cmip 0.0.9

An efficient information processing program.

cmip

一个高效的信息处理库。

安装

pip install -U cmip

用法

1. 动态渲染异步爬虫

example:

from cmip.web import web_scraping
import asyncio
urls = [
        "https://baidu.com",
        "https://qq.com",
        # ...More URL
    ]
asyncio.run(web_scraping(urls, output_path="output", max_concurrent_tasks=10, save_image=True, min_img_size=200))

参数含义：

urls	网页链接（包含协议头）
output_path	输出路径
max_concurrent_tasks	最大同时执行任务数，根据自身机器资源和网络情况调整
save_image	是否保存图片
min_img_size	当图片小于这个值时不爬取

2. 计算网页结构相似度

example:

from cmip.web import html, simhash_array, hamming_distance_array
import requests

headers = {
    "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.0.0 Safari/537.36"
}

html_text_baidu = requests.get("https://baidu.com", headers=headers).text
html_text_example_com = requests.get("https://example.com", headers=headers).text
html_text_example_org = requests.get("https://example.org", headers=headers).text
dom_tree_baidu = html.dom_tree(html_text_baidu)
dom_tree_example_com = html.dom_tree(html_text_example_com)
dom_tree_example_org = html.dom_tree(html_text_example_org)
simhash_baidu = simhash_array(dom_tree_baidu)
simhash_example_com = simhash_array(dom_tree_example_com)
simhash_example_org = simhash_array(dom_tree_example_org)

print("Similarity:", hamming_distance_array([simhash_example_com], [simhash_baidu, simhash_example_org]))

一般而言，当网页距离在4以内时，网页结构较为相似。