milkersarac

Shallow

Real unit test (isolation, no children render)

Simple shallow

Calls:

• constructor
• render

milkersarac

#!/bin/bash
# MUSTAFA ILKER SARAC
# This script can be used for building multiple react-native apps from a single git repo.
# It needs master files for the default configurations.
# master files are generally the copy of the current config files of that git repo.
# If current state of the app changes i.e. adding new 3rd party components so package.json changes;
# then one should be responsible to reflect these changes to the master files to be synced with the current state of the repo.
# This script can be used to alter the current state, so that new apps could be generated with new names etc.
# scriptAndroid.sh
# "chmod +x ./scriptAndroid" to make script executable.

milkersarac

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milkersarac

A Git Workflow for Agile Teams

Mar 2nd, 2009

An efficient workflow for developers in Agile teams that handles features and bugs while keeping a clean and sane history.

At Hashrocket we use git both internally and in our Agile mentoring and training. Git gives us the flexibility to design a version control workflow that meets the needs of either a fully Agile team or a team

milkersarac

#!/bin/bash
from bs4 import BeautifulSoup
import requests
import urllib2
import os
import re, urlparse
import time
import pdb
from interruptingcow import timeout

milkersarac

// create file:
sudo vim /usr/share/applications/intellij.desktop

// add the following
[Desktop Entry]
Version=13.0
Type=Application
Terminal=false
Icon[en_US]=/home/rob/.intellij-13/bin/idea.png
Name[en_US]=IntelliJ

milkersarac

function phow_caltech101()
% PHOW_CALTECH101 Image classification in the Caltech-101 dataset
%   This program demonstrates how to use VLFeat to construct an image
%   classifier on the Caltech-101 data. The classifier uses PHOW
%   features (dense SIFT), spatial histograms of visual words, and a
%   Chi2 SVM. To speedup computation it uses VLFeat fast dense SIFT,
%   kd-trees, and homogeneous kernel map. The program also
%   demonstrates VLFeat PEGASOS SVM solver, although for this small
%   dataset other solvers such as LIBLINEAR can be more efficient.
%

milkersarac

function mosaic = sift_mosaic(im1, im2)
% SIFT_MOSAIC Demonstrates matching two images using SIFT and RANSAC
%
%   SIFT_MOSAIC demonstrates matching two images based on SIFT
%   features and RANSAC and computing their mosaic.
%
%   SIFT_MOSAIC by itself runs the algorithm on two standard test
%   images. Use SIFT_MOSAIC(IM1,IM2) to compute the mosaic of two
%   custom images IM1 and IM2.

milkersarac

#!/bin/bash

# https://gist.github.com/robwierzbowski/5430952/
# Create and push to a new github repo from the command line.  
# Grabs sensible defaults from the containing folder and `.gitconfig`.  
# Refinements welcome.

# Gather constant vars
CURRENTDIR=${PWD##*/}
GITHUBUSER=$(git config github.user)

milkersarac

#!/bin/bash
//install opencv to machine
arch=$(uname -m)
if [ "$arch" == "i686" -o "$arch" == "i386" -o "$arch" == "i486" -o "$arch" == "i586" ]; then
flag=1
else
flag=0
fi
echo "Installing OpenCV 2.4.3"
mkdir OpenCV