我正在嘗試從該網站獲取表格中的公司名稱，但是當我嘗試時，我得到了
TypeError: 'str' object is not callable
參考 XPATH 有沒有辦法解決這個問題？
from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import Select
s = Service("C:\Program Files (x86)\chromedriver.exe")
browser = webdriver.Chrome(service=s)
# click accept on pop up
url = "https://www.dbs.com.sg/treasures/aics/stock-coverage/index.html"
browser.get(url)
WebDriverWait(browser, 10).until(EC.element_to_be_clickable((By.XPATH, "//button[text()='Accept']"))).click()
# getting data from table
# count no of rows
rows = len(browser.find_elements(By.XPATH("//*[@id='buyholdsell']/div/div/div/div/div[1]/div/div/div/div/table/tbody/tr")))
print(rows)
uj5u.com熱心網友回復：
這個錯誤
TypeError: 'str' object is not callable
意味著，這
find_elements(By.XPATH("//")
應該
find_elements(By.XPATH, "")
因此，您的有效代碼塊將是：
代碼：
wait = WebDriverWait(driver, 30)
url = "https://www.dbs.com.sg/treasures/aics/stock-coverage/index.html"
driver.get(url)
try:
wait.until(EC.element_to_be_clickable((By.XPATH, "//button[text()='Accept']"))).click()
except:
pass
# getting data from table
# count no of rows
rows = len(driver.find_elements(By.XPATH, "//*[@id='buyholdsell']/div/div/div/div/div[1]/div/div/div/div/table/tbody/tr"))
print(rows)
進口：
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
輸出：
10
uj5u.com熱心網友回復：
這里不需要硒。您可以通過 POST 請求獲取表：
import requests
import pandas as pd
page = 0
data_present = True
url = 'https://www.dbs.com.sg/contentapi/dbsstore_main_www_global-ia_en_article_equity/search'
rows = []
while data_present == True:
payload = {"query":
{"bool":
{"filter":
[{"range":
{"date_sort.PublishedDate":
{"lte":"now/d"}}},
{"range":
{"date_sort.ExpiryDate":
{"gte":"now/d"}}},
{"term":
{"results_data.QuickViews.POWType.raw":"Equity"}},
{"term":{"meta.Country":"sg"}},
{"terms":{"results_data.Industry.raw":
["Industrials","BasicMaterials","ConsumerGoods","ConsumerServices",
"Financials","HealthCare","OilGas","RealEstate","Technology",
"Telecommunications","Utilities"]}},
{"terms":
{"results_data.QuickViews.Recommendation.raw":
["BUY","HOLD","SELL","FV"]}}]}},
"sort":{"results_data.Title.raw":{"order":"asc"}},
"from":page*10}
jsonData = requests.post(url, json=payload).json()
if len(jsonData['hits']['hits']) != 0:
page =1
print(f'Page: {page}')
hits = jsonData['hits']['hits']
for hit in hits:
company_name = hit['_source']['results_data']['CompanyName']
stock_code = hit['_source']['results_data']['BloombergReutersCode']
sector = hit['_source']['results_data']['Industry']
market_capital = hit['_source']['results_data']['QuickViews']['MarketCap']
target_price = hit['_source']['results_data']['QuickViews']['TargetPrice']
time = hit['_source']['results_data']['QuickViews']['Time']
cell = hit['_source']['results_data']['QuickViews']['Recommendation']
row = {
'Cell':cell,
'Company Name':company_name,
'Stock Code':stock_code,
'Sector':sector,
'Market Capital':market_capital,
'Target Price':target_price,
'Time':time}
rows.append(row)
else:
print('No more data.')
data_present = False
results = pd.DataFrame(rows)
輸出：
print(results)
Cell Company Name ... Target Price Time
0 BUY AEM Holdings Ltd ... 4.98 12 months
1 BUY AIMS APAC REIT ... 1.60140929562329 12 months
2 HOLD APAC Realty ... 0.877765749701783 12 months
3 BUY ARA US Hospitality Trust ... 0.752986472516872 12 months
4 BUY Ascendas India Trust ... 1.8 12 months
.. ... ... ... ... ...
98 HOLD Vicom Ltd ... 2.13 12 months
99 BUY Wilmar International ... 6.67 12 months
100 BUY Yangzijiang Shipbuilding ... 1.95 12 months
101 BUY iFAST Corporation ... 12.93 12 months
102 HOLD mm2 Asia ... 0.0673190399546146 12 months
[103 rows x 7 columns]
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