# 3.4 Google Finance 個股資訊 這隻要細心一點, 除了會把指定編號的股票資訊顯示出來之外, 另外也實作了取得不同頁歷史資訊的方法: ```python import requests from bs4 import BeautifulSoup # To query the specific stock info, add "MARKET:STOCK_ID" after the url. # e.g.: https://www.google.com/finance?q=[MARKET]:[STOCK_ID] GOOGLE_FINANCE_INFO = "https://www.google.com/finance?q=" GOOGLE_FINANCE_HISTORY = "https://www.google.com/finance/historical?q=" CODE_TSMC = "TPE:2330" FINANCE_HISTORY_START_BASE = 30 FINANCE_HISTORY_RECORD_SIZE = 30 def get_web_page(url, query): if query: resp = requests.get(url+query) else: resp = requests.get(url) if resp.status_code != 200: print('Invalid url: ', resp.url) return None else: return resp.text def get_stock_info(dom): soup = BeautifulSoup(dom, 'html5lib') stock = dict() stock['name'] = soup.title.text.split(':')[0] stock['current_price'] = soup.find(id='price-panel').span.span.text stock['current_change'] = soup.find(id='price-panel').find('div', 'id-price-change').text.strip().replace('\n', '') for table in soup.find('div', 'snap-panel').find_all('table'): for tr in table.find_all('tr'): key = tr.find('td', 'key').text.lower().strip() value = tr.find('td', 'val').text.strip() stock[key] = value return stock def get_stock_history(dom): soup = BeautifulSoup(dom, 'html5lib') table = soup.find('table', 'historical_price') header_row = table.find('tr', 'bb') headers = [header for header in header_row.stripped_strings] print(headers) for tds in table.find_all('tr')[1:]: print([data for data in tds.stripped_strings]) def main(): finance_info_page = get_web_page(GOOGLE_FINANCE_INFO, CODE_TSMC) if finance_info_page: stock = get_stock_info(finance_info_page) for k, v in stock.items(): print(k + ":", v) # To fetch history data by pagination, you need to add two query params: start and num. # Just like the following link: # https://www.google.com/finance/historical?q=TPE:2330&start=30&num=30 for page in range(0, 3, 1): history_url = GOOGLE_FINANCE_HISTORY + CODE_TSMC + "&start=" + str(page * FINANCE_HISTORY_START_BASE) + "&num=" + str(FINANCE_HISTORY_RECORD_SIZE) finance_history_page = get_web_page(history_url, None) get_stock_history(finance_history_page) if __name__ == '__main__': main() ``` 輸出如下: ``` name: Taiwan Semiconductor Mfg. Co. Ltd. current_price: 207.00 current_change: 0.00(0.00%) range: 205.00 - 207.00 52 week: 153.50 - 208.50 open: 205.00 vol.: 32.56M mkt cap: 5.37T p/e: 15.03 div/yield: 7.00/2.90 eps: 13.77 shares: 25.93B beta: - inst. own: - ['Date', 'Open', 'High', 'Low', 'Close', 'Volume'] ['May 26, 2017', '205.00', '207.00', '205.00', '207.00', '32,492,000'] ['May 25, 2017', '206.00', '207.00', '205.50', '207.00', '22,311,000'] ['May 24, 2017', '205.00', '206.00', '205.00', '205.50', '13,378,000'] ['May 23, 2017', '205.00', '207.00', '204.50', '205.00', '19,988,000'] ['May 22, 2017', '203.50', '205.00', '203.00', '205.00', '13,714,000'] ['May 19, 2017', '203.50', '204.50', '202.50', '203.00', '16,483,000'] ['May 18, 2017', '202.50', '204.00', '201.50', '203.50', '22,448,000'] ['May 17, 2017', '203.00', '204.00', '203.00', '204.00', '21,558,000'] ['May 16, 2017', '205.00', '205.00', '203.50', '204.50', '33,212,000'] ['May 15, 2017', '204.00', '206.00', '204.00', '206.00', '25,655,000'] ['May 12, 2017', '205.00', '207.00', '205.00', '206.00', '24,996,000'] ['May 11, 2017', '204.50', '208.50', '204.00', '207.50', '43,692,000'] ['May 10, 2017', '204.00', '206.00', '204.00', '205.50', '28,296,000'] ['May 9, 2017', '205.50', '207.00', '203.50', '203.50', '48,047,000'] ['May 8, 2017', '199.00', '202.50', '199.00', '202.50', '36,514,000'] ['May 5, 2017', '197.00', '198.50', '197.00', '197.50', '17,022,000'] ['May 4, 2017', '198.50', '199.00', '197.00', '198.00', '22,076,000'] ['May 3, 2017', '198.00', '198.50', '197.00', '198.00', '25,702,000'] ['May 2, 2017', '198.50', '199.00', '195.50', '196.50', '44,102,000'] ['Apr 28, 2017', '193.50', '194.50', '193.00', '194.50', '34,837,000'] ['Apr 27, 2017', '192.00', '193.00', '190.50', '193.00', '27,936,000'] ['Apr 26, 2017', '192.00', '192.00', '190.50', '191.00', '29,905,000'] ['Apr 25, 2017', '190.50', '192.00', '189.50', '192.00', '31,926,000'] ['Apr 24, 2017', '191.00', '191.50', '188.50', '190.00', '19,312,000'] ['Apr 21, 2017', '187.50', '190.00', '187.50', '190.00', '17,360,000'] ['Apr 20, 2017', '186.50', '188.00', '186.50', '187.00', '21,487,000'] ['Apr 19, 2017', '187.50', '187.50', '186.50', '186.50', '30,472,000'] ['Apr 18, 2017', '188.00', '189.50', '187.50', '188.00', '24,964,000'] ['Apr 17, 2017', '189.00', '189.00', '187.50', '187.50', '17,091,000'] ['Apr 14, 2017', '189.50', '189.50', '188.00', '189.00', '30,662,000'] ['Date', 'Open', 'High', 'Low', 'Close', 'Volume'] ['Apr 13, 2017', '189.50', '192.00', '189.50', '191.50', '14,762,000'] ['Apr 12, 2017', '190.50', '191.50', '190.00', '191.00', '17,270,000'] ['Apr 11, 2017', '190.00', '191.00', '189.00', '191.00', '8,433,000'] ['Apr 10, 2017', '191.00', '191.50', '189.50', '190.00', '17,005,000'] ['Apr 7, 2017', '192.00', '192.00', '188.50', '191.00', '18,898,000'] ['Apr 6, 2017', '193.00', '193.00', '191.00', '191.50', '16,170,000'] ['Apr 5, 2017', '189.50', '193.00', '189.50', '193.00', '43,707,000'] ['Mar 31, 2017', '191.00', '192.00', '189.00', '189.00', '33,621,000'] ['Mar 30, 2017', '192.50', '193.00', '190.50', '191.50', '28,296,000'] ['Mar 29, 2017', '194.50', '194.50', '191.00', '191.50', '33,367,000'] ['Mar 28, 2017', '195.00', '195.00', '192.50', '194.50', '38,247,000'] ['Mar 27, 2017', '194.50', '194.50', '192.00', '193.00', '29,239,000'] ['Mar 24, 2017', '192.00', '193.00', '192.00', '192.50', '17,515,000'] ['Mar 23, 2017', '192.00', '193.50', '192.00', '193.50', '18,463,000'] ['Mar 22, 2017', '192.50', '193.50', '191.50', '193.50', '27,368,000'] ['Mar 21, 2017', '192.00', '195.00', '191.50', '195.00', '32,234,000'] ['Mar 20, 2017', '191.50', '191.50', '189.50', '191.50', '16,211,000'] ['Mar 17, 2017', '189.50', '191.50', '189.00', '191.50', '33,690,000'] ['Mar 16, 2017', '188.00', '190.00', '188.00', '190.00', '31,480,000'] ['Mar 15, 2017', '185.50', '187.00', '185.50', '186.50', '14,129,000'] ['Mar 14, 2017', '188.00', '188.00', '186.00', '186.00', '22,241,000'] ['Mar 13, 2017', '185.00', '186.50', '185.00', '186.50', '10,475,000'] ['Mar 10, 2017', '184.00', '184.50', '183.00', '183.50', '20,046,000'] ['Mar 9, 2017', '185.50', '186.00', '184.00', '184.50', '28,483,000'] ['Mar 8, 2017', '186.00', '188.00', '185.50', '187.00', '31,786,000'] ['Mar 7, 2017', '184.00', '185.50', '184.00', '185.50', '18,791,000'] ['Mar 6, 2017', '184.00', '184.50', '183.50', '183.50', '12,527,000'] ['Mar 3, 2017', '184.50', '185.00', '184.00', '184.00', '28,085,000'] ['Mar 2, 2017', '188.00', '188.50', '185.00', '186.00', '39,914,000'] ['Mar 1, 2017', '188.50', '188.50', '186.00', '186.00', '46,176,000'] ['Date', 'Open', 'High', 'Low', 'Close', 'Volume'] ['Feb 24, 2017', '187.50', '190.50', '187.50', '189.00', '22,746,000'] ['Feb 23, 2017', '188.00', '189.50', '187.00', '188.50', '35,720,000'] ['Feb 22, 2017', '190.50', '191.00', '188.50', '188.50', '25,672,000'] ['Feb 21, 2017', '190.00', '190.00', '188.50', '190.00', '31,138,000'] ['Feb 17, 2017', '190.00', '190.50', '189.00', '189.50', '20,373,000'] ['Feb 16, 2017', '190.00', '190.50', '188.00', '189.00', '26,986,000'] ['Feb 15, 2017', '187.00', '189.50', '186.50', '189.00', '39,206,000'] ['Feb 14, 2017', '189.00', '190.00', '187.50', '187.50', '45,690,000'] ['Feb 13, 2017', '186.50', '188.00', '186.50', '187.50', '25,078,000'] ['Feb 10, 2017', '184.50', '185.50', '184.00', '185.50', '34,694,000'] ['Feb 9, 2017', '184.00', '185.50', '183.50', '184.00', '18,966,000'] ['Feb 8, 2017', '183.50', '184.50', '183.00', '183.50', '29,144,000'] ['Feb 7, 2017', '183.50', '185.00', '183.00', '184.50', '23,614,000'] ['Feb 6, 2017', '184.50', '185.50', '184.00', '184.50', '24,767,000'] ['Feb 3, 2017', '186.00', '186.00', '183.50', '184.50', '29,508,000'] ['Feb 2, 2017', '188.00', '188.50', '184.00', '184.50', '94,068,000'] ['Jan 24, 2017', '185.00', '186.50', '184.50', '185.50', '55,004,000'] ['Jan 23, 2017', '182.50', '185.00', '182.50', '185.00', '36,985,000'] ['Jan 20, 2017', '181.00', '181.50', '180.50', '181.00', '23,420,000'] ['Jan 19, 2017', '179.50', '181.00', '179.50', '180.50', '24,595,000'] ['Jan 18, 2017', '180.50', '181.00', '179.50', '181.00', '23,685,000'] ['Jan 17, 2017', '180.50', '181.00', '179.50', '181.00', '13,148,000'] ['Jan 16, 2017', '180.00', '180.50', '179.00', '179.50', '30,736,000'] ['Jan 13, 2017', '180.50', '182.50', '180.50', '181.50', '52,340,000'] ['Jan 12, 2017', '182.50', '185.50', '182.50', '184.50', '41,122,000'] ['Jan 11, 2017', '185.00', '185.00', '181.50', '182.00', '29,089,000'] ['Jan 10, 2017', '184.50', '185.50', '183.50', '184.00', '20,169,000'] ['Jan 9, 2017', '184.00', '185.00', '183.00', '184.00', '18,555,000'] ['Jan 6, 2017', '184.00', '184.50', '183.50', '184.00', '22,429,000'] ['Jan 5, 2017', '182.00', '183.50', '181.50', '183.50', '20,962,000'] Process finished with exit code 0 ``` ~~十萬青年十萬肝 GG輪班救台灣~~ ~~十萬青年十萬肝 GG輪班妹來含~~ 原始碼[點我](https://github.com/yotsuba1022/web-crawler-practice/blob/master/ch3/google_finance.py) --- # Agent Instructions: Querying This Documentation If you need additional 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