This is a pre-production deployment of Warehouse, however changes made here WILL affect the production instance of PyPI.
Help us improve Python packaging - Donate today!
Project Description

Introduction

Instances of the RunnincCalc classes in this library can be fed one input value at a time. This allows running several calculations in a single pass over an iterator. This isn’t possible with the built-in variants of most calculations, such as max() and heapq.nlargest().

RunningCalc instances can be fed values directly, for example:

mean_rc, stddev_rc = RunningMean(), RunningStdDev()
for x in values:
    mean_rc.feed(x)
    stddev_rc.feed(x)
mean, stddev = mean_rc.value, stddev_rc.value

Additionally, the apply_in_parallel() function is supplied, which makes performing several calculations in parallel easy (and fast!). For example:

mean, stddev = apply_in_parallel([RunningMean(), RunningStdDev()], values)
five_smallest, five_largest = apply_in_parallel([RunningNSmallest(5), RunningNLargest(5)], values)

Optimizations

In addition to the basic feed() method, some RunningCalc classes also implement an optimized feedMultiple() method, which accepts a sequence of values to be processed. This allows values to be processed in chunks, allowing for faster processing in many cases.

The apply_in_parallel() function automatically splits the given iterable of input values into chunks (chunk size can be controlled via the chunk_size keyword argument). Therefore using apply_in_parallel() is both fast and easy.

Writing Your Own RunningCalc Class

  1. sub-class RunningCalc
  2. implement the __init__() and feed() methods
  3. make the calculation output value accessible via the value attribute
  4. optionally implement an optimized feedMultiple() method Note: the RunningCalc base class includes a default naive implementation of feedMultiple()
Release History

Release History

0.4

This version

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.3

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.2

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

0.1

History Node

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Show More

Download Files

Download Files

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

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
RunningCalcs-0.4.zip (6.6 kB) Copy SHA256 Checksum SHA256 Source Feb 17, 2013

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting