I am using the official **Kite Connect Python client (kiteconnect)**
tracks approximately **200 NSE equity symbols** and uses both the Historical Data API and the WebSocket feed.
I have observed the following behavior:
* **Before market hours (pre-open/post-market):** Historical data for a large number of symbols loads relatively quickly with no erros. * **During market hours:** Loading historical data becomes significantly slower and mostly timeout errors. For example:
I understand from the documentation that the Historical Data API has a limit of **3 requests per second** and the Quote API has a limit of **1 request per second**.
I have a few questions:
1. Are these rate limits enforced uniformly throughout the day, or does the Historical Data API experience additional latency or throttling during market hours due to server load?
2. Is there any recommended approach from Zerodha for efficiently initializing historical data for a large watchlist (around 500 symbols)
3. Is there any bulk historical API available (or planned) that supports fetching historical candles for multiple instruments in a single request? i understand that the Quote API supports multiple instruments, but the Historical Data API appears to require one request per instrument.
5. Are there any best practices or recommendations from Zerodha to monitor several hundred symbols simultaneously while remaining within the supported API limits?
