catlan

Diff output of two lldb commands

Setup

1. Copy the contents of the last snippet (lldbinit) from the gist page, and paste into your .lldbinit file. This makes the ksdiff macro known inside lldb.
2. Put file ksdiff.py in ~/.lldb/
3. sudo pip install temp
4. Restart Xcode debug session

Example

(lldb) ksdiff <any lldb command>; <any lldb command>

bishboria

These links no longer work. Springer have pulled the free plug.

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

garybernhardt

Things that programmers don't know but should

(A book that I might eventually write!)

Gary Bernhardt

I imagine each of these chapters being about 2,000 words, making the whole book about the size of a small novel. For comparison, articles in large papers like the New York Times average about 1,200 words. Each topic gets whatever level of detail I can fit into that space. For simple topics, that's a lot of space: I can probably walk through a very basic, but working, implementation of the IP protocol.

syllog1sm

"""A simple implementation of a greedy transition-based parser. Released under BSD license."""
from os import path
import os
import sys
from collections import defaultdict
import random
import time
import pickle

SHIFT = 0; RIGHT = 1; LEFT = 2;

lelandbatey

Description

This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.

The script is here:

#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"

Results

debasishg

1. General Background and Overview

• 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.
• Models and Issues in Data Stream Systems
• 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
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

lfzawacki

#!/bin/sh

while inotifywait -e modify $1; do
    gradle --daemon test
done

plentz

# to generate your dhparam.pem file, run in the terminal
openssl dhparam -out /etc/nginx/ssl/dhparam.pem 2048

steipete

// Taken from the commercial iOS PDF framework http://pspdfkit.com.
// Copyright (c) 2014 Peter Steinberger, PSPDFKit GmbH. All rights reserved.
// Licensed under MIT (http://opensource.org/licenses/MIT)
//
// You should only use this in debug builds. It doesn't use private API, but I wouldn't ship it.

// PLEASE DUPE rdar://27192338 (https://openradar.appspot.com/27192338) if you would like to see this in UIKit.

#import <objc/runtime.h>
#import <objc/message.h>

markd2

#!/usr/sbin/dtrace -s

/* Run like:
% sudo csh
# ./spy.d $PROCESS_ID [$INTERESTING_PROBEPROV]

Prints a line of dashes every 5 seconds to delineate different experiments.
*/

#pragma D option quiet