为什么我不能在 `requests` 中循环遍历 `payload` 来迭代我的网络爬虫？

2024-06-11 21:39:34 发布

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摘要：我想迭代一个requests有效负载，这样我就可以更改每次刮取的登录ID号。在

我用requests&beautiful soup做了一个网页浏览。 要登录到该页面，我需要输入一个唯一的ID号；我有一个这样的号码列表，名为hit_list。在

对于任何给定的ID号，这个脚本都可以正常工作。但我想做的是让它自动化，这样它就可以贯穿我的整个hit_list

换句话说，我希望num中的num为每次迭代更改。目前num保持不变，并且刮片只是根据hit_list的长度迭代（即，在这种情况下，相同的刮擦将运行五次）

请注意，我对编码非常陌生，这是我的第一个项目。我知道它可能会有问题，很高兴收到建设性的批评。在

Importing Libraries
import requests
import pymysql.cursors
from pymysql import connect, err, sys, cursors
import sys
import time
import bs4
import time
from datetime import datetime
import openpyxl


#Recording time @ Start
startTime = datetime.now()
print(datetime.now())

#use pymysql to create database- omitted here for parsimony

#This is a sample list, in reality the list will have 100,000 + numbers.
hit_list = [100100403,100100965,100101047,100100874,100100783]

"""
This is my code for importing the real list, included here incase the way the list is imported is relevant to the problem
wb = openpyxl.load_workbook('/Users/Seansmac/Desktop/stage2_trial.xlsx')
sheet= wb.get_sheet_by_name('Sheet1')
type(wb)
#LOUIS: Only importing first twenty (for trial purposes)
for id in range(1,20):
   hit_list.append(sheet.cell(row=id, column =1).value)
"""

def web_scrape():
#I'm only creating a function, because I'm told it's always good practice to put any 'bit' of logic into a function- I'm aware this probably looks amateurish.   
#Open page
    url = 'https://ndber.seai.ie/pass/ber/search.aspx' 

with requests.session() as r:
        r.headers.update({
    'user-agent': 'For more information on this data collection please contact **************************************'
})    

  for num in hit_list:
      #***LOCATION OF THE PROBLEM***
      payload_1 = {
                'ctl00$DefaultContent$BERSearch$dfSearch$txtBERNumber':num, 
                'ctl00$DefaultContent$BERSearch$dfSearch$Bottomsearch': 'Search',
                '__VIEWSTATE' :'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',
            }            
            r.post(url, data=payload_1)              
#click intermediate page    
            payload_2 = {
                    '__EVENTTARGET': 'ctl00$DefaultContent$BERSearch$gridRatings$gridview$ctl02$ViewDetails',
                    '__VIEWSTATE': "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",
                    '__VIEWSTATEGENERATOR':"1F9CCB97",                
                    '__EVENTVALIDATION': "/wEdAAbaTEcivWuxiWecwu4mVYO9eUnQmzIzqu4hlt+kSDcrOBWCa0ezllZh+jGXjO1EB1dmMORt6G1O0Qbn0WLg3p+rPmLeN6mjN7eq7JtUZMjpL2DXqeB/GqPe7AFtNDKiJkEPdN6Y/vq7o/49hX+o366Ioav3zEBl37yPlq3sYQBXpQ==",
               }              
            s=r.post(url, data=payload_2)          
#scrape the page      
            soup = bs4.BeautifulSoup(s.content, 'html.parser')

"""   

FOR THE PURPOSES OF MY ISSUE EVERYTHING BELOW WORKS FINE & CAN BE SKIPPED

"""

 print('\nBEGINNING SCRAPE....')                  
# First Section                    
            ber_dec = soup.find('fieldset', {'id':'ctl00_DefaultContent_BERSearch_fsBER'})            
#Address- clean scrape
            address = ber_dec.find('div', {'id':'ctl00_DefaultContent_BERSearch_dfBER_div_PublishingAddress'})
            address = (address.get_text(',').strip())
            print('address:', address)            
#Date of Issue- clean scrape
            date_issue1 = ber_dec.find('span', {'id':'ctl00_DefaultContent_BERSearch_dfBER_container_DateOfIssue'})
            date_issue =  date_issue1.find('div', {'class':'formControlReadonly'})        
            date_issue = (date_issue.get_text().strip())
            print('date_of_issue:',date_issue)            
#MPRN -Clean scrape
            MPRN1 = ber_dec.find('span',{'id':'ctl00_DefaultContent_BERSearch_dfBER_container_MPRN'})
            MPRN = MPRN1.find('div',{'class':'formControlReadonly'})
            MPRN = MPRN.get_text().strip()
            print('MPRN:', MPRN)            
#Emissions Indicator- clean scrape
            emissions_indicator1 = ber_dec.find('div',{'id':'ctl00_DefaultContent_BERSearch_dfBER_div_CDERValue'})
            emissions_indicator_bunched = emissions_indicator1.get_text().strip()            
            print('\n\nem_bunched:',emissions_indicator_bunched)        
            emissions_indicator, emissions_indicator_unit = emissions_indicator_bunched.split()
            print('emissions_indicator:',emissions_indicator)      
            emissions_indicator_unit= emissions_indicator_unit.replace("(","")
            emissions_indicator_unit=emissions_indicator_unit.replace(")","")
            print('emissions_indicator_unit:',emissions_indicator_unit)              

            #BER Score- clean scrape      
            BER_bunched = ber_dec.find('div', {'id':'ctl00_DefaultContent_BERSearch_dfBER_div_EnergyRating'})
            BER_bunched =(BER_bunched.get_text().strip())
            print ('\n \nBER_bunched:', BER_bunched)                  
            BER_score, BER_actual_rating, BER_unit  = BER_bunched.split()      
            print('\nBER_score:',BER_score)
            print('\nBER_actual_rating:',BER_actual_rating)
            BER_unit = BER_unit.replace("(", " ")
            BER_unit = BER_unit.replace(")","")
            print('\nClean_BER_unit:',BER_unit )

            #Type of Rating- clean scrape
            type_of_rating1= ber_dec.find('span',{'id':'ctl00_DefaultContent_BERSearch_dfBER_container_TypeOfRating'})
            type_of_rating= type_of_rating1.find('div',{'class':'formControlReadonly'})
            type_of_rating = type_of_rating.get_text().strip()
            print('type_of_rating:',type_of_rating )


            # Second Section

            dwelling_details = soup.find('fieldset', {'id':'ctl00_DefaultContent_BERSearch_fsStructure'})

            #Dwelling Type- clean scrape
            dwelling_type1 = dwelling_details.find('span',{'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_DwellingType'})
            dwelling_type = dwelling_type1.find('div',{'class':'formControlReadonly'})
            dwelling_type = dwelling_type.get_text().strip()
            print ('Dwelling Type:', dwelling_type)      

            #Number of Stories- clean scrape
            num_stories1 = dwelling_details.find('span', {'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_NoStoresy'})
            num_stories = num_stories1.find('div',{'class':'formControlReadonly'})
            num_stories = num_stories.get_text().strip()
            print('Number of Stories:', num_stories)

            #Year of Construction- clean scrape
            yr_construction1 = dwelling_details.find('span',{'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_DateOfConstruction'})
            yr_construction = yr_construction1.find('div',{'class':'formControlReadonly'})    
            yr_construction = yr_construction.get_text().strip()
            print('Year of Construction:', yr_construction)            

            #Floor Area- clean scrape
            floor_area= dwelling_details.find('div', {'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_div_FloorArea'})
            floor_area = floor_area.get_text().strip()
            floor_area, floor_area_unit =floor_area.split()
            floor_area_unit = floor_area_unit.replace("(","")
            floor_area_unit=floor_area_unit.replace(")","")
            print('\nFloor Area:', floor_area)
            print('floor_area_unit:', floor_area_unit)

            #Wall Type- clean scrape
            wall_type1 = dwelling_details.find('span',{'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_WallType'})
            wall_type = wall_type1.find('div',{'class':'formControlReadonly'})      
            wall_type= wall_type.get_text().strip()
            print('Wall Type:', wall_type)

            #Glazing Type- clean scrape
            glazing_type1 =dwelling_details.find('span',{'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_GlazingType'})
            glazing_type =glazing_type1.find('div',{'class':'formControlReadonly'})
            glazing_type = glazing_type.get_text().strip()
            print('Glazing Type:', glazing_type)

            #Percent Low Energy Lighting- clean scrape
            percent_low_energy_lighting1= dwelling_details.find('span', {'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_PercentLowEnergyLight'})
            percent_low_energy_lighting = percent_low_energy_lighting1.find('div',{'class':'formControlReadonly'})      
            percent_low_energy_lighting = percent_low_energy_lighting.get_text().strip()
            print('% Low Energy Lighting:', percent_low_energy_lighting)

            #Space Heating Fuel- clean scrape
            space_heating_fuel1 =dwelling_details.find('span', {'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_MainSpaceHeatingFuel'})
            space_heating_fuel =space_heating_fuel1.find('div',{'class':'formControlReadonly'})
            space_heating_fuel = space_heating_fuel.get_text().strip()
            print('Space Heating Fuel:',space_heating_fuel)

            #Space Heating Efficiency- clean scrape
            space_heating_efficiency1= dwelling_details.find('span', {'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_MainSpaceHeatingEfficiency'})
            space_heating_efficiency = space_heating_efficiency1.find('div',{'class':'formControlReadonly'})        
            space_heating_efficiency= space_heating_efficiency.get_text().strip()
            print('Space Heating Efficiency:', space_heating_efficiency)

            #Water Heatng Fuel- clean scrape
            water_heating_fuel1 = dwelling_details.find('span', {'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_MainWaterHeatingFuel'})
            water_heating_fuel =water_heating_fuel1.find('div',{'class':'formControlReadonly'})
            water_heating_fuel = water_heating_fuel.get_text().strip()
            print('Water Heating Fuel:', water_heating_fuel)

            #Water Heating Efficiency- clean scrape
            water_heating_efficiency1 =dwelling_details.find('span',{'id':'ctl00_DefaultContent_BERSearch_dfNasStructuralDetails_container_MainWaterHeatingEfficiency'})
            water_heating_efficiency =water_heating_efficiency1.find('div',{'class':'formControlReadonly'})    
            water_heating_efficiency= water_heating_efficiency.get_text().strip()
            print('Water Heating Efficiency:', water_heating_efficiency)


            #thrid section
            assessor_details = soup.find('fieldset', {'id':'ctl00_DefaultContent_BERSearch_fsAssessor'})

            #Assessor Number- clean scrape
            assessor_num1 = assessor_details.find('span', {'id':'ctl00_DefaultContent_BERSearch_dfAssessor_container_AssessorNumber'})
            assessor_num = assessor_num1.find('div',{'class':'formControlReadonly'})
            assessor_num= assessor_num.get_text().strip()
            print('Assessor Number:', assessor_num)

            print('BER:', num)

            print('\***************nSCRAPE FINISHED***************\n')


            #Populate datebase      
            print('\nRECONNECTING WITH DATABASE')
            with connection.cursor() as cursor:
                print('SUCCESSFUL CONNECTION')
                sql =("INSERT INTO table1(BER_number, MPRN, address, BER_score, BER_actual_rating, BER_unit, emissions_indicator, emissions_indicator_unit, date_issue, floor_area, floor_area_unit, dwelling_type, num_stories, yr_construction, wall_type, assessor_num, water_heating_efficiency, glazing_type, percent_low_energy_lighting, space_heating_fuel, space_heating_efficiency, water_heating_fuel, type_of_rating)VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)")
                cursor.execute(sql, (num, MPRN, address, BER_score, BER_actual_rating, BER_unit, emissions_indicator, emissions_indicator_unit, date_issue, floor_area, floor_area_unit, dwelling_type, num_stories, yr_construction, wall_type, assessor_num, water_heating_efficiency, glazing_type, percent_low_energy_lighting, space_heating_fuel, space_heating_efficiency, water_heating_fuel, type_of_rating))
                print('ROW POPULATED')

#Calling the function
web_scrape()

#Metadata
print('Gathering Details...')
Run_time = datetime.now() - startTime
print('Run Time:', Run_time)

#Loop Finished        

print('\n***************PROGRAMME FINISHED***************')

Tags： dividgettypeunitfindnumprint
2条回答
网友
1楼 · 编辑于 2024-06-11 21:39:34

@padraickunningham提供了这个答案的大部分逻辑，但是正如我在他的答案下面的评论所描述的，他的解决方案只让我走了一半。
我已经能够在他的工作基础上解决这个问题。
还有一个步骤需要完成，那就是“点击”一个中介页面，这将导致我想要获取的数据所在的位置。在

提前为我的不标准标签和格式道歉。我是初学者。在

import requests
import pymysql.cursors
from pymysql import connect, err, sys, cursors
import sys
import time
import bs4
import time
from datetime import datetime
import openpyxl

hit_list = [100100403,100100965,100101047,100100874,100100783] #this is a sample list
#Open page 
url = 'https://ndber.seai.ie/pass/ber/search.aspx'


def field_update(s):
    soup = bs4.BeautifulSoup(s.get(url).content,"html.parser")
    return {"__VIEWSTATE": soup.select_one("#__VIEWSTATE")["value"],
    "__VIEWSTATEGENERATOR": soup.select_one("#__VIEWSTATEGENERATOR")    ["value"],
    "__EVENTVALIDATION": soup.select_one("#__EVENTVALIDATION")["value"]}
    print('field updated')

with requests.session() as s:
    for ber in hit_list:
        payload_1 = {
            'ctl00$DefaultContent$BERSearch$dfSearch$txtBERNumber': ber,
            'ctl00$DefaultContent$BERSearch$dfSearch$Bottomsearch': 'Search'}
# update the post data with new token values
    payload_1.update(field_update(s))
    r = s.post(url, data=payload_1)

#'click through' intermediate page
#THIS IS THE ADDITIONAL CODE THAT BUILDS ON PADRAIC'S ANSWER
    soup = bs4.BeautifulSoup(r.content,"html.parser")
    stage_two= {
        "__EVENTTARGET": 'ctl00$DefaultContent$BERSearch$gridRatings$gridview$ctl02$ViewDetails',
        "__VIEWSTATE": soup.select_one("#__VIEWSTATE")["value"],
        "__VIEWSTATEGENERATOR": soup.select_one("#__VIEWSTATEGENERATOR")["value"],
        "__EVENTVALIDATION": soup.select_one("#__EVENTVALIDATION")["value"]}        

    q=s.post(url, data=stage_two)
    print('payload_2 posted')    
    soup = bs4.BeautifulSoup(q.content, 'html.parser')


    print('\nBEGINNING SCRAPE....')
    #FOR DATA TO BE SCRAPED, SEE ORIGINAL QUESTION
网友
2楼 · 编辑于 2024-06-11 21:39:34

您需要获得新的__EVENTVALIDATION令牌等。。。对于每个帖子，您不能只从浏览器中复制值并将其硬编码到帖子数据中：

import requests

url = 'https://ndber.seai.ie/pass/ber/search.aspx'
hit_list = [100100403, 100100965, 100101047, 100100874, 100100783]
h = {}


def renew(s):
    soup = BeautifulSoup(s.get(url).content,"html.parser.)
    return {"__VIEWSTATE": soup.select_one("#__VIEWSTATE")["value"],
            "__VIEWSTATEGENERATOR": soup.select_one("#__VIEWSTATEGENERATOR")["value"],
            "__EVENTVALIDATION": soup.select_one("#__EVENTVALIDATION")["value"]}


with requests.session() as s:
    for num in hit_list:
        payload_1 = {
            'ctl00$DefaultContent$BERSearch$dfSearch$txtBERNumber': num,
            'ctl00$DefaultContent$BERSearch$dfSearch$Bottomsearch': 'Search'}
        # update the post data with new token values
        payload_1.update(renew(s))
        r = s.post(url, data=payload_1)

        # scrape the page
        soup = BeautifulSoup(r.content, 'html.parser')

如果我们运行代码并分析一些返回的内容，您可以看到我们正确地获取了每个页面：

^{pr2}$

这给了你所有的信息，从表格栏的BER证书编号，你已经有了，所以你不需要担心它。在

当您发现您只需要将数据从第一个post返回的内容传递到第二个有效负载时，如果您将逻辑封装在函数中，那么您的代码也会更易于管理：

def renew(soup):
    return {"__VIEWSTATE": soup.select_one("#__VIEWSTATE")["value"],
            "__VIEWSTATEGENERATOR": soup.select_one("#__VIEWSTATEGENERATOR")["value"],
            "__EVENTVALIDATION": soup.select_one("#__EVENTVALIDATION")["value"]}


def parse_data(soup):
    address = soup.select_one("#ctl00_DefaultContent_BERSearch_dfBER_div_PublishingAddress").text.strip()
    MPRN = soup.select_one("#ctl00_DefaultContent_BERSearch_dfBER_container_MPRN div.formControlReadonly").text.strip()
    emissions_indicator, emissions_indicator_unit = soup.select_one(
        "#ctl00_DefaultContent_BERSearch_dfBER_div_CDERValue").text.split()
    emissions_indicator_unit = emissions_indicator_unit.strip("()")
    BER_score, BER_actual_rating, BER_unit = soup.select_one(
        "#ctl00_DefaultContent_BERSearch_dfBER_div_EnergyRating").text.split()
    BER_unit = BER_unit.strip("()")
    return {"MPRN": MPRN, "emissions_indicator": emissions_indicator,
            "emissions_indicator_unit": emissions_indicator_unit,
            "BER_score": BER_score, "BER_actual_rating": BER_actual_rating,
            "BER_unit": BER_unit, "address": address}

def submint_to_db(dct):
    with connection.cursor() as cursor:
        print('SUCCESSFUL CONNECTION')
        sql = "INSERT INTO table1 ( %s ) VALUES ( %s )" % (",".join(dct),  ', '.join(['%s'] * len(dct)))
        cursor.execute(sql, dct.values())

payload_1 = {
    'ctl00$DefaultContent$BERSearch$dfSearch$Bottomsearch': 'Search'}
payload_2 = {
    '__EVENTTARGET': 'ctl00$DefaultContent$BERSearch$gridRatings$gridview$ctl02$ViewDetails',
}

with requests.session() as s:
    tokens = renew(BeautifulSoup(requests.get(url).content, "html.parser"))
    for num in hit_list:
        # update the post data with new token values
        payload_1['ctl00$DefaultContent$BERSearch$dfSearch$txtBERNumber'] = num
        payload_1.update(tokens)
        r = s.post(url, data=payload_1)
        tokens2 = renew(BeautifulSoup(r.content, 'html.parser'))
        payload_2.update(tokens2)
        soup = BeautifulSoup(requests.post(url, data=payload_2).content, "html.parser")
        submint_to_db(parse_data(soup))

我没有解析所有数据，但其余数据的逻辑是相同的，打印解析后返回的dict将为您提供：

{'BER_unit': 'kWh/m2/yr', 'emissions_indicator_unit': 'kgCO2/m2/yr', 'emissions_indicator': '57.83', 'address': '24 CLONEE COURTMAIN STREETCLONEECO. MEATH', 'BER_score': 'D1', 'BER_actual_rating': '235.54', 'MPRN': '10003467711'}
{'BER_unit': 'kWh/m2/yr', 'emissions_indicator_unit': 'kgCO2/m2/yr', 'emissions_indicator': '42.4', 'address': '19 GORTANORADINGLECO. KERRY', 'BER_score': 'C1', 'BER_actual_rating': '165.79', 'MPRN': '10301654014'}
{'BER_unit': 'kWh/m2/yr', 'emissions_indicator_unit': 'kgCO2/m2/yr', 'emissions_indicator': '34.03', 'address': '8 CANNON PLACE1 HERBERT ROADDUBLIN 4', 'BER_score': 'C2', 'BER_actual_rating': '175.32', 'MPRN': '10002082335'}
{'BER_unit': 'kWh/m2/yr', 'emissions_indicator_unit': 'kgCO2/m2/yr', 'emissions_indicator': '53.51', 'address': '12 GORTANORADINGLECO. KERRY', 'BER_score': 'C3', 'BER_actual_rating': '208.45', 'MPRN': '10301653940'}
{'BER_unit': 'kWh/m2/yr', 'emissions_indicator_unit': 'kgCO2/m2/yr', 'emissions_indicator': '121.54', 'address': '13 RENMORE ROADGALWAY CITY', 'BER_score': 'G', 'BER_actual_rating': '472.19', 'MPRN': '10010500405'}

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