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Update app.py
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app.py
CHANGED
@@ -1,12 +1,22 @@
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import streamlit as st
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import pandas as pd
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import requests
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from bs4 import BeautifulSoup
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from io import BytesIO
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def extract_article_info(url):
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try:
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response.raise_for_status()
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soup = BeautifulSoup(response.text, 'html.parser')
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@@ -19,15 +29,15 @@ def extract_article_info(url):
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if meta_tag and meta_tag.get('content'):
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meta_description = meta_tag['content']
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# Extract heading
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heading = soup.find('h1').get_text(strip=True) if soup.find('h1') else None
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# Extract subheadings
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subheadings = [h2.get_text(strip=True) for h2 in soup.find_all('h2')]
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# Extract all text from <p> tags and add two breaks between paragraphs
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all_paragraphs = [p.get_text(strip=True) for p in soup.find_all('p')]
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article_text = "\n\n".join(all_paragraphs)
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# Combine heading and subheadings with article text
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full_article_text = f"{heading}\n\n" if heading else ""
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@@ -42,43 +52,59 @@ def extract_article_info(url):
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except Exception as e:
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return f"Error processing the content: {e}"
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def
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#
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df = pd.read_excel(
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df.to_excel(output, index=False)
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output.seek(0)
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return output
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else:
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uploaded_file = st.file_uploader("Choose an Excel file", type=["xlsx"])
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if uploaded_file:
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# Process the file
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processed_file = process_excel(uploaded_file)
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if processed_file:
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st.success("File processed successfully!")
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st.download_button(
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label="Download Modified Excel File",
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data=processed_file,
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file_name="updated_file.xlsx",
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mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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)
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else:
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st.error("The uploaded file does not contain a column named 'URL'.")
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if __name__ == "__main__":
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main()
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import pandas as pd
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import requests
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from bs4 import BeautifulSoup
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from tqdm import tqdm
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import streamlit as st
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from io import BytesIO
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def extract_article_info(url):
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"""
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Extracts meta title, meta description, heading, subheadings, and all text in <p> tags from a blog post URL.
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Args:
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url (str): The URL of the blog post.
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Returns:
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str: A string containing the extracted information.
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"""
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try:
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# Fetch the HTML content of the URL
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response = requests.get(url, timeout=10)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, 'html.parser')
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if meta_tag and meta_tag.get('content'):
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meta_description = meta_tag['content']
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# Extract heading (Assuming <h1> is used for the main heading)
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heading = soup.find('h1').get_text(strip=True) if soup.find('h1') else None
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# Extract subheadings (Assuming <h2> tags are used for subheadings)
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subheadings = [h2.get_text(strip=True) for h2 in soup.find_all('h2')]
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# Extract all text from <p> tags and add two breaks between paragraphs
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all_paragraphs = [p.get_text(strip=True) for p in soup.find_all('p')]
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article_text = "\n\n".join(all_paragraphs) # Add two breaks between paragraphs
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# Combine heading and subheadings with article text
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full_article_text = f"{heading}\n\n" if heading else ""
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except Exception as e:
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return f"Error processing the content: {e}"
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def process_file(uploaded_file):
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# Load the Excel file
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df = pd.read_excel(uploaded_file)
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# Check if 'URL' column exists
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if 'URL' not in df.columns:
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return None, "The 'URL' column is missing from the Excel file."
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# List to hold results
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results = []
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# Use ThreadPoolExecutor for parallel processing
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with ThreadPoolExecutor() as executor:
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# Submit tasks to the executor
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future_to_url = {executor.submit(extract_article_info, url): url for url in df['URL']}
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for future in as_completed(future_to_url):
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url = future_to_url[future]
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try:
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# Append the result to the results list
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results.append(future.result())
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except Exception as e:
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# Handle exceptions during execution
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results.append(f"Error processing the URL {url}: {e}")
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# Add the results to a new column in the DataFrame
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df['Article Text'] = results
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# Save the updated DataFrame to a BytesIO object
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output = BytesIO()
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df.to_excel(output, index=False, engine='openpyxl')
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output.seek(0)
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return output, None
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# Streamlit App
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st.title("Web Article Extractor")
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st.markdown("Upload an Excel file with a column named 'URL' containing the links to process.")
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# File upload
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uploaded_file = st.file_uploader("Upload Excel file", type=["xlsx"])
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if uploaded_file is not None:
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with st.spinner("Processing your file..."):
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output, error = process_file(uploaded_file)
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if error:
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st.error(error)
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else:
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st.success("File processed successfully!")
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st.download_button(
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label="Download Processed File",
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data=output,
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file_name="processed_file.xlsx",
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mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
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)
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