Python rate limit decorator hackerrank solution

Python rate limit decorator hackerrank solution

I'd be happy to help with the Python rate limit decorator Hackerrank problem!

Problem Statement

Write a Python function that implements a rate limiter using the decorator pattern. The rate limiter should allow a maximum of n requests per t seconds.

Constraints

Sample Code

Here's a Python function that implements the rate limiter using a decorator:

import time
from functools import wraps
class RateLimitExceeded(Exception):
pass
def rate_limited(n, t):
def decorator(func):
request_count = 0
last_request_time = time.time()
@wraps(func)
def wrapper(*args, **kwargs):
nonlocal request_count, last_request_time
current_time = time.time()
if current_time - last_request_time > t:
request_count = 1
last_request_time = current_time
else:
request_count += 1
if request_count > n:
raise RateLimitExceeded("Rate limit exceeded")
return func(*args, **kwargs)
return wrapper
return decorator

How it Works

The rate_limited function takes two parameters: n (the maximum number of requests) and t (the time window in seconds). It returns a decorator that counts the number of requests made within the given time window.

When a request is made, the decorator checks if the current time minus the last request time is greater than or equal to the time window (t). If it is, the request count is reset to 1 and the last request time is updated. Otherwise, the request count is incremented by 1.

If the request count exceeds n, the decorator raises a RateLimitExceeded exception.

Example Usage

Here's an example of how you can use the rate limiter decorator:

@rate_limited(5, 10)  # allow up to 5 requests per 10 seconds
def my_function():
print("Hello!")
try:
for i in range(15):
my_function()
except RateLimitExceeded as e:
print(e)

In this example, the my_function function is decorated with the rate limiter decorator. When you call my_function 15 times, it will raise a RateLimitExceeded exception after the 5th request.

Conclusion

The rate_limited function provides a Python decorator that implements a rate limiter using the decorator pattern. It allows a maximum of n requests per t seconds and raises a RateLimitExceeded exception if the limit is exceeded. This can be useful in scenarios where you want to control the frequency of requests made to an API or other resource.

What is the rate limit per user in Python?

I'm glad you asked! In Python, there isn't a specific built-in rate limiter for HTTP requests. However, you can implement one yourself using various libraries and techniques. Let me walk you through some examples.

You can create a simple rate limiter by tracking the time of your last request and then checking if enough time has passed since the previous request. Here's an example:

import time
class SimpleRateLimiter:
def init(self, max_requests_per_second):
self.max_requests_per_second = max_requests_per_second
self.requests_made = 0
self.last_request_time = time.time()
def check_rate(self):
current_time = time.time()
elapsed_time = current_time - self.last_request_time
self.requests_made += 1
if elapsed_time < 1 / self.max_requests_per_second:
return False  # Too many requests in the last second, wait!
else:
self.last_request_time = current_time
return True  # Okay to proceed with the request
def make_request(self):
while not self.check_rate():
print("Rate limit exceeded! Waiting...")
time.sleep(0.5)  # Wait for a bit before trying again
Example usage:
rate_limiter = SimpleRateLimiter(max_requests_per_second=10)
for _ in range(30):  # Make 30 requests
if rate_limiter.make_request():
print("Request made!")

This simple rate limiter tracks the number of requests and the time since your last request. It checks if enough time has passed before allowing a new request to be made. If too many requests are made in a short period, it will wait for a bit before trying again.

Another approach is to use the requests library with built-in rate limiting capabilities. You can install the ratelimit package using pip:

pip install ratelimit

Then, you can decorate your request function with a rate limiter:

import requests
from ratelimit import RateLimiter
Create a rate limiter for 10 requests per second
rate_limiter = RateLimiter(retries=0)
def fetch_data():
Make the request (decorator will handle rate limiting)
response = requests.get("https://example.com")
return response.text
Use the decorated function
fetch_data()  # This is actually the wrapped function with rate limiting!

This package provides a simple way to implement rate limiting for your HTTP requests.

If you're working with asynchronous code, you can use the asyncio and aiohttp libraries to create a more advanced rate limiter. Here's an example:

import asyncio
import aiohttp
class AsyncRateLimiter:
def init(self, max_requests_per_second):
self.max_requests_per_second = max_requests_per_second
self.last_request_time = 0
async def check_rate(self):
current_time = time.time()
elapsed_time = current_time - self.last_request_time
if elapsed_time < 1 / self.max_requests_per_second:
return False  # Too many requests in the last second, wait!
else:
self.last_request_time = current_time
return True  # Okay to proceed with the request
async def make_request(self):
while not await self.check_rate():
print("Rate limit exceeded! Waiting...")
await asyncio.sleep(0.5)  # Wait for a bit before trying again

This example demonstrates how you can use asyncio and aiohttp to create an asynchronous rate limiter that tracks the time since your last request.

Remember, these are just examples to get you started. You'll likely need to customize and adapt them to fit your specific use case.

Please let me know if you have any further questions or if there's anything else I can help with!