python 股價實時數據饋送（腳本調試）

Question

我剛剛開始學習編碼，如果這個問題是微不足道的，我想提前道歉。

我一直在嘗試找到一種將股市數據實時輸入 python 的方法，並遇到了這個博客http://www.quantatrisk.com/2015/05/07/hacking-google-finance-in-pre-market-trading -Python/

下面是我復制粘貼的腳本。

import urllib2  # works fine with Python 2.7.9 (not 3.4.+)
import json
import time

def fetchPreMarket(symbol, exchange):
    link = "http://finance.google.com/finance/info?client=ig&q="
    url = link+"%s:%s" % (exchange, symbol)
    u = urllib2.urlopen(url)
    content = u.read()
    data = json.loads(content[3:])
    info = data[0]
    t = str(info["elt"])    # time stamp
    l = float(info["l"])    # close price (previous trading day)
    p = float(info["el"])   # stock price in pre-market (after-hours)
    return (t,l,p)


p0 = 0
while True:
    t, l, p = fetchPreMarket("AAPL","NASDAQ")
    if(p!=p0):
        p0 = p
        print("%s\t%.2f\t%.2f\t%+.2f\t%+.2f%%" % (t, l, p, p-l,
                                                 (p/l-1)*100.))
    time.sleep(60)

它似乎是一個很棒的代碼，除非我運行它時，我收到以下錯誤消息

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-11-012ec6dc7b0c> in <module>()
     18 p0 = 0
     19 while True:
---> 20     t, l, p = fetchPreMarket("AAPL","NASDAQ")
     21     if(p!=p0):
     22         p0 = p

<ipython-input-11-012ec6dc7b0c> in fetchPreMarket(symbol, exchange)
     10     data = json.loads(content[3:])
     11     info = data[0]
---> 12     t = str(info["elt"])    # time stamp
     13     l = float(info["l"])    # close price (previous trading day)
     14     p = float(info["el"])   # stock price in pre-market (after-hours)

KeyError: 'elt'

我嘗試修改 fetchPreMarket 使其僅輸出info = data[0]但是當我嘗試“打印信息”時，什么也沒有。

提前致謝

Answer 1

所以... Google Finance API 已停產 。 我很驚訝鏈接有效，但是數據中沒有"etl" （或"el" ）鍵。

因此，您將在info["elt"]處收到KeyError: 'elt'

以供參考，

{
"id": "22144"
,"t" : "AAPL"
,"e" : "NASDAQ"
,"l" : "95.52"
,"l_fix" : "95.52"
,"l_cur" : "95.52"
,"s": "0"
,"ltt":"2:34PM EST"
,"lt" : "Feb 24, 2:34PM EST"
,"lt_dts" : "2016-02-24T14:34:54Z"
,"c" : "+0.83"
,"c_fix" : "0.83"
,"cp" : "0.88"
,"cp_fix" : "0.88"
,"ccol" : "chg"
,"pcls_fix" : "94.69"
}

與googlefinance或yahoo-finance python模塊相比，您可能會更好，而不是直接調用API地址。

值得注意的是，雅虎API並非“實時”。 大約延遲15分鍾報價。

Answer 2

如果您不想使用googlefinance package，您可以使用BeautifulSoup創建自己的解析器。

在使用 BeautifulSoup 的在線 IDE 中檢查代碼。

from bs4 import BeautifulSoup
import requests, json, lxml, re
from itertools import zip_longest


def scrape_google_finance(ticker: str):
    # https://docs.python-requests.org/en/master/user/quickstart/#passing-parameters-in-urls
    params = {
        "hl": "en" # language
        }

    # https://docs.python-requests.org/en/master/user/quickstart/#custom-headers
    # https://www.whatismybrowser.com/detect/what-is-my-user-agent
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/100.0.4896.60 Safari/537.36",
        }

    html = requests.get(f"https://www.google.com/finance/quote/{ticker}", params=params, headers=headers, timeout=30)
    soup = BeautifulSoup(html.text, "lxml")    
    
    ticker_data = {"ticker_info": {},
                    "right_panel_data": {},
                    "finance_perfomance": {"table": []}
                    }
    
    ticker_data["ticker_info"]["title"] = soup.select_one(".zzDege").text
    ticker_data["ticker_info"]["current_price"] = soup.select_one(".AHmHk .fxKbKc").text
    
    right_panel_keys = soup.select(".gyFHrc .mfs7Fc")
    right_panel_values = soup.select(".gyFHrc .P6K39c")
    
    for key, value in zip_longest(right_panel_keys, right_panel_values):
        key_value = key.text.lower().replace(" ", "_")

        ticker_data["right_panel_data"][key_value] = value.text
    

    if soup.select(".slpEwd .roXhBd"):
        # https://regex101.com/r/Sf2TaC/1
        fin_perf_col_2 = re.search(r"\w+\s?\d{4}", soup.select_one(".PFjsMe+ .yNnsfe").text).group(0)                # e.g. JUN 2022
        fin_perf_col_3 = soup.select_one(".PFjsMe~ .yNnsfe+ .yNnsfe").text       # e.g. Year/year change
         
        for fin_perf in soup.select(".slpEwd .roXhBd"):
            if fin_perf.select(".rsPbEe"):
                perf_key = fin_perf.select_one(".rsPbEe").text                   # e.g. Revenue, Net Income, Operating Income..
                perf_value_col_1 = fin_perf.select_one(".QXDnM").text            #  48.23B, ... 

                try:
                  perf_value_col_2 = fin_perf.select_one(".gEUVJe .JwB6zf").text # -21.82%, ...
                except:
                  perf_value_col_2 = None  # 
                
                ticker_data["finance_perfomance"]["table"].append({
                    perf_key: {
                        fin_perf_col_2: perf_value_col_1,
                        fin_perf_col_3: perf_value_col_2
                    }
                })
    else:
        ticker_data["finance_perfomance"]["error"] = f"No 'finence perfomance table' for {ticker}."

    return ticker_data

  
data = scrape_google_finance(ticker="AAPL:NASDAQ")

print(json.dumps(data, indent=2))

示例 output

[
    {
  "ticker_info": {
    "title": "Apple Inc",
    "current_price": "$174.55"
  },
  "right_panel_data": {
    "previous_close": "$173.03",
    "day_range": "$172.57 - $176.15",
    "year_range": "$129.04 - $182.94",
    "market_cap": "2.81T USD",
    "avg_volume": "68.49M",
    "p/e_ratio": "28.84",
    "dividend_yield": "0.53%",
    "primary_exchange": "NASDAQ",
    "ceo": "Tim Cook",
    "founded": "Apr 1, 1976",
    "headquarters": "Cupertino, CaliforniaUnited States",
    "website": "apple.com",
    "employees": "154,000"
  },
  "finance_perfomance": {
    "table": [
      {
        "Revenue": {
          "Jun 2022": "82.96B",
          "Y/Y change": "1.87%"
        }
      },
      {
        "Operating expense": {
          "Jun 2022": "12.81B",
          "Y/Y change": "15.10%"
        }
      },
      {
        "Net income": {
          "Jun 2022": "19.44B",
          "Y/Y change": "-10.59%"
        }
      # ...
]

---

如果您需要從 Google Finance 中抓取更多數據，請參閱 Python 博客文章中的抓取 Google Finance Ticker Quote Data 。