Futured provides a consistent interface for concurrent functional programming in Python. It wraps any callable to return a concurrent.futures.Future, wraps any async coroutine to return an asyncio.Future, and provides concurrent iterators and context managers for futures.
Usage
threaded, processed
Transform any callable into one which runs in a thread or process pool, and returns a future.
from futured import threaded, processed
import httpx
fetch = threaded(httpx.Client().get)
fetch(url) # return Future
fs = (fetch(url + path) for path in paths)
threaded.results(fs) # generate results from futures
threaded.results(fs, timeout=...) # generate results as completed
fetch.map(urls) # generate results in order
fetch.map(urls, timeout=...) # generate results as completed
fetch.mapzip(urls) # generate (url, result) pairs as completedThread and process pool executors may be used as context managers, customized with options, and reused with different callables.
threaded(max_workers=...)(func, ...)
processed(max_workers=...)(func, ...)futured classes have a waiting context manager which collects results from tasks. Futures can be registered at creation, or appended to the list of tasks.
with threaded.waiting(*fs) as tasks:
tasks.append(future)
tasks # list of completed resultsfutured classes provide a tasks interface which generalizes futures.as_completed and futures.wait, while allowing the set of tasks to be modified, e.g., for retries.
threaded.tasks(fs, timeout=...) # mutable set of running tasks which iterate as completedasynced
The same interface works for asyncio.
from futured import asynced
import httpx
fetch = asynced(httpx.AsyncClient().get)
fetch(url) # return coroutine
asynced.results(fs) # generate results from futures
asynced.results(fs, timeout=...) # generate results as completed
fetch.map(urls) # generate results in order
fetch.map(urls, timeout=...) # generate results as completed
fetch.mapzip(urls) # generate (url, result) pairs as completedasynced provides utilities for calling coroutines from a synchronous context. waiting is similar to trio's nursery, but returns results from a synchronous with block.
asynced.run(async_func, ...) # call and run until complete
asynced.run(async_gen, ...) # call and run synchronous iterator
with asynced.waiting(*fs) as tasks: # concurrent coroutines completed in a block
asynced.tasks(fs, timeout=...) # mutable set of running tasks which iterate as completeddecorators
Naturally futured wrappers can be used as decorators, but arguments can also be partially bound.
@threaded
def slow():
...
fetch = threaded(httpx.Client().get, url)
fetch(params=...)Methods are supported, as well as a decorated utility for automatically subclassing.
from futured import decorated
FutureClient = decorated(httpx.Client, request=threaded)
# equivalent to
class FutureClient(httpx.Client):
request = threaded(httpx.Client.request)command
command wraps subprocess.Popen to provide a Future compatible interface.
from futured import futured, command
command('ls').result() # return stdout or raises stderr
command('ls').pipe('wc') # pipes into next command, or | ('wc',... )
for line in command('ls'): # iterable lines
command.coroutine('ls') # return coroutine
futured(command, 'ls') # supports `map` interface
asynced(command.coroutine, 'ls') # supports `map` interface with timeoutforked
forked allows iteration in separate child processes.
from futured import forked
for value in forked(values, max_workers=...):
# in a child process
# in parent after children have exitedInstallation
% pip install futuredTests
100% branch coverage.
% pytest [--cov]Changes
1.4
- Python >=3.8 required
1.3
- Python >=3.7 required
- Python 3.10 event loop changes
- Streams replaced with tasks
1.2
- Python >=3.6 required
1.1
- Stream completed futures from a pending pool
1.0
- Executed functions are context managers
-
starmapsupported
0.3
-
forkedhas optional maximum number of workers -
waitingcontext manager -
commandpipes (|) -
distributed.Clientsupport
0.2
-
command.coroutinecreates asyncio subprocesses -
futured.mapzipgenerates results zipped with arguments -
asynced.runsupports asynchronous iterators
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