# requests-futures **Repository Path**: iprintf/requests-futures ## Basic Information - **Project Name**: requests-futures - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2017-11-20 - **Last Updated**: 2024-06-26 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README Asynchronous Python HTTP Requests for Humans ============================================ .. image:: https://travis-ci.org/ross/requests-futures.png?branch=master :target: https://travis-ci.org/ross/requests-futures Small add-on for the python requests_ http library. Makes use of python 3.2's `concurrent.futures`_ or the backport_ for prior versions of python. The additional API and changes are minimal and strives to avoid surprises. The following synchronous code: .. code-block:: python from requests import Session session = Session() # first requests starts and blocks until finished response_one = session.get('http://httpbin.org/get') # second request starts once first is finished response_two = session.get('http://httpbin.org/get?foo=bar') # both requests are complete print('response one status: {0}'.format(response_one.status_code)) print(response_one.content) print('response two status: {0}'.format(response_two.status_code)) print(response_two.content) Can be translated to make use of futures, and thus be asynchronous by creating a FuturesSession and catching the returned Future in place of Response. The Response can be retrieved by calling the result method on the Future: .. code-block:: python 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) By default a ThreadPoolExecutor is created with 2 workers. If you would like to adjust that value or share a executor across multiple sessions you can provide one to the FuturesSession constructor. .. code-block:: python from concurrent.futures import ThreadPoolExecutor from requests_futures.sessions import FuturesSession session = FuturesSession(executor=ThreadPoolExecutor(max_workers=10)) # ... As a shortcut in case of just increasing workers number you can pass `max_workers` straight to the `FuturesSession` constructor: .. code-block:: python from requests_futures.sessions import FuturesSession session = FuturesSession(max_workers=10) FutureSession will use an existing session object if supplied: .. code-block:: python from requests import session from requests_futures.sessions import FuturesSession my_session = session() future_session = FuturesSession(session=my_session) That's it. The api of requests.Session is preserved without any modifications beyond returning a Future rather than Response. As with all futures exceptions are shifted (thrown) to the future.result() call so try/except blocks should be moved there. Canceling queued requests (a.k.a cleaning up after yourself) ========================= If you know that you won't be needing any additional responses from futures that haven't yet resolved, it's a good idea to cancel those requests. You can do this by using the session as a context manager: .. code-block:: python from requests_futures.sessions import FuturesSession with FuturesSession(max_workers=1) as session: future = session.get('https://httpbin.org/get') future2 = session.get('https://httpbin.org/delay/10') future3 = session.get('https://httpbin.org/delay/10') response = future.result() In this example, the second or third request will be skipped, saving time and resources that would otherwise be wasted. Working in the Background ========================= There is one additional parameter to the various request functions, background_callback, which allows you to work with the Response objects in the background thread. This can be useful for shifting work out of the foreground, for a simple example take json parsing. .. code-block:: python from pprint import pprint from requests_futures.sessions import FuturesSession session = FuturesSession() def bg_cb(sess, resp): # parse the json storing the result on the response object resp.data = resp.json() future = session.get('http://httpbin.org/get', background_callback=bg_cb) # do some other stuff, send some more requests while this one works response = future.result() print('response status {0}'.format(response.status_code)) # data will have been attached to the response object in the background pprint(response.data) Using ProcessPoolExecutor ========================= Similarly to `ThreadPoolExecutor`, it is possible to use an instance of `ProcessPoolExecutor`. As the name suggest, the requests will be executed concurrently in separate processes rather than threads. .. code-block:: python from concurrent.futures import ProcessPoolExecutor from requests_futures.sessions import FuturesSession session = FuturesSession(executor=ProcessPoolExecutor(max_workers=10)) # ... use as before .. HINT:: Using the `ProcessPoolExecutor` is useful, in cases where memory usage per request is very high (large response) and cycling the interpretor is required to release memory back to OS. A base requirement of using `ProcessPoolExecutor` is that the `Session.request`, `FutureSession` and (the optional) `background_callback` all be pickle-able. This means that only Python 3.5 is fully supported, while Python versions 3.4 and above REQUIRE an existing `requests.Session` instance to be passed when initializing `FutureSession`. Python 2.X and < 3.4 are currently not supported. .. code-block:: python # Using python 3.4 from concurrent.futures import ProcessPoolExecutor from requests import Session from requests_futures.sessions import FuturesSession session = FuturesSession(executor=ProcessPoolExecutor(max_workers=10), session=Session()) # ... use as before In case pickling fails, an exception is raised pointing to this documentation. .. code-block:: python # Using python 2.7 from concurrent.futures import ProcessPoolExecutor from requests import Session from requests_futures.sessions import FuturesSession session = FuturesSession(executor=ProcessPoolExecutor(max_workers=10), session=Session()) Traceback (most recent call last): ... RuntimeError: Cannot pickle function. Refer to documentation: https://github.com/ross/requests-futures/#using-processpoolexecutor .. IMPORTANT:: * Python >= 3.4 required * A session instance is required when using Python < 3.5 * If sub-classing `FuturesSession` it must be importable (module global) * If using `background_callback` it too must be importable (module global) Installation ============ pip install requests-futures .. _`requests`: https://github.com/kennethreitz/requests .. _`concurrent.futures`: http://docs.python.org/dev/library/concurrent.futures.html .. _backport: https://pypi.python.org/pypi/futures