Spaces:
Running
Running
File size: 8,601 Bytes
d999bba | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 | """Tests for shopstack.services.analytics (Phase 8 — analytics dashboard)."""
from __future__ import annotations
from dataclasses import dataclass
from datetime import datetime, timedelta
import pytest
from shopstack.services.analytics import (
HouseholdAnalytics,
aggregate_analytics,
render_analytics_html,
)
@dataclass
class FakeTrace:
action_type: str
created_at: datetime
user_id: str = "hh-1"
payload: dict | None = None
# ── aggregate_analytics basics ────────────────────────────────────
def test_aggregate_analytics_empty_input():
a = aggregate_analytics([])
assert a.purchase_count == 0
assert a.spend_this_month == 0.0
assert a.spend_this_year == 0.0
assert a.waste_rate_pct == 0.0
def test_aggregate_analytics_counts_purchases():
today = datetime(2026, 6, 13, 10, 0, 0)
traces = [
FakeTrace("add_purchase", today, payload={"total": 100}),
FakeTrace("add_purchase", today, payload={"total": 50}),
]
a = aggregate_analytics(traces, today=today)
assert a.purchase_count == 2
assert a.spend_this_month == 150.0
assert a.spend_this_year == 150.0
def test_aggregate_analytics_separates_month_year():
today = datetime(2026, 6, 13)
# Use 2026-01-15 (in 2026, this year) for the year-trace so it's counted
in_2026 = datetime(2026, 1, 15)
traces = [
FakeTrace("add_purchase", today, payload={"total": 200}),
FakeTrace("add_purchase", in_2026, payload={"total": 100}),
]
a = aggregate_analytics(traces, today=today)
assert a.spend_this_year == 300.0
assert a.spend_this_month == 200.0
def test_aggregate_analytics_excludes_previous_year():
today = datetime(2026, 6, 13)
last_year = datetime(2025, 12, 1)
traces = [
FakeTrace("add_purchase", today, payload={"total": 200}),
FakeTrace("add_purchase", last_year, payload={"total": 100}),
]
a = aggregate_analytics(traces, today=today)
# 2025-12 is not in "this year" (2026)
assert a.spend_this_year == 200.0
assert a.spend_this_month == 200.0
def test_aggregate_analytics_groups_by_store():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("add_purchase", today, payload={"total": 100, "store": "DMart"}),
FakeTrace("add_purchase", today, payload={"total": 200, "store": "Reliance"}),
]
a = aggregate_analytics(traces, today=today)
assert a.spend_by_store == {"Reliance": 200.0, "DMart": 100.0}
def test_aggregate_analytics_groups_by_category():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("add_purchase", today, payload={"total": 100, "category": "dairy"}),
FakeTrace("add_purchase", today, payload={"total": 50, "category": "snacks"}),
]
a = aggregate_analytics(traces, today=today)
assert a.spend_by_category == {"dairy": 100.0, "snacks": 50.0}
def test_aggregate_analytics_top_items():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("add_purchase", today, payload={"total": 100, "canonical_name": "milk"}),
FakeTrace("add_purchase", today, payload={"total": 200, "canonical_name": "bread"}),
FakeTrace("add_purchase", today, payload={"total": 50, "canonical_name": "egg"}),
]
a = aggregate_analytics(traces, today=today)
assert a.top_items[0] == ("bread", 200.0)
assert a.top_items[1] == ("milk", 100.0)
def test_aggregate_analytics_consume_count():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("consume_item", today),
FakeTrace("consume", today),
FakeTrace("add_purchase", today, payload={"total": 100}),
]
a = aggregate_analytics(traces, today=today)
assert a.consume_count == 2
assert a.purchase_count == 1
def test_aggregate_analytics_use_soon_count():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("use_soon", today),
FakeTrace("waste", today),
]
a = aggregate_analytics(traces, today=today)
assert a.use_soon_count == 2
def test_aggregate_analytics_waste_rate():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("consume", today),
FakeTrace("consume", today),
FakeTrace("use_soon", today),
]
a = aggregate_analytics(traces, today=today)
assert a.waste_rate_pct == 50.0 # 1 of 2 consumptions was use-soon
def test_aggregate_analytics_waste_rate_zero_consume():
a = aggregate_analytics([])
assert a.waste_rate_pct == 0.0
def test_aggregate_analytics_spend_trend_six_months():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("add_purchase", today, payload={"total": 100}),
]
a = aggregate_analytics(traces, today=today)
assert len(a.spend_trend) == 6
# The most recent month (2026-06) has 100
assert a.spend_trend[-1] == ("2026-06", 100.0)
def test_aggregate_analytics_top_merchants():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("add_purchase", today, payload={"total": 50, "store": "DMart"}),
FakeTrace("add_purchase", today, payload={"total": 50, "store": "DMart"}),
FakeTrace("add_purchase", today, payload={"total": 50, "store": "Reliance"}),
]
a = aggregate_analytics(traces, today=today)
assert a.top_merchants[0] == ("DMart", 2)
def test_aggregate_analytics_new_items_added():
today = datetime(2026, 6, 13)
traces = [
FakeTrace("add_inventory_item", today),
FakeTrace("add_inventory_item", today),
FakeTrace("add_purchase", today, payload={"total": 50}),
]
a = aggregate_analytics(traces, today=today)
assert a.new_items_added == 2
def test_aggregate_analytics_handles_dict_traces():
today = datetime(2026, 6, 13)
traces = [
{"action_type": "add_purchase", "created_at": today,
"payload": {"total": 100, "store": "DMart"}},
]
a = aggregate_analytics(traces, today=today)
assert a.purchase_count == 1
assert a.spend_this_month == 100.0
def test_aggregate_analytics_handles_string_timestamp():
today = datetime(2026, 6, 13)
traces = [
{"action_type": "add_purchase", "created_at": "2026-06-13T10:00:00",
"payload": {"total": 50}},
]
a = aggregate_analytics(traces, today=today)
assert a.spend_this_month == 50.0
def test_aggregate_analytics_respects_window():
today = datetime(2026, 6, 13)
old = today - timedelta(days=400)
traces = [
FakeTrace("add_purchase", today, payload={"total": 100}),
FakeTrace("add_purchase", old, payload={"total": 200}), # outside window
]
a = aggregate_analytics(traces, window_days=180, today=today)
# Only the in-window one counts
assert a.purchase_count == 1
assert a.spend_this_month == 100.0
# ── render_analytics_html ──────────────────────────────────────────
def test_render_analytics_html_empty():
a = HouseholdAnalytics()
html = render_analytics_html(a)
assert "No purchase history" in html
def test_render_analytics_html_basic():
a = HouseholdAnalytics(
spend_this_month=500.0,
spend_this_year=2500.0,
purchase_count=12,
new_items_added=5,
spend_trend=[("2026-01", 100), ("2026-02", 200), ("2026-03", 300)],
top_items=[("milk", 150.0), ("bread", 100.0)],
top_merchants=[("DMart", 8)],
)
html = render_analytics_html(a)
assert "ha-block" in html
assert "₹500" in html
assert "₹2,500" in html
assert "12" in html
assert "5" in html
assert "Monthly trend" in html
assert "Top items" in html
assert "Top merchants" in html
def test_render_analytics_html_waste_rate_badge():
a = HouseholdAnalytics(
spend_this_month=100.0,
purchase_count=2,
consume_count=10,
use_soon_count=3,
)
html = render_analytics_html(a)
assert "Waste rate" in html
# The renderer formats the rate with one decimal, so "30.0%"
assert "30.0%" in html # 3 / 10 = 30%
def test_render_analytics_html_escapes_xss():
a = HouseholdAnalytics(
spend_this_month=100.0,
purchase_count=1,
top_items=[("<script>alert(1)</script>", 50.0)],
)
html = render_analytics_html(a)
# The canonical name is title-cased; check for the escaped form
assert "<script>" in html.lower()
# The raw <script> tag must never appear unescaped
assert "<script>alert" not in html.lower()
|