paco 0.1.4

Small utility for asynchronous coroutine generic programming in Python +3.4.

paco

Small and idiomatic utility library for coroutine-driven, asynchronous-oriented generic programming in Python +3.4.

Built on top of asyncio, paco provides missing capabilities from Python stdlib to write asynchronous cooperative multitasking in a nice-ish way, plus higher-order function goodness.

paco can be your utility belt to deal with I/O-bound non-blocking concurrent code in a better and elegant way.

Features

• Simple and idiomatic API, extending Python stdlib with async coroutines gotchas.

• Built-in configurable control-flow concurrency support.

• Useful iterables, decorators, functors and convenient helpers.

• Coroutine-based functional helpers: compose, throttle, partial, timeout, times, until, race…

• Asynchronous coroutine port of Python built-in functions: filter, map, dropwhile, filterfalse, reduce…

• Concurrent iterables and higher-order functions.

• Better asyncio.gather() and asyncio.wait() with optional concurrency control and ordered results.

• Works with both async/await and yield from coroutines syntax.

• Designed for intensive I/O-bound concurrent non-blocking tasks.

• Good interoperability with asyncio and Python stdlib functions.

• Composable pipelines of functors for iterables via | operator overloading.

• Small and dependency free.

• Compatible with Python +3.4.

Installation

Using pip package manager:

pip install paco

Or install the latest sources from Github:

pip install -e git+git://github.com/h2non/paco.git#egg=paco

API

• paco.run

• paco.partial

• paco.apply

• paco.constant

• paco.throttle

• paco.compose

• paco.wraps

• paco.once

• paco.times

• paco.defer

• paco.timeout

• paco.wait

• paco.gather

• paco.each

• paco.series

• paco.map

• paco.flat_map

• paco.filter

• paco.reduce

• paco.some

• paco.every

• paco.filterfalse

• paco.dropwhile

• paco.repeat

• paco.until

• paco.whilst

• paco.race

• paco.ConcurrentExecutor

Examples

Asynchronously and concurrently execute multiple HTTP requests.

import paco
import aiohttp

async def fetch(url):
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as res:
            return res

async def fetch_urls():
    urls = [
        'https://www.google.com',
        'https://www.yahoo.com',
        'https://www.bing.com',
        'https://www.baidu.com',
        'https://duckduckgo.com',
    ]

    # Map concurrent executor with concurrent limit of 3
    responses = await paco.map(fetch, urls, limit=3)

    for res in responses:
        print('Status:', res.status)

# Run in event loop
paco.run(fetch_urls())

Concurrent pipeline-style composition of functors over an iterable object.

import paco

async def filterer(x):
    return x < 8

async def mapper(x):
    return x * 2

async def drop(x):
    return x < 10

async def reducer(acc, x):
    return acc + x

async def task(numbers):
    return await (numbers
                   | paco.filter(filterer)
                   | paco.map(mapper)
                   | paco.dropwhile(drop)
                   | paco.reduce(reducer, initializer=0))

# Run in event loop
number = paco.run(task((1, 2, 3, 4, 5, 6, 7, 8, 9, 10)))
print('Number:', number) # => 36

License

MIT - Tomas Aparicio

History

0.1.4 (2016-11-28)

• fix(#24): explicitly pass loop instance to asyncio.wait (b76d128).

0.1.3 (2016-10-27)

• feat(#17): add flat_map function.

• feat(#18): add pipeline-style operator overloading composition.

0.1.2 (2016-10-25)

• fix(setup.py): fix pip installation.

• refactor(api): minor refactors in several functions and tests.

0.1.1 (2016-10-24)

• refactor(name): use new project name.

0.1.0 (2016-10-23)

• First version (beta)