I tried the sample provided within the documentation of the requests library for python.
With async.map(rs), I get the response codes, but I want to get the content of each page requested. This, for example, does not work:
out = async.map(rs)
print out[0].content
The below answer is not applicable to requests v0.13.0+. The asynchronous functionality was moved to grequests after this question was written. However, you could just replace requests with grequests below and it should work.
I've left this answer as is to reflect the original question which was about using requests < v0.13.0.
To do multiple tasks with async.map asynchronously you have to:
async.map on a list of all the requests / actionsExample:
from requests import async
# If using requests > v0.13.0, use
# from grequests import async
urls = [
'http://python-requests.org',
'http://httpbin.org',
'http://python-guide.org',
'http://kennethreitz.com'
]
# A simple task to do to each response object
def do_something(response):
print response.url
# A list to hold our things to do via async
async_list = []
for u in urls:
# The "hooks = {..." part is where you define what you want to do
#
# Note the lack of parentheses following do_something, this is
# because the response will be used as the first argument automatically
action_item = async.get(u, hooks = {'response' : do_something})
# Add the task to our list of things to do via async
async_list.append(action_item)
# Do our list of things to do via async
async.map(async_list)
async is now an independent module : grequests.
See here : https://github.com/kennethreitz/grequests
And there: Ideal method for sending multiple HTTP requests over Python?
$ pip install grequests
build a stack:
import grequests
urls = [
'http://www.heroku.com',
'http://tablib.org',
'http://httpbin.org',
'http://python-requests.org',
'http://kennethreitz.com'
]
rs = (grequests.get(u) for u in urls)
send the stack
grequests.map(rs)
result looks like
[<Response [200]>, <Response [200]>, <Response [200]>, <Response [200]>, <Response [200]>]
grequests don't seem to set a limitation for concurrent requests, ie when multiple requests are sent to the same server.
I tested both requests-futures and grequests. Grequests is faster but brings monkey patching and additional problems with dependencies. requests-futures is several times slower than grequests. I decided to write my own and simply wrapped requests into ThreadPoolExecutor and it was almost as fast as grequests, but without external dependencies.
import requests
import concurrent.futures
def get_urls():
return ["url1","url2"]
def load_url(url, timeout):
return requests.get(url, timeout = timeout)
with concurrent.futures.ThreadPoolExecutor(max_workers=20) as executor:
future_to_url = {executor.submit(load_url, url, 10): url for url in get_urls()}
for future in concurrent.futures.as_completed(future_to_url):
url = future_to_url[future]
try:
data = future.result()
except Exception as exc:
resp_err = resp_err + 1
else:
resp_ok = resp_ok + 1
maybe requests-futures is another choice.
from requests_futures.sessions import FuturesSession
session = FuturesSession()
# first request is started in background
future_one = session.get('http://httpbin.org/get')
# second requests is started immediately
future_two = session.get('http://httpbin.org/get?foo=bar')
# wait for the first request to complete, if it hasn't already
response_one = future_one.result()
print('response one status: {0}'.format(response_one.status_code))
print(response_one.content)
# wait for the second request to complete, if it hasn't already
response_two = future_two.result()
print('response two status: {0}'.format(response_two.status_code))
print(response_two.content)
It is also recommended in the office document. If you don't want involve gevent, it's a good one.
I have a lot of issues with most of the answers posted - they either use deprecated libraries that have been ported over with limited features, or provide a solution with too much magic on the execution of the request, making it difficult to error handle. If they do not fall into one of the above categories, they're 3rd party libraries or deprecated.
Some of the solutions works alright purely in http requests, but the solutions fall short for any other kind of request, which is ludicrous. A highly customized solution is not necessary here.
Simply using the python built-in library asyncio is sufficient enough to perform asynchronous requests of any type, as well as providing enough fluidity for complex and usecase specific error handling.
import asyncio
loop = asyncio.get_event_loop()
def do_thing(params):
async def get_rpc_info_and_do_chores(id):
# do things
response = perform_grpc_call(id)
do_chores(response)
async def get_httpapi_info_and_do_chores(id):
# do things
response = requests.get(URL)
do_chores(response)
async_tasks = []
for element in list(params.list_of_things):
async_tasks.append(loop.create_task(get_chan_info_and_do_chores(id)))
async_tasks.append(loop.create_task(get_httpapi_info_and_do_chores(ch_id)))
loop.run_until_complete(asyncio.gather(*async_tasks))
How it works is simple. You're creating a series of tasks you'd like to occur asynchronously, and then asking a loop to execute those tasks and exit upon completion. No extra libraries subject to lack of maintenance, no lack of functionality required.
Unfortunately, as far as I know, the requests library is not equipped for performing asynchronous requests. You can wrap async/await syntax around requests, but that will make the underlying requests no less synchronous. If you want true async requests, you must use other tooling that provides it. One such solution is aiohttp (Python 3.5.3+). It works well in my experience using it with the Python 3.7 async/await syntax. Below I write three implementations of performing n web requests using
sync_requests_get_all) using the Python requests libraryasync_requests_get_all) using the Python requests library wrapped in Python 3.7 async/await syntax and asyncioasync_aiohttp_get_all) with the Python aiohttp library wrapped in Python 3.7 async/await syntax and asyncioimport time
import asyncio
import requests
import aiohttp
from types import SimpleNamespace
durations = []
def timed(func):
"""
records approximate durations of function calls
"""
def wrapper(*args, **kwargs):
start = time.time()
print(f'{func.__name__:<30} started')
result = func(*args, **kwargs)
duration = f'{func.__name__:<30} finished in {time.time() - start:.2f} seconds'
print(duration)
durations.append(duration)
return result
return wrapper
async def fetch(url, session):
"""
asynchronous get request
"""
async with session.get(url) as response:
response_json = await response.json()
return SimpleNamespace(**response_json)
async def fetch_many(loop, urls):
"""
many asynchronous get requests, gathered
"""
async with aiohttp.ClientSession() as session:
tasks = [loop.create_task(fetch(url, session)) for url in urls]
return await asyncio.gather(*tasks)
@timed
def sync_requests_get_all(urls):
"""
performs synchronous get requests
"""
# use session to reduce network overhead
session = requests.Session()
return [SimpleNamespace(**session.get(url).json()) for url in urls]
@timed
def async_requests_get_all(urls):
"""
asynchronous wrapper around synchronous requests
"""
loop = asyncio.get_event_loop()
# use session to reduce network overhead
session = requests.Session()
async def async_get(url):
return session.get(url)
async_tasks = [loop.create_task(async_get(url)) for url in urls]
return loop.run_until_complete(asyncio.gather(*async_tasks))
@timed
def asnyc_aiohttp_get_all(urls):
"""
performs asynchronous get requests
"""
loop = asyncio.get_event_loop()
return loop.run_until_complete(fetch_many(loop, urls))
if __name__ == '__main__':
# this endpoint takes ~3 seconds to respond,
# so a purely synchronous implementation should take
# little more than 30 seconds and a purely asynchronous
# implementation should take little more than 3 seconds.
urls = ['https://postman-echo.com/delay/3']*10
sync_requests_get_all(urls)
async_requests_get_all(urls)
asnyc_aiohttp_get_all(urls)
print('----------------------')
[print(duration) for duration in durations]
On my machine, this is the output:
sync_requests_get_all started
sync_requests_get_all finished in 30.92 seconds
async_requests_get_all started
async_requests_get_all finished in 30.87 seconds
asnyc_aiohttp_get_all started
asnyc_aiohttp_get_all finished in 3.22 seconds
----------------------
sync_requests_get_all finished in 30.92 seconds
async_requests_get_all finished in 30.87 seconds
asnyc_aiohttp_get_all finished in 3.22 seconds
I know this has been closed for a while, but I thought it might be useful to promote another async solution built on the requests library.
list_of_requests = ['http://moop.com', 'http://doop.com', ...]
from simple_requests import Requests
for response in Requests().swarm(list_of_requests):
print response.content
The docs are here: http://pythonhosted.org/simple-requests/
You can use httpx for that.
import httpx
async def get_async(url):
async with httpx.AsyncClient() as client:
return await client.get(url)
urls = ["http://google.com", "http://wikipedia.org"]
# Note that you need an async context to use `await`.
await asyncio.gather(*map(get_async, urls))
if you want a functional syntax, the gamla lib wraps this into get_async.
Then you can do
await gamla.map(gamla.get_async(10))(["http://google.com", "http://wikipedia.org"])
The 10 is the timeout in seconds.
(disclaimer: I am its author)
If you want to use asyncio, then requests-async provides async/await functionality for requests - https://github.com/encode/requests-async
I have been using python requests for async calls against github's gist API for some time.
For an example, see the code here:
https://github.com/davidthewatson/flasgist/blob/master/views.py#L60-72
This style of python may not be the clearest example, but I can assure you that the code works. Let me know if this is confusing to you and I will document it.
DISCLAMER: Following code creates different threads for each function.
This might be useful for some of the cases as it is simpler to use. But know that it is not async but gives illusion of async using multiple threads, even though decorator suggests that.
You can use the following decorator to give a callback once the execution of function is completed, the callback must handle the processing of data returned by the function.
Please note that after the function is decorated it will return a Future object.
import asyncio
## Decorator implementation of async runner !!
def run_async(callback, loop=None):
if loop is None:
loop = asyncio.get_event_loop()
def inner(func):
def wrapper(*args, **kwargs):
def __exec():
out = func(*args, **kwargs)
callback(out)
return out
return loop.run_in_executor(None, __exec)
return wrapper
return inner
Example of implementation:
urls = ["https://google.com", "https://facebook.com", "https://apple.com", "https://netflix.com"]
loaded_urls = [] # OPTIONAL, used for showing realtime, which urls are loaded !!
def _callback(resp):
print(resp.url)
print(resp)
loaded_urls.append((resp.url, resp)) # OPTIONAL, used for showing realtime, which urls are loaded !!
# Must provide a callback function, callback func will be executed after the func completes execution
# Callback function will accept the value returned by the function.
@run_async(_callback)
def get(url):
return requests.get(url)
for url in urls:
get(url)
If you wish to see which url are loaded in real-time then, you can add the following code at the end as well:
while True:
print(loaded_urls)
if len(loaded_urls) == len(urls):
break
I have also tried some things using the asynchronous methods in python, how ever I have had much better luck using twisted for asynchronous programming. It has fewer problems and is well documented. Here is a link of something simmilar to what you are trying in twisted.
http://pythonquirks.blogspot.com/2011/04/twisted-asynchronous-http-request.html
