How to convert live stock market API data into a usable format to calculate technical indicators?

Question

I'm trying to automate a trading strategy using python. I already have angelbroking stock market API which fetches open high low close values of a stock.

The problem is, by default the API prints the data. I'm unable to understand how to convert this data to a usable format like DataFrames that will update prices accordingly.

In case of historic data, I can create DataFrames to plot various charts with Matplotlib, Plotly and calculate indicators using TA-lib or math formulas in some cases.

So, how to convert the live stock market API data into a usable format to calculate the technical indicators?

Below is the API:

from smartapi import 
SmartWebSocket

# feed_token=092017047
FEED_TOKEN="YOUR_FEED_TOKEN"
CLIENT_CODE="YOUR_CLIENT_CODE"
# token="mcx_fo|224395"
token="EXCHANGE|TOKEN_SYMBOL"    
#SAMPLE: nse_cm|2885&nse_cm|1594&nse_cm|11536&nse_cm|3045
task="mw"   # mw|sfi|dp

ss = SmartWebSocket(FEED_TOKEN, CLIENT_CODE)

def on_message(ws, message):
    print("Ticks: {}".format(message))

def on_open(ws):
    print("on open")
    ss.subscribe(task,token)

def on_error(ws, error):
    print(error)

def on_close(ws):
    print("Close")

# Assign the callbacks.
ss._on_open = on_open
ss._on_message = on_message
ss._on_error = on_error
ss._on_close = on_close

ss.connect()

Any suggestion is helpful. Thanks for your valuable time.

Answer 1

You have access to the documentation since you have an account. Please read it first and watch some tutorials before asking questions. I do not have access to the documentation since there is an account wall.