Functional interface for concurrent futures, including asynchronous I/O.
Futured provides a simple consistent interface for concurrent functional programming in Python. It can wrap any callable to return concurrent.futures.Future objects, and it can wrap any async coroutine to return asyncio.Future objects.
Transform any callable into one which runs in a thread or process pool, and returns a future.
from futured import threaded, processed import requests fetch = threaded(requests.Session().get) fetch(url) # returns Future fs = (fetch(url + path) for path in paths) fetch.results(fs) # generates results in order fetch.results(fs, timeout=...) # generates results as completed fetch.map(urls) # generates results in order fetch.map(urls, timeout=...) # generates results as completed fetch.mapzip(urls) # generates (url, result) pairs as completed
Naturally futured wrappers can be used as decorators, but arguments can also be partially bound.
@threaded def slow(): ... fetch = threaded(requests.Session().get, url) fetch(params=...)
Methods are supported, as well as a decorated utility for automatically subclassing.
from futured import decorated FutureSession = decorated(requests.Session, request=threaded) # equivalent to class FutureSession(requests.Session): request = threaded(requests.Session.request)
Thread and process pool executors may be customized and reused.
threaded(max_workers=...)(func, ...) processed(max_workers=...)(func, ...)
The same interface works for aynscio. For convenience, there’s also a synchronous run method.
from futured import asynced import aiohttp fetch = asynced(aiohttp.ClientSession().get) fetch(url) # returns coroutine fetch.run(url) # single synchronous call # generate results as described above fetch.results(fs) fetch.map(urls) fetch.mapzip(urls)
command wraps subprocess.Popen to provide a Future compatible interface.
from futured import futured, command command('ls').result() # returns stdout or raises stderr command('ls').pipe('wc') # pipes into next command for line in command('ls'): # iterable lines command.coroutine('ls') # returns coroutine futured(command, 'ls') # supports `map` interface asynced(command.coroutine, 'ls') # supports `map` interface with timeout
forked allows iteration in separate child processes.
from futured import forked for value in forked(values): # in a child process # in parent after children have exited
$ pip install futured
- Python 3.5+
100% branch coverage.
$ pytest [--cov]
- command.coroutine creates asyncio subprocesses
- futured.mapzip generates results zipped with arguments
- asynced.run supports asynchronous iterators
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|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
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