Ethereum: How to add time delay in asynchronous coroutines?

Ethereum: Adding Time Delay in Asynchronous Coroutines

As asynchronous coroutines become increasingly popular, they offer numerous benefits such as improved readability and maintainability. However, when dealing with real-time data retrieval, adding a time delay can be crucial to prevent overwhelming the API with concurrent requests.

In this article, we’ll explore how to add a time delay in asynchronous Ethereum coroutines using the asyncio' library.



Why Time Delay?

Before diving into the solution, let's quickly discuss why adding a time delay is necessary. When retrieving historical data concurrently from Binance for each crypto pair in your database, you're likely facing API bans due to excessive concurrent requests. The reason behind this ban lies in API rate limiting, which restricts the number of requests you can make within a specific time frame.

Solution: Adding Time Delay

To add a time delay in asynchronous Ethereum coroutines, we'll use theasynciolibrary to create a custom asyncio event loop that waits for a specified amount of time before proceeding. Here's an example code snippet:




import async


class DelayedEthereumCoroutine:

    def __init__(self, delay: float):

        self.delay = delay


    async def run(self, data):

        await asyncio.sleep(self.delay) 




Wait for the specified amount of time

        return data


async def main():

    
Create an instance of our delayed coroutine with a 2-second delay

    del_ = DelayedEthereumCoroutine(2)


    
Retrieve historical data from Binance using our delayed coroutine

    async def fetch_data():

        
Simulate API request

        import async

        await asyncio.sleep(1) 
Simulate an API call


        
Fetch historical data

        return [fetch_data() for _ in range(len(data))]


    
Retrieve historical data concurrently from Binance for each crypto pair

    async def fetch_and_fetch_all():

        pairs = ["BTC/USDT", "ETH/BTC"]

        results = await asyncio.gather(*[fetch_data() for pair in pairs])


    
Run our main function, which waits for the delayed coroutine to complete before proceeding

    start_time = asyncio.get_event_loop().time()

    del_ = DelayedEthereumCoroutine(2)

    result = await fetch_and_fetch_all()


    end_time = asyncio.get_event_loop().time()

    print(f"Time tasks: {end_time - start_time} seconds")



Run the main function

async.run(main())

In this example, we create a custom DelayedEthereumCoroutineclass that takes adelayparameter. We then use an asyncmain()function to retrieve historical data from Binance using our delayed coroutine.



How it Works

Here's a step-by-step explanation of the code:

We import theasynciolibrary and define our customDelayedEthereumCoroutineclass.

Within this class, we have an__init__()method that takes adelayparameter and stores it in an instance variable.

Therun()method is an async function that simulates the API request by sleeping for the specified amount of time (in seconds).

In themain()function, we create an instance of our delayed coroutine with a 2-second delay usingDel_ = DelayedEthereumCoroutine(2).

We define another asyncfetch_data()function that simulates an API call.

To retrieve historical data concurrently from Binance for each crypto pair, we use theasyncio.gather()function to run multiple instances of our delayed coroutine in parallel.

Finally, we start and end times are obtained usingasyncio.get_event_loop().time()`, which gives us the current time before and after the delay.

Conclusion

Adding a time delay is crucial when retrieving historical data concurrently from Binance in asynchronous Ethereum coroutines.

DECENTRALIZED BRIDGING FIAT

Blog

Ethereum: How to add time delay in asynchronous coroutines?