jfeist

#!/bin/sh
jq -r 'def banner: "\(.) " + (28-(.|length))*"-";
("Non-cell info" | banner), del(.cells), "",
(.cells[] |  ("\(.cell_type) cell" | banner),
	     "\(.source|add)",
	     if ($show_output == "1") then
                 "",
		 ( select(.cell_type=="code" and (.outputs|length)>0) |
		   ("output" | banner),
		   (.outputs[] |

thedod

config.py
env-*
*.pyc

pbugnion

This gist lets you keep IPython notebooks in git repositories. It tells git to ignore prompt numbers and program outputs when checking that a file has changed.

To use the script, follow the instructions given in the script's docstring.

For further details, read this blogpost.

The procedure outlined here is inspired by this answer on Stack Overflow.

wence-

bzr_branch=''
function find_bzr_branch {
    local dir=. dirty head nick
    # Parse all the bzr config stuff by hand, rather than calling out
    # to the binary, cos it's so damn slow.
    until [ "$dir" -ef / ]; do
        if [ -d "$dir/.bzr/checkout" ]; then
            head=$(readlink -f $dir)
            dirty=''
            bzr_branch=" ${red}b${green}"

takluyver

Copy nbflatten.py to somewhere on $PATH. Then, in the root of a git repository, run these commands:

echo "*.ipynb diff=ipynb" >> .gitattributes 
git config diff.ipynb.textconv nbflatten.py

When you change a notebook and run git diff, you'll see the diff of flattened, simplified notebooks, rather than the full JSON. This does lose some information (metadata, non-text output), but it makes it easier to see simple changes in the notebook.

This doesn't help with merging conflicting changes in notebooks. For that, see nbdiff.org.

DrPaulBrewer

#!/usr/bin/python
# Copyright 2014 Dr Paul Brewer -- Economic and Financial Technology Consulting LLC
# This script is made available under the terms of the MIT LICENSE
# Intended as a helper for refactoring template-enhanced html
# warning: overwrites existing files. 
# Does not delete or modify original file templates.html
# Thanks to Stack Overflow users for these helpful hints:
# use of htmlparser to unescape entities 
# http://stackoverflow.com/a/21894821/103081
# http://stackoverflow.com/a/663128/103081

d11wtq

docker run -rm -t -i -v $(dirname $SSH_AUTH_SOCK) -e SSH_AUTH_SOCK=$SSH_AUTH_SOCK ubuntu /bin/bash

debasishg

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

jhoff

/*
 * http://www.myersdaily.org/joseph/javascript/md5-text.html
 */

(function() {

var md5cycle = function(x, k) {
var a = x[0], b = x[1], c = x[2], d = x[3];

a = ff(a, b, c, d, k[0], 7, -680876936);

lisamelton

#!/bin/bash
#
# transcode-video.sh
#
# Copyright (c) 2013-2015 Don Melton
#

about() {
    cat <<EOF
$program 5.13 of April 8, 2015