Create app.py

app.py

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+import os
+import requests
+import pandas as pd
+import matplotlib as mpl
+import matplotlib.font_manager as fm
+import matplotlib.pyplot as plt
+import streamlit as st
+import time
+import json
+from io import BytesIO
+
+# Streamlit app title
+st.title("MOMO & PCHOME 商品搜索和價格分析")
+
+# 從使用者獲取搜索關鍵字和頁數
+search_keyword = st.text_input("請輸入要搜索的關鍵字: ", "筆電")
+page_number = st.number_input("請輸入要搜索的頁數: ", min_value=1, max_value=100, value=1, step=1)
+
+# 如果用戶輸入了搜索關鍵字
+if st.button("抓取並分析"):
+    # MOMO 数据抓取
+    momo_url = "https://apisearch.momoshop.com.tw/momoSearchCloud/moec/textSearch"
+    momo_headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/127.0.0.0 Safari/537.36"
+    }
+    momo_payload = {
+        "host": "momoshop",
+        "flag": "searchEngine",
+        "data": {
+            "searchValue": search_keyword,
+            "curPage": str(page_number),
+            "priceS": "0",
+            "priceE": "9999999",
+            "searchType": "1"
+        }
+    }
+    momo_response = requests.post(momo_url, headers=momo_headers, json=momo_payload)
+    
+    if momo_response.status_code == 200:
+        momo_data = momo_response.json().get('rtnSearchData', {}).get('goodsInfoList', [])
+        momo_products = []
+        for product in momo_data:
+            name = product.get('goodsName', '')
+            price = product.get('goodsPrice', '')
+            price_str = str(price).split('(')[0].replace(',', '').replace('$', '')
+            try:
+                product_price = float(price_str)
+            except ValueError:
+                product_price = 0
+            momo_products.append({'title': name, 'price': product_price})
+        momo_df = pd.DataFrame(momo_products)
+        st.write("MOMO 商品數據:", momo_df)
+    else:
+        st.error(f"MOMO 請求失敗，狀態碼: {momo_response.status_code}")
+
+    # PCHOME 数据抓取
+    pchome_url = f'https://ecshweb.pchome.com.tw/search/v3.3/all/results?q={search_keyword}&page={page_number}&sort=sale/dc'
+    pchome_response = requests.get(pchome_url)
+    
+    if pchome_response.status_code == 200:
+        pchome_data = json.loads(pchome_response.content).get('prods', [])
+        pchome_df = pd.DataFrame(pchome_data)[["name", "price"]]
+        st.write("PCHOME 商品數據:", pchome_df)
+    else:
+        st.error(f"PCHOME 請求失敗，狀態碼: {pchome_response.status_code}")
+
+    # 數據分析和視覺化
+    if not momo_df.empty:
+        momo_avg_price = momo_df['price'].mean()
+        st.write(f"MOMO 平均價格: {momo_avg_price:.2f}")
+        st.write(f"MOMO 最高價格: {momo_df['price'].max():.2f}")
+        st.write(f"MOMO 最低價格: {momo_df['price'].min():.2f}")
+
+    if not pchome_df.empty:
+        pchome_avg_price = pchome_df['price'].mean()
+        st.write(f"PCHOME 平均價格: {pchome_avg_price:.2f}")
+        st.write(f"PCHOME 最高價格: {pchome_df['price'].max():.2f}")
+        st.write(f"PCHOME 最低價格: {pchome_df['price'].min():.2f}")
+
+    # 字型設定
+    font_url = "https://drive.google.com/uc?id=1eGAsTN1HBpJAkeVM57_C7ccp7hbgSz3_&export=download"
+    font_response = requests.get(font_url)
+    with open("TaipeiSansTCBeta-Regular.ttf", "wb") as font_file:
+        font_file.write(font_response.content)
+    fm.fontManager.addfont("TaipeiSansTCBeta-Regular.ttf")
+    mpl.rc('font', family='Taipei Sans TC Beta')
+
+    # MOMO 繪製價格折線圖
+    if not momo_df.empty:
+        fig_momo, ax_momo = plt.subplots(figsize=(15, 8))
+        momo_df['price'][:70].plot(ax=ax_momo, marker='o', linestyle='-', color='skyblue', linewidth=2, markersize=8)
+        plt.title(f'MOMO 電商網站上 "{search_keyword}" 的銷售價格', fontsize=20, fontweight='bold', color='navy')
+        plt.axhline(y=momo_avg_price, color='red', linestyle='--', linewidth=2, label=f'參考價格: {momo_avg_price:.2f}')
+        plt.legend(fontsize=12, loc='upper left')
+        plt.grid(axis='y', linestyle='--', alpha=0.5)
+        plt.tight_layout()
+        st.pyplot(fig_momo)
+
+    # PCHOME 繪製價格折線圖
+    if not pchome_df.empty:
+        fig_pchome, ax_pchome = plt.subplots(figsize=(15, 8))
+        pchome_df['price'][:70].plot(ax=ax_pchome, marker='o', linestyle='-', color='skyblue', linewidth=2, markersize=8)
+        plt.title(f'PCHOME 電商網站上 "{search_keyword}" 的銷售價格', fontsize=20, fontweight='bold', color='navy')
+        plt.axhline(y=pchome_avg_price, color='red', linestyle='--', linewidth=2, label=f'參考價格: {pchome_avg_price:.2f}')
+        plt.legend(fontsize=12, loc='upper left')
+        plt.grid(axis='y', linestyle='--', alpha=0.5)
+        plt.tight_layout()
+        st.pyplot(fig_pchome)