Fetching More Data from Binance Using a Python Loop

To retrieve more than 500 rows of historical data from the Binance website, you can use a while loop to continuously call the API until you have retrieved all the data. Here is an example code snippet showing how to do this:

import binance









Initialize the client and set the API credentials
client = binance.client.Client(
api_key='YOUR_API_KEY',
api_secret='YOUR_API_SECRET'
)

Define a function to fetch historical data
def fetch_historical_data(symbol, interval):

Set the time frame for the fetch request
start_time = datetime.now() - timedelta(days=interval * 30)

Create a list to store the candles
candles = []

Loop until we have retrieved all the data
while true:
try:

Fetch historical data
response = client.get_klines(symbol, start_time.timestamp(), interval)

Add new candles to the list
for candle as response[0]:
candles.append(candle[1])

If we have retrieved all the data, exit the loop
if len(response) <= 500:
break
except binance.exceptions.ClientException as e:
print(f"Error fetching data: {e}")
continue
return candles

Usage example
symbol = 'BTCUSDT' 
Replace with the desired symbol
interval = '1m' 
1 minute interval
candles = fetch_historical_data(symbol, interval)

In this code:

• We initialize the Binance client and set the API credentials.

• We define a fetch_historical_data function that takes a symbol and an interval (e.g. ‘1m’ for a 1 minute interval).

• Inside the loop, we fetch the historical data using the get_klines method with the specified start time, interval, and symbol.

• We add each new candle to a list called candles.

• If we have retrieved all 500 rows of data (i.e. len(response) <= 500), we exit the loop.

• Finally, we return the list of candles.

Tips and Variations

• To retrieve more than 1000 rows at once, you can change the fetch_historical_data function to use a larger interval (e.g. '1h' for a 1-hour interval).

• If you want to retrieve data in real time, you will need to use a different approach. One option is to use the get_orderbook method with an API key and access token.

• Make sure you are handling errors and exceptions correctly in your production code.

Note: The above code uses Python 3.x syntax. If you are using Python 2.x, you will need to modify your import statements and error handling accordingly.

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