bugfixing
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7c18bb971e
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@ -35,7 +35,7 @@ async def download_data(ticker, start_date, end_date):
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df = df.rename(columns={"Date": "ds", "Adj Close": "y"})
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df = df.rename(columns={"Date": "ds", "Adj Close": "y"})
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if len(df) > 252*2: #At least 2 years of history is necessary
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if len(df) > 252*2: #At least 2 years of history is necessary
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q_high= df["y"].quantile(0.99)
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q_high= df["y"].quantile(0.99)
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q_low = df["y"].quantile(0.05)
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q_low = df["y"].quantile(0.01)
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df = df[(df["y"] > q_low)]
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df = df[(df["y"] > q_low)]
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df = df[(df["y"] < q_high)]
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df = df[(df["y"] < q_high)]
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#df['y'] = df['y'].rolling(window=10).mean()
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#df['y'] = df['y'].rolling(window=10).mean()
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@ -65,12 +65,12 @@ async def run():
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total_symbols = stock_symbols
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total_symbols = stock_symbols
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print(f"Total tickers: {len(total_symbols)}")
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print(f"Total tickers: {len(total_symbols)}")
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start_date = datetime(2020, 1, 1).strftime("%Y-%m-%d")
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start_date = datetime(2017, 1, 1).strftime("%Y-%m-%d")
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end_date = datetime.today().strftime("%Y-%m-%d")
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end_date = datetime.today().strftime("%Y-%m-%d")
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chunk_size = len(total_symbols) // 70 # Divide the list into N chunks
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chunk_size = len(total_symbols) // 70 # Divide the list into N chunks
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chunks = [total_symbols[i:i + chunk_size] for i in range(0, len(total_symbols), chunk_size)]
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chunks = [total_symbols[i:i + chunk_size] for i in range(0, len(total_symbols), chunk_size)]
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#chunks = [['TSLA']]
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#chunks = [['NVDA','GME','TSLA','AAPL']]
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for chunk in chunks:
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for chunk in chunks:
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tasks = []
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tasks = []
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for ticker in tqdm(chunk):
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for ticker in tqdm(chunk):
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