Concurrent.futures of python concurrent modules (2)

Last time, we briefly understood some basic methods and usage of the module. Here we further understand and expand concurrent.futures
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Concurrent.futures of python concurrent modules (2)
Take downloading pictures as an example. The following program downloads 24 expressions of http://www.58pic.com/newpic/28660111.html website in sequence.

from requests_html import HTMLSession
import os
import time

BASE_PATH="downloads"
class Get_Image():

    def __init__(self):

        self.timeout=20

        self.session=HTMLSession()

    def getiamge(self,url):

        req=self.session.get(url,timeout=self.timeout)

        if req.status_code==200:

            imgurllist=req.html.xpath("//ul[@class='emoticon-model']/li/img/@data-big")

            for index,url in enumerate(imgurllist):

                print(f"Start downloading the{index+1}Zhang picture")

                self.save_image(url,index+1)

        else:

            print("Download failed")

    def save_image(self,imgurl,index):

        print(f"Current download link:{imgurl}")

        buff=self.session.get(imgurl,timeout=self.timeout).content

        file_path=os.path.join(os.path.dirname(os.path.abspath(__file__)),BASE_PATH)

        if not os.path.exists(file_path):

            os.makedirs(file_path)

        with open(os.path.join(file_path,f"{index}.png"),"wb") as fs:

            fs.write(buff)
if __name__ == '__main__':

    start_url="http://www.58pic.com/newpic/28660111.html"

    start=time.time()

    Get_Image().getiamge(start_url)

    end=time.time()

    print(f"Download 24 pictures in sequence:{end-start}")
#The results of two runs are
#Download 24 pictures in sequence:14.926000356674194
#Time for downloading 24 pictures in sequence: 14.07800030708313

After using concurrent.futures to modify to concurrent

from requests_html import HTMLSession
import os
import time
from concurrent.futures import ThreadPoolExecutor

BASE_PATH="downloads"

MAX_WORKERS = 10 #Up to 10 threads
class Get_Image():

    def __init__(self):

        self.timeout=20

        self.session=HTMLSession()

    def getiamge(self,url):

        req=self.session.get(url,timeout=self.timeout)

        if req.status_code==200:

            imgurllist=req.html.xpath("//ul[@class='emoticon-model']/li/img/@data-big")

            works=min(len(imgurllist),MAX_WORKERS)

            with ThreadPoolExecutor(works) as excutor:

                res=excutor.map(self.save_image,imgurllist,range(1,25))

            return len(list(res))

        else:

            print("Download failed")

    def save_image(self,imgurl,index):

        print(f"Current download link:{imgurl}")

        buff=self.session.get(imgurl,timeout=self.timeout).content

        file_path=os.path.join(os.path.dirname(os.path.abspath(__file__)),BASE_PATH)

        if not os.path.exists(file_path):

            os.makedirs(file_path)

        with open(os.path.join(file_path,f"{index}.png"),"wb") as fs:

            fs.write(buff)
if __name__ == '__main__':

    start_url="http://www.58pic.com/newpic/28660111.html"

    start=time.time()

    Get_Image().getiamge(start_url)

    end=time.time()

    print(f"Download 24 pictures at the same time:{end-start}")
#The results of two runs are
#Download 24 pictures at the same time:7.737000226974487
#Download 24 pictures at the same time: 7.083999872207642

Through observation, it is found that the efficiency is greatly improved after the speed is concurrent.