Python中怎么定時執行網站爬蟲

Python中怎么定時執行網站爬蟲，針對這個問題，這篇文章詳細介紹了相對應的分析和解答，希望可以幫助更多想解決這個問題的小伙伴找到更簡單易行的方法。

編寫爬蟲代碼

編寫一個爬蟲程序，使用requests與beautifulsoup4包爬取和解析Yahoo!股市-上市成交價排行與Yahoo!股市-上柜成交價排行的資料，再利用pandas包將解析后的展示出來。

import datetime
import requests
from bs4 import BeautifulSoup
import pandas as pd

def get_price_ranks():
    current_dt = datetime.datetime.now().strftime("%Y-%m-%d %X")
    current_dts = [current_dt for _ in range(200)]
    stock_types = ["tse", "otc"]
    price_rank_urls = ["https://tw.stock.yahoo.com/d/i/rank.php?t=pri&e={}&n=100".format(st) for st in stock_types]
    tickers = []
    stocks = []
    prices = []
    volumes = []
    mkt_values = []
    ttl_steps = 10*100
    each_step = 10
    for pr_url in price_rank_urls:
        r = requests.get(pr_url)
        soup = BeautifulSoup(r.text, 'html.parser')
        ticker = [i.text.split()[0] for i in soup.select(".name a")]
        tickers += ticker
        stock = [i.text.split()[1] for i in soup.select(".name a")]
        stocks += stock
        price = [float(soup.find_all("td")[2].find_all("td")[i].text) for i in range(5, 5+ttl_steps, each_step)]
        prices += price
        volume = [int(soup.find_all("td")[2].find_all("td")[i].text.replace(",", "")) for i in range(11, 11+ttl_steps, each_step)]
        volumes += volume
        mkt_value = [float(soup.find_all("td")[2].find_all("td")[i].text)*100000000 for i in range(12, 12+ttl_steps, each_step)]
        mkt_values += mkt_value
    types = ["上市" for _ in range(100)] + ["上柜" for _ in range(100)]
    ky_registered = [True if "KY" in st else False for st in stocks]
    df = pd.DataFrame()
    df["scrapingTime"] = current_dts
    df["type"] = types
    df["kyRegistered"] = ky_registered
    df["ticker"] = tickers
    df["stock"] = stocks
    df["price"] = prices
    df["volume"] = volumes
    df["mktValue"] = mkt_values
    return df

price_ranks = get_price_ranks()
print(price_ranks.shape)

這個的結果展示為

## (200, 8)

接下來我們利用pandas進行前幾行展示

price_ranks.head()
price_ranks.tail()

接下來我們就開始往服務器上部署

對于服務器的選擇，環境配置不在本課的討論范圍之內，我們主要是要講一下怎么去設置定時任務。

接下來我們改造一下代碼，改造成結果有sqlite存儲。

import datetime
import requests
from bs4 import BeautifulSoup
import pandas as pd
import sqlite3

def get_price_ranks():
    current_dt = datetime.datetime.now().strftime("%Y-%m-%d %X")
    current_dts = [current_dt for _ in range(200)]
    stock_types = ["tse", "otc"]
    price_rank_urls = ["https://tw.stock.yahoo.com/d/i/rank.php?t=pri&e={}&n=100".format(st) for st in stock_types]
    tickers = []
    stocks = []
    prices = []
    volumes = []
    mkt_values = []
    ttl_steps = 10*100
    each_step = 10
    for pr_url in price_rank_urls:
        r = requests.get(pr_url)
        soup = BeautifulSoup(r.text, 'html.parser')
        ticker = [i.text.split()[0] for i in soup.select(".name a")]
        tickers += ticker
        stock = [i.text.split()[1] for i in soup.select(".name a")]
        stocks += stock
        price = [float(soup.find_all("td")[2].find_all("td")[i].text) for i in range(5, 5+ttl_steps, each_step)]
        prices += price
        volume = [int(soup.find_all("td")[2].find_all("td")[i].text.replace(",", "")) for i in range(11, 11+ttl_steps, each_step)]
        volumes += volume
        mkt_value = [float(soup.find_all("td")[2].find_all("td")[i].text)*100000000 for i in range(12, 12+ttl_steps, each_step)]
        mkt_values += mkt_value
    types = ["上市" for _ in range(100)] + ["上櫃" for _ in range(100)]
    ky_registered = [True if "KY" in st else False for st in stocks]
    df = pd.DataFrame()
    df["scrapingTime"] = current_dts
    df["type"] = types
    df["kyRegistered"] = ky_registered
    df["ticker"] = tickers
    df["stock"] = stocks
    df["price"] = prices
    df["volume"] = volumes
    df["mktValue"] = mkt_values
    return df

price_ranks = get_price_ranks()
conn = sqlite3.connect('/home/ubuntu/yahoo_stock.db')
price_ranks.to_sql("price_ranks", conn, if_exists="append", index=False)

接下來如果我們讓他定時啟動，那么，我們需要linux的crontab命令：

如果我們要設置每天的 9:30 到 16:30 之間每小時都執行一次

那么我們只需要先把文件命名為price_rank_scraper.py

關于Python中怎么定時執行網站爬蟲問題的解答就分享到這里了，希望以上內容可以對大家有一定的幫助，如果你還有很多疑惑沒有解開，可以關注億速云行業資訊頻道了解更多相關知識。