Bastin Robin BastinRobin

Build Script Challenge

Write a python or shell script when its executed inside a directory it should convert all python .py files inside the current directory and all its subdirectories into .pyc and remove all .py files

For eg:

base(dir)
   - init.py
   - lib(dir)
     - base.py

lib.py

Common Regular Expressions for Django URLs

A list of comman regular expressions for use in django url's regex.

Example Django URLs patterns:

urlpatterns = patterns('',

	// Explicitly save/update a url parameter using HTML5's replaceState().
	function updateQueryStringParam(param, value) {
	baseUrl = [location.protocol, '//', location.host, location.pathname].join('');
	urlQueryString = document.location.search;
	var newParam = key + '=' + value,
	params = '?' + newParam;

	// If the "search" string exists, then build params from it
	if (urlQueryString) {
	keyRegex = new RegExp('([\?&])' + key + '[^&]*');

	import compileall
	import os

	# Get current working directory
	curr_dir = os.getcwd()

	# Compiles all python files to pyc
	compileall.compile_dir(curr_dir, force=True)

	# Recursively iterates to find .py files and remove them

	"""
	Machine Learning Classifier Beginner
	Classify if the given features is an apple or orange
	"""
	from sklearn import tree
	features = [[140, 1], [130, 1], [150, 0], [170, 0]] # 0 - orange and 1 - apple
	labels = [0,0,1,1] # 0 - Orange and 1 - Apple
	clf = tree.DecisionTreeClassifier()
	clf = clf.fit(features, labels)
	print clf.predict([[150, 0]])

	<html>
	<head>
	<title>Dynamic Stacked Bar Chart using d3.js</title>
	<script src="http://mbostock.github.com/d3/d3.v2.js"></script>
	<style>
	rect.a {
	fill: green;
	}
	rect.b {
	fill: orange;

	""" sampleText.txt
	1,2
	2,3
	3,6
	4,9
	5,4
	6,7
	7,7
	8,4
	9,3

	from bs4 import BeautifulSoup as bs
	import re
	import urllib2

	page = urllib2.urlopen("https://twitter.com/sumantewary")
	soup = bs(page)
	tweets = soup.findAll("p",{"class":"js-tweet-text"})

	model = Model.objects
	for k,vals in request.GET.lists():
	for v in vals:
	result = model.filter(**{"%s__in" % k: vals})