Ethereum: Adding a Time Delay in Asynchronous Coroutines

As asynchronous coroutines have become increasingly popular, they offer a number of benefits, such as better readability and maintainability. However, when dealing with real-time data retrieval, adding a time delay can be crucial to prevent the API from being overloaded with concurrent requests.

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

Why a time delay?

Before diving into the solution, let’s quickly discuss why adding a time delay is necessary. When concurrently retrieving historical data from Binance for each crypto pair in your database, you are likely to face API bans due to excessive concurrent requests. The reason for this ban lies in the API rate limit, which limits the number of requests you can make in a given time frame.

Solution: Adding a Time Delay

To add a time delay in Ethereum asynchronous coroutines, we will use the asyncio library to create a custom asyncio event loop that waits a certain amount of time before continuing. Here is an example code snippet:

import asyncio
class DelayedEthereumCoroutine:
def __init__(self, delay: float):
self.delay = delay
async def run (self, data):
wait asyncio.sleep(self.delay) 




Wait for the specified time
return data
async def main():

Create an instance of our delayed coroutine with a 2-second delay
del_ = DelayedEthereumCoroutine(2)

Get historical data from Binance using our delayed coroutine
async def fetch_data():

Simulate an API request
import asyncio
wait asyncio.sleep(1) 
Simulate an API call

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

Fetch historical data simultaneously from Binance for each crypto pair
async def fetch_and_fetch_all():
pairs = ["BTC/USDT", "ETH/BTC"]
results = wait asyncio.gather(*[fetch_data() for pair in pairs])

Run our main function, which waits for the delayed coroutine to complete before continuing
start_time = asyncio.get_event_loop().time()
del_ = DelayedEthereumCoroutine(2)
result = wait fetch_and_fetch_all()
end_time = asyncio.get_event_loop().time()
print(f"Time: {end_time - start_time} seconds")

Run the main function
asyncio.run(main())

In this example, we will create a custom DelayedEthereumCoroutine class that takes a delay parameter. Then we will use the asynchronous main() function to fetch historical data from Binance using our delayed coroutine.

How ​​​it works

Here is a detailed explanation of the code:

• We import the asyncio library and define our own DelayedEthereumCoroutine class.

• Within this class, we have a __init__() method that takes a delay parameter and stores it in an instance variable.

• The run() method is an asynchronous function that simulates an API request by sleeping for a specified time (in seconds).

• In the main() function, we instantiate our delayed coroutine with a 2-second delay using Del_ = DelayedEthereumCoroutine(2).

• We define another asynchronous function fetch_data() that simulates an API call.

• To get historical data from Binance simultaneously for each crypto pair, we use the asyncio.gather() function to run multiple instances of our delayed coroutine in parallel.

• Finally, we get the start and end times using asyncio.get_event_loop().time(), which gives us the current time before and after the delay.

Conclusion

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

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