<jupyter_start><jupyter_text>Web Scraping<jupyter_code># Dependencies
from bs4 import BeautifulSoup
import requests
# URL of page to be scraped
url = "http://dog.rescueme.org/California"
response = requests.get(url)
print(response.text)
soup = BeautifulSoup(response.text, 'html.parser')
print(soup.prettify())
names = soup.find_all('span', class_= '_cpn')

for name in names:
    print(name.text)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1288056206088993, 'fraction_numerical': 0.00234192037470726, 'mean_word_length': 6.781818181818182, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '490480', 'license': 'MIT', 'n_tokens_mistral': 158, 'n_tokens_neox': 153, 'n_words': 33, 'path': '.ipynb_checkpoints/Pet_Adoption_Analysis_REVISED-checkpoint.ipynb', 'repo_name': 'mhandipranata/ETL-Challenge-PetAdoption', 'size': '427'}