Popularity
5.6
Stable
Activity
0.0
Declining
1,461
50
107

Description

Magic decorator syntax for asynchronous code in Python 2.7.

Please don't actually use this in production. It's more of a thought experiment than anything else, and relies heavily on behavior specific to Python's old style classes. Pull requests, issues, comments and suggestions welcome.

Code Quality Rank: L5
Programming language: Python
License: MIT License

Tomorrow alternatives and similar packages

Based on the "Concurrency and Parallelism" category.
Alternatively, view Tomorrow alternatives based on common mentions on social networks and blogs.

Do you think we are missing an alternative of Tomorrow or a related project?

Add another 'Concurrency and Parallelism' Package

README

Codeship Status for madisonmay/Tomorrow

Tomorrow

Magic decorator syntax for asynchronous code in Python 2.7.

Please don't actually use this in production. It's more of a thought experiment than anything else, and relies heavily on behavior specific to Python's old style classes. Pull requests, issues, comments and suggestions welcome.

Installation

Tomorrow is conveniently available via pip:

pip install tomorrow

or installable via git clone and setup.py

git clone [email protected]:madisonmay/Tomorrow.git
sudo python setup.py install

To ensure Tomorrow is properly installed, you can run the unittest suite from the project root:

nosetests -v 

Usage

The tomorrow library enables you to utilize the benefits of multi-threading with minimal concern about the implementation details.

Behind the scenes, the library is a thin wrapper around the Future object in concurrent.futures that resolves the Future whenever you try to access any of its attributes.

Enough of the implementation details, let's take a look at how simple it is to speed up an inefficient chunk of blocking code with minimal effort.

Naive Web Scraper

You've collected a list of urls and are looking to download the HTML of the lot. The following is a perfectly reasonable first stab at solving the task.

For the following examples, we'll be using the top sites from the Alexa rankings.

urls = [
    'http://google.com',
    'http://facebook.com',
    'http://youtube.com',
    'http://baidu.com',
    'http://yahoo.com',
]

Right then, let's get on to the code.

import time
import requests

def download(url):
    return requests.get(url)

if __name__ == "__main__":

    start = time.time()
    responses = [download(url) for url in urls]
    html = [response.text for response in responses]
    end = time.time()
    print "Time: %f seconds" % (end - start)

More Efficient Web Scraper

Using tomorrow's decorator syntax, we can define a function that executes in multiple threads. Individual calls to download are non-blocking, but we can largely ignore this fact and write code identically to how we would in a synchronous paradigm.

import time
import requests

from tomorrow import threads

@threads(5)
def download(url):
    return requests.get(url)

if __name__ == "__main__":
    start = time.time()
    responses = [download(url) for url in urls]
    html = [response.text for response in responses]
    end = time.time()
    print "Time: %f seconds" % (end - start)

Awesome! With a single line of additional code (and no explicit threading logic) we can now download websites ~10x as efficiently.

You can also optionally pass in a timeout argument, to prevent hanging on a task that is not guaranteed to return.

import time

from tomorrow import threads

@threads(1, timeout=0.1)
def raises_timeout_error():
    time.sleep(1)

if __name__ == "__main__":
    print raises_timeout_error()

How Does it Work?

Feel free to read the source for a peek behind the scenes -- it's less than 50 lines of code.