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import re
from collections import defaultdict
from pprint import pprint

import requests
from bs4 import BeautifulSoup


departments = [
    "https://ocw.mit.edu/courses/architecture",

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<img srcset="{{ site.image_path }}{{page.bucket}}/{{img.sizes[0]}}.xs.{{img.sizes[1]}} 600w,
             {{ site.image_path }}{{page.bucket}}/{{img.sizes[0]}}.s.{{img.sizes[1]}} 800w,
             {{ site.image_path }}{{page.bucket}}/{{img.sizes[0]}}.{{img.sizes[1]}} 1280w,
             {{ site.image_path }}{{page.bucket}}/{{img.sizes[0]}}.m.{{img.sizes[1]}} 2000w,
             {{ site.image_path }}{{page.bucket}}/{{img.sizes[0]}}.l.{{img.sizes[1]}} 3000w"
     sizes="(max-width: 800px) 600px,
            (max-width: 1064px) 800px,
            (max-width: 1700px) 1280px,
            (max-width: 3000px) 2000px,
            3000px"

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import json
import os

from collections import Counter
# pip install TwitterAPI
from TwitterAPI import TwitterAPI

# Edit ff.py for your account. Go to https://apps.twitter.com/ to get API keys
# Don't forget to fill in your  screen name (or someone else's).

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rm(list=ls())

library(ggplot2)
library(ggmap)
library(plotKML)

cityMap <- qmap(location = 'san francisco', extent = 'device', zoom=12, source="google", maptype="terrain")
cityMap
kinds <- c('transport', 'walking', 'cycling')
colors <- c('#FF7400', '#1240AB', '#FFD300')

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library(XML)
library(ggplot2)

df <- readHTMLTable("http://projects.dailycal.org/paychecker")[[1]]
colnames(df)[4] <- "Salary"
df$Salary <- as.numeric(gsub('[$,]', '', df$Salary))

p <- ggplot(df, aes(x=Department, y=Salary)) + coord_flip()
p + geom_boxplot(aes(color=Rank,
                     x=reorder(Department, Salary, FUN=max))) +

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import threading

n = 0


def foo():
    global n
    n += 1

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# Timing script to compare various ways to compute the mean of list of ints
# Short explanation, and results of the experiment can be found here:
# www.faingezicht.com/articles/2016/12/25/means/

import random
import timeit
import statistics
import numpy as np

random.seed(1)

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import os
import re
import shlex
import requests
import subprocess

from multiprocessing import Pool
from bs4 import BeautifulSoup

reg = re.compile("http:\/\/files.*.mp3")

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Radiohead
LCD Soundsystem
Lionel Richie
Lana Del Rey
J. Cole
Duran Duran
Zedd
Ryan Adams
Major Lazer
Air