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Python crawler actual combat, pyecharts module, python data analysis tells you which goods are popular on free fish~

2022-01-31 13:08:58 Dai mubai

「 This is my participation 11 The fourth of the yuegengwen challenge 12 God , Check out the activity details :2021 One last more challenge 」.


Make use of Python Automation to obtain the best selling goods of a certain kind for reference . I don't say much nonsense .

Let's start happily ~

development tool

Python edition : 3.6.4

Related modules :

pyecharts modular ;

As well as some Python Built in modules .

Environment building

install Python And add to environment variable ,pip Install the relevant modules required .


1、 Good configuration Android ADB development environment

2、Python Install in virtual environment  pocoui Dependency Library

# pocoui\
pip3 install pocoui

#  Data visualization charts 
pip3 install pyecharts -U
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We can offer 7  To achieve this function , Namely : Open the target application client 、 Search keywords to the product list interface 、 Calculate the best sliding distance 、 Screen products 、 Get product link address 、 Write files, sort and count products 、 Configuration parameters .

The first 1 Step , Use pocoui Automatically open the target application .

def __pre(self):
    """      preparation      :return:     """
    start_my_app(package_name, activity)

    #  Waiting to get to the desktop 
    self.poco(text=' Idle fish ').wait_for_appearance()
    self.poco(text=' Fish pond ').wait_for_appearance()
    self.poco(text=' news ').wait_for_appearance()
    self.poco(text=' my ').wait_for_appearance()

    print(' Enter the idle fish main interface ')
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After entering the home page of idle fish , The application side will get the data of the shear board , When there is a specific law of password , A dialog box will pop up immediately , So we need to simulate closing the dialog box .

#  If there is a search password within the specified time , Just shut it down \
for i in range(10, -1, -1):\
      close_element = self.poco('')\
      if close_element.exists():\
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The first 2 Step , Search keywords to the product list interface

By the keywords to be searched , Analog input into input box , Then click the search button , Wait until the search list appears .


in addition , In order to process data more conveniently , Item list switch to list mode , That is, one line only shows one product .

def __input_key_word(self):
    """      Enter key      :return:     """
    #  Enter the search interface 

    #  Enter text in the search box 

    #  Click the search button 
    while True:
         #  Wait for the search result list to appear 
         if not self.poco('').exists():
              perform_click(self.poco('', text=' Search for '))

    #  Wait for the product list to appear 

    #  Switch to list 
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The first  3 Step , Calculate the best sliding distance .

In order to ensure the efficiency of crawling data , Get the best distance for each slide .

First get Of the current interface UI Control tree , Then through the properties of the control ID Get the coordinates of the goods , And then get the height of each item .

Last , By observing the number of products on the screen to get the best sliding distance .

def __get_good_swipe_distance(self):
    """      Get every slide , The most suitable distance      :return:     """
    element = Element()
    #  Save the current UI Tree to local 

    #  The first product Item Coordinates of 
    position_item = element.find_elment_position_by_id_and_index("",
    #  Height of commodity 
    item_height = position_item[1][1] - position_item[0][1]

    #  Through observation , The current screen has 3 Commodity 
    return item_height * 3
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The first 4 Step , Screen products .

The above steps get the best sliding distance , Constantly sliding the page, traversing the list of elements of the child Item.

It should be noted that , To avoid errors caused by sliding inertia , The duration of each slide should be set to 2s above .

Through Commodities Item select Desired number Items larger than the preset number .

#  How many people want to 
want_element_parent = item.offspring('')

if want_element_parent.exists():
     #  Want to count / Amount paid 
     want_element = want_element_parent.children()[0]

     want_content = want_element.get_text()

     #  To filter out 【 Paid 】 And other products , Keep only personal publications 
     if ' People want it ' not in want_content:
      #  Get the exact number of items you want , Represents the heat of the product 
      want_num = get_num(want_content)

      if int(want_num) < self.num_assign:
             # print(' Substandard , To filter out ')
            #  The goods want to reach the standard , Add Statistics 
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The first 5 Step , Get product link address

For products that meet the conditions in the previous step , Click on the product Item Go to the product details page .

Then click the share button in the upper right corner , The sharing dialog box will pop up immediately .

 Sharing dialog

Then click on the password control , You will be prompted that the password was successfully copied to the system clipboard .

#  Click More 
while True:
     if self.poco('').exists():
     print(' Click More ~')
     perform_click(self.poco(text=' more '))

#  Click to copy the password 
perform_click(self.poco('', text=' Ambush '))

#  Get the password code 
taobao_code_element = self.poco('')

taobao_code = taobao_code_element.get_text()
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The first 6 Step , Write product 、 Sort and count the data


The title of the product obtained above 、 Want to count 、 Write the shared address to CSV In file .

And then read the data file , By comparing the second column in the table Reverse sorting , Arrange the goods in descending order according to the desired number .

def __sort_result(self):
    """      Sort the results of crawling      :return:     """
    reader = csv.reader(open(self.file_path), delimiter=",")

    #  Head title 
    head_title = next(reader)

    #  Reverse the order in the second column 
    sortedlist = sorted(reader, key=lambda x: (int(x[1])), reverse=True)

    #  Write header data 
    write_to_csv(self.file_path, [(head_title[0], head_title[1], head_title[2])], False)

    for value in sortedlist:
       write_to_csv(self.file_path, [(value[0], value[1], value[2])], False)

    return sortedlist
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Before you finally get it 10 Data , utilize  pyecharts  Generate statistical charts .

def draw_image(self, sortedlist):
     """       drawing       :param sortedlist:      :return:      """

     #  Title list 
     titles = []

     #  sales 
     sales_num = []

     #  Get the title of the crawl results 、 Two lists of sales 
     with open(self.file_path, 'r'as csvfile:
         #  Read the file 
         reader = csv.DictReader(csvfile)

         #  Add to the list 
         for row in reader:

     #  Number limit 
     if len(titles) > self.num:
         titles = titles[:self.num]
         sales_num = sales_num[:self.num]

     #  drawing 
     bar = (
                .add_yaxis(" What's good to sell ", sales_num)
                .set_global_opts(title_opts=opts.TitleOpts(title=" I want to sell "))
     bar.render('%s.html' % self.good_msg)
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The first 7  Step , Configuration parameters

To write yaml file , Specify the keywords to crawl the product 、 Crawling time 、 Want to count the number of assessment indicators 、 Number of items to be screened .

  #  Search for products 1, Contains search keywords 、 Crawling time 
    key_word: ' Information '   #  Search for keywords 
    key_num: 100  #  Screening 【 Want to count 】 The critical point of 
    num: 10      #  Only select the hot ones 
    time: 600   #  Crawling time ( second )
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Effect display

Configure the key words in advance 、 Crawling time and other parameters , That is to say, it can climb up to meet the requirements of 、 Best selling product data , Finally, it is shown in the form of a graph .


copyright notice
author[Dai mubai],Please bring the original link to reprint, thank you.

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