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import pandas as pd
from datetime import datetime,timezone
import httpx
import pandas_ta as ta

class BinanceDataDownloader:
Base_url = "https://api2.binance.com"

def download(self, symbol: str, timeframe: str, start_date, end_date, save_to_csv=False, csv_filename="binance_data.csv")-> pd.DataFrame:
method = "GET"
end_point = "/api/v3/klines"
start_timestamp = int(datetime.strptime(start_date, "%Y-%m-%d").replace(tzinfo=timezone.utc).timestamp() * 1000)
end_timestamp = int(datetime.strptime(end_date, "%Y-%m-%d").replace(tzinfo=timezone.utc).timestamp() * 1000)
Parameters = {
"symbol" : symbol,
"interval" : timeframe,
"startTime":  start_timestamp,
"endTime" : end_timestamp,
"limit": 1000
}
url = self.Base_url + end_point
response = httpx.request(method, url, params=Parameters)
# print(response)
# print(response.json())
candle_data = []
if response.status_code == 200:
data = response.json()
for candle in data:
timestamp = datetime.fromtimestamp(candle[0] / 1000, tz=timezone.utc)
open_price = float(candle[1])
high_price = float(candle[2])
low_price = float(candle[3])
close_price = float(candle[4])
volume = float(candle[5])
candle_data.append([timestamp, open_price, high_price, low_price, close_price, volume,])
Data = pd.DataFrame(candle_data,columns=["Timestamp", "Open", "High", "Low", "Close", "Volume"])
Data.set_index('Timestamp', inplace=True)
if save_to_csv:
Data.to_csv(csv_filename)
print(f"Data saved to {csv_filename}")
return Data
else:
print("error")
return pd.DataFrame()

if __name__ == "__main__":
a = BinanceDataDownloader()
df = a.download("BTCUSDT","1m","2024-01-01", "2024-12-31", save_to_csv=True, csv_filename="BTCUSDT_1m_data_2024.csv")
# print(df)
df["ema"] = ta.ema(df["Close"],9)
print(df)