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Html – Using Python 3.9, How do I get in MS excel ALL physical addresses from the URL -> https://www.tamoil.ch/en/store-locator

I would like to get all physical addresses in MS-excel from this url [https://www.tamoil.ch/en/store-locator]. The spreadsheet only has a header, but no output from the code.

import requests
from bs4 import BeautifulSoup
import pandas as pd

# Send a GET request to the website
url = "https://www.tamoil.ch/en/store-locator"

response = requests.get(url)

# Parse the HTML content
soup = BeautifulSoup(response.content, 'html.parser')

# Find all elements containing store information
store_elements = soup.find_all('div', class_='store-element')

# Extract addresses
addresses = []
for store in store_elements:
    address = store.find('p', class_='address').text.strip()
    addresses.append(address)

# Create a DataFrame
df = pd.DataFrame({'Address': addresses})

# Save to Excel file
excel_file = 'tamoil_addresses.xlsx'
df.to_excel(excel_file, index=False)

print(f"Addresses saved to {excel_file}")
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2

Answers


  1. 0

    Can you check this out if this is what you are looking for?

    import requests
import pandas as pd
from requests.packages.urllib3.exceptions import InsecureRequestWarning


requests.packages.urllib3.disable_warnings(InsecureRequestWarning)

url = "https://www.tamoil.ch/page-data/en/store-locator/page-data.json" #address and location in JSON format

resp = requests.get(url, verify=False)
data = resp.json()['result']['data']['allStation']['nodes']

slug_r = []
name_r = []
lat_r = []
lng_r = []
street_r = []
zip_code_r = []
city_r = []
phone_r = []

for i in data:
    slug = i['slug']
    name = i['name']
    lat = i['lat']
    lng = i['lng']
    street = i['street']
    zip_code = i['zip']
    city = i['city']['name']
    phone_1 = i['phone_1']
    
    #append 
    slug_r.append(slug)
    name_r.append(name)
    lat_r.append(lat)
    lng_r.append(lng)
    street_r.append(street)
    zip_code_r.append(zip_code)
    city_r.append(city)
    phone_r.append(phone_1)
    print(f"-----------------------nSLUG:   {slug}nNAME:   {name}nLATITUDE:   {lat}nLONITUDE:   {lng}nSTREET ADDRESS:   {street}nPHONE:   {phone_1}nZIP CODE:   {zip_code}nCITY:   {city}")

data_dict = {
    'SLUG': slug_r,
    'NAME': name_r,
    'LATITUDE': lat_r,
    'LONGITUDE': lng_r,
    'STREET': street_r,
    'ZIP CODE': zip_code_r,
    'PHONE': phone_r,
    'CITY': city_r
}
df = pd.DataFrame(data_dict)
df.to_excel('Address.xlsx', index=False)

    I used their page-data (JSON) endpoint to grab all these addresses.

    Let me know if I missed something based on your question

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  2. 0

    All the information you need can be found here which means that you only have to parse a JSON document to get the required results.

    import requests
import pandas as pd

filename = "tamoil.xlsx"
url = "https://www.tamoil.ch/page-data/en/store-locator/page-data.json"
# add other elements of interest to this list
keylist = ["name", "street", "zip"]

def make_dict(node):
    return {key.title(): node.get(key, "n/a") for key in keylist}

with requests.get(url) as response:
    response.raise_for_status()
    data = response.json()
    addresses = [make_dict(n) for n in data["result"]["data"]["allStation"]["nodes"]]
    df = pd.DataFrame(addresses)
    df.to_excel(filename, index=False)
    for address in addresses[:10]:  # sample
        print(address)

    Output:

    {'Name': 'TAMOIL Basel Aéroport', 'Street': 'Parkplatz 11 Aéroport', 'Zip': '4030'}
{'Name': 'TAMOIL Bellwald', 'Street': 'Fuergangen', 'Zip': '3997'}
{'Name': 'TAMOIL Commugny', 'Street': 'Rte de Genève 19', 'Zip': '1291'}
{'Name': 'TAMOIL Flawil', 'Street': 'St.Galler-Strasse 144', 'Zip': '9230'}
{'Name': 'TAMOIL Glarus', 'Street': 'Buchholzstrasse 44', 'Zip': '8750'}
{'Name': 'TAMOIL Grandson', 'Street': 'Rue de Neuchâtel 43 / CP91', 'Zip': '1422'}
{'Name': 'TAMOIL Hermance', 'Street': "564, rte D'Hermance", 'Zip': '1248'}
{'Name': "TAMOIL L'Orient", 'Street': '20, rue du Pont-Neuf', 'Zip': '1341'}
{'Name': 'TAMOIL Le Châble (Le Cotterg)', 'Street': 'Le Cotterg', 'Zip': '1934'}
{'Name': 'TAMOIL Le Pont', 'Street': 'Sur les Quais 39', 'Zip': '1342'}
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