Skip to main content

Parallel computing framework

Project description

link.parallel is a database agnostic query system.

See documentation for more informations.

License Development Status Latest release Supported Python versions Supported Python implementations Download format Build status Code test coverage Downloads Code Health

Installation

pip install link.parallel

Features

  • parallel loops interface with IPython and multiprocessing drivers

  • Map/Reduce middleware

Examples

Create your map/reduce functions:

from b3j0f.task import register_task


@register_task('mymap')
def mymap(mapper, item):
    if item['i'] < 5:
        mapper.emit('i_lt_5', item)

    elif item['i'] > 5:
        mapper.emit('i_gt_5', item)

    else:
        mapper.emit('i_eq_5', item)


@register_task('myreduce')
def myreduce(key, values):
    return (key, len(values))

Get input data and pass it to the middleware:

from link.middleware.core import Middleware

mapreduce = Middleware.get_middleware_by_uri(
    'mapreduce+ipython:///test/classify?mapcb=mymap&reducecb=myreduce'
)

items = # load items
result = dict(mapreduce(items))

print(result)

Donating

Support via Liberapay

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

link.parallel-1.1.tar.gz (6.4 kB view hashes)

Uploaded Source

Built Distribution

link.parallel-1.1-py2.py3-none-any.whl (12.6 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page