ZacCranko

push!(LOAD_PATH, pwd())

# Run _init.jl at runtime if it exists
if VERSION < v"0.4-"
	if isinteractive() && isfile("_init.jl")
		info("Found ", joinpath(pwd(),"_init.jl"))
		include(joinpath(pwd(),"_init.jl"))
	end
else
	atreplinit() do repl

Ismael-VC

# Installation: 
# - Put this in your .bash_profile
# - Replace my directory with your exobrain directory on line 10
#
# What you get:
#    A Jupyter notebook open on a well-defined port that is always
#    on for exobrain-ing your ideas...

exec 6<>/dev/tcp/localhost/10000 || (
    source activate py27 && 

jbn

# Installation: 
# - Put this in your .bash_profile
# - Replace my directory with your exobrain directory on line 10
#
# What you get:
#    A Jupyter notebook open on a well-defined port that is always
#    on for exobrain-ing your ideas...

exec 6<>/dev/tcp/localhost/10000 || (
    source activate py27 && 

jbn

# Requested gist of code to produce:
#   https://www.scribd.com/doc/271871142/Julia-Type-Hierarchy
# 
# I just redirected the output to a dot file, then executed:
#    dot -Tpdf julia.dot -o julia.pdf
function print_type_tree(t, parent=Any, seen=Set{DataType}())
    # Avoid redundant edges.
    t ∈ seen && return 
    push!(seen, t)
    

meggart

if VERSION > v"0.4.0-dev+4268"
	const marcoexpandkeys = Dict{Any,Any}("^I" => function (s,o...)
           if !isempty(s)
               
                   line = parse(Base.LineEdit.input_string(s))
                   s.kill_buffer=Base.LineEdit.input_string(s)
                   Base.LineEdit.edit_clear(s)
                   Base.LineEdit.edit_insert(s,string(macroexpand(line)))
               
           end

Andy-P

# This code is part of a presentation on streaming analytics in Julia
# It was inspired by a number of individuals and makes use of some of their ideas
#     1. FastML.com got me thinking about inline processing after 
#        reading his great Vowpal Wabbit posts
#     2. John Lanford and his fantastic Vowpal Wabbit library. 
#        Check out his NYU video course to learn more (see below)
#     3. John Myles White's presentation on online SDG and his StreamStats.jl library 
# Thank you all!

nrshrivatsan

#Importing Requests package
Pkg.add("Requests")
using Requests.get;

import JSON;

url = "http://query.yahooapis.com/v1/public/yql?q=select%20DaysRange%20from%20yahoo.finance.quotes%20where%20symbol%20in%20%28%22EBAY%22,%22GOOG%22%29%20&env=http://datatables.org/alltables.env&format=json";

#Reads the data from HTTP URL
es = get(url);

kimwalisch

/// @file     segmented_sieve.cpp
/// @author   Kim Walisch, <[email protected]> 
/// @brief    This is a simple implementation of the segmented sieve of
///           Eratosthenes with a few optimizations. It generates the
///           primes below 10^9 in 0.8 seconds (single-threaded) on an
///           Intel Core i7-6700 3.4 GHz CPU.
/// @license  Public domain.

#include <iostream>
#include <algorithm>

Ismael-VC

## Algoritmos de caminos más cortos

from estructuras import Cola, ColaMin
from conectividad import ordenamiento_topologico

inf = float('inf') #Tratar infinito como un numero

def recorrido_a_lo_ancho(G, s):
    dist, padre = {v:inf for v in G}, {v:v for v in G}
    dist[s] = 0

knkillname

## Algoritmos de caminos más cortos

from estructuras import Cola, ColaMin
from conectividad import ordenamiento_topologico

inf = float('inf') #Tratar infinito como un numero

def recorrido_a_lo_ancho(G, s):
    dist, padre = {v:inf for v in G}, {v:v for v in G}
    dist[s] = 0