Create app.py

app.py

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+import requests
+from bs4 import BeautifulSoup
+import pandas as pd
+from urllib.parse import quote
+import streamlit as st
+import json
+
+@st.cache_data
+def scrape_e_commerce(nama_barang, num_items):
+    products = []
+    page = 1
+    query = quote(nama_barang)
+    progress_text = "Scraping in progress. Please wait."
+    my_bar = st.progress(len(data), text=progress_text)
+    
+    while len(products) < num_items:
+        url = f"https://www.klikindomaret.com/search/?key={query}&categories=&productbrandid=&sortcol=&pagesize=54&page={page}&startprice=&endprice=&attributes=&ShowItem="
+        response = requests.get(url)
+        soup = BeautifulSoup(response.text, 'html.parser')
+
+        product_list = soup.find_all('a', href=True)
+
+        for product in product_list:
+            product_href = product['href']
+            if '/product/' in product_href:
+                product_name = product.find('div', class_='title').text.strip()
+                product_price = product.find('span', class_='normal price-value').text.strip()
+                product_link = f"https://www.klikindomaret.com{product_href}"
+                products.append({
+                    'product': product_name,
+                    'price': product_price,
+                    'link': product_link
+                })
+                
+        prop = min(len(products) / num_items, 1)
+        my_bar.progress(prop, text=progress_text)
+        if len (products) > num_items :
+          products = products[:num_items]
+          break
+        page += 1
+        
+    time.sleep(1)   
+    my_bar.empty()
+    return products
+
+#---------------------------------------------------User Interface----------------------------------------------------------------------
+
+# Streamlit UI
+st.title("Scraping E-Commerce")
+
+with st.expander("Settings :"):
+    # Pilihan untuk memilih situs web
+    selected_site = st.selectbox("Pilih Situs Web :", ["klikindomaret.com"])
+    
+    nama_barang = st.text_input("Masukkan Nama Barang :")
+    estimated_num_items = st.number_input("Masukkan Estimasi Banyak Data :", min_value = 1, step = 1, placeholder="Type a number...")
+    
+    download_format = st.selectbox("Pilih Format Unduhan :", ["XLSX", "CSV", "JSON"])
+    st.info('Tekan "Mulai Scraping" kembali jika tampilan menghilang ', icon="ℹ️")
+
+# Variabel tersembunyi untuk menyimpan hasil scraping
+hidden_data = []
+
+scraping_done = False  # Tambahkan variabel ini
+
+if selected_site == "klikindomaret.com":
+    if st.button("Mulai Scraping"):
+        if not query:
+            st.error("Mohon isi query.")
+        else:
+            data_df = scrape_e_commerce(nama_barang, estimated_num_items)
+            hidden_data = data_df  # Simpan data ke dalam variabel tersembunyi
+            scraping_done = True  # Set scraping_done menjadi True
+
+scraped_products = scrape_e_commerce(nama_barang, estimated_num_items)
+
+
+
+# Simpan DataFrame ke dalam file
+output_file = f"scraped_{nama_barang}.xlsx"
+output_file_csv = f"scraped_{nama_barang}.csv"
+output_file_json = f"scraped_{nama_barang}.json"
+
+
+#---------------------------------------------------Download File & Hasil Scraping----------------------------------------------------------------------
+
+# Tampilkan hasil scraping
+if scraping_done:
+    if hidden_data:
+        # Menampilkan hasil sentimen dalam kotak yang dapat diperluas
+        with st.expander(f"Hasil Scraping {selected_site} :"):
+            st.write(pd.DataFrame(scraped_products)
+        if download_format == "XLSX":
+            df = pd.DataFrame(scraped_products)
+            df.to_excel(output_file, index=False)
+            st.download_button(label=f"Unduh XLSX ({len(hidden_data)} data)", data=open(output_file, "rb").read(), key="xlsx_download", file_name=output_file)
+        elif download_format == "CSV":
+            df = pd.DataFrame(scraped_products)
+            csv = df.to_csv(index=False)
+            st.download_button(label=f"Unduh CSV ({len(hidden_data)} data)", data=csv, key="csv_download", file_name=output_file_csv)
+        elif download_format == "JSON":
+            json_data = pd.DataFrame(scraped_products).to_json(orient="records")
+            st.download_button(label=f"Unduh JSON ({len(hidden_data)} data)", data=json_data, key="json_download", file_name=output_file_json)
+if not scraping_done:
+    st.write("Tidak ada data untuk diunduh.")
+
+st.divider()
+github_link = "https://github.com/naufalnashif/"
+st.markdown(f"GitHub: [{github_link}]({github_link})")
+instagram_link = "https://www.instagram.com/naufal.nashif/"
+st.markdown(f"Instagram: [{instagram_link}]({instagram_link})")
+st.write('Terima kasih telah mencoba demo ini!')