9739849f68
- dashboard.py: RealDashboard assembles real Thai data (tourism + auto+NPL + energy TOP + macro BOT) with uniform z-score surprise per theme, per-theme thesis, sources provenance table, 49-symbol combined board - macro_thai.py: BOT Thai Economy macro backdrop (consumption +4.9%, inflation 1.95%, unemployment 0.93%, tourists 16.2mn) - GET /api/v1/dashboard endpoint (real data, no fixture fallback per user) - 7 new tests; full suite 195 OK; live verified (3 theme surprise: 0.571/0.81/1.623)
68 lines
2.6 KiB
Python
68 lines
2.6 KiB
Python
"""Tests for the real multi-theme dashboard assembly."""
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from __future__ import annotations
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import unittest
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from unittest.mock import patch
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from app.dashboard import RealDashboard, _auto_read, _zscore
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class _FakeCache:
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"""Minimal cache that invokes the fetcher each call."""
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def __init__(self, data: dict):
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self.data = data
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def fetch_or_stale(self, key, fetcher):
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val = self.data.get(key)
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if val is not None:
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return val
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return fetcher()
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class DashboardTest(unittest.TestCase):
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def test_zscore_centers(self):
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self.assertAlmostEqual(_zscore(1.0, 1.0, 1.0), 0.0)
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self.assertAlmostEqual(_zscore(2.0, 1.0, 1.0), 1.0)
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def test_auto_read_multisource(self):
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auto = {"new_car_sales_yoy": 20.07, "total_vehicle_sales": 59000,
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"vehicle_production": 120000, "auto_exports": 80000}
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npl = {"pct_of_npls": 3.95, "npl_amount": 20602}
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read = _auto_read(auto, npl, _FakeCache({}))
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self.assertEqual(read["new_car_sales_yoy"], 20.07)
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self.assertEqual(read["auto_npl_pct"], 3.95)
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self.assertIn("thesis", read)
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@patch("app.auto_credit.fetch_auto_credit")
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@patch("app.auto_npl.fetch_auto_npl")
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@patch("app.energy_thai.fetch_energy_thai")
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@patch("app.macro_thai.fetch_macro_thai")
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def test_build_returns_structure(self, macro, energy, npl, auto):
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class _Factory:
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def __init__(self, data): self._data = data
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def to_dict(self): return self._data
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macro.return_value = _Factory({
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"private_consumption_yoy": 4.9, "headline_inflation_yoy": 1.95, "periods": {}})
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energy.return_value = _Factory({
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"quarterly": {"Q2/2026": {"net_profit": 8000.0, "ebitda": 9000.0}}})
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auto.return_value = _Factory({
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"new_car_sales_yoy": 20.07, "total_vehicle_sales": 59000})
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npl.return_value = _Factory({
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"pct_of_npls": 3.95, "npl_amount": 20602, "period": "Q2/2568"})
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cache = _FakeCache({})
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dash = RealDashboard([], cache).build()
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self.assertEqual(len(dash["themes"]), 3)
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self.assertEqual(len(dash["sources"]), 5)
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self.assertIn("macro", dash)
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self.assertIn("board", dash)
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def test_auto_read_npl_piece(self):
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read = _auto_read({"new_car_sales_yoy": -3.0, "total_vehicle_sales": 20000},
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{"pct_of_npls": 6.0, "npl_amount": 90000}, _FakeCache({}))
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self.assertEqual(read["new_car_sales_yoy"], -3.0)
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self.assertEqual(read["auto_npl_pct"], 6.0)
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if __name__ == "__main__":
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unittest.main()
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