Dog Web Scraper V2

import requests
from requests import get
from bs4 import BeautifulSoup
import pandas as pd
import numpy as np
import datetime

url = "https://fetchwi.org/adopt"
results = requests.get(url)
soup = BeautifulSoup(results.text, "html.parser")

names = []
tags = []
pagelinks = []

name_div = soup.find_all('div', class_="summary-content sqs-gallery-meta-container")

for container in name_div:
    name = container.find('a', class_="summary-title-link").text
    names.append(name)
    
    href = container.find('a', class_="summary-title-link")['href']
    pagelinks.append(href)
    
    div1 = container('div', class_="summary-metadata-container summary-metadata-container--below-content")
    
    for span in div1:
        tag = span('div', class_="summary-metadata summary-metadata--primary")
        
        for tag1 in tag:
            tag2 = tag1.text
            tags.append(tag2)

## Additional date column to potentially track over-time changes
date = datetime.datetime.now()

dates = [date] * len(tags)

doggos = pd.DataFrame({
    'name': names,
    'tags':tags,
    'link':pagelinks,
    'date': dates
    
})

doggos = doggos.replace(to_replace=r"\n", value="", regex=True)
doggos["link"] = doggos["link"].replace(to_replace="/doggos/", value="", regex=True)
doggos = doggos.astype({
    'name': "string",
    'tags': "string",
    'link': "string",
    'date': "object"
})

potential_doggos = doggos.loc[doggos["tags"].str.contains("Could live in an apartment")]

potential_doggos

dog_url = []
dog_url = potential_doggos['link'].tolist()

names2 = []
dog_infos = []
tags2 = []
description = []

url = "http://fetchwi.org/doggos/"

for dogs in dog_url: 
    results = requests.get(url + dogs)
    soup = BeautifulSoup(results.text, "html.parser")

    name = soup.find('h1', class_="entry-title entry-title--large p-name").text
    names2.append(name)

    dog_info = soup.find('div', class_="blog-item-content e-content").h4.text
    dog_infos.append(dog_info)

    tag = soup.find_all('p', class_="")[0].text
    tags2.append(tag)

    desc = soup.find_all('p', class_="")[1].text
    description.append(desc)

print("names:",len(names2))
print("dog_info:",len(dog_infos))
print("tags:",len(tags2))
print("descrpt:",len(description))

    names: 3
    dog_info: 3
    tags: 3
    descrpt: 3

potential_doggos_ext = pd.DataFrame({
    'name': names2,
    'dog_info': dog_infos,
    'tags': tags2,
    'description': description
})

new = potential_doggos_ext["dog_info"].str.split("|", n=3, expand=True)

potential_doggos_ext["Breed"] = new[0]
potential_doggos_ext["Sex"] = new[1]
potential_doggos_ext["Age"] = new[2]
potential_doggos_ext["Weight"] = new[3]

potential_doggos_ext = potential_doggos_ext.astype("string", errors="ignore")

potential_doggos_ext