python爬虫算法深度优先遍历_爬虫基础 之深度优先，广度优先策略

1.深度优先递归方式;

import re

import requests

headers = {

'User-Agent':"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.83 Safari/537.36 Edg/85.0.564.41"

}

def get_html(url):

try:

res= requests.get(url,headers=headers)

return res.text

except:

return ""

def get_son_url(url):

# 获取

html = get_html(url)

html_re = ''

href_list = re.findall(html_re,html,re.S)

return href_list

def deep_path(url):

if deepdict[url] > 3:

return

print("\t"*deepdict[url],"当前层级:%d" % deepdict[url])

# 获取子url列表

sonurl_list = get_son_url(url) #返回的是一个列表

#遍历所有的子url

for sonurl in sonurl_list:

if sonurl.startswith('https') or sonurl.startswith('http'):

if sonurl not in deepdict:

deepdict[sonurl] = deepdict[url]+1

deep_path(sonurl)

if __name__ == '__main__':

url = "https://www.baidu.com/s?wd=%E6%AD%A6%E6%B1%89%E5%85%89%E8%B0%B7"

# 控制层级

deepdict = {}

deepdict[url] = 1

deep_path(url)

2.广度优先策略之队列方法：

import re

import requests

headers = {

'User-Agent':"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.83 Safari/537.36 Edg/85.0.564.41"

}

#获取网页源代码

def get_html(url):

try:

res= requests.get(url,headers=headers)

return res.text

except:

return ""

#获取子url列表

def get_son_url(url):

# 获取

html = get_html(url)

html_re = ''

href_list = re.findall(html_re,html,re.S)

return href_list

#广度爬取

def vast_path(url):

#队列方法 先进先出

#append 入队列 pop 出队列 用列表 模拟队列

url_queue = []

url_queue.append(url) #默认先把第一个放进来

while len(url_queue)>0:

#出队列 每次取出一个

url = url_queue.pop(0)

print("\t" * deepdict[url],'当前层级:%d'%deepdict[url])

if deepdict[url]<3:

#获取子url列表

sonurl_list = get_son_url(url)

for sonurl in sonurl_list:

#过滤出有效链接

if sonurl.startswith('https') or sonurl.startswith('http'):

if sonurl not in deepdict: #过滤重复url

deepdict[sonurl] = deepdict[url]+1

#入队列

url_queue.append(sonurl)

if __name__ == '__main__':

url = "https://www.baidu.com/s?wd=%E6%AD%A6%E6%B1%89%E5%85%89%E8%B0%B7"

# 控制层级

deepdict = {} #控制层级

deepdict[url] = 1 # 默认第一级

vast_path(url)

3.深度优先策略之栈方法：

import re

import requests

headers = {

'User-Agent':"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/85.0.4183.83 Safari/537.36 Edg/85.0.564.41"

}

#获取网页源代码

def get_html(url):

try:

res= requests.get(url,headers=headers)

return res.text

except:

return ""

#获取子url列表

def get_son_url(url):

# 获取

html = get_html(url)

html_re = ''

href_list = re.findall(html_re,html,re.S)

return href_list

#广度爬取

def vast_path(url):

#队列方法 先进先出

#append 入栈 pop 出栈 用列表 模拟栈

url_queue = []

url_queue.append(url) #默认先把第一个放进来

while len(url_queue)>0:

#出栈 每次取出最后一个

url = url_queue.pop()

print("\t" * deepdict[url],'当前层级:%d'%deepdict[url])

if deepdict[url]<3:

#获取子url列表

sonurl_list = get_son_url(url)

for sonurl in sonurl_list:

#过滤出有效链接

if sonurl.startswith('https') or sonurl.startswith('http'):

if sonurl not in deepdict: #过滤重复url

deepdict[sonurl] = deepdict[url]+1 #子url相比父url层级+1

#入队列

url_queue.append(sonurl)

if __name__ == '__main__':

url = "https://www.baidu.com/s?wd=%E6%AD%A6%E6%B1%89%E5%85%89%E8%B0%B7"

# 控制层级

deepdict = {} #控制层级

deepdict[url] = 1 # 默认第一级

vast_path(url)