<jupyter_start><jupyter_text>HTML Page Read and Upload<jupyter_code># Import useful libraries and classes.
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
#html page upload and read in web_page variable.
my_url=  "https://www.flipkart.com/search?p%5B%5D=facets.brand%255B%255D%3DSamsung&sid=tyy%2F4io&sort=recency_desc&wid=1.productCard.PMU_V2_1"
web_page= uReq(my_url)
page_html= web_page.read()<jupyter_output><empty_output><jupyter_text>Parsing<jupyter_code>#html parser. It is to beautify the HTML code.
page_soup= soup(page_html)
page_soup<jupyter_output><empty_output><jupyter_text>Extraction of information<jupyter_code>#read class attribute from web page in containers variable.
# Print the length of containers.
containers= page_soup.findAll("div", {"class": "_1-2Iqu row"})
print(len(containers))
# Extract the model name of 6th phone in the list.

# how many elements does 'tVe95H' class contained in it?

# Read the camera specification of 8th phone in the list.<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.09739633558341369, 'fraction_numerical': 0.020250723240115717, 'mean_word_length': 7.370967741935484, 'pattern_counts': {'":': 1, '<': 13, '<?xml version=': 0, '>': 13, 'https://': 1, 'lorem ipsum': 0, 'www.': 1, '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': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '21593', 'license': 'MIT', 'n_tokens_mistral': 385, 'n_tokens_neox': 370, 'n_words': 97, 'path': 'Data Science/EDA/.ipynb_checkpoints/Flipkart_Web+Scraping_Graded_Question-checkpoint.ipynb', 'repo_name': 'manash-ranjan-khamari/notebook', 'size': '1037'}