To limit your Python requests to 1.39 requests per second, you can use the time.sleep()
function from the time
module to introduce a delay between requests. You can also use third-party libraries like pyrate-limiter
, requests-ratelimiter
, or ratelimiter
to achieve rate limiting.
Here’s an example using the time
module:
import requests
import time
urls = [...] # List of URLs to send requests to
for url in urls:
response = requests.get(url)
print(response.status_code)
time.sleep(1 / 1.39) # Introduce a delay to achieve 1.39 requests per second
Alternatively, you can use the pyrate-limiter
library:
from pyrate_limiter import Duration, RequestRate, Limiter
import requests
rate_limit = RequestRate(1, Duration.SECOND / 1.39) # 1 request per 1.39 seconds
limiter = Limiter(rate_limit)
urls = [...] # List of URLs to send requests to
for url in urls:
with limiter:
response = requests.get(url)
print(response.status_code)
Another option is to use the requests-ratelimiter
library:
from requests import Session
from requests_ratelimiter import LimiterAdapter
session = Session()
# Apply a rate limit of 1.39 requests per second to all requests
adapter = LimiterAdapter(per_second=1.39)
session.mount('http://', adapter)
session.mount('https://', adapter)
urls = [...] # List of URLs to send requests to
for url in urls:
response = session.get(url)
print(response.status_code)
These examples demonstrate different ways to limit your Python requests to 1.39 requests per second. Choose the method that best suits your needs and project requirements.
Citations: [1] https://stackoverflow.com/questions/26098711/limiting-number-of-http-requests-per-second-on-python [2] https://pypi.org/project/requests-ratelimiter/ [3] https://github.com/vutran1710/PyrateLimiter [4] https://akshayranganath.github.io/Rate-Limiting-With-Python/ [5] https://stackoverflow.com/questions/40748687/python-api-rate-limiting-how-to-limit-api-calls-globally [6] https://pypi.org/project/limiter/ [7] https://github.com/JWCook/requests-ratelimiter [8] https://levelup.gitconnected.com/implement-rate-limiting-in-python-d4f86b09259f [9] https://limits.readthedocs.io [10] https://github.com/encode/httpx/issues/815 [11] https://365datascience.com/tutorials/python-tutorials/limit-rate-requests-web-scraping/ [12] https://www.seelk.co/blog/efficient-client-side-handling-of-api-throttling-in-python-with-tenacity [13] https://www.cisco.com/c/en/us/support/docs/security/firepower-ngfw/217900-troubleshoot-firepower-threat-defense-an.html [14] https://scrapfly.io/blog/how-to-rate-limit-asynchronous-python-requests/ [15] https://dev.to/paymon123/the-easiest-way-to-rate-limit-a-python-api-3njc [16] https://cloud.google.com/python/docs/reference/storage/1.39.0/retry_timeout [17] https://medium.com/clover-platform-blog/conquering-api-rate-limiting-dcac5552714d [18] https://subscription.packtpub.com/book/web_development/9781838983994/9/ch09lvl1sec72/api-rate-limiting [19] https://towardsdatascience.com/speeding-up-python-code-fast-filtering-and-slow-loops-8e11a09a9c2f [20] https://katiekodes.com/python-wrap-requests-functions/ [21] https://www.reddit.com/r/Python/comments/12xahnb/i_built_a_simple_and_efficient_rate_limiter_for/ [22] https://docs.alcf.anl.gov/theta/performance-tools/craypat/ [23] https://coderpad.io/blog/development/a-guide-to-api-rate-limiting-in-django/
To achieve a rate of 1.39 requests per second, you can use a global variable to keep track of the time elapsed between requests and then calculate the delay based on that time. Here’s a modified version of your
fetch_github_data
function that implements this:import time import requests import logging PERSONAL_ACCESS_TOKEN = "your_personal_access_token" DELAY = 1 / 1.39 # Calculate the delay for 1.39 requests per second last_request_time = 0 # Initialize a global variable to store the last request time def fetch_github_data(url): global last_request_time # Access the global variable try: headers = { "Accept": "application/vnd.github+json", "Authorization": f"Bearer {PERSONAL_ACCESS_TOKEN}", "X-GitHub-Api-Version": "2022-11-28", } # Calculate the time elapsed since the last request time_elapsed = time.time() - last_request_time # Calculate the required delay based on the time elapsed required_delay = max(0, DELAY - time_elapsed) # Sleep for the required delay time.sleep(required_delay) response = requests.get(url, headers=headers) # Update the last request time last_request_time = time.time() logging.info(f"Fetched data from {url}") return response.json() except requests.exceptions.RequestException as e: logging.exception(f"Error fetching data from {url}\n{e}") raise
This code calculates the required delay based on the desired rate of 1.39 requests per second and the time elapsed since the last request. It then sleeps for the required delay before making the next request. The global variable
last_request_time
is used to keep track of the time of the last request.Citations: [1] https://www.geeksforgeeks.org/how-to-add-time-delay-in-python/ [2] https://stackoverflow.com/questions/66229987/calculate-attempts-per-second [3] https://pypi.org/project/requests-ratelimiter/ [4] https://akshayranganath.github.io/Rate-Limiting-With-Python/ [5] https://stackoverflow.com/questions/32815451/are-global-variables-thread-safe-in-flask-how-do-i-share-data-between-requests [6] https://stackoverflow.com/questions/44014718/python-request-get-after-few-seconds [7] https://realpython.com/python-sleep/ [8] https://algotrading101.com/learn/yahoo-finance-api-guide/ [9] https://stackoverflow.com/questions/26098711/limiting-number-of-http-requests-per-second-on-python [10] https://realpython.com/python-use-global-variable-in-function/ [11] https://scrapeops.io/python-scrapy-playbook/scrapy-delay-between-requests/ [12] https://cloud.google.com/python/docs/reference/storage/1.44.0/client [13] https://github.com/JWCook/requests-ratelimiter [14] https://discuss.python.org/t/global-variables-shared-across-modules/16833 [15] https://coderslegacy.com/python/delay-between-requests-in-scrapy/ [16] https://jrnold.github.io/r4ds-exercise-solutions/transform.html [17] https://levelup.gitconnected.com/implement-rate-limiting-in-python-d4f86b09259f [18] https://docs.python.org/3/faq/programming.html [19] https://www.javatpoint.com/how-to-add-time-delay-in-python [20] https://koji.mbox.centos.org/koji/buildinfo?buildID=22406 [21] https://pypi.org/project/ratelimit/ [22] https://docs.python.org/3/library/timeit.html [23] https://www.purplefrogsystems.com/2020/07/how-to-delay-a-python-loop/ [24] https://medium.com/clover-platform-blog/conquering-api-rate-limiting-dcac5552714d [25] https://learning.postman.com/docs/writing-scripts/pre-request-scripts/ [26] https://python-forum.io/thread-35631.html [27] https://365datascience.com/tutorials/python-tutorials/limit-rate-requests-web-scraping/ [28] https://instructobit.com/tutorial/108/How-to-share-global-variables-between-files-in-Python [29] https://learn.microsoft.com/en-us/azure/storage/blobs/storage-blobs-latency [30] https://dev.to/astagi/rate-limiting-using-python-and-redis-58gk [31] https://www.simplilearn.com/tutorials/python-tutorial/global-variable-in-python
how come there are citations ? is it chatgpt with web search plugin ? or something else ?
It isn’t chatgpt. It’s an LLM with search
which one ?