This is my case study about web scraping. I got a problem in the final code 'NoneType' object has no attribute 'text' so I tried to fix it with 'getattr' function but it didn't work.
'''
import requests
from bs4 import BeautifulSoup
url = 'https://www.birdsnest.com.au/womens/dresses'
source = requests.get(url)
soup = BeautifulSoup(source.content, 'lxml')
'''
productlist= soup.find_all('div', id='items')
'''
productlinks = []
for item in productlist:
for link in item.find_all('a',href=True):
productlinks.append(url + link['href'])
print(len(productlinks))
'''
productlinks = []
for x in range(1,28):
source = requests.get(f'https://www.birdsnest.com.au/womens/dresses?_lh=1&page={x}')
soup = BeautifulSoup(source.content, 'lxml')
for item in productlist:
for link in item.find_all('a',href=True):
productlinks.append(url + link['href'])
print(productlinks)
'''
for link in productlinks:
source = requests.get(link)
soup = BeautifulSoup(source.content, 'lxml')
name = soup.find('h1',class_='item-heading__name').text.strip()
price = soup.find('p',class_='item-heading__price').text.strip()
feature = soup.find('div',class_='tab-accordion__content active').text.strip()
sum = {
'name':name,
'price':price,
'feature':feature
}
print(sum)
'''
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-7-d4d46558690d> in <module>()
3 soup = BeautifulSoup(source.content, 'lxml')
4
----> 5 name = soup.find('h1',class_='item-heading__name').text.strip()
6 price = soup.find('p',class_='item-heading__price').text.strip()
7 feature = soup.find('div',class_='tab-accordion__content active').text.strip()
AttributeError: 'NoneType' object has no attribute 'text'
---------------------------------------------------------------------------
So I tried to fix with this method, but it didn't work.
for link in productlinks:
source = requests.get(link)
soup = BeautifulSoup(source.content, 'lxml')
name = getattr(soup.find('h1',class_='item-heading__name'),'text',None)
price = getattr(soup.find('p',class_='item-heading__price'),'text',None)
feature = getattr(soup.find('div',class_='tab-accordion__content active'),'text',None)
sum = {
'name':name,
'price':price,
'feature':feature
}
print(sum)
This is the output. It show only 'Nonetype'
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
{'name': None, 'price': None, 'feature': None}
First of all, always turn JS
off for the page you're scraping. Then you'll realize that tag classes change and these are the ones you want to target.
Also, when looping through the pages, don't forget that Python's range()
stop value is not inclusive. Meaning, this range(1, 28)
will stop on page 27
.
Here's how I would go about it:
import json
import requests
from bs4 import BeautifulSoup
cookies = {
"ServerID": "1033",
"__zlcmid": "10tjXhWpDJVkUQL",
}
headers = {
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36"
}
def extract_info(bs: BeautifulSoup, tag: str, attr_value: str) -> list:
return [i.text.strip() for i in bs.find_all(tag, {"itemprop": attr_value})]
all_pages = []
for page in range(1, 29):
print(f"Scraping data from page {page}...")
current_page = f"https://www.birdsnest.com.au/womens/dresses?page={page}"
source = requests.get(current_page, headers=headers, cookies=cookies)
soup = BeautifulSoup(source.content, 'html.parser')
brand = extract_info(soup, tag="strong", attr_value="brand")
name = extract_info(soup, tag="h2", attr_value="name")
price = extract_info(soup, tag="span", attr_value="price")
all_pages.extend(
[
{
"brand": b,
"name": n,
"price": p,
} for b, n, p in zip(brand, name, price)
]
)
print(f"{all_pages}\nFound: {len(all_pages)} dresses.")
with open("all_the_dresses2.json", "w") as jf:
json.dump(all_pages, jf, indent=4)
This gets you a JSON
with all the dresses.
{
"brand": "boho bird",
"name": "Prissy Dress",
"price": "$189.95"
},
{
"brand": "boho bird",
"name": "Dandelion Dress",
"price": "$139.95"
},
{
"brand": "Lula Soul",
"name": "Dandelion Dress",
"price": "$179.95"
},
{
"brand": "Honeysuckle Beach",
"name": "Cotton V-Neck A-Line Splice Dress",
"price": "$149.95"
},
{
"brand": "Honeysuckle Beach",
"name": "Lenny Pinafore",
"price": "$139.95"
},
and so on for the next 28 pages ...