tdd

# Put this in your ~/.gitconfig or ~/.config/git/config
# Windows users: "~" is your profile's home directory, e.g. C:\Users\<YourName>
[user]
  name = Your Full Name
  email = your@email.tld
[color]
  # Enable colors in color-supporting terminals
  ui = auto
[alias]
  # List available aliases

kgorman

/* MongoDB cheat sheet */

// replication lag via serverStatus()
db._adminCommand( { serverStatus : 1 , repl ; 2 } )

// stats
db.stats()
db.foo.stats()

// size of BSON of some query

DazWorrall

in upload handler
in file close
..
----------------------------------------------------------------------
Ran 2 tests in 0.021s

OK

lost-theory

import unittest
from app import app
from cStringIO import StringIO

class UploadTest(unittest.TestCase):
    def setUp(self):
        self.app = app
        self.app.config['TESTING'] = True
        self.client = self.app.test_client()

areski

# Install xapian Core and Bindings

apt-get install zlib1g-dev
apt-get install g++

curl -O http://oligarchy.co.uk/xapian/1.2.18/xapian-core-1.2.18.tar.xz
curl -O http://oligarchy.co.uk/xapian/1.2.18/xapian-bindings-1.2.18.tar.xz

unxz xapian-core-1.2.18.tar.xz
unxz xapian-bindings-1.2.18.tar.xz

rain1024

PdfLatex is a tool that converts Latex sources into PDF. This is specifically very important for researchers, as they use it to publish their findings. It could be installed very easily using Linux terminal, though this seems an annoying task on Windows. Installation commands are given below.

• Install the TexLive base

sudo apt-get install texlive-latex-base

• Also install the recommended and extra fonts to avoid running into the error [1], when trying to use pdflatex on latex files with more fonts.

Vestride

Encoding Video

Installing

Install FFmpeg with homebrew. You'll need to install it with a couple flags for webm and the AAC audio codec.

brew install ffmpeg --with-libvpx --with-libvorbis --with-fdk-aac --with-opus

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

kastnerkyle

raise ValueError("DEPRECATED/FROZEN - see https://github.com/kastnerkyle/tools for the latest")

# License: BSD 3-clause
# Authors: Kyle Kastner
# Harvest, Cheaptrick, D4C, WORLD routines based on MATLAB code from M. Morise
# http://ml.cs.yamanashi.ac.jp/world/english/
# MGC code based on r9y9 (Ryuichi Yamamoto) MelGeneralizedCepstrums.jl
# Pieces also adapted from SPTK
from __future__ import division
import numpy as np

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats