Initial commit of IQFeed API client

iqfeed/iqfeed.py

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+import pandas as pd
+import socket
+
+from datetime import datetime
+from io import StringIO
+
+def read_data_from_socket(sock, recv_buffer=4096):
+    buffer = b''
+    data = b''
+    while True:
+        data = sock.recv(recv_buffer)
+        buffer += data
+
+        if b'!ENDMSG!' in buffer:
+            break
+
+    # Remove the ENDMSG string
+    buffer = buffer[:-12]
+    return buffer.decode('utf-8')
+
+def _get_daily_data(symbol: str, max_days: int) -> pd.DataFrame:
+    host = '127.0.0.1'
+    port = 9100  # Historical data socket port
+    
+    message = 'HDX,{symbol},{max_days},1\n'.format(
+        symbol=symbol,
+        max_days=max_days
+    )
+
+    sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+    sock.connect((host, port))
+
+    sock.sendall(message.encode('utf-8'))
+    data = read_data_from_socket(sock)
+    sock.close()
+
+    # Remove extraneous line endings
+    data = ''.join(data.split('\r'))
+    data = data.replace(',\n','\n')[:-1]
+
+    data = StringIO(data)
+    return pd.read_csv(data, index_col=False, 
+        names=['Date', 'High', 'Low', 'Open', 'Close', 'Total Volume', 'Period Volume'])
+
+def get_daily_data(symbol: str, start_date: datetime, end_date: datetime) -> pd.DataFrame:
+    max_days = (datetime.today() - start_date).days
+    data = _get_daily_data(symbol, max_days)
+
+    # Filter data between start_date and end_date
+    data['Date'] = pd.to_datetime(data['Date'])
+    data['Date'] = data['Date'].dt.date
+    data = data[(data['Date'] >= start_date.date()) & (data['Date'] <= end_date.date())]
+    data = data.reset_index(drop=True)
+    return data
+
+def seconds(value):
+    return value
+
+def minutes(value):
+    return value * 60
+
+def hours(value):
+    return value * 3600
+
+def get_historical_data(symbol: str, interval: int, 
+        start_date: datetime, end_date: datetime = None, 
+        start_filter_time: datetime = datetime.strptime('093000', '%H%M%S').time(), 
+        end_filter_time: datetime = datetime.strptime('160000', '%H%M%S').time()) -> pd.DataFrame:
+    host = '127.0.0.1'
+    port = 9100  # Historical data socket port
+    
+    message = 'HIT,{symbol},{interval},{begin},{end},,{begin_filter},{end_filter},1\n'.format(
+        symbol=symbol,
+        interval=interval,
+        begin=start_date.strftime('%Y%m%d %H%M%S'),
+        end=end_date.strftime('%Y%m%d %H%M%S') if end_date else '',
+        begin_filter=start_filter_time.strftime('%H%M%S') if start_filter_time else '',
+        end_filter=end_filter_time.strftime('%H%M%S') if end_filter_time else ''
+    )
+
+    sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+    sock.connect((host, port))
+
+    sock.sendall(message.encode('utf-8'))
+    data = read_data_from_socket(sock)
+    sock.close()
+
+    # Remove extraneous line endings
+    data = ''.join(data.split('\r'))
+    data = data.replace(',\n','\n')[:-1]
+
+    data = StringIO(data)
+    return pd.read_csv(data, index_col=False, 
+        names=['Date', 'High', 'Low', 'Open', 'Close', 'Total Volume', 'Period Volume'])
+
+if __name__ == '__main__':
+    symbols = ['SPY']
+    start_date = datetime(2023, 1, 1, 7, 50)
+    end_date = datetime(2023, 1, 31, 16, 0)
+    for symbol in symbols:
+        data = get_historical_data(symbol, minutes(5), start_date, end_date)
+        data.to_csv(symbol + '.csv')

requirements.txt

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+pandas

setup.py

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+from setuptools import setup, find_packages
+
+setup(
+    name="iqfeed",
+    version="1.0",
+    packages=find_packages(),
+    install_requires=[
+        'pandas'
+    ]
+)