I tried to scrapeimagesthey will give me 23 imagesbut I don't want to apply limitthey will only give me 10 pictures can you help me with these?

 import requests
    from bs4 import BeautifulSoup
    import pandas as pd
    baseurl='https://twillmkt.com'
    headers={
        'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.114 Safari/537.36'
    }
    r=requests.get('https://twillmkt.com/collections/denim')
    soup=BeautifulSoup(r.content, 'html.parser')
    tra=soup.find_all('div',class_='ProductItem__Wrapper')
    productlinks=[]
    for links in tra:
        for link in links.find_all('a',href=True):
            comp=baseurl link['href']
            productlinks.append(comp)
    
    data=[]
    
    for link in set(productlinks):
        r=requests.get(link,headers=headers)
        soup=BeautifulSoup(r.content, 'html.parser')
        up=soup.find('div',class_='Product__SlideshowNavScroller')
        for e,pro in enumerate(up):
            t=pro.find('img').get('src')
            data.append({'id':t.split('=')[-1], 'image':'Image ' str(e) ' UI','link':t}) 
            
    df=pd.DataFrame(data)
    df.image=pd.Categorical(df.image,categories=df.image.unique(),ordered=True)
    df=df.pivot(index='id', columns='image', values='link').reset_index().fillna('')
    df.to_csv('kj.csv')

uj5u.com enthusiastic netizens replied:

Slice the resulting set of images[:10]

...
up=soup.select('div.Product__SlideshowNavScroller img')[:10]
for e,pro in enumerate(up):
    t=pro.get('src')
    data.append({'id':t.split('=')[-1], 'image':'Image ' str(e) ' UI','link':t}) 
...

If you want to name images starting with 1 instead of 0:

...
up=soup.select('div.Product__SlideshowNavScroller img')[:10]
for e,pro in enumerate(up, start=1):
    t=pro.get('src')
    data.append({'id':t.split('=')[-1], 'image':'Image ' str(e) ' UI','link':t}) 
...

Edit

Ok got it-the behavior is not based on the number of images, the problem here is that the id is not unique, it Not the id/sku of the product.

How to fix it?

Let's select the sku from the product and use it as the id in the data frame:

sku=soup.select_one('.oos_sku').text.strip().split(' ')[-1]
for e,pro in enumerate(up, start=1):
    t=pro.get('src')
    data.append({'id':sku, 'image':'Image ' str(e) ' UI','link':t})

Example

import requests
from bs4 import BeautifulSoup
import pandas as pd
baseurl='https://twillmkt.com'
headers={
    'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.114 Safari/537.36'
}
r=requests.get('https://twillmkt.com/collections/denim')
soup=BeautifulSoup(r.content, 'html.parser')
tra=soup.find_all('div',class_='ProductItem__Wrapper')
productlinks=[]
for links in tra:
    for link in links.find_all('a',href=True):
        comp=baseurl link['href']
        productlinks.append(comp)

data=[]

for link in set(productlinks):
    r=requests.get(link,headers=headers)
    soup=BeautifulSoup(r.content, 'html.parser')
    up=soup.select('div.Product__SlideshowNavScroller img')
    sku=soup.select_one('.oos_sku').text.strip().split(' ')[-1]
    for e,pro in enumerate(up, start=1):
        t=pro.get('src')
        data.append({'id':sku, 'image':'Image ' str(e) ' UI','link':t})

df=pd.DataFrame(data)
df.image=pd.Categorical(df.image,categories=df.image.unique(),ordered=True)
df=df.pivot(index='id', columns='image', values='link').reset_index().fillna('')
df#.to_excel('test.xlsx')

output

	ID th>	Figure 1 User Interface	Figure 2 User Interface	Figure 3 User Interface	Figure 4 User Interface	Figure 5 User Interface	Figure 6 User Interface	Figure 7 User Interface	Figure 8 User Interface	Figure 9 User Interface	Figure 10 User Interface	Figure 11 User Interface	Figure 12 User Interface	Figure 13 User Interface	Figure 14 User Interface	Figure 15 User Interface	Figure 16 User Interface	Figure 17 User Interface	Figure 18 User Interface	Figure 19 User Interface	Figure 20 User Interface	Figure 21 User Interface	Figure 22 User Interface	Figure 23 User Interface	Figure 24 User Interface
0 td>	LOTFEELPJ023-30	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim_160x.jpg?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-2_160x.jpg?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-3_160x.jpg?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-4_160x.jpg ?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-5_160x.jpg ?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-6_160x.jpg ?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-7_160x.jpg ?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-8_160x.jpg ?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-9_160x.jpg ?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-10_160x.jpg ?v=1631812617	//cdn.shopify.com/s/files/1/0089/7912/0206/products/Blue-Ripped-Knee-Distressed-Skinny-Denim-11_160x.jpg?v=1631812617
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47 td>	LOTFEELPJ564-S-BRN font>	//cdn.shopify.com/s/files/1/0089/7912/0206/products/LOTFEELPJ564_16_160x.jpg?v=1639467815	//cdn.shopify.com/s/files/1/0089/7912/0206/products/LOTFEELPJ564_17_160x.jpg?v=1639467815	//cdn.shopify.com/s/files/1/0089/7912/0206/products/LOTFEELPJ564_22_160x.jpg?v=1639467815	//cdn.shopify.com/s/files/1/0089/7912/0206/products/LOTFEELPJ564_15_160x.jpg?v=1639467815	//cdn.shopify.com/s/files/1/0089/7912/0206/products/LOTFEELPJ564_6_160x.jpg?v=1639467815	//cdn.shopify.com/s/files/1/0089/7912/0206/products/LOTFEELPJ564_9_160x.jpg?v=1639467815	//cdn.shopify.com/s/files/1/0089/7912/0206/products/sizechart-stretch-pants_3_ec7e0b0c-1043-4306-a766-33f7e0b3edc8_160x.png?v=166994677