Aleck Landgraf alecklandgraf

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The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

In General

Values

"Build tools for others that you want to be built for you." - Kenneth Reitz
"Simplicity is alway better than functionality." - Pieter Hintjens

Python Engineer Take Home Project

Building Energy strives to help businesses and governments understand where energy usage occurs, and how to improve energy efficiency. Let’s look at some real-world data in a similar field; check out World Bank Data on Carbon Emissions. Click "Download Data" and select the format you want to work with, (CSV might be simplest).

Let’s build a simple application to read in this data from the commandline and sort the rows by a function applied across the columns of said rows.

We should be able to answer the following questions:

Sort countries according to the average change in carbon emissions per capita (ascending, descending, etc.).

	<html>
	<head>
	<title>React StopWatch sample</title>
	<meta name="viewport" content="width=device-width">
	<script src="http://fb.me/react-0.13.1.js"></script>
	<script src="http://fb.me/JSXTransformer-0.13.1.js"></script>
	</head>
	<body>
	<script type="text/jsx">
	var StopWatch = React.createClass({

	#! /usr/bin/env python

	import redis
	import random
	import pylibmc
	import sys

	r = redis.Redis(host = 'localhost', port = 6389)
	mc = pylibmc.Client(['localhost:11222'])

	def dicty(d, key=None):
	"""removes empty string and None values from a nested dict, if key, then prints all values within the dict"""
	if key:
	for k, v in d.items():
	if k.lower() == key.lower():
	print "{}: {}".format(k, v)
	if isinstance(v, dict):
	dicty(v, key)
	if isinstance(v, list):
	for x in v:

	//Practically all this code comes from https://github.com/alangrafu/radar-chart-d3
	//I only made some additions and aesthetic adjustments to make the chart look better
	//(of course, that is only my point of view)
	//Such as a better placement of the titles at each line end,
	//adding numbers that reflect what each circular level stands for
	//Not placing the last level and slight differences in color
	//
	//For a bit of extra information check the blog about it:
	//http://nbremer.blogspot.nl/2013/09/making-d3-radar-chart-look-bit-better.html

	def reindex_orgs(org_ids):
	from seed.services import es_search_query
	from elasticsearch import Elasticsearch
	s = es_search_query()
	s = s.filter('terms', building_snapshot__super_organization=org_ids)
	from seed.services import elasticsearch_client
	es = elasticsearch_client()
	es.delete_by_query(index=settings.ES_INDEX, doc_type='canonical_building', body=s.to_dict())
	from seed.utils.seed_elasticsearch import canon_serializer
	import itertools

	description "uWSGI server for electris CMS"

	start on runlevel [2345] # start on all runlevels.
	stop on runlevel [!2345] # stop when shutting down.

	respawn # respawn if job crashes or is stopped ungracefully.
	env DEPLOYMENT_TARGET=production # set any environment variables you like here.
	env DJANGO_SETTINGS_FILE=conf/settings.py # more environment variables if you like.
	env PYTHONPATH=/home/ubuntu/apps/my_app:/home/ubuntu/.virtualenv/my_app

	try:
	import xlrd

	def XLSDictReader(f, sheet_index=0):
	data = mmap.mmap(f.fileno(), 0, access=mmap.ACCESS_READ)
	book = xlrd.open_workbook(file_contents=data)
	sheet = book.sheet_by_index(sheet_index)

	def item(i, j):
	return (sheet.cell_value(0,j), sheet.cell_value(i,j))