如何使用 python 请求对过滤后的结果进行网络抓取？

Question

我正在尝试从该网站https://www.gurufocus.com/insider/summary 抓取过滤后的结果。现在我只能从第一页获取信息。但我真正想做的是过滤几个行业并获得相关数据（您可以在过滤区域看到“行业”）。但是当我选择行业时，网址不会改变，我不能直接从网址中抓取。我看到有人说你可以使用requests.post 来获取数据，但我真的不知道它是如何工作的。

这是我现在的一些代码。

TradeUrl = "https://www.gurufocus.com/insider/summary"
r = requests.get(TradeUrl)
data=r.content
soup=BeautifulSoup(data, 'html.parser')

ticker = []
for tk in soup.find_all('td',{'class': 'table-stock-info', 'data-column': 'Ticker'}):
    ticker.append(tk.text)

如果我只需要金融服务行业的代码，我应该怎么做？

Answer 1

按照建议使用发布请求的问题是该请求需要一个授权令牌，该令牌具有到期时间。您可以在 Chrome 或 Firefox 中看到 post 请求，如果您右键单击页面 -> 选择 Inspect -> 选择 Network 然后选择 Industry 点击 POST 请求并点击 Cookies 有一个 cookie password_grant_custom.client.expires 具有授权将不再起作用的时间戳。

但是，您可以使用 selenium 从所有页面上刮取数据。

首先安装 Selenium：

`sudo pip3 install selenium` on Linux or `pip install selenium` on Windows

那就找个驱动https://sites.google.com/a/chromium.org/chromedriver/downloads, 为您的 Chrome 版本获取正确的版本并将其从 zip 文件中解压缩。

注意在 Windows 上，您需要将 chromedriver 的路径添加到

driver = webdriver.Chrome(options=options)

在 Linux 上将 chromedriver 复制到 /usr/local/bin/chromedriver

from selenium import webdriver
from selenium.webdriver.common.by import By
import selenium.webdriver.support.expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from selenium.common.exceptions import TimeoutException
from bs4 import BeautifulSoup
import time

# Start with the driver maximised to see the drop down menus properly
options = webdriver.ChromeOptions()
options.add_argument("--start-maximized")
driver = webdriver.Chrome(options=options)
driver.get('https://www.gurufocus.com/insider/summary')

# Set the page size to 100 to reduce page loads
driver.find_element_by_xpath("//span[contains(text(),'40 / Page')]").click()
wait = WebDriverWait(driver, 10).until(
    EC.presence_of_element_located((
        By.XPATH,
        "//div[contains(text(),'100')]"))
)
element = driver.find_element_by_xpath("//div[contains(text(),'100')]").click()

# Wait for the page to load and don't overload the server
time.sleep(2)

# select Industry
driver.find_element_by_xpath("//span[contains(text(),'Industry')]").click()

# Select Financial Services
element = WebDriverWait(driver, 5).until(
    EC.presence_of_element_located((
        By.XPATH,
        "//span[contains(text(),'Financial Services')]"))
)
element.click()

ticker = []

while True:
    # Wait for the page to load and don't overload the server
    time.sleep(6)
    # Parse the HTML
    soup = BeautifulSoup(driver.page_source, 'html.parser')
    for tk in soup.find_all('td', {'class': 'table-stock-info', 'data-column': 'Ticker'}):
        ticker.append(tk.text)
    try:
        # Move to the next page
        element = WebDriverWait(driver, 5).until(EC.element_to_be_clickable((By.CLASS_NAME, 'btn-next')))
        element.click()
    except TimeoutException as ex:
        # No more pages so break
        break
driver.quit()

print(len(ticker))
print(ticker)

输出

4604
['PUB   ', 'ARES   ', 'EIM   ', 'CZNC   ', 'SSB   ', 'CNA   ', 'TURN   ', 'FNF   ', 'EGIF   ', 'NWPP  etc...

更新

如果您想从所有页面上刮取所有数据和/或写入 csv，请使用 pandas：

from selenium import webdriver
from selenium.webdriver.common.by import By
import selenium.webdriver.support.expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from selenium.common.exceptions import TimeoutException
import pandas as pd
import time

# Start with the driver maximised to see the drop down menus properly
options = webdriver.ChromeOptions()
options.add_argument("--start-maximized")
driver = webdriver.Chrome(options=options)
driver.get('https://www.gurufocus.com/insider/summary')

# Set the page size to 100 to reduce page loads
driver.find_element_by_xpath("//span[contains(text(),'40 / Page')]").click()
wait = WebDriverWait(driver, 10).until(
    EC.presence_of_element_located((
        By.XPATH,
        "//div[contains(text(),'100')]"))
)
driver.find_element_by_xpath("//div[contains(text(),'100')]").click()

# Wait for the page to load and don't overload the server
time.sleep(2)

# select Industry
driver.find_element_by_xpath("//span[contains(text(),'Industry')]").click()

# Select Financial Services
element = WebDriverWait(driver, 5).until(
    EC.presence_of_element_located((
        By.XPATH,
        "//span[contains(text(),'Financial Services')]"))
)
element.click()


columns = [
    'Ticker', 'Links', 'Company', 'Price1', 'Insider Name', 'Insider Position',
    'Date', 'Buy/Sell', 'Insider Trading Shares', 'Shares Change', 'Price2',
    'Cost(000)', 'Final Share', 'Price Change Since Insider Trade (%)',
    'Dividend Yield %', 'PE Ratio', 'Market Cap ($M)', 'None'
]
df = pd.DataFrame(columns=columns)


while True:
    # Wait for the page to load and don't overload the server
    time.sleep(6)
    # Parse the HTML
    df = df.append(pd.read_html(driver.page_source, attrs={'class': 'data-table'})[0], ignore_index=True)

    try:
        # Move to the next page
        element = WebDriverWait(driver, 5).until(EC.element_to_be_clickable((By.CLASS_NAME, 'btn-next')))
        element.click()
    except TimeoutException as ex:
        # No more pages so break
        break
driver.quit()

# Write to csv
df.to_csv("Financial_Services.csv", encoding='utf-8', index=False)

针对 cme​​ts 进行了更新： 首先从https://github.com/mozilla/geckodriver/releases下载Firefox驱动geckodriver解压驱动。再次在 Windows 上，您需要将 geckodriver 的路径添加到 driver = webdriver.Firefox() 或在 linux 上将 geckodriver 复制到 /usr/local/bin/geckodriver

from selenium import webdriver
from selenium.webdriver.common.by import By
import selenium.webdriver.support.expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from selenium.common.exceptions import TimeoutException
import pandas as pd
import time

# Start with the driver maximised to see the drop down menus properly
driver = webdriver.Firefox()
driver.maximize_window()
driver.get('https://www.gurufocus.com/insider/summary')

# Set the page size to 100 to reduce page loads
driver.find_element_by_xpath("//span[contains(text(),'40 / Page')]").click()
wait = WebDriverWait(driver, 10).until(
    EC.presence_of_element_located((
        By.XPATH,
        "//div[contains(text(),'100')]"))
)
driver.find_element_by_xpath("//div[contains(text(),'100')]").click()

# Wait for the page to load and don't overload the server
time.sleep(2)

# select Industry
driver.find_element_by_xpath("//span[contains(text(),'Industry')]").click()

# Select Financial Services
element = WebDriverWait(driver, 5).until(
    EC.presence_of_element_located((
        By.XPATH,
        "//span[contains(text(),'Financial Services')]"))
)
element.click()

columns = [
    'Ticker', 'Links', 'Company', 'Price1', 'Insider Name', 'Insider Position',
    'Date', 'Buy/Sell', 'Insider Trading Shares', 'Shares Change', 'Price2',
    'Cost(000)', 'Final Share', 'Price Change Since Insider Trade (%)',
    'Dividend Yield %', 'PE Ratio', 'Market Cap ($M)', 'None'
]
df = pd.DataFrame(columns=columns)
page_limit = 5
page = 0

while True:
    # Wait for the page to load and don't overload the server
    time.sleep(6)
    # Parse the HTML
    df = df.append(pd.read_html(driver.page_source, attrs={'class': 'data-table'})[0], ignore_index=True)

    # Stop after page limit is reached.
    page = page + 1
    if page >= page_limit:
        break

    try:
        # Move to the next page
        element = WebDriverWait(driver, 5).until(EC.element_to_be_clickable((By.CLASS_NAME, 'btn-next')))
        element.click()
    except TimeoutException as ex:
        # No more pages so break
        break

driver.quit()

# Write to csv
df.to_csv("Financial_Services.csv", encoding='utf-8', index=False)