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# http://dlo.me/archives/2014/09/08/pythonrc/
# vim: set ft=python :

from __future__ import print_function

import json
import sys
import datetime

from redis import StrictRedis as Redis

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@doc doc"""
    Takes a 2d array where each column is a pattern which maps to a row in
    the resulting dataframe. Each pattern index is its own column in 
    the dataframe.
""" ->
function DataFrame(data::Array{Float64, 2})
    m = data'
    result = DataFrame()
    
    for i in 1:size(data, 1)

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function query() {
  var 
    total = 0, shown = 0,
    // HN is done with very unsemantic classes.
    job_list = Array.prototype.slice.call(document.querySelectorAll('.c5a,.cae,.c00,.c9c,.cdd,.c73,.c88')),
    query_list = Array.prototype.slice.call(arguments);
    
  // This traverses up the dom stack trying to find a match of a specific class
  function up_to(node, klass) {
    if (node.className === klass) {

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// takes arguments and produces an array of functions that accept context
function handle_args() {
  var args = Array.prototype.slice.call(arguments);
  return args.map(function(arg) {
    if(arg instanceof Function) return arg; // Presumably already a contex-accepting function.
    if(arg instanceof Array) return and.apply(this, arg); // make arrays behave as and.
    // Presuming a string, build a function to check.
    var my_regex = new RegExp(arg.toString(), 'i');
    return function(context) {
      return context.search(my_regex) > -1;

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# Fortran-like array with arbitrary starting indices
#
# usage:
#
# julia> include("FArray.jl")
# size (generic function with 51 methods)
# 
# julia> y = FArray(Float64, -1:1, -7:7, -128:512, -5:5, -1:1, -3:3, -2:2, -1:1);
# 
# julia> y[-1,-7,-128,-5,-1,-3,-2,-1] = 14

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using HTTPClient: HTTPC
using JSON

# Fill in your city name and GitHub API token
const MEETUP_LOCATION = lowercase("Seattle")
const API_TOKEN = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
# Pages of search results to examine. Warning - you WILL hit the rate limit
const NUM_PAGES = 1

typealias Field Union{AbstractString,Void}

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#!/bin/bash

# I keep Julia binaries in /opt/julia with the same directory structure
# as ~/.julia to store different versions, and use this script to switch
# between them. I also like to maintain a link of the ~/.julia folder to
# ~/julia, for easier package development.

JBIN=""
PDIR=""

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A quick and dirty syntax translation / conversion reference guide to ease the transition between Python and Julia. This is not meant as a reference to the language. For that you should read the manual.

Some important differences

• Arrays in Julia are indexed starting from 1.
• In Julia classes (i.e. types) don't own methods. Methods are implementations of generic functions and are invoked in a "static style", i.e. instead of Python's str1.rstrip(), we will have rstrip( str1 ), instead of file1.close(), close( file1 ).

Some important similarities.