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Optional numeric return head (predicts percent change for 1s,1m,1h,1d)

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Dobromir Popov
2025-08-23 15:17:04 +03:00
parent 9992b226ea
commit 81749ee18e
8 changed files with 124 additions and 30 deletions
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11
core/data_provider.py
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@@ -1268,15 +1268,12 @@ class DataProvider:
logger.debug(f"No valid candles generated for {symbol}")
return None
# Convert to DataFrame (timestamps remain UTC tz-aware)
# Convert to DataFrame and normalize timestamps to UTC tz-aware
df = pd.DataFrame(candles)
# Ensure timestamps are timezone-aware (UTC to match COB WebSocket data)
if not df.empty and 'timestamp' in df.columns:
# Normalize to UTC tz-aware using pandas idioms
if df['timestamp'].dt.tz is None:
df['timestamp'] = pd.to_datetime(df['timestamp'], utc=True)
else:
df['timestamp'] = df['timestamp'].dt.tz_convert('UTC')
# Coerce to datetime with UTC; avoid .dt on non-datetimelike
df['timestamp'] = pd.to_datetime(df['timestamp'], utc=True, errors='coerce')
df = df.dropna(subset=['timestamp'])
df = df.sort_values('timestamp').reset_index(drop=True)