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feat: implement Polymarket data collection and dashboard UI for weather market analysis

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This commit is contained in:
2569718930@qq.com
2026-04-25 03:59:02 +08:00
parent 0e5a1f2652
commit 77c0597e74
5 changed files with 323 additions and 103 deletions
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src/data_collection/polymarket_readonly.py
+35 -6
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@@ -2153,7 +2153,8 @@ class PolymarketReadOnlyLayer:
question = str(market.get("question") or market.get("title") or "").strip()
direction = self._extract_market_bucket_direction(market)
bucket_range = self._extract_market_bucket_range(market)
unit = bucket_range[2] if bucket_range else "C"
raw_unit = bucket_range[2] if bucket_range else "C"
unit = "°F" if str(raw_unit).upper().endswith("F") else "°C"
if bucket_range and bucket_range[1] is not None:
return f"{bucket_range[0]:g}-{bucket_range[1]:g}{unit}"
if bucket_temp is not None:
@@ -2520,6 +2521,18 @@ class PolymarketReadOnlyLayer:
peak = context.get("peak") if isinstance(context.get("peak"), dict) else {}
first_h = int(_safe_float(peak.get("first_h")) or 13)
last_h = int(_safe_float(peak.get("last_h")) or 15)
first_minutes = max(0, first_h * 60)
last_minutes = min(23 * 60 + 59, last_h * 60)
display_last_minutes = min(23 * 60 + 59, last_h * 60 + 59)
peak_fields: Dict[str, Any] = {
"peak_window_start": f"{first_h:02d}:00",
"peak_window_end": f"{last_h:02d}:59",
"peak_window_label": f"{first_h:02d}:00-{last_h:02d}:59",
"minutes_until_peak_start": None,
"minutes_until_peak_end": None,
"peak_start_minutes": first_minutes,
"peak_end_minutes": display_last_minutes,
}
target_iso = _extract_iso_date(target_date)
if not local_date or not target_iso:
return {
@@ -2527,6 +2540,7 @@ class PolymarketReadOnlyLayer:
"score": 0.65,
"remaining_minutes": None,
"same_day": True,
**peak_fields,
}
try:
@@ -2537,19 +2551,26 @@ class PolymarketReadOnlyLayer:
except Exception:
diff_days = 0
now_minutes = _parse_hhmm_to_minutes(local_time)
if now_minutes is not None:
peak_fields["minutes_until_peak_start"] = diff_days * 1440 + first_minutes - now_minutes
peak_fields["minutes_until_peak_end"] = diff_days * 1440 + display_last_minutes - now_minutes
if diff_days >= 2:
return {
"phase": "week_ahead",
"score": 0.45,
"remaining_minutes": None,
"remaining_minutes": peak_fields["minutes_until_peak_start"],
"same_day": False,
**peak_fields,
}
if diff_days == 1:
return {
"phase": "tomorrow",
"score": 0.60,
"remaining_minutes": None,
"remaining_minutes": peak_fields["minutes_until_peak_start"],
"same_day": False,
**peak_fields,
}
if diff_days < 0:
return {
@@ -2557,25 +2578,25 @@ class PolymarketReadOnlyLayer:
"score": 0.0,
"remaining_minutes": None,
"same_day": False,
**peak_fields,
}
now_minutes = _parse_hhmm_to_minutes(local_time)
if now_minutes is None:
return {
"phase": "today_default",
"score": 0.65,
"remaining_minutes": None,
"same_day": True,
**peak_fields,
}
first_minutes = max(0, first_h * 60)
last_minutes = min(23 * 60 + 59, last_h * 60)
if now_minutes > last_minutes + 120:
return {
"phase": "post_peak",
"score": 0.50,
"remaining_minutes": 0,
"same_day": True,
**peak_fields,
}
if first_minutes <= now_minutes <= last_minutes + 120:
return {
@@ -2583,6 +2604,7 @@ class PolymarketReadOnlyLayer:
"score": 1.00,
"remaining_minutes": max(0, last_minutes + 120 - now_minutes),
"same_day": True,
**peak_fields,
}
if first_minutes - 180 <= now_minutes < first_minutes:
return {
@@ -2590,12 +2612,14 @@ class PolymarketReadOnlyLayer:
"score": 0.85,
"remaining_minutes": max(0, last_minutes + 120 - now_minutes),
"same_day": True,
**peak_fields,
}
return {
"phase": "early_today",
"score": 0.70,
"remaining_minutes": max(0, first_minutes - now_minutes),
"same_day": True,
**peak_fields,
}
def _resolve_market_target_threshold(
@@ -3198,6 +3222,11 @@ class PolymarketReadOnlyLayer:
"window_phase": window_meta.get("phase"),
"window_score": window_meta.get("score"),
"remaining_window_minutes": window_meta.get("remaining_minutes"),
"peak_window_start": window_meta.get("peak_window_start"),
"peak_window_end": window_meta.get("peak_window_end"),
"peak_window_label": window_meta.get("peak_window_label"),
"minutes_until_peak_start": window_meta.get("minutes_until_peak_start"),
"minutes_until_peak_end": window_meta.get("minutes_until_peak_end"),
"liquidity_score": liquidity_score,
"price_usefulness_score": price_usefulness_score,
"spread_penalty": spread_penalty,