pip install requests

Step 2: Create an Exchange API Client
Use a library likerequeststo create an API client that can interact with the exchange's public API. For example, you can use the following code snippet:
python
import requests
def get_live_ticker_data(exchange_url, api_key, secret):
url = f"{exchange_url}/api/v1/ohlcv"
headers = {"x-api-key": api-key}
response = requests. get(url, headers=headers)
return response. json()

Step 3: Extracting Kline data from live ticker information

Using the API client, retrieve Kline data for a specific currency in a 5-minute interval. You can modify this code snippet to suit your needs:

live_ticker_data = get_live_ticker_data(

"

"YOUR API KEY HERE",

"YOUR SECRET KEY IS HERE"

)

Parse Kline data as JSON

kline_data = live_ticker_data[0]["ohlcv"]

print(cline_data)

This will extract and print the 5-minute OHLCV (Open, High, Low, Close, Volume) data for a specific coin.

Step 4: Preprocessing and Storing Kline Data
In order to use this data in your trading application, you will need to preprocess and store it. A common approach is to create a list of dictionaries, where each dictionary represents a data point.
python
line_data = [
{"open": float(kline_data["0"].split(",")[1]), "high": kline_data["2"].split(",")[1], "low": kline_data["3"].split(",")[1], "close": kline_data["4"].split(",")[1], "volume": int(kline_data["5"].split(",")[1])},

Add more data points if needed...
]

Store Kline data in a database or file
import json
with open("kline_data.json", "w") as f:
json.dump(kline_data, f)

This will save the preprocessed Kline data to a JSON file.

Conclusion