python爬取点击后的结果 python爬取例子

1、爬取百度

import requests
keyword = "Python"
try:
	kv = {'wd':keyword}
	r = requests.get("http://www.baidu.com/s",params=kv)
	print(r.request.url)
	r.raise_for_status()
	print(r.text)
except:
    print("爬取失败")

2、查询IP地址

import requests
url = "https://ip138.com/iplookup.asp?ip="
kv={'user-agent':'Mozilla/5.0'}
try:
    r= requests.get(url+'ip'+'&action=2','202.204.80.112',headers=kv)
    r.raise_for_status()
    r.encoding = r.apparent_encoding
    print(r.text[-500:])
except:
    print("失败")

3、股票爬取

import requests
from bs4 import BeautifulSoup
import traceback
import re
def getHTMLText(url):
    try:
        r=requests.get(url)
        r.raise_for_ststus()
        r.encoding=r.apparent_encoding
        return r.text
    except:
        return""
def getStockList(lst,stockURL):
    html=getHTMLText(stockURL)
    soup=BeautifulSoup(html,'html.parser')
    a=soup.find_all('a')
    for i in a:
        try:
            href=i.attrs['href']
            lst.append(re.finall(r"[s][hz]\d{6}",href)[0])
        except:
            continue
        return ""
def getStockInfo(lst,stockURL,fpath):
    count=0
    timel=time.time()
    for stock in lst:
        url = stockURL + stock
        html = getHTMLText(url)
        try:
            if html == "":
                continue
            infoDict = {}
            soup = BeautifulSoup(html,'html.parser')
            stockInfo = soup.find('header',attrs = {'class':'stock_title'})
 
            name = stockInfo.find_all(attrs = {'h1':''})[0]
            infoDict.update({'股票名称':name.text.split('</h1>')[0]})
 
            stockInfo = soup.find('div',attrs = {'class':'stock_top clearfix'})
 
            keyList = stockInfo.find_all('dt')
            valueList = stockInfo.find_all('dd')
            for i in range(len(keyList)):
                key = keyList[i].text
                val = valueList[i].text
                infoDict[key] = val
            with open(fpath,'a',encoding = 'utf-8') as f:
                f.write(str(infoDict) + '\n')
                count = count + 1
                time2 = time.time() - time1 
                print('\r当前速度：{:.2f}%\t用时：{:.2f}秒'.format((count * 100 /len(lst)),time2),end ='')
        except:
            count = count + 1
            time2 = time.time() - time1
            print('\r当前速度：{:.2f}%\t用时：{:.2f}秒'.format((count * 100 /len(lst)),time2),end ='')
            traceback.print_exc()
            continue
        return ""
def main():
    stock_list_url = 'https://hq.gucheng.com/gpdmylb.html'
    stock_info_url = 'https://hq.gucheng.com/'
    output_file = 'C:\\StockInfo.txt'
    slist = []
    getStockList(slist,stock_list_url)
    getStockInfo(slist,stock_info_url,output_file)
main()

4、爬取京东商品

import requests
url="http://item.jd.com/2967929.html"
try:
    r=requests.get(url)
    r.raise_for_status()
    r.encoding=r.apparent_encoding
    print(r.text[:1000])
except:
    print("爬取失败")

5、爬取图片

import requests
import os
url= "http://pic.87g.com/upload/2020/0102/20200102093322295.jpg"
root= "C://Users//15133//Pictures//Camera Roll"
path=root+url.split('/')[-1]
try:
    if not os.path.exists(root):
        os.mkdir(root)
    if not os.path.exists(path):
        r=requests.get(url)
        with open(path,'wb') as f:
            f.write(r.content)
            f.close()
            print("成功")
    else:
        print("存在")
except:
    print("失败")

6、图表库练习

import matplotlib.pyplot as plt
labels= 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30,45, 10]
explode = (0, 0.1,0, 0)
plt.pie(sizes, explode=explode, labels=labels, autopct= '%1.1f%%',shadow=False, startangle=90)
plt. show()

7、图片转水墨画

from PIL import Image
import numpy as np

a = np.asarray(Image.open('C:\Users\15133\Pictures\Saved Pictures\QQ图片20191029201945.jpg').convert('L')).astype('float')

depth = 10. 						# (0-100)
grad = np.gradient(a)				#取图像灰度的梯度值
grad_x, grad_y = grad 				#分别取横纵图像梯度值
grad_x = grad_x*depth/100.
grad_y = grad_y*depth/100.
A = np.sqrt(grad_x**2 + grad_y**2 + 1.)
uni_x = grad_x/A
uni_y = grad_y/A
uni_z = 1./A

vec_el = np.pi/2.2 					# 光源的俯视角度，弧度值
vec_az = np.pi/4. 					# 光源的方位角度，弧度值
dx = np.cos(vec_el)*np.cos(vec_az) 	#光源对x 轴的影响
dy = np.cos(vec_el)*np.sin(vec_az) 	#光源对y 轴的影响
dz = np.sin(vec_el) 				#光源对z 轴的影响

b = 255*(dx*uni_x + dy*uni_y + dz*uni_z) 	#光源归一化
b = b.clip(0,255)


im = Image.fromarray(b.astype('uint8')) 	#重构图像
im.save('C:\Users\15133\Pictures\Saved Pictures\QQ图片20191029201945.jpg')

8、爬取高校排名

import requests
from bs4 import BeautifulSoup
import bs4
def getHTMLText(url) :
    try:
        r= requests.get(url,timeout=30)
        r.raise_for_status()
        r.encoding=r.apparent_encoding
        return r.text
    except:
        return ""

def fillUnivList(ulist,html):
    soup=BeautifulSoup(html,"html.parser")
    for tr in soup.find('tbody').children:
        if isinstance(tr,bs4.element.Tag):
            tds=tr('td')
            ulist.append([tds[0].string,tds[1].string,tds[3].string])
def printUnivList(ulist,num):
    print("{:^10}\t{:^6}\t{:^10}".format("排名","学校","总分"))
    for i in range(num):
        u=ulist[i]
        print("{:^10}\t{:^6}\t{:^10}".format(u[0],u[1],u[2]))
def main():
    uinfo=[]
    url='http://www.zuihaodaxue.cn/zuihaodaxuepaiming2019.html'
    html=getHTMLText(url)
    fillUnivList(uinfo,html)
    printUnivList(uinfo,20)# 20 unives
main()

9、亚马逊商品爬取

import requests
url = "https://www.amazon.cn/gp/product/B01M8L5Z3Y"
try:
    kv = {'user-agent':'Mozilla/5.0'}
    r = requests.get(url,headers=kv)
    r.raise_for_status()
    r.encoding = r.apparent_encoding
    print(r.text[1000:2000])
except:
    print("爬取失败")