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Update app.py
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app.py
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@@ -1,133 +1,338 @@
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| 1 |
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import requests
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from bs4 import BeautifulSoup
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import pandas as pd
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from typing import List, Tuple
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import time
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from pandas.io.formats.style import Styler
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import streamlit as st
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import os
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from datetime import datetime
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import io
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BASE_URL = "https://cgc.twse.com.tw/front/chPage"
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def fetch_page(offset: int, max_per: int = 30, fmt: str = "") -> str:
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params = {"offset": offset, "max": max_per, "format": fmt}
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resp = requests.get(BASE_URL, params=params, timeout=10)
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resp.raise_for_status()
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return resp.text
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def parse_companies(html: str) -> List[Tuple[str, str, str]]:
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soup = BeautifulSoup(html, "html.parser")
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results = []
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for tr in soup.select("table tr"):
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tds = tr.find_all("td")
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if len(tds) >= 3:
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code = tds[1].get_text(strip=True)
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| 27 |
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name = tds[2].get_text(strip=True)
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| 28 |
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link_tag = tds[2].find("a")
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| 29 |
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url = link_tag["href"].strip() if link_tag and "href" in link_tag.attrs else ""
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if code.isdigit():
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results.append((code, name, url))
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return results
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| 33 |
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def collect_all(start_offset: int = 0, max_per: int = 30, max_pages: int = 100, progress_bar=None, status_text=None) -> pd.DataFrame:
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all_rows = []
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| 36 |
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offset = start_offset
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| 37 |
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| 38 |
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for i in range(max_pages):
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try:
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# 更新進度條和狀態
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| 41 |
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if progress_bar:
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| 42 |
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progress_bar.progress((i + 1) / max_pages)
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| 43 |
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if status_text:
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| 44 |
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status_text.text(f"正在爬取第 {i + 1} 頁,偏移量: {offset}")
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| 45 |
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| 46 |
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html = fetch_page(offset, max_per)
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| 47 |
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rows = parse_companies(html)
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| 48 |
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if not rows:
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| 49 |
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if status_text:
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| 50 |
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status_text.text(f"已完成爬取,共處理 {i + 1} 頁")
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| 51 |
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break
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| 52 |
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all_rows.extend(rows)
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| 53 |
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offset += max_per
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| 54 |
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time.sleep(0.5)
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| 55 |
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except Exception as e:
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| 56 |
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if status_text:
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| 57 |
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status_text.text(f"錯誤發生於偏移量 {offset}: {e}")
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| 58 |
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break
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| 59 |
+
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| 60 |
+
# 加入編號欄位
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| 61 |
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df = pd.DataFrame(all_rows, columns=["公司代碼", "公司名稱", "公司網址"])
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| 62 |
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df.insert(0, "編號", range(1, len(df) + 1))
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| 63 |
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return df
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| 64 |
+
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| 65 |
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def style_dataframe(df: pd.DataFrame) -> Styler:
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| 66 |
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"""
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| 67 |
+
設定DataFrame的樣式:
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| 68 |
+
- 編號、公司代碼、公司名稱欄位標題為藍色背景
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| 69 |
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- 每個欄位的值交替黃色背景
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| 70 |
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"""
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| 71 |
+
def header_style(s):
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| 72 |
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"""設定標題樣式"""
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| 73 |
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styles = []
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| 74 |
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for col in s.index:
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| 75 |
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if col in ["編號", "公司代碼", "公司名稱"]:
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| 76 |
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styles.append('background-color: #4472C4; color: white; font-weight: bold')
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| 77 |
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else:
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| 78 |
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styles.append('background-color: #D9D9D9; color: black; font-weight: bold')
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| 79 |
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return styles
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| 80 |
+
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| 81 |
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def alternating_rows(s):
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| 82 |
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"""設定交替行顏色"""
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| 83 |
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styles = []
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| 84 |
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for i, col in enumerate(s.index):
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| 85 |
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if col in ["編號", "公司代碼", "公司名稱"]:
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| 86 |
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if s.name % 2 == 0: # 偶數行
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| 87 |
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styles.append('background-color: #FFF2CC') # 淺黃色
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| 88 |
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else: # 奇數行
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| 89 |
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styles.append('background-color: #FFFFFF') # 白色
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| 90 |
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else:
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| 91 |
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styles.append('background-color: #F8F8F8') # 淺灰色
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| 92 |
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return styles
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| 93 |
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| 94 |
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# 應用樣式
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| 95 |
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styled = df.style.apply(alternating_rows, axis=1).apply(header_style, axis=0)
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| 96 |
+
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| 97 |
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# 設定表格整體樣式
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| 98 |
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styled = styled.set_table_styles([
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| 99 |
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{'selector': 'th', 'props': [('text-align', 'center'), ('padding', '8px')]},
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| 100 |
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{'selector': 'td', 'props': [('text-align', 'center'), ('padding', '6px')]},
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| 101 |
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{'selector': 'table', 'props': [('border-collapse', 'collapse'), ('margin', 'auto')]},
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| 102 |
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{'selector': 'th, td', 'props': [('border', '1px solid #CCCCCC')]}
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| 103 |
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])
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| 104 |
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| 105 |
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return styled
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| 106 |
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| 107 |
+
def save_to_excel(df: pd.DataFrame) -> bytes:
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| 108 |
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"""儲存為Excel格式並應用樣式,返回bytes"""
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| 109 |
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output = io.BytesIO()
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| 110 |
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| 111 |
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# 建立樣式化的DataFrame
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| 112 |
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with pd.ExcelWriter(output, engine='openpyxl') as writer:
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| 113 |
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# 先寫入基本資料
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| 114 |
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df.to_excel(writer, sheet_name='公司資料', index=False)
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| 115 |
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| 116 |
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# 取得工作表以進行格式設定
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| 117 |
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worksheet = writer.sheets['公司資料']
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| 118 |
+
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| 119 |
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# 設定欄寬
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| 120 |
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worksheet.column_dimensions['A'].width = 8 # 編號
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| 121 |
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worksheet.column_dimensions['B'].width = 12 # 公司代碼
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| 122 |
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worksheet.column_dimensions['C'].width = 25 # 公司名稱
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| 123 |
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worksheet.column_dimensions['D'].width = 40 # 公司網址
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| 124 |
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|
| 125 |
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# 使用openpyxl進行進階格式設定
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| 126 |
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from openpyxl.styles import PatternFill, Font, Alignment, Border, Side
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| 127 |
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|
| 128 |
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# 定義顏色
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| 129 |
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blue_fill = PatternFill(start_color="4472C4", end_color="4472C4", fill_type="solid")
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| 130 |
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yellow_fill = PatternFill(start_color="FFF2CC", end_color="FFF2CC", fill_type="solid")
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| 131 |
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white_fill = PatternFill(start_color="FFFFFF", end_color="FFFFFF", fill_type="solid")
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| 132 |
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gray_fill = PatternFill(start_color="D9D9D9", end_color="D9D9D9", fill_type="solid")
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| 133 |
+
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| 134 |
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# 定義字體
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| 135 |
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header_font = Font(bold=True, color="FFFFFF")
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| 136 |
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normal_font = Font(color="000000")
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| 137 |
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| 138 |
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# 定義對齊
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| 139 |
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center_alignment = Alignment(horizontal="center", vertical="center")
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| 140 |
+
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| 141 |
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# 定義邊框
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| 142 |
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thin_border = Border(
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| 143 |
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left=Side(style='thin'),
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| 144 |
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right=Side(style='thin'),
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| 145 |
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top=Side(style='thin'),
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| 146 |
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bottom=Side(style='thin')
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| 147 |
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)
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| 148 |
+
|
| 149 |
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# 設定標題行格式
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| 150 |
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for col_num, col_name in enumerate(['編號', '公司代碼', '公司名稱', '公司網址'], 1):
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| 151 |
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cell = worksheet.cell(row=1, column=col_num)
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| 152 |
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cell.font = header_font
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| 153 |
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cell.alignment = center_alignment
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| 154 |
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cell.border = thin_border
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| 155 |
+
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| 156 |
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if col_name in ['編號', '公司代碼', '公司名稱']:
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| 157 |
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cell.fill = blue_fill
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| 158 |
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else:
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| 159 |
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cell.fill = gray_fill
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| 160 |
+
|
| 161 |
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# 設定資料行格式
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| 162 |
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for row_num in range(2, len(df) + 2):
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| 163 |
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for col_num in range(1, 5):
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| 164 |
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cell = worksheet.cell(row=row_num, column=col_num)
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| 165 |
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cell.font = normal_font
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| 166 |
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cell.alignment = center_alignment
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| 167 |
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cell.border = thin_border
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| 168 |
+
|
| 169 |
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# 針對編號、公司代碼、公司名稱欄位設定交替顏色
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| 170 |
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if col_num <= 3: # 編號、公司代碼、公司名稱
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| 171 |
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if (row_num - 2) % 2 == 0: # 偶數行
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| 172 |
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cell.fill = yellow_fill
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| 173 |
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else: # 奇數行
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| 174 |
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cell.fill = white_fill
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| 175 |
+
|
| 176 |
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output.seek(0)
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| 177 |
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return output.getvalue()
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| 178 |
+
|
| 179 |
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def save_to_csv(df: pd.DataFrame) -> str:
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| 180 |
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"""儲存為CSV格式,返回CSV字串"""
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| 181 |
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return df.to_csv(index=False, encoding="utf-8-sig")
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| 182 |
+
|
| 183 |
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def main():
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| 184 |
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st.set_page_config(
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| 185 |
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page_title="台灣證交所公司資料爬取工具",
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| 186 |
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page_icon="🏢",
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| 187 |
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layout="wide",
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| 188 |
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initial_sidebar_state="expanded"
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| 189 |
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)
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| 190 |
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|
| 191 |
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st.title("🏢 台灣證交所公司資料爬取工具")
|
| 192 |
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st.markdown("這個工具可以幫您從台灣證交所網站爬取上市公司資料,並提供CSV或Excel格式下載。")
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| 193 |
+
|
| 194 |
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# 側邊欄參數設定
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| 195 |
+
with st.sidebar:
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| 196 |
+
st.header("⚙️ 參數設定")
|
| 197 |
+
|
| 198 |
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start_offset = st.number_input(
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| 199 |
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"起始偏移量",
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| 200 |
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min_value=0,
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| 201 |
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value=0,
|
| 202 |
+
step=1,
|
| 203 |
+
help="從第幾筆資料開始爬取"
|
| 204 |
+
)
|
| 205 |
+
|
| 206 |
+
max_per = st.slider(
|
| 207 |
+
"每頁筆數",
|
| 208 |
+
min_value=1,
|
| 209 |
+
max_value=100,
|
| 210 |
+
value=30,
|
| 211 |
+
step=1,
|
| 212 |
+
help="每次請求爬取的資料筆數"
|
| 213 |
+
)
|
| 214 |
+
|
| 215 |
+
max_pages = st.slider(
|
| 216 |
+
"最大頁數",
|
| 217 |
+
min_value=1,
|
| 218 |
+
max_value=100,
|
| 219 |
+
value=50,
|
| 220 |
+
step=1,
|
| 221 |
+
help="最多爬取幾頁資料"
|
| 222 |
+
)
|
| 223 |
+
|
| 224 |
+
output_format = st.radio(
|
| 225 |
+
"輸出格式",
|
| 226 |
+
options=["CSV", "Excel", "兩者都要"],
|
| 227 |
+
index=1,
|
| 228 |
+
help="選擇要下載的檔案格式"
|
| 229 |
+
)
|
| 230 |
+
|
| 231 |
+
st.markdown("---")
|
| 232 |
+
|
| 233 |
+
# 使用說明
|
| 234 |
+
with st.expander("📖 使用說明"):
|
| 235 |
+
st.markdown("""
|
| 236 |
+
### 參數說明:
|
| 237 |
+
- **起始偏移量**:從第幾筆資料開始爬取,通常設為0
|
| 238 |
+
- **每頁筆數**:每次API請求的資料筆數,建議30-50
|
| 239 |
+
- **最大頁數**:最多爬取幾頁,避免設定太大導致執行時間過長
|
| 240 |
+
- **輸出格式**:
|
| 241 |
+
- CSV:純文字格式,適合後續程式處理
|
| 242 |
+
- Excel:包含樣式格式的Excel檔案
|
| 243 |
+
- 兩者都要:同時產生CSV和Excel檔案
|
| 244 |
+
|
| 245 |
+
### 注意事項:
|
| 246 |
+
- 爬取過程中請勿關閉瀏覽器
|
| 247 |
+
- 建議先用較小的參數測試
|
| 248 |
+
- 檔案會自動加上時間戳記避免重複
|
| 249 |
+
""")
|
| 250 |
+
|
| 251 |
+
# 主要內容區域
|
| 252 |
+
col1, col2 = st.columns([2, 1])
|
| 253 |
+
|
| 254 |
+
with col2:
|
| 255 |
+
start_scraping = st.button("🚀 開始爬取", type="primary", use_container_width=True)
|
| 256 |
+
|
| 257 |
+
# 執行爬取
|
| 258 |
+
if start_scraping:
|
| 259 |
+
# 驗證輸入參數
|
| 260 |
+
if start_offset < 0:
|
| 261 |
+
st.error("起始偏移量不能小於0")
|
| 262 |
+
return
|
| 263 |
+
if max_per <= 0 or max_per > 100:
|
| 264 |
+
st.error("每頁筆數必須在1-100之間")
|
| 265 |
+
return
|
| 266 |
+
if max_pages <= 0 or max_pages > 1000:
|
| 267 |
+
st.error("最大頁數必須在1-1000之間")
|
| 268 |
+
return
|
| 269 |
+
|
| 270 |
+
try:
|
| 271 |
+
# 建立進度條和狀態顯示
|
| 272 |
+
progress_bar = st.progress(0)
|
| 273 |
+
status_text = st.empty()
|
| 274 |
+
|
| 275 |
+
# 開始爬取資料
|
| 276 |
+
status_text.text("開始爬取資料...")
|
| 277 |
+
df = collect_all(start_offset, max_per, max_pages, progress_bar, status_text)
|
| 278 |
+
|
| 279 |
+
if df.empty:
|
| 280 |
+
st.warning("未爬取到任何資料")
|
| 281 |
+
return
|
| 282 |
+
|
| 283 |
+
# 產生時間戳記
|
| 284 |
+
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
| 285 |
+
|
| 286 |
+
# 完成狀態
|
| 287 |
+
progress_bar.progress(1.0)
|
| 288 |
+
status_text.text(f"✅ 成功爬取 {len(df)} 筆公司資料!")
|
| 289 |
+
|
| 290 |
+
# 顯示資料預覽
|
| 291 |
+
st.subheader("📊 資料預覽(前10筆)")
|
| 292 |
+
st.dataframe(df.head(10), use_container_width=True)
|
| 293 |
+
|
| 294 |
+
# 檔案下載區域
|
| 295 |
+
st.subheader("📁 檔案下載")
|
| 296 |
+
|
| 297 |
+
download_col1, download_col2 = st.columns(2)
|
| 298 |
+
|
| 299 |
+
if output_format in ["CSV", "兩者都要"]:
|
| 300 |
+
csv_data = save_to_csv(df)
|
| 301 |
+
with download_col1:
|
| 302 |
+
st.download_button(
|
| 303 |
+
label="⬇️ 下載 CSV 檔案",
|
| 304 |
+
data=csv_data,
|
| 305 |
+
file_name=f"companies_{timestamp}.csv",
|
| 306 |
+
mime="text/csv",
|
| 307 |
+
use_container_width=True
|
| 308 |
+
)
|
| 309 |
+
|
| 310 |
+
if output_format in ["Excel", "兩者都要"]:
|
| 311 |
+
excel_data = save_to_excel(df)
|
| 312 |
+
with download_col2:
|
| 313 |
+
st.download_button(
|
| 314 |
+
label="⬇️ 下載 Excel 檔案",
|
| 315 |
+
data=excel_data,
|
| 316 |
+
file_name=f"companies_styled_{timestamp}.xlsx",
|
| 317 |
+
mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
|
| 318 |
+
use_container_width=True
|
| 319 |
+
)
|
| 320 |
+
|
| 321 |
+
# 顯示統計資訊
|
| 322 |
+
st.subheader("📈 統計資訊")
|
| 323 |
+
stat_col1, stat_col2, stat_col3 = st.columns(3)
|
| 324 |
+
|
| 325 |
+
with stat_col1:
|
| 326 |
+
st.metric("總公司數量", len(df))
|
| 327 |
+
|
| 328 |
+
with stat_col2:
|
| 329 |
+
st.metric("有網址的公司", len(df[df['公司網址'] != '']))
|
| 330 |
+
|
| 331 |
+
with stat_col3:
|
| 332 |
+
st.metric("執行頁數", min(max_pages, (len(df) // max_per) + 1))
|
| 333 |
+
|
| 334 |
+
except Exception as e:
|
| 335 |
+
st.error(f"❌ 爬取過程中發生錯誤:{str(e)}")
|
| 336 |
+
|
| 337 |
+
if __name__ == "__main__":
|
| 338 |
+
main()
|