233 lines
9.8 KiB
Python
233 lines
9.8 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Feature: spi-spending-power-index — SPI 消费力指数属性测试
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使用 hypothesis 验证 SPI 算法的正确性属性：
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- Property 1: SPI 总分非负性
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- Property 2: Level 子分关于消费金额单调非递减
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- Property 3: Speed 子分关于 spend_30 单调非递减
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- Property 4: Stability 子分取值范围 [0, 1]
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- Property 5: Display Score 取值范围 [0, 10]
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测试策略：
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- 子分计算为 @staticmethod 纯函数，不依赖数据库，直接调用
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- batch_normalize_to_display 为实例方法，通过 MagicMock 构造最小实例
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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from unittest.mock import MagicMock
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from hypothesis import given, settings, assume
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import hypothesis.strategies as st
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# ── 将 ETL 模块加入 sys.path ──
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_ETL_ROOT = (
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Path(__file__).resolve().parent.parent
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/ "apps" / "etl" / "connectors" / "feiqiu"
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)
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if str(_ETL_ROOT) not in sys.path:
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sys.path.insert(0, str(_ETL_ROOT))
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from tasks.dws.index.spending_power_index_task import (
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SpendingPowerIndexTask,
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SPIMemberFeatures,
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)
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from tasks.dws.index.base_index_task import BaseIndexTask
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# ══════════════════════════════════════════════════════════════════
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# 辅助：构造最小可用的 SpendingPowerIndexTask 实例（仅用于 Property 5）
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# ══════════════════════════════════════════════════════════════════
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def _make_spi_task() -> SpendingPowerIndexTask:
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"""构造不依赖真实 DB/API 的 SPI 任务实例，仅用于调用 batch_normalize_to_display。"""
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config = MagicMock()
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# BaseTask.__init__ 会调用 config.get("app.timezone", "Asia/Shanghai")
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# MagicMock.get() 默认返回 Mock 对象，导致 ZoneInfo 报错，需要正确返回字符串
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config.get = lambda key, default=None: {
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"app.timezone": "Asia/Shanghai",
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}.get(key, default)
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db = MagicMock()
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api = MagicMock()
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logger = MagicMock()
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return SpendingPowerIndexTask(config, db, api, logger)
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# ══════════════════════════════════════════════════════════════════
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# Property 1: SPI 总分非负性
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# ══════════════════════════════════════════════════════════════════
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@given(
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level=st.floats(min_value=0, max_value=100),
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speed=st.floats(min_value=0, max_value=100),
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stability=st.floats(min_value=0, max_value=1),
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)
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@settings(max_examples=200)
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def test_spi_raw_non_negative(level, speed, stability):
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"""Property 1: SPI 总分非负性
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对于任意非负的 Level、Speed、Stability 子分，
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compute_spi_raw 的返回值应为非负。
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**Validates: Requirements 6.1, 10.1**
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"""
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params = SpendingPowerIndexTask.DEFAULT_PARAMS
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result = SpendingPowerIndexTask.compute_spi_raw(level, speed, stability, params)
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assert result >= 0, f"SPI_raw={result} < 0 (L={level}, S={speed}, P={stability})"
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# ══════════════════════════════════════════════════════════════════
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# Property 2: Level 子分关于消费金额单调非递减
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# ══════════════════════════════════════════════════════════════════
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@given(
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spend_30=st.floats(min_value=0, max_value=50000),
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spend_90=st.floats(min_value=0, max_value=150000),
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recharge_90=st.floats(min_value=0, max_value=100000),
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avg_ticket_90=st.floats(min_value=0, max_value=5000),
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delta=st.floats(min_value=0.01, max_value=10000),
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)
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@settings(max_examples=200)
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def test_level_monotonic_on_spend(spend_30, spend_90, recharge_90, avg_ticket_90, delta):
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"""Property 2: Level 子分关于消费金额单调非递减
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在其他条件不变时，增加 spend_30 或 spend_90 不会导致 Level 子分下降。
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**Validates: Requirements 3.1, 10.2**
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"""
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params = SpendingPowerIndexTask.DEFAULT_PARAMS
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base = SPIMemberFeatures(
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member_id=1, site_id=1,
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spend_30=spend_30, spend_90=spend_90,
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recharge_90=recharge_90, avg_ticket_90=avg_ticket_90,
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)
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level_before = SpendingPowerIndexTask.compute_level(base, params)
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# 增加 spend_30
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inc_30 = SPIMemberFeatures(
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member_id=1, site_id=1,
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spend_30=spend_30 + delta, spend_90=spend_90,
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recharge_90=recharge_90, avg_ticket_90=avg_ticket_90,
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)
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level_after_30 = SpendingPowerIndexTask.compute_level(inc_30, params)
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assert level_after_30 >= level_before, (
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f"Level 下降: spend_30 增加 {delta} 后 {level_after_30} < {level_before}"
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)
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# 增加 spend_90
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inc_90 = SPIMemberFeatures(
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member_id=1, site_id=1,
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spend_30=spend_30, spend_90=spend_90 + delta,
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recharge_90=recharge_90, avg_ticket_90=avg_ticket_90,
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)
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level_after_90 = SpendingPowerIndexTask.compute_level(inc_90, params)
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assert level_after_90 >= level_before, (
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f"Level 下降: spend_90 增加 {delta} 后 {level_after_90} < {level_before}"
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)
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# ══════════════════════════════════════════════════════════════════
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# Property 3: Speed 子分关于 spend_30 单调非递减
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# ══════════════════════════════════════════════════════════════════
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@given(
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spend_30=st.floats(min_value=0, max_value=50000),
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spend_90=st.floats(min_value=0, max_value=150000),
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visit_days_30=st.integers(min_value=0, max_value=30),
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daily_spend_ewma_90=st.floats(min_value=0, max_value=10000),
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delta=st.floats(min_value=0.01, max_value=10000),
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)
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@settings(max_examples=200)
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def test_speed_monotonic_on_spend_30(spend_30, spend_90, visit_days_30, daily_spend_ewma_90, delta):
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"""Property 3: Speed 子分关于 spend_30 单调非递减
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在其他条件不变时，增加 spend_30 不会导致 Speed 子分下降。
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**Validates: Requirements 4.1, 4.4, 10.3**
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"""
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params = SpendingPowerIndexTask.DEFAULT_PARAMS
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base = SPIMemberFeatures(
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member_id=1, site_id=1,
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spend_30=spend_30, spend_90=spend_90,
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visit_days_30=visit_days_30,
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daily_spend_ewma_90=daily_spend_ewma_90,
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)
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speed_before = SpendingPowerIndexTask.compute_speed(base, params)
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inc = SPIMemberFeatures(
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member_id=1, site_id=1,
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spend_30=spend_30 + delta, spend_90=spend_90,
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visit_days_30=visit_days_30,
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daily_spend_ewma_90=daily_spend_ewma_90,
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)
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speed_after = SpendingPowerIndexTask.compute_speed(inc, params)
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assert speed_after >= speed_before, (
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f"Speed 下降: spend_30 增加 {delta} 后 {speed_after} < {speed_before}"
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)
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# ══════════════════════════════════════════════════════════════════
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# Property 4: Stability 子分取值范围 [0, 1]
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# ══════════════════════════════════════════════════════════════════
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@given(active_weeks=st.integers(min_value=0, max_value=13))
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@settings(max_examples=200)
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def test_stability_in_range(active_weeks):
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"""Property 4: Stability 子分取值范围 [0, 1]
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对于任意 active_weeks_90 ∈ [0, 13]，compute_stability 返回值应在 [0, 1]。
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**Validates: Requirements 5.2, 5.4, 10.4**
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"""
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params = SpendingPowerIndexTask.DEFAULT_PARAMS
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features = SPIMemberFeatures(
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member_id=1, site_id=1,
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active_weeks_90=active_weeks,
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)
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stability = SpendingPowerIndexTask.compute_stability(features, params)
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assert 0 <= stability <= 1, (
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f"Stability={stability} 超出 [0, 1] (active_weeks_90={active_weeks})"
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)
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# ══════════════════════════════════════════════════════════════════
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# Property 5: Display Score 取值范围 [0, 10]
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# ══════════════════════════════════════════════════════════════════
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@given(
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raw_scores=st.lists(
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st.floats(min_value=0, max_value=1000),
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min_size=1,
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max_size=50,
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),
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)
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@settings(max_examples=200)
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def test_display_score_in_range(raw_scores):
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"""Property 5: Display Score 取值范围 [0, 10]
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对于任意非空的非负 raw_score 列表，batch_normalize_to_display
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映射后的 display_score 应在 [0.00, 10.00]。
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**Validates: Requirements 6.6, 10.5**
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"""
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task = _make_spi_task()
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# 构造 (entity_id, raw_score) 输入
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input_scores = [(i, s) for i, s in enumerate(raw_scores)]
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results = task.batch_normalize_to_display(
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raw_scores=input_scores,
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compression=None, # 无压缩，直接 MinMax
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use_smoothing=False, # 不使用 EWMA 平滑（避免 DB 调用）
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)
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for entity_id, raw_score, display_score in results:
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assert 0.0 <= display_score <= 10.0, (
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f"display_score={display_score} 超出 [0, 10] (raw={raw_score})"
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)
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