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%load_ext autoreload
%autoreload 2 
%matplotlib inline


    

    




The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

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import pandas as pd
import numpy as np
import os
import matplotlib.pyplot as plt


    

In [36]:

    

#%load_ext soup
import requests
from bs4 import BeautifulSoup
from os import path


    

In [37]:

    

url = "http://www.brandsoftheworld.com/logos/countries/ch"


    

In [47]:

    

def retrieve_swiss_brands():
    arguments = {'page':0} # grab HTML data
    all_brands = []
    # retrieve the html web page containing the list of brands
    r = requests.get(url, params=arguments)
    soup_of_brands = BeautifulSoup(r.text, 'html.parser')
    # select the tags containing the names of these brands
    resulting_brands = soup_of_brands.findAll("span", { "class" : "title" })
    # remove the tags and only keep the actual brands
    brands = [brand.string for brand in resulting_brands]
    while(len(brands) > 0):
        # print progress
        print("Finished page "+str(arguments['page'])+" of swiss brands")
        all_brands += brands
        arguments['page'] += 1
        # rinse and repeat
        r = requests.get(url, params=arguments)
        soup_of_brands = BeautifulSoup(r.text, 'html.parser')
        resulting_brands = soup_of_brands.findAll("span", { "class" : "title" })
        brands = [brand.string for brand in resulting_brands]
    return all_brands


    

In [48]:

    

all_swiss_brands = retrieve_swiss_brands()


    

    




Finished page 0 of swiss brands
Finished page 1 of swiss brands
Finished page 2 of swiss brands
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Finished page 58 of swiss brands

In [50]:

    

len(all_swiss_brands)


    

    
Out[50]:





1885

In [52]:

    

import pickle

with open('data/all_swiss_brands.pickle', 'wb') as fp:
    pickle.dump(all_swiss_brands, fp)


    

In [53]:

    

with open ('data/all_swiss_brands.pickle', 'rb') as fp:
    brand_list = pickle.load(fp)


    

In [55]:

    

len(brand_list)


    

    
Out[55]:





1885

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