前言
我们在学习机器学习相关内容时，一般是不需要我们自己去爬取数据的，因为很多的算法学习很友好的帮助我们打包好了相关数据，但是这并不代表我们不需要进行学习和了解相关知识。在这里我们了解三种数据的爬取：鲜花/明星图像的爬取、中国艺人图像的爬取、股票数据的爬取。分别对着三种爬虫进行学习和使用。
- 体会
个人感觉爬虫的难点就是URL的获取，URL的获取与自身的经验有关，这点我也很难把握，一般URL获取是通过访问该网站通过抓包进行分析获取的。一般也不一定需要抓包工具，通过浏览器的开发者工具（F12/Fn+F12）即可进行获取。
鲜花/明星图像爬取
URL获取
- 百度搜索鲜花关键词，并打开开发者工具，点击NrtWork
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找到数据包进行分析,分析重要参数
- pn 表示第几张图片加载
- rn 表示加载多少图片
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查看返回值进行分析，可以看到图片体制在ThumbURL中
下载过程
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拼接tn 进行访问可以得到每个图片的URL，在返回数据的thumbURL中
https://image.baidu.com/search/acjson?+tn -
进行分离图片的URL然后访问下载
代码
import requests import os import urllib class GetImage(): def __init__(self,keyword='鲜花',paginator=1): self.url = 'http://image.baidu.com/search/acjson?' self.headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/102.0.0.0 Safari/537.36' } self.keyword = keyword self.paginator = paginator def get_param(self): keyword = urllib.parse.quote(self.keyword) params = [] for i in range(1,self.paginator+1): params.append( 'tn=resultjson_com&logid=10338332981203604364&ipn=rj&ct=201326592&is=&fp=result&fr=&word={}&queryWord={}&cl=2&lm=-1&ie=utf-8&oe=utf-8&adpicid=&st=&z=&ic=&hd=&latest=©right=&s=&se=&tab=&width=&height=&face=&istype=&qc=&nc=1&expermode=&nojc=&isAsync=&pn={}&rn=30&gsm=78&1650241802208='.format(keyword,keyword,30*i) ) return params def get_urls(self,params): urls = [] for param in params: urls.append(self.url+param) return urls def get_image_url(self,urls): image_url = [] for url in urls: json_data = requests.get(url,headers = self.headers).json() json_data = json_data.get('data') for i in json_data: if i: image_url.append(i.get('thumbURL')) return image_url def get_image(self,image_url): ##根据图片url，存入图片 file_name = os.path.join("", self.keyword) #print(file_name) if not os.path.exists(file_name): os.makedirs(file_name) for index,url in enumerate(image_url,start=1): with open(file_name+'/{}.jpg'.format(index),'wb') as f: f.write(requests.get(url,headers=self.headers).content) if index != 0 and index%30 == 0: print("第{}页下载完成".format(index/30)) def __call__(self, *args, **kwargs): params = self.get_param() urls = self.get_urls(params) image_url = self.get_image_url(urls) self.get_image(image_url=image_url) if __name__ == '__main__': spider = GetImage('鲜花',3) spider() 明星图像爬取
- 只需要把main函数里的关键字换一下就可以了，换成明星即可
if __name__ == '__main__': spider = GetImage('明星',3) spider() 其他主题
- 同理的我们需要其他图片也可以换
if __name__ == '__main__': spider = GetImage('动漫',3) spider() 艺人图像爬取
方法一
- 我们可以使用上面的爬取图片的方式，把关键词换为中国艺人也可以爬取图片
方法二
- 显然上面的方式可以满足我们部分需求，我们如果需要爬取不同艺人那么上面的方式就不是那么好了。
- 我们下载10个不同艺人的图片，然后用他们的名字命名图片名，再把他们存入picture文件内
代码
import requests import json import os import urllib def getPicinfo(url): headers = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:101.0) Gecko/20100101 Firefox/101.0', } response = requests.get(url,headers) if response.status_code == 200: return response.text return None Download_dir = 'picture' if os.path.exists(Download_dir) == False: os.mkdir(Download_dir) pn_num = 1 rn_num = 10 for k in range(pn_num): url = "https://sp0.baidu.com/8aQDcjqpAAV3otqbppnN2DJv/api.php?resource_id=28266&from_mid=500&format=json&ie=utf-8&oe=utf-8&query=%E4%B8%AD%E5%9B%BD%E8%89%BA%E4%BA%BA&sort_key=&sort_type=1&stat0=&stat1=&stat2=&stat3=&pn="+str(pn_num)+"&rn="+str(rn_num)+"&_=1580457480665" res = getPicinfo(url) json_str = json.loads(res) figs = json_str['data'][0]['result'] for i in figs: name = i['ename'] img_url = i['pic_4n_78'] img_res = requests.get(img_url) if img_res.status_code == 200: ext_str_splits = img_res.headers['Content-Type'].split('/') ext = ext_str_splits[-1] fname = name+'.'+ext open(os.path.join(Download_dir,fname),'wb').write(img_res.content) print(name,img_url,'saved') 股票数据爬取
我们对http://quote.eastmoney.com/center/gridlist.html 内的股票数据进行爬取，并且把数据储存下来
爬取代码
# http://quote.eastmoney.com/center/gridlist.html import requests from fake_useragent import UserAgent import json import csv import urllib.request as r import threading def getHtml(url): r = requests.get(url, headers={ 'User-Agent': UserAgent().random, }) r.encoding = r.apparent_encoding return r.text # 爬取多少 num = 20 stockUrl = 'http://52.push2.eastmoney.com/api/qt/clist/get?cb=jQuery112409623798991171317_1654957180928&pn=1&pz=20&po=1&np=1&ut=bd1d9ddb04089700cf9c27f6f7426281&fltt=2&invt=2&wbp2u=|0|0|0|web&fid=f3&fs=m:0+t:80&fields=f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f12,f13,f14,f15,f16,f17,f18,f20,f21,f23,f24,f25,f22,f11,f62,f128,f136,f115,f152&_=1654957180938' if __name__ == '__main__': responseText = getHtml(stockUrl) jsonText = responseText.split("(")[1].split(")")[0]; resJson = json.loads(jsonText) datas = resJson['data']['diff'] dataList = [] for data in datas: row = [data['f12'],data['f14']] dataList.append(row) print(dataList) f = open('stock.csv', 'w+', encoding='utf-8', newline="") writer = csv.writer(f) writer.writerow(("代码","名称")) for data in dataList: writer.writerow((data[0]+"t",data[1]+"t")) f.close() def getStockList(): stockList = [] f = open('stock.csv', 'r', encoding='utf-8') f.seek(0) reader = csv.reader(f) for item in reader: stockList.append(item) f.close() return stockList def downloadFile(url,filepath): try: r.urlretrieve(url,filepath) except Exception as e: print(e) print(filepath,"is downLoaded") pass sem = threading.Semaphore(1) def dowmloadFileSem(url,filepath): with sem: downloadFile(url,filepath) urlStart = 'http://quotes.money.163.com/service/chddata.html?code=' urlEnd = '&end=20210221&fields=TCLOSW;HIGH;TOPEN;LCLOSE;CHG;PCHG;VOTURNOVER;VATURNOVER' if __name__ == '__main__': stockList = getStockList() stockList.pop(0) print(stockList) for s in stockList: scode = str(s[0].split("t")[0]) url = urlStart+("0" if scode.startswith('6') else '1')+ scode + urlEnd print(url) filepath = (str(s[1].split("t")[0])+"_"+scode)+".csv" threading.Thread(target=dowmloadFileSem,args=(url,filepath)).start() 数据处理代码
有可能当时爬取的数据是脏数据，运行下面代码不一定能跑通，需要你自己处理数据还是其他方法
## 主要利用matplotlib进行图像绘制 import pandas as pd import matplotlib.pyplot as plt import csv import 股票数据爬取 as gp plt.rcParams['font.sans-serif'] = ['simhei'] #指定字体 plt.rcParams['axes.unicode_minus'] = False #显示-号 plt.rcParams['figure.dpi'] = 100 #每英寸点数 files = [] def read_file(file_name): data = pd.read_csv(file_name,encoding='gbk') col_name = data.columns.values return data,col_name def get_file_path(): stock_list = gp.getStockList() paths = [] for stock in stock_list[1:]: p = stock[1].strip()+"_"+stock[0].strip()+".csv" print(p) data,_=read_file(p) if len(data)>1: files.append(p) print(p) get_file_path() print(files) def get_diff(file_name): data,col_name = read_file(file_name) index = len(data['日期'])-1 sep = index//15 plt.figure(figsize=(15,17)) x = data['日期'].values.tolist() x.reverse() xticks = list(range(0,len(x),sep)) xlabels = [x[i] for i in xticks] xticks.append(len(x)) y1 = [float(c) if c!='None' else 0 for c in data['涨跌额'].values.tolist()] y2 = [float(c) if c != 'None' else 0 for c in data['涨跌幅'].values.tolist()] y1.reverse() y2.reverse() ax1 = plt.subplot(211) plt.plot(range(1,len(x)+1),y1,c='r') plt.title('{}-涨跌额/涨跌幅'.format(file_name.split('_')[0]),fontsize = 20) ax1.set_xticks(xticks) ax1.set_xticklabels(xlabels,rotation = 40) plt.ylabel('涨跌额') ax2 = plt.subplot(212) plt.plot(range(1, len(x) + 1), y1, c='g') #plt.title('{}-涨跌额/涨跌幅'.format(file_name.splir('_')[0]), fontsize=20) ax2.set_xticks(xticks) ax2.set_xticklabels(xlabels, rotation=40) plt.xlabel('日期') plt.ylabel('涨跌额') plt.show() print(len(files)) for file in files: get_diff(file) 总结
上文描述了三个数据爬取的案例，不同的数据爬取需要我们对不同的URL进行获取，不同参数进行输入，URL如何组合、如何获取、这是数据爬取的难点，需要有一定的经验和基础。
