前言
为了巩固所学的知识，作者尝试着开始发布一些学习笔记类的博客，方便日后回顾。当然，如果能帮到一些萌新进行新技术的学习那也是极好的。作者菜菜一枚，文章中如果有记录错误，欢迎读者朋友们批评指正。
（博客的参考源码可以在我主页的资源里找到，如果在学习的过程中有什么疑问欢迎大家在评论区向我提出）
发现宝藏
前些天发现了一个巨牛的人工智能学习网站，通俗易懂，风趣幽默，忍不住分享一下给大家。【宝藏入口】。
import os
import re
from datetime import datetime
import requests
import json
from bs4 import BeautifulSoup
from pymongo import MongoClient
from tqdm import tqdm
class ArticleCrawler:
def __init__(self, catalogues_url, card_root_url, output_dir, db_name='ren-ming-wang'):
self.catalogues_url = catalogues_url
self.card_root_url = card_root_url
self.output_dir = output_dir
self.client = MongoClient('mongodb://localhost:27017/')
self.db = self.client[db_name]
self.catalogues = self.db['catalogues']
self.cards = self.db['cards']
self.headers = {
'Referer': 'https://jhsjk.people.cn/result?',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
'Chrome/119.0.0.0 Safari/537.36',
'Cookie': '替换成你自己的',
}
# 发送带参数的get请求并获取页面内容
def fetch_page(self, url, page):
params = {
'keywords': '',
'isFuzzy': '0',
'searchArea': '0',
'year': '0',
'form': '',
'type': '0',
'page': page,
'origin': '全部',
'source': '2',
}
response = requests.get(url, params=params, headers=self.headers)
soup = BeautifulSoup(response.text, 'html.parser')
return soup
# 解析请求版面
def parse_catalogues(self, json_catalogues):
card_list = json_catalogues['list']
for list in card_list:
a_tag = 'article/'+list['article_id']
card_url = self.card_root_url + a_tag
card_title = list['title']
updateTime = list['input_date']
self.parse_cards(card_url, updateTime)
date = datetime.now()
catalogues_id = list['article_id']+'01'
# 检查重复标题
existing_docs = self.catalogues.find_one({'id': catalogues_id})
if existing_docs is not None:
print(f'版面id: {catalogues_id}【已经存在】')
continue
card_data = {
'id': catalogues_id,
'title': card_title,
'page': 1,
'serial': 1,
# 一个版面一个文章
'dailyId': '',
'cardSize': 1,
'subjectCode': '50',
'updateTime': updateTime,
'institutionnCode': '10000',
'date': date,
'snapshot': {
}
}
self.catalogues.insert_one(card_data)
print(f'版面id: {catalogues_id}【插入成功】')
# 解析请求文章
def parse_cards(self, url, updateTime):
response = requests.get(url, headers=self.headers)
soup = BeautifulSoup(response.text, "html.parser")
try:
title = soup.find("div", "d2txt clearfix").find('h1').text
except:
try:
title = soup.find('h1').text
except:
print(f'【无法解析该文章标题】{url}')
html_content = soup.find('div', 'd2txt_con clearfix')
text = html_content.get_text()
imgs = [img.get('src') or img.get('data-src') for img in html_content.find_all('img')]
cleaned_content = self.clean_content(text)
# 假设我们有一个正则表达式匹配对象match
match = re.search(r'\d+', url)
# 获取匹配的字符串
card_id = match.group()
date = datetime.now()
if len(imgs) != 0:
# 下载图片
self.download_images(imgs, card_id)
# 创建文档
document = {
'id': card_id,
'serial': 1,
'page': 1,
'url' : url,
'type': 'ren-ming-wang',
'catalogueId': card_id + '01',
'subjectCode': '50',
'institutionCode': '10000',
'updateTime': updateTime,
'flag': 'true',
'date': date,
'title': title,
'illustrations': imgs,
'html_content': str(html_content),
'content': cleaned_content
}
# 检查重复标题
existing_docs = self.cards.find_one({'id': card_id})
if existing_docs is None:
# 插入文档
self.cards.insert_one(document)
print(f"文章id：{card_id}【插入成功】")
else:
print(f"文章id：{card_id}【已经存在】")
# 文章数据清洗
def clean_content(self, content):
if content is not None:
content = re.sub(r'\r', r'\n', content)
content = re.sub(r'\n{2,}', '', content)
# content = re.sub(r'\n', '', content)
content = re.sub(r' {6,}', '', content)
content = re.sub(r' {3,}\n', '', content)
content = content.replace('<P>', '').replace('<\P>', '').replace(' ', ' ')
return content
# 下载图片
def download_images(self, img_urls, card_id):
# 根据card_id创建一个新的子目录
images_dir = os.path.join(self.output_dir, card_id)
if not os.path.exists(images_dir):
os.makedirs(images_dir)
downloaded_images = []
for img_url in img_urls:
try:
response = requests.get(img_url, stream=True)
if response.status_code == 200:
# 从URL中提取图片文件名
image_name = os.path.join(images_dir, img_url.split('/')[-1])
# 确保文件名不重复
if os.path.exists(image_name):
continue
with open(image_name, 'wb') as f:
f.write(response.content)
downloaded_images.append(image_name)
print(f"Image downloaded: {img_url}")
except Exception as e:
print(f"Failed to download image {img_url}. Error: {e}")
return downloaded_images
# 如果文件夹存在则跳过
else:
print(f'文章id为{card_id}的图片文件夹已经存在')
# 查找共有多少页
def find_page_all(self, soup):
# 查找<em>标签
em_tag = soup.find('em', onclick=True)
# 从onclick属性中提取页码
if em_tag and 'onclick' in em_tag.attrs:
onclick_value = em_tag['onclick']
page_number = int(onclick_value.split('(')[1].split(')')[0])
return page_number
else:
print('找不到总共有多少页数据')
# 关闭与MongoDB的连接
def close_connection(self):
self.client.close()
# 执行爬虫，循环获取多页版面及文章并存储
def run(self):
soup_catalogue = self.fetch_page(self.catalogues_url, 1)
page_all = self.find_page_all(soup_catalogue)
if page_all:
for index in tqdm(range(1, page_all), desc='Page'):
# for index in tqdm(range(1, 50), desc='Page'):
soup_catalogues = self.fetch_page(self.catalogues_url, index).text
# 解析JSON数据
soup_catalogues_json = json.loads(soup_catalogues)
self.parse_catalogues(soup_catalogues_json)
print(f'======================================Finished page {index}======================================')
self.close_connection()
if __name__ == "__main__":
crawler = ArticleCrawler(
catalogues_url='http://jhsjk.people.cn/testnew/result',
card_root_url='http://jhsjk.people.cn/',
output_dir='D:\\ren-ming-wang\\img'
)
crawler.run() # 运行爬虫，搜索所有内容
crawler.close_connection() # 关闭数据库连接