wen 数据准备-
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
-
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
-
查看返回值进行分析，可以看到图片体制在ThumbURL中
下载过程
-
http://image.baidu.com/search/acjson? 百度图片地址
-
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]+" ",data[1]+" "))
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(" ")[0])
url = urlStart+("0" if scode.startswith("6") else "1")+ scode + urlEnd
print(url)
filepath = (str(s[1].split(" ")[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。
