreakdown. - WeeklyUtilisation, BookingVsActual: same Active/Soft stack treatment. - Resourcing now passes the timelog hash through to summary so loggedHours actually populates there too (was 0 before). - Sync Airtable button on both Department and Resourcing — force- refreshes bookings cache, re-derives summary. - Tutorial steps re-mapped to the original SPA's chapter titles: "Reading the Utilisation Chart", "Hours & Utilisation", "Drill-In", "Forecast Line & Filters", "Spotting Resource Issues", "Sync Airtable Bookings". Tutorial page heading is now "Interactive Walkthrough" with the original copy. - Defensive coercion in Bookings table totalHoursBooked rendering. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
316 lines
12 KiB
Python
316 lines
12 KiB
Python
"""Unit tests for services.merge.summarise."""
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from __future__ import annotations
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from datetime import date
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import pytest
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from app.services.merge import (
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breakdown_by_project,
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compute_totals,
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iter_periods,
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summarise,
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)
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def test_iter_periods_week():
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periods = iter_periods(date(2026, 5, 4), date(2026, 5, 17), "week")
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labels = [p.label for p in periods]
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# 2026-05-04 is Mon of ISO week 2026-W19; through 2026-05-17 covers W19 and W20.
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assert labels == ["2026-W19", "2026-W20"]
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def test_iter_periods_month():
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periods = iter_periods(date(2026, 5, 1), date(2026, 6, 30), "month")
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assert [p.label for p in periods] == ["2026-05", "2026-06"]
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def test_empty_inputs():
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rows = summarise([], [], [], from_=date(2026, 5, 4), to_=date(2026, 5, 8))
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assert rows == []
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def test_basic_utilisation(sample_resources, sample_bookings, sample_logged):
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# Bhakti: 40h/week avail, 35h logged (5 days × 7h), 38h booked (within W19).
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rows = summarise(
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sample_logged,
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sample_bookings,
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sample_resources,
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from_=date(2026, 5, 4),
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to_=date(2026, 5, 8),
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period="week",
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)
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bhakti = [r for r in rows if r["employee"] == "Bhakti Doshi" and r["period"] == "2026-W19"]
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assert len(bhakti) == 1
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b = bhakti[0]
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assert b["availableHours"] == 40.0
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assert b["loggedHours"] == 35.0
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assert b["bookedHours"] == 38.0
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assert b["billableHours"] == 28.0 # 4 of 5 days billable × 7
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assert b["nonBillableHours"] == 7.0
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assert b["actualUtilisationPct"] == 87.5
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assert b["bookedUtilisationPct"] == 95.0
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assert b["employmentType"] == "FTE"
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def test_booking_spans_two_weeks(sample_resources):
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"""A booking that straddles a week boundary must be split by working-day overlap."""
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# Booking: 2026-05-07 (Thu W19) .. 2026-05-12 (Tue W20). Total weekdays = 4 (Thu, Fri, Mon, Tue).
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# 50/50 split: 2 days in W19, 2 days in W20. totalHoursBooked = 40 → 20/20.
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bookings = [{
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"id": "bk-span",
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"task": "Spanning",
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"startDate": date(2026, 5, 7),
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"endDate": date(2026, 5, 12),
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"resourceName": "Bhakti Doshi",
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"projectNumber": "P-1",
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"projectName": "Span",
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"department": "Creative Team",
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"division": "Production",
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"hoursSelection": [],
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"totalHoursBooked": 40.0,
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"bookingStatus": "Active",
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"placeholder": False,
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}]
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rows = summarise(
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[],
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bookings,
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sample_resources,
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from_=date(2026, 5, 4),
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to_=date(2026, 5, 17),
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period="week",
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)
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by_period = {r["period"]: r for r in rows if r["employee"] == "Bhakti Doshi"}
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assert by_period["2026-W19"]["bookedHours"] == pytest.approx(20.0)
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assert by_period["2026-W20"]["bookedHours"] == pytest.approx(20.0)
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assert by_period["2026-W19"]["forecastHours"] == pytest.approx(20.0)
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def test_employment_type_grouping(sample_resources, sample_logged):
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rows = summarise(
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sample_logged,
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[],
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sample_resources,
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from_=date(2026, 5, 4),
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to_=date(2026, 5, 8),
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period="week",
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)
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by_emp = {r["employee"]: r for r in rows if r["period"] == "2026-W19"}
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assert by_emp["Bhakti Doshi"]["employmentType"] == "FTE"
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assert by_emp["Jamie Freelance"]["employmentType"] == "Freelancer"
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def test_partial_month_at_boundary(sample_resources):
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"""If the requested window starts mid-week, available hours should pro-rate."""
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# Window: 2026-05-06 (Wed) .. 2026-05-08 (Fri). 3 weekdays out of 5.
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# availHoursPerWeek = 40 → available = 40 * 3/5 = 24.
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rows = summarise(
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[],
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[],
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[sample_resources[0]],
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from_=date(2026, 5, 6),
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to_=date(2026, 5, 8),
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period="week",
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)
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bhakti = [r for r in rows if r["employee"] == "Bhakti Doshi"]
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assert len(bhakti) == 1
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assert bhakti[0]["availableHours"] == pytest.approx(24.0)
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def test_filters_department(sample_resources, sample_logged, sample_bookings):
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rows = summarise(
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sample_logged,
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sample_bookings,
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sample_resources,
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from_=date(2026, 5, 4),
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to_=date(2026, 5, 8),
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filters={"department": "Creative Team"},
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)
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assert all(r["department"] == "Creative Team" for r in rows)
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def test_filters_name(sample_resources):
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rows = summarise(
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[],
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[],
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sample_resources,
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from_=date(2026, 5, 4),
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to_=date(2026, 5, 8),
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filters={"name": "Bhakti"},
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)
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assert all("Bhakti" in r["employee"] for r in rows)
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def test_zero_available_no_division_error(sample_resources):
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# Drop avail to 0 → expect 0.0 percentages, not a crash.
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resources = [dict(sample_resources[0], availHoursPerWeek=0.0)]
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rows = summarise([], [], resources, from_=date(2026, 5, 4), to_=date(2026, 5, 8))
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assert rows[0]["availableHours"] == 0.0
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assert rows[0]["actualUtilisationPct"] == 0.0
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assert rows[0]["bookedUtilisationPct"] == 0.0
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def test_leave_hours_split_out_from_non_billable(sample_resources):
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"""A row tagged 'Leave Hours' should land in leaveHours, not
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nonBillableHours; billable client work stays in billableHours."""
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# 8h leave + 32h client-related, all inside W19.
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logged = [
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{"date": date(2026, 5, 4), "employee": "Bhakti Doshi", "project": "PTO",
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"task": "Annual leave", "hours": 8.0, "billable": False,
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"billingType": "leave hours"},
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{"date": date(2026, 5, 5), "employee": "Bhakti Doshi", "project": "Acme",
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"task": "Design", "hours": 8.0, "billable": True,
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"billingType": "client related"},
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{"date": date(2026, 5, 6), "employee": "Bhakti Doshi", "project": "Acme",
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"task": "Design", "hours": 8.0, "billable": True,
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"billingType": "client related"},
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{"date": date(2026, 5, 7), "employee": "Bhakti Doshi", "project": "Acme",
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"task": "Design", "hours": 8.0, "billable": True,
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"billingType": "client related"},
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{"date": date(2026, 5, 8), "employee": "Bhakti Doshi", "project": "Acme",
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"task": "Design", "hours": 8.0, "billable": True,
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"billingType": "client related"},
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]
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rows = summarise(
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logged,
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[],
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sample_resources,
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from_=date(2026, 5, 4),
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to_=date(2026, 5, 8),
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period="week",
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)
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bhakti = next(r for r in rows if r["employee"] == "Bhakti Doshi" and r["period"] == "2026-W19")
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assert bhakti["leaveHours"] == 8.0
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assert bhakti["billableHours"] == 32.0
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assert bhakti["nonBillableHours"] == 0.0
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assert bhakti["loggedHours"] == 40.0
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# ---------------------------------------------------------------------------
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# Active vs Soft split + totals
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# ---------------------------------------------------------------------------
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def test_active_vs_soft_split(sample_resources):
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"""Bookings tagged 'Soft Booking' must land in softBookedHours; others active."""
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bookings = [
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{
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"id": "bk-active", "task": "A", "startDate": date(2026, 5, 4),
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"endDate": date(2026, 5, 8), "resourceName": "Bhakti Doshi",
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"projectNumber": "P-A", "projectName": "Active proj",
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"department": "Creative Team", "division": "Production",
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"hoursSelection": [], "totalHoursBooked": 20.0,
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"bookingStatus": "Active", "placeholder": False,
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},
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{
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"id": "bk-soft", "task": "S", "startDate": date(2026, 5, 4),
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"endDate": date(2026, 5, 8), "resourceName": "Bhakti Doshi",
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"projectNumber": "P-S", "projectName": "Soft proj",
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"department": "Creative Team", "division": "Production",
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"hoursSelection": [], "totalHoursBooked": 12.0,
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"bookingStatus": "Soft Booking", "placeholder": False,
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},
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]
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rows = summarise(
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[], bookings, sample_resources,
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from_=date(2026, 5, 4), to_=date(2026, 5, 8), period="week",
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)
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bhakti = next(r for r in rows if r["employee"] == "Bhakti Doshi" and r["period"] == "2026-W19")
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assert bhakti["activeBookedHours"] == pytest.approx(20.0)
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assert bhakti["softBookedHours"] == pytest.approx(12.0)
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assert bhakti["bookedHours"] == pytest.approx(32.0)
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def test_unknown_status_defaults_to_active(sample_resources):
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"""Null/unknown statuses fall through to active (not silently dropped)."""
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bookings = [
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{
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"id": "bk-null", "task": "N", "startDate": date(2026, 5, 4),
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"endDate": date(2026, 5, 8), "resourceName": "Bhakti Doshi",
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"projectNumber": "P-N", "projectName": "Null proj",
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"department": "Creative Team", "division": "Production",
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"hoursSelection": [], "totalHoursBooked": 15.0,
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"bookingStatus": None, "placeholder": False,
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},
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{
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"id": "bk-junk", "task": "J", "startDate": date(2026, 5, 4),
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"endDate": date(2026, 5, 8), "resourceName": "Bhakti Doshi",
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"projectNumber": "P-J", "projectName": "Junk status proj",
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"department": "Creative Team", "division": "Production",
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"hoursSelection": [], "totalHoursBooked": 5.0,
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"bookingStatus": "Pencilled In Tentatively", "placeholder": False,
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},
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]
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rows = summarise(
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[], bookings, sample_resources,
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from_=date(2026, 5, 4), to_=date(2026, 5, 8), period="week",
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)
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bhakti = next(r for r in rows if r["employee"] == "Bhakti Doshi" and r["period"] == "2026-W19")
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assert bhakti["activeBookedHours"] == pytest.approx(20.0)
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assert bhakti["softBookedHours"] == 0.0
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assert bhakti["bookedHours"] == pytest.approx(20.0)
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def test_compute_totals(sample_resources, sample_bookings, sample_logged):
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rows = summarise(
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sample_logged, sample_bookings, sample_resources,
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from_=date(2026, 5, 4), to_=date(2026, 5, 8), period="week",
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)
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totals = compute_totals(
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rows, sample_bookings,
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from_=date(2026, 5, 4), to_=date(2026, 5, 8),
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)
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assert totals["totalBooked"] == pytest.approx(38.0)
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assert totals["activeBooked"] == pytest.approx(38.0)
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assert totals["softBooked"] == 0.0
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assert totals["totalLogged"] == pytest.approx(35.0)
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assert totals["totalBillable"] == pytest.approx(28.0)
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assert totals["totalProjects"] == 1 # one distinct projectName
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assert totals["activePeople"] == 1 # only Bhakti has loggedHours > 0
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assert totals["activeBookingsCount"] == 1
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assert totals["periodFrom"] == "2026-05-04"
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assert totals["periodTo"] == "2026-05-08"
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# allocated net of leave: avail (40 + 40 for two FTEs in W19) - 0 leave = 80
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assert totals["allocatedNetOfLeave"] == pytest.approx(80.0)
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def test_breakdown_by_project_logged_and_booked(sample_resources, sample_bookings, sample_logged):
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out = breakdown_by_project(
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sample_logged, sample_bookings,
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period="2026-W19", employee="Bhakti Doshi",
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)
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assert out["period"] == "2026-W19"
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assert out["employee"] == "Bhakti Doshi"
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assert out["hasLogged"] is True
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# Logged side: Acme (28h billable across 4 days) + Internal (7h non-billable)
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logged_by_project = {row["project"]: row for row in out["logged"]}
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assert logged_by_project["Acme"]["hours"] == pytest.approx(28.0)
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assert logged_by_project["Acme"]["billable"] == pytest.approx(28.0)
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assert logged_by_project["Internal"]["hours"] == pytest.approx(7.0)
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assert logged_by_project["Internal"]["nonBillable"] == pytest.approx(7.0)
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# Booked side: one booking on Acme Spring Launch = 38h, all active
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booked_by_project = {row["project"]: row for row in out["booked"]}
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assert booked_by_project["Acme Spring Launch"]["hours"] == pytest.approx(38.0)
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assert booked_by_project["Acme Spring Launch"]["active"] == pytest.approx(38.0)
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def test_breakdown_no_timelog(sample_resources, sample_bookings):
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"""Empty timelog input: hasLogged should be False so the UI can prompt."""
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out = breakdown_by_project([], sample_bookings, period="2026-W19", employee="Bhakti Doshi")
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assert out["hasLogged"] is False
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assert out["logged"] == []
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# Booked side still works
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assert any(row["project"] == "Acme Spring Launch" for row in out["booked"])
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def test_breakdown_month_period(sample_resources, sample_bookings):
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"""Month-level period label resolves to that month's day-range."""
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out = breakdown_by_project([], sample_bookings, period="2026-05")
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# The single sample booking falls inside May 2026.
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assert any(row["project"] == "Acme Spring Launch" for row in out["booked"])
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def test_breakdown_invalid_period_returns_empty(sample_bookings):
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out = breakdown_by_project([], sample_bookings, period="not-a-period")
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assert out["logged"] == [] and out["booked"] == []
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