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package mapreduce
/**
* This is an attempt to find a minimal set of type classes that describe the map-reduce programming model
* (the underlying model of Google map/reduce, Hadoop, Spark and others)
* The idea is to have:
* 1) lawful types that fully constrain correctness
* 2) a minimal set of laws (i.e. we can't remove any laws,
* 3) able to fully express existing map/reduce in terms of these types
*
# Author: Randal S. Olson (randalolson.com / @randal_olson)
# Uses Tableau's Tableau20 color scheme
figure.figsize: 12, 7
figure.edgecolor: white
figure.facecolor: white
lines.linewidth: 2.5
lines.markeredgewidth: 0
lines.markersize: 10
Robs-MacBook-Pro:testenv robstory$ sh PIPALLTHETHINGS.sh
New python executable in .env/bin/python2.7
Also creating executable in .env/bin/python
Installing setuptools, pip...done.
Warning: libevent-2.0.21 already installed
Warning: libyaml-0.1.6 already installed
Downloading/unpacking cython
Downloading Cython-0.20.2-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl (3.4MB): 3.4MB downloaded
Installing collected packages: cython
Successfully installed cython
@wrobstory
wrobstory / gist:98033556dd590132852e
Created September 8, 2014 04:17
PIP ALL THE THINGS
#!/bin/bash
virtualenv .env &&
source .env/bin/activate &&
brew install libevent &&
brew install libyaml &&
pip install cython &&
pip install numpy &&
pip install scipy &&
pip install pandas &&
pip install matplotlib &&
@staltz
staltz / introrx.md
Last active April 19, 2025 05:10
The introduction to Reactive Programming you've been missing
@johnmyleswhite
johnmyleswhite / abstract.md
Created February 11, 2014 22:49
Abstract for UC Davis Talk

Julia and Statistical Computing

Julia is a new language for technical computing. The language is designed to solve the "two language problem", in which scientists prototype code in a higher-level language like R and then rewrite parts (or all) of their code in a lower-level language like C. Julia strives to expose a set of basic abstractions that allow programmers to transition easily between quick-and-dirty prototype code and production-quality code.

@debasishg
debasishg / gist:8172796
Last active April 16, 2025 13:43
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t
@sloria
sloria / bobp-python.md
Last active April 17, 2025 08:09
A "Best of the Best Practices" (BOBP) guide to developing in Python.

The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

In General

Values

  • "Build tools for others that you want to be built for you." - Kenneth Reitz
  • "Simplicity is alway better than functionality." - Pieter Hintjens
@andrequeiroz
andrequeiroz / holtwinters.py
Last active February 3, 2025 04:35
Implementation of Holt-Winters algorithms in Python 2
#The MIT License (MIT)
#
#Copyright (c) 2015 Andre Queiroz
#
#Permission is hereby granted, free of charge, to any person obtaining a copy
#of this software and associated documentation files (the "Software"), to deal
#in the Software without restriction, including without limitation the rights
#to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
#copies of the Software, and to permit persons to whom the Software is
#furnished to do so, subject to the following conditions: