feat: Implement initial PolyWeather application with interactive map UI, backend API, and Polymarket data client.

2026-03-06 09:38:28 +08:00
parent b308709edb
commit d9876256b3
18 changed files with 755 additions and 1097 deletions
@@ -0,0 +1,90 @@
+from src.data_collection import polymarket_client as pm
+
+
+def test_extract_best_prices():
+    book = {
+        "bids": [{"price": "0.41", "size": "100"}, {"price": "0.39", "size": "80"}],
+        "asks": [{"price": "0.45", "size": "90"}, {"price": "0.47", "size": "70"}],
+        "last_trade_price": "0.44",
+    }
+    out = pm._extract_best_prices(book)
+    assert out["best_bid"] == 0.41
+    assert out["best_ask"] == 0.45
+    assert out["spread"] == 0.04
+    assert out["last_trade_price"] == 0.44
+
+
+def test_build_city_market_snapshot_buy_sell_and_alerts(monkeypatch):
+    pm._prev_snapshots.clear()
+
+    markets = [
+        {
+            "id": "m1",
+            "question": "Highest temperature in Ankara on March 7?",
+            "city": "ankara",
+            "date": "2026-03-07",
+            "slug": "m1",
+            "url": "https://polymarket.com/event/m1",
+            "volume": 1000.0,
+            "liquidity": 500.0,
+            "outcomes": [
+                {"name": "6-7°C", "token_id": "t1", "last_price": 0.32},
+                {"name": "8-9°C", "token_id": "t2", "last_price": 0.40},
+            ],
+        }
+    ]
+
+    books = {
+        "t1": {
+            "bids": [{"price": "0.30", "size": "50"}],
+            "asks": [{"price": "0.36", "size": "55"}],
+            "last_trade_price": "0.34",
+            "timestamp": "2026-03-06T10:00:00Z",
+        },
+        # one-sided book + thin liquidity to trigger anomaly
+        "t2": {
+            "bids": [],
+            "asks": [{"price": "0.52", "size": "10"}],
+            "last_trade_price": "0.51",
+            "timestamp": "2026-03-06T10:00:00Z",
+        },
+    }
+
+    def fake_get_city_markets(**kwargs):
+        return markets
+
+    def fake_fetch_order_books(*args, **kwargs):
+        return books
+
+    monkeypatch.setattr(pm, "get_city_markets", fake_get_city_markets)
+    monkeypatch.setattr(pm, "fetch_order_books", fake_fetch_order_books)
+
+    # Seed previous snapshot for token t1, so we can detect a price jump alert
+    pm._prev_snapshots["t1"] = {
+        "ts": 1.0,
+        "best_bid": 0.20,
+        "best_ask": 0.24,
+        "spread": 0.04,
+        "last_trade_price": 0.22,
+    }
+
+    snap = pm.build_city_market_snapshot(city="ankara", target_date="2026-03-07")
+
+    assert snap["city"] == "ankara"
+    assert snap["target_date"] == "2026-03-07"
+    assert snap["summary"]["market_count"] == 1
+    assert snap["summary"]["outcome_count"] == 2
+
+    first_market = snap["markets"][0]
+    row_t1 = next(x for x in first_market["outcomes"] if x["token_id"] == "t1")
+    row_t2 = next(x for x in first_market["outcomes"] if x["token_id"] == "t2")
+
+    # Buy uses ask, sell uses bid
+    assert row_t1["buy_price"] == 0.36
+    assert row_t1["sell_price"] == 0.30
+    assert round(row_t1["spread"], 2) == 0.06
+
+    # one-sided orderbook has no sell price
+    assert row_t2["buy_price"] == 0.52
+    assert row_t2["sell_price"] is None
+    assert "one_sided_orderbook" in row_t2["anomaly_flags"]