Delete app.py

app.py

@@ -1,196 +0,0 @@
-pip install selenium
-import time
-import random
-import re
-from datetime import datetime
-import pandas as pd
-from selenium import webdriver
-from selenium.webdriver.common.by import By
-from selenium.webdriver.chrome.options import Options
-from selenium.webdriver.chrome.service import Service
-from selenium.webdriver.support.ui import WebDriverWait
-from selenium.webdriver.support import expected_conditions as EC
-import gradio as gr
-
-def scrape_amazon(search_term, pincode, num_pages=5):
-    options = Options()
-    options.add_argument('--headless')
-    options.add_argument('--disable-blink-features=AutomationControlled')
-    options.add_argument('--disable-gpu')
-    options.add_argument('--no-sandbox')
-
-    driver = webdriver.Chrome(service=Service(), options=options)
-
-    all_products = []
-    seen_titles = set()
-
-    for page in range(1, num_pages + 1):
-        url = f"https://www.amazon.in/s?k={search_term}&page={page}&crid=2M096C61O4MLT&sprefix={search_term},aps,283"
-        driver.get(url)
-
-        time.sleep(random.uniform(3, 5))  # Let page load
-
-        # Scroll down to load dynamic content
-        driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
-        time.sleep(random.uniform(2, 4))
-
-        products = driver.find_elements(By.XPATH, "//div[@data-component-type='s-search-result']")
-        print(f"Scraping page {page}, found {len(products)} products...")
-
-        for product in products:
-
-            try:
-                title_elem = product.find_element(By.XPATH, ".//h2//span")
-                title = title_elem.text.strip()
-            except:
-                title = "No Title"
-
-            if title in seen_titles:
-                continue
-            seen_titles.add(title)
-
-            # Link Extraction
-            try:
-                link_elem = product.find_element(By.XPATH, ".//a[@class='a-link-normal s-no-outline']")
-                link = link_elem.get_attribute('href')
-                if link and link.startswith("/"):
-                    link = "https://www.amazon.com" + link
-            except:
-                link = "No Link"
-
-            # Selling Price Extraction
-            try:
-                price_elem = product.find_element(By.XPATH, ".//span[@class='a-price-whole']")
-                selling_price = (price_elem.text).replace(',', '').strip()
-            except:
-                try:
-                    price_elem = product.find_element(By.XPATH, ".//span[@class='a-offscreen']")
-                    selling_price = price_elem.text.replace('₹', '').replace(',', '').strip()
-                except:
-                    selling_price = "No Price"
-
-            try:
-                mrp_elem = product.find_element(By.XPATH, ".//span[@class='a-price a-text-price']//span[@class='a-offscreen']")
-                mrp = mrp_elem.text.replace('₹', '').replace(',', '').strip()
-
-            except:
-                mrp = selling_price
-
-            # Discount Extraction
-            try:
-                if selling_price != "No Price" and mrp != "No Price":
-                    discount_percent = round(100 * (float(mrp) - float(selling_price)) / float(mrp), 2)
-                else:
-                    discount_percent = 0.0
-            except:
-                discount_percent = 0.0
-
-            # Grammage Extraction
-            try:
-                grammage_match = re.search(r'(\d+\.?\d*\s?(ml|g|kg|l))', title.lower())
-                grammage = grammage_match.group(0) if grammage_match else "No Grammage"
-            except:
-                grammage = "No Grammage"
-
-            # Deal Tags Extraction
-            try:
-                badge = product.find_element(By.XPATH, ".//div[contains(@class, 'a-color-secondary')]//span[contains(translate(text(), 'ABCDEFGHIJKLMNOPQRSTUVWXYZ', 'abcdefghijklmnopqrstuvwxyz'), 'deal') or contains(translate(text(), 'ABCDEFGHIJKLMNOPQRSTUVWXYZ', 'abcdefghijklmnopqrstuvwxyz'), 'coupon') or contains(translate(text(), 'ABCDEFGHIJKLMNOPQRSTUVWXYZ', 'abcdefghijklmnopqrstuvwxyz'), 'save') or contains(translate(text(), 'ABCDEFGHIJKLMNOPQRSTUVWXYZ', 'abcdefghijklmnopqrstuvwxyz'), 'limited')]")
-                deal_tag = badge.text.strip()
-            except:
-                deal_tag = "No Deal"
-
-            # Quantity Bought Extraction
-            try:
-                qty = product.find_element(By.XPATH, ".//span[contains(text(),'bought in past month')]").text.strip()
-            except:
-                qty = "No data"
-
-            # Rating Extraction
-            try:
-                rating_elem = product.find_element(By.XPATH, ".//span[contains(@aria-label,'out of 5 stars')]")
-                rating = rating_elem.get_attribute("aria-label").split()[0]
-            except:
-                rating = "No Rating"
-
-            # Reviews Extraction
-            try:
-                reviews = product.find_element(By.XPATH, ".//a[contains(@aria-label,'ratings')]/span").text.strip()
-            except:
-                reviews = "No Reviews"
-
-            # Ad / Not Ad Detection
-            try:
-                ad_elem = product.find_element(By.XPATH, ".//span[contains(@class, 'puis-sponsored-label-text') and contains(text(), 'Sponsored')]")
-                ad_status = "Ad"
-            except:
-                ad_status = "Not Ad"
-
-            # Compile product info
-            product_data = {
-                'Title': title,
-                'Grammage': grammage,
-                'Selling Price': selling_price,
-                'MRP': mrp,
-                'Discount %': discount_percent,
-                'Deal Tags': deal_tag,
-                'Quantity Bought': qty,
-                'Rating': rating,
-                'Reviews': reviews,
-                'Link': link,
-                'Ad/Not Ad': ad_status,
-                'Date': datetime.now().strftime("%d-%m-%Y"),
-                'Search Term': search_term,
-                'Pincode': pincode,
-                'Category': search_term,
-            }
-
-            all_products.append(product_data)
-
-        time.sleep(random.uniform(2, 4))  # Pause between pages
-
-    driver.quit()
-
-    # Create DataFrame
-    df = pd.DataFrame(all_products)
-
-    # Save outputs
-    today_date = datetime.now().strftime("%Y-%m-%d")
-    filename_base = f"{search_term}scrape{today_date}"
-
-    excel_path = f"{filename_base}.xlsx"
-    csv_path = f"{filename_base}.csv"
-    json_path = f"{filename_base}.json"
-
-    df.to_excel(excel_path, index=False)
-    df.to_csv(csv_path, index=False)
-    df.to_json(json_path, orient="records", lines=True)
-
-    return excel_path, csv_path, json_path
-
-
-def scrape_and_return_files(product_name, pincode, num_pages):
-    excel_path, csv_path, json_path = scrape_amazon(product_name, pincode, int(num_pages))
-    return excel_path, csv_path, json_path
-
-
-with gr.Blocks() as demo:
-    gr.Markdown("## 🛒 Amazon Scraper")
-    
-    with gr.Row():
-        product_name = gr.Textbox(label="Product Name", placeholder="e.g., atta")
-        pincode = gr.Textbox(label="Pincode", placeholder="e.g., 400076")
-        num_pages = gr.Number(label="Number of Pages", value=2)
-
-    scrape_button = gr.Button("Scrape Amazon!")
-
-    output_excel = gr.File(label="Download Excel (.xlsx)")
-    output_csv = gr.File(label="Download CSV (.csv)")
-    output_json = gr.File(label="Download JSON (.json)")
-
-    scrape_button.click(
-        scrape_and_return_files,
-        inputs=[product_name, pincode, num_pages],
-        outputs=[output_excel, output_csv, output_json]
-    )
-
-demo.launch(share=True)