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🗣 Wd提问: Python SEO爬虫

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Python SEO爬虫开发指南

SEO(搜索引擎优化)爬虫是帮助网站优化排名的有用工具。以下是使用Python开发SEO相关爬虫的几种常见方法和实现。

基础SEO爬虫功能

1、网站地图(Sitemap)解析器

python
import requests
from bs4 import BeautifulSoup
from urllib.parse import urljoin

def parse_sitemap(sitemap_url):
try:
response = requests.get(sitemap_url)
soup = BeautifulSoup(response.content, 'lxml-xml')
urls = [loc.text for loc in soup.find_all('loc')]

处理嵌套的sitemap索引
sitemap_tags = soup.find_all('sitemap')
if sitemap_tags:
for sitemap in sitemap_tags:
nested_sitemap_url = sitemap.find('loc').text
urls.extend(parse_sitemap(nested_sitemap_url))

return urls
except Exception as e:
print(fError parsing sitemap: {e})
return []

使用示例
sitemap_url = https://65.hk/sitemap.xml
urls = parse_sitemap(sitemap_url)
print(fFound {len(urls)} URLs in sitemap)

2、检查页面SEO元素

python
def check_seo_elements(url):
try:
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

检查标题
title = soup.find('title')
title_text = title.text if title else No title found
title_length = len(title_text)

检查meta描述
meta_desc = soup.find('meta', attrs={'name': 'description'})
meta_desc_text = meta_desc['content'] if meta_desc else No meta description
meta_desc_length = len(meta_desc_text)

检查h1标签
h1_tags = [h1.text for h1 in soup.find_all('h1')]

检查图片alt属性
images = soup.find_all('img')
images_without_alt = [img['src'] for img in images if 'alt' not in img.attrs]

return {
'url': url,
'title': title_text,
'title_length': title_length,
'meta_description': meta_desc_text,
'meta_description_length': meta_desc_length,
'h1_tags': h1_tags,
'images_without_alt': images_without_alt
}
except Exception as e:
print(fError checking {url}: {e})
return None

进阶SEO爬虫功能

3、内部链接分析

python
from collections import defaultdict

def analyze_internal_links(base_url, start_url):
visited = set()
to_visit = {start_url}
link_graph = defaultdict(list)

while to_visit:
url = to_visit.pop()
if url in visited:
continue

print(fProcessing: {url})
try:
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

找出所有链接
for link in soup.find_all('a', href=True):
href = link['href']
absolute_url = urljoin(url, href)

如果是内部链接
if absolute_url.startswith(base_url):
link_graph[url].append(absolute_url)
if absolute_url not in visited:
to_visit.add(absolute_url)

visited.add(url)
except Exception as e:
print(fError processing {url}: {e})

分析链接结构
incoming_links = defaultdict(int)
for src, dests in link_graph.items():
for dest in dests:
incoming_links[dest] += 1

return link_graph, incoming_links

4、关键词密度分析

python
from collections import Counter
import string
import nltk
from nltk.corpus import stopwords

nltk.download('stopwords')

def analyze_keyword_density(url):
try:
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

获取主要内容文本
text = ' '.join([p.get_text() for p in soup.find_all(['p', 'h1', 'h2', 'h3', 'h4'])])

清理文本
text = text.lower()
text = text.translate(str.maketrans('', '', string.punctuation))
words = text.split()

移除停用词
stop_words = set(stopwords.words('english'))
filtered_words = [word for word in words if word not in stop_words]

计算词频
word_counts = Counter(filtered_words)
total_words = len(filtered_words)

计算密度
keyword_density = {
word: (count/total_words)*100
for word, count in word_counts.most_common(20)
}

return keyword_density
except Exception as e:
print(fError analyzing {url}: {e})
return None

专业SEO工具

5、结合SEO API (如Moz, Ahrefs等)

python
import requests

def get_moz_metrics(url, access_id, secret_key):
endpoint = http://lsapi.seomoz.com/linkscape/url-metrics/
payload = {
Cols: 103079215104, 基本指标
AccessID: access_id,
Expires: str(int(time.time()) + 300),
Signature: generate_moz_signature(secret_key)
}

response = requests.get(endpoint + url, params=payload)
if response.status_code == 200:
return response.json()
else:
raise Exception(fMOZ API error: {response.text})

def generate_moz_signature(secret_key):
实现MOZ签名生成逻辑
pass

最佳实践和注意事项

1、遵守robots.txt：始终检查并遵守网站的robots.txt规则
2、设置合理延迟：避免对目标服务器造成负担
python
import time
time.sleep(1) 每次请求之间暂停1秒

3、使用User-Agent：模拟真实浏览器访问
python
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
}
response = requests.get(url, headers=headers)

4、处理JavaScript渲染：对于SPA网站，可能需要Selenium或Playwright
python
from selenium import webdriver

driver = webdriver.Chrome()
driver.get(url)
html = driver.page_source

5、存储结果：将爬取数据保存到数据库或文件
python
import csv

with open('seo_data.csv', 'w', newline='') as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=seo_data.keys())
writer.writeheader()
writer.writerow(seo_data)

这些代码示例提供了SEO爬虫的基础框架，您可以根据具体需求进行扩展和修改。

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