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| import streamlit as st | |
| import pandas as pd | |
| import requests | |
| from bs4 import BeautifulSoup | |
| from io import BytesIO | |
| def extract_article_info(url): | |
| try: | |
| response = requests.get(url) | |
| response.raise_for_status() | |
| soup = BeautifulSoup(response.text, 'html.parser') | |
| # Extract meta title | |
| meta_title = soup.find('title').get_text(strip=True) if soup.find('title') else None | |
| # Extract meta description | |
| meta_description = None | |
| meta_tag = soup.find('meta', attrs={'name': 'description'}) | |
| if meta_tag and meta_tag.get('content'): | |
| meta_description = meta_tag['content'] | |
| # Extract heading | |
| heading = soup.find('h1').get_text(strip=True) if soup.find('h1') else None | |
| # Extract subheadings | |
| subheadings = [h2.get_text(strip=True) for h2 in soup.find_all('h2')] | |
| # Extract all text from <p> tags and add two breaks between paragraphs | |
| all_paragraphs = [p.get_text(strip=True) for p in soup.find_all('p')] | |
| article_text = "\n\n".join(all_paragraphs) | |
| # Combine heading and subheadings with article text | |
| full_article_text = f"{heading}\n\n" if heading else "" | |
| for subheading in subheadings: | |
| full_article_text += f"{subheading}\n\n" | |
| full_article_text += article_text | |
| return full_article_text | |
| except requests.exceptions.RequestException as e: | |
| return f"Error fetching the URL: {e}" | |
| except Exception as e: | |
| return f"Error processing the content: {e}" | |
| def process_excel(file): | |
| # Read the uploaded Excel file | |
| df = pd.read_excel(file) | |
| if 'URL' in df.columns: | |
| # Apply extract_article_info to each URL and store the result in a new column | |
| df['Article Text'] = df['URL'].apply(extract_article_info) | |
| # Save the updated DataFrame to a BytesIO object to prepare it for download | |
| output = BytesIO() | |
| df.to_excel(output, index=False) | |
| output.seek(0) | |
| return output | |
| else: | |
| return None | |
| def main(): | |
| st.title("Excel URL Processor") | |
| st.markdown("Upload an Excel file with a column named 'URL' to extract article information.") | |
| # Upload Excel file | |
| uploaded_file = st.file_uploader("Choose an Excel file", type=["xlsx"]) | |
| if uploaded_file: | |
| # Process the file | |
| processed_file = process_excel(uploaded_file) | |
| if processed_file: | |
| st.success("File processed successfully!") | |
| st.download_button( | |
| label="Download Modified Excel File", | |
| data=processed_file, | |
| file_name="updated_file.xlsx", | |
| mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" | |
| ) | |
| else: | |
| st.error("The uploaded file does not contain a column named 'URL'.") | |
| if __name__ == "__main__": | |
| main() | |