Scraping Webpage With Tabs That Do Not Change Url

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Scrape webpage that does not change URL

However, the URL does not change when I navigate to different dates or adresses (‘Område’). I have read a couple of similar problems suggesting to inspect the webpage, look under ’Network’ and then ‘XHR’ or ‘JS’ to find the data source of the table and get information from there.

# load libraries
library(RSelenium)

# open browser
selCommand <- wdman::selenium(jvmargs = c("-Dwebdriver.chrome.verboseLogging=true"), retcommand = TRUE)
Sys.sleep(2)
shell(selCommand, wait = FALSE, minimized = TRUE)
Sys.sleep(2)
remdr <- remoteDriver(port = 4567L, browserName = "firefox")
Sys.sleep(10)
remdr$open()
remdr$navigate(url = 'https://matchpadel.halbooking.dk/newlook/proc_baner.asp')

Scrape data from web page source where url doesn't change

Therefore, I'm not able to write the code that will scrape those pages because I don't know how to specify the URL for each hospital. I apologize, this has to be a very basic question but I wasn't able to google anything useful on it for Access VBA buttons and drop-down lists before scraping data on .aspx web pages. Related. 302. Change the

Public Function btnGetWebData_Click() 
    Dim strURL
    Dim HTML_Content As HTMLDocument
    Dim dados As Object

    'Create HTMLFile Object
    Set HTML_Content = New HTMLDocument

    'Get the WebPage Content to HTMLFile Object
    With CreateObject("msxml2.xmlhttp")
        .Open "GET", "http://healthapps.state.nj.us/facilities/acFacilityList.aspx", False
        'http://healthapps.state.nj.us/facilities/acFacilityList.aspx
        .Send
        HTML_Content.Body.innerHTML = .responseText
        Debug.Print .responseText
        Debug.Print HTML_Content.Body.innerHTML
    End With
End Function
Option Explicit
Public Sub VisitPages()
    Dim IE As New InternetExplorer
    With IE
        .Visible = True
        .navigate "http://healthapps.state.nj.us/facilities/acSetSearch.aspx?by=county"

        While .Busy Or .readyState < 4: DoEvents: Wend

        With .document
            .querySelector("#middleContent_cbType_5").Click
            .querySelector("#middleContent_cbType_12").Click
            .querySelector("#middleContent_btnGetList").Click
        End With

        While .Busy Or .readyState < 4: DoEvents: Wend

        Dim list As Object, i  As Long
        Set list = .document.querySelectorAll("#main_table [href*=doPostBack]")
        For i = 0 To list.Length - 1
            list.item(i).Click

            While .Busy Or .readyState < 4: DoEvents: Wend

            Application.Wait Now + TimeSerial(0, 0, 3) '<== Delete me later. This is just to demo page changes
            'do stuff with new page
            .Navigate2 .document.URL             '<== back to homepage
            While .Busy Or .readyState < 4: DoEvents: Wend
            Set list = .document.querySelectorAll("#main_table [href*=doPostBack]") 'reset list (often required in these scenarios)
        Next
        Stop                                     '<== Delete me later
        '.Quit '<== Remember to quit application
    End With
End Sub
Option Explicit
Public Sub VisitPages()
    Dim IE As New InternetExplorer
    With IE
        .Visible = True
        .navigate "http://healthapps.state.nj.us/facilities/acSetSearch.aspx?by=county"

        While .Busy Or .readyState < 4: DoEvents: Wend

        With .document
            .querySelector("#middleContent_cbType_5").Click
            .querySelector("#middleContent_cbType_12").Click
            .querySelector("#middleContent_btnGetList").Click
        End With

        While .Busy Or .readyState < 4: DoEvents: Wend

        Dim list As Object, i  As Long, col As Collection
        Set col = New Collection
        Set list = .document.querySelectorAll("#main_table [href*=doPostBack]")
        For i = 0 To list.Length - 1
           col.Add CStr(list.item(i))
        Next
        For i = 1 To col.Count
            .document.parentWindow.execScript col.item(i)
             While .Busy Or .readyState < 4: DoEvents: Wend
            'Do stuff with page
            .Navigate2 .document.URL
            While .Busy Or .readyState < 4: DoEvents: Wend
        Next
        Stop                                     '<== Delete me later
        '.Quit '<== Remember to quit application
    End With
End Sub
def startWebDriver():
    global driver
    options = Options()
    options.add_argument("--disable-extensions")
    driver = webdriver.Chrome(executable_path = '/home/Downloads/chromedriver_linux64/chromedriver',options=options)

startWebDriver()
count = 0 
s = set()

driver.get('https://www.nytimes.com/search? endDate=20181231&query=trump&sort=best&startDate=20180101')
time.sleep(4)
element = driver.find_element_by_xpath('//*[@id="site-content"]/div/div/div[2]/div[2]/div/button')

while(count < 10):
    element.click()
    time.sleep(4)
    count=count+1

url = driver.current_url
import requests
url = 'https://samizdat-graphql.nytimes.com/graphql/v2'
headers = {
         'nyt-app-type': 'project-vi',
         'nyt-app-version': '0.0.3',
         'nyt-token': 'MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAlYOpRoYg5X01qAqNyBDM32EI/E77nkFzd2rrVjhdi/VAZfBIrPayyYykIIN+d5GMImm3wg6CmTTkBo7ixmwd7Xv24QSDpjuX0gQ1eqxOEWZ0FHWZWkh4jfLcwqkgKmfHJuvOctEiE/Wic5Qrle323SMDKF8sAqClv8VKA8hyrXHbPDAlAaxq3EPOGjJqpHEdWNVg2S0pN62NSmSudT/ap/BqZf7FqsI2cUxv2mUKzmyy+rYwbhd8TRgj1kFprNOaldrluO4dXjubJIY4qEyJY5Dc/F03sGED4AiGBPVYtPh8zscG64yJJ9Njs1ReyUCSX4jYmxoZOnO+6GfXE0s2xQIDAQAB'
}

data = '''
{"operationName":"SearchRootQuery","variables":{"first":10,"sort":"best","beginDate":"20180101","text":"trump","cursor":"YXJyYXljb25uZWN0aW9uOjk="},"extensions":{"persistedQuery":{"version":1,"sha256Hash":"d2895d5a5d686528b9b548f018d7d0c64351ad644fa838384d94c35c585db813"}}}
'''
with requests.Session() as r:
    re = r.post(url, headers = headers, data = data)
    print(re.json())
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException

options = webdriver.ChromeOptions() 
options.add_argument("start-maximized")
options.add_argument('disable-infobars')
driver = webdriver.Chrome(chrome_options=options, executable_path=r'C:\Utility\BrowserDrivers\chromedriver.exe')
driver.get("https://www.nytimes.com/search?%20endDate=20181231&query=trump&sort=best&startDate=20180101")
myLength = len(WebDriverWait(driver, 20).until(EC.visibility_of_all_elements_located((By.XPATH, "//main[@id='site-content']//figure[@class='css-rninck toneNews']//following::a[1]"))))

while True:
    driver.execute_script("window.scrollTo(0, document.body.scrollHeight);")
    try:
        WebDriverWait(driver, 20).until(EC.element_to_be_clickable((By.XPATH, "//button[text()='Show More']"))).click()
        WebDriverWait(driver, 20).until(lambda driver: len(driver.find_elements_by_xpath("//main[@id='site-content']//figure[@class='css-rninck toneNews']//following::a[1]")) > myLength)
        titles = driver.find_elements_by_xpath("//main[@id='site-content']//figure[@class='css-rninck toneNews']//following::a[1]")
        myLength = len(titles)
    except TimeoutException:
        break

for title in titles:
    print(title.get_attribute("href"))
driver.quit()
{
    "operationName":"SearchRootQuery",
    "variables":{
        "first":10,
        "sort":"best",
        "beginDate":"20180101",
        "endDate":"20181231",
        "text":"trump" ...
}}
prefix = 'https://www.timeanddate.com'
weather_request = requests.get(prefix + '/weather/belgium/antwerp/historic?month=4&year=2017', 
                       'html.parser')
weather = BeautifulSoup(weather_request.content)

for option in weather.select('select > option'):
     append_to_mylist(option.get('value'), option.text)
import re
import json
import requests
import pandas as pd
from bs4 import BeautifulSoup


for day in range(1, 31):
    print('Getting info for day {}..'.format(day))
    url = 'https://www.timeanddate.com/scripts/cityajax.php?n=belgium/antwerp&mode=historic&hd=201704{:02d}&month=4&year=2017&json=1'.format(day)

    data = requests.get(url).text
    data = json.loads(re.sub(r'(c|h|s):', r'"\1":', data))

    # uncomment this to print raw data:
    # print(json.dumps(data, indent=4))

    # construct the table from json:
    table = '<table>'
    for row in data:
        table += '<tr>'
        for cell in row['c']:
            table += '<td>' + BeautifulSoup(cell['h'], 'html.parser').get_text(strip=True, separator=' ') + '</td>'
        table += '</tr>'
    table += '</table>'

    # now in `table` is HTML table, you can parse it with BeautifulSoup, or pass it to Pandas:
    df = pd.read_html(table)[0]
    print(df)
    print('-' * 120)
Getting info for day 1..
                      0   1      2                            3      4  5     6          7      8
0   12:20 am Sat, Apr 1 NaN  50 °F                       Clear.  2 mph  ↑   94%  29.92 "Hg   2 mi
1              12:50 am NaN  46 °F                         Fog.  2 mph  ↑  100%  29.92 "Hg   2 mi
2               1:20 am NaN  48 °F                   Light fog.  3 mph  ↑   87%  29.89 "Hg   0 mi
3               1:50 am NaN  48 °F                       Clear.  3 mph  ↑   94%  29.89 "Hg   1 mi
4               2:20 am NaN  46 °F                         Fog.  5 mph  ↑  100%  29.89 "Hg   1 mi
5               3:20 am NaN  46 °F                       Clear.  3 mph  ↑   93%  29.89 "Hg   1 mi
6               3:50 am NaN  46 °F                         Fog.  6 mph  ↑   93%  29.86 "Hg   1 mi
7               4:20 am NaN  46 °F                         Fog.  3 mph  ↑  100%  29.86 "Hg   1 mi
8               4:50 am NaN  46 °F                         Fog.  3 mph  ↑  100%  29.86 "Hg   1 mi
9               5:20 am NaN  46 °F                         Fog.  2 mph  ↑   93%  29.86 "Hg   2 mi
10              5:50 am NaN  48 °F                       Clear.  3 mph  ↑   87%  29.86 "Hg   4 mi
11              6:20 am NaN  48 °F                       Clear.  5 mph  ↑   87%  29.83 "Hg   4 mi
12              6:50 am NaN  48 °F                       Clear.  5 mph  ↑   94%  29.86 "Hg   4 mi
13              7:20 am NaN  50 °F            Sprinkles. Clear.  6 mph  ↑   94%  29.86 "Hg   4 mi
14              7:50 am NaN  52 °F    Sprinkles. Broken clouds.  9 mph  ↑   88%  29.86 "Hg   3 mi
15              8:20 am NaN  52 °F    Light rain. Partly sunny.  8 mph  ↑   88%  29.86 "Hg   5 mi
16              8:50 am NaN  52 °F  Light rain. Passing clouds.  6 mph  ↑   94%  29.86 "Hg   5 mi
17              9:20 am NaN  52 °F       Drizzle. Partly sunny.  5 mph  ↑   94%  29.86 "Hg   5 mi
18              9:50 am NaN  52 °F               Broken clouds.  5 mph  ↑   94%  29.86 "Hg   5 mi
19             10:20 am NaN  52 °F               Broken clouds.  6 mph  ↑   94%  29.89 "Hg    NaN
20             10:50 am NaN  52 °F    Sprinkles. Broken clouds.  8 mph  ↑   94%  29.89 "Hg   5 mi
21             11:20 am NaN  52 °F                Partly sunny.  5 mph  ↑   94%  29.89 "Hg    NaN
22             11:50 am NaN  54 °F            Scattered clouds.  2 mph  ↑   88%  29.89 "Hg    NaN
23             12:20 pm NaN  55 °F            Scattered clouds.  5 mph  ↑   82%  29.89 "Hg    NaN
24             12:50 pm NaN  55 °F            Scattered clouds.  3 mph  ↑   77%  29.89 "Hg    NaN
25              1:20 pm NaN  57 °F              Passing clouds.  5 mph  ↑   72%  29.89 "Hg    NaN
26              1:50 pm NaN  57 °F              Passing clouds.  3 mph  ↑   67%  29.89 "Hg    NaN
27              2:20 pm NaN  57 °F              Passing clouds.  7 mph  ↑   72%  29.89 "Hg    NaN
28              2:50 pm NaN  57 °F            Scattered clouds.  3 mph  ↑   72%  29.89 "Hg    NaN
29              3:20 pm NaN  55 °F    Sprinkles. Broken clouds.  9 mph  ↑   77%  29.89 "Hg   4 mi
30              3:50 pm NaN  55 °F    Sprinkles. Broken clouds.  3 mph  ↑   77%  29.86 "Hg   5 mi
31              4:20 pm NaN  55 °F    Sprinkles. Broken clouds.  2 mph  ↑   82%  29.89 "Hg    NaN
32              4:50 pm NaN  57 °F            Scattered clouds.  2 mph  ↑   77%  29.86 "Hg    NaN
33              5:20 pm NaN  57 °F            Scattered clouds.  7 mph  ↑   72%  29.89 "Hg    NaN
34              5:50 pm NaN  55 °F            Scattered clouds.  6 mph  ↑   88%  29.89 "Hg    NaN
35              6:20 pm NaN  55 °F              Passing clouds.  6 mph  ↑   82%  29.89 "Hg    NaN
36              6:50 pm NaN  55 °F              Passing clouds.  3 mph  ↑   82%  29.89 "Hg    NaN
37              7:20 pm NaN  54 °F              Passing clouds.  5 mph  ↑   94%  29.89 "Hg    NaN
38              7:50 pm NaN  54 °F              Passing clouds.  5 mph  ↑   88%  29.89 "Hg    NaN
39              8:20 pm NaN  54 °F              Passing clouds.  7 mph  ↑   88%  29.92 "Hg    NaN
40              8:50 pm NaN  54 °F                       Clear.  7 mph  ↑   88%  29.92 "Hg  10 mi
41              9:20 pm NaN  54 °F                       Clear.  2 mph  ↑   88%  29.92 "Hg  10 mi
42              9:50 pm NaN  52 °F                       Clear.  5 mph  ↑   94%  29.92 "Hg  10 mi
43             10:20 pm NaN  48 °F                       Clear.  2 mph  ↑  100%  29.95 "Hg  10 mi
44             10:50 pm NaN  52 °F                       Clear.  3 mph  ↑   88%  29.95 "Hg   4 mi
45             11:20 pm NaN  46 °F                         Fog.  2 mph  ↑   93%  29.95 "Hg   1 mi
46             11:50 pm NaN  46 °F                       Clear.  3 mph  ↑   93%  29.95 "Hg   0 mi
------------------------------------------------------------------------------------------------------------------------
Getting info for day 2..
                      0   1      2                  3       4  5     6          7      8
0   12:20 am Sun, Apr 2 NaN  45 °F               Fog.   2 mph  ↑  100%  29.95 "Hg   0 mi
1              12:50 am NaN  45 °F               Fog.   2 mph  ↑   93%  29.98 "Hg   1 mi
2               1:20 am NaN  45 °F               Fog.   2 mph  ↑  100%  29.95 "Hg   0 mi
3               1:50 am NaN  45 °F             Clear.   3 mph  ↑   87%  29.98 "Hg   4 mi
4               2:20 am NaN  48 °F             Clear.   6 mph  ↑   87%  29.98 "Hg  10 mi
5               2:50 am NaN  48 °F             Clear.   2 mph  ↑   87%  29.98 "Hg  10 mi
6               3:20 am NaN  48 °F             Clear.   5 mph  ↑   87%  29.98 "Hg  10 mi
7               3:50 am NaN  48 °F             Clear.   2 mph  ↑   87%  29.98 "Hg   6 mi
8               4:50 am NaN  46 °F             Clear.   2 mph  ↑   87%  30.01 "Hg  10 mi
9               5:20 am NaN  46 °F    Passing clouds.   3 mph  ↑   87%  30.01 "Hg    NaN
10              5:50 am NaN  46 °F             Clear.   2 mph  ↑   87%  30.01 "Hg  10 mi
11              6:20 am NaN  46 °F             Clear.   1 mph  ↑   87%  30.04 "Hg   4 mi
12              6:50 am NaN  45 °F         Light fog.   2 mph  ↑   93%  30.04 "Hg   5 mi


... and so on.

Web Scraping Python Tutorial – How to Scrape Data From A Website

This was also a simple lab where we had to change the URL and print the page title. This code would pass the lab. Part 3: Soup-ed body and head. This is the link to this lab. In the last lab, you saw how you can extract the title from the page. It is equally easy to extract out certain sections too.

import requests

res = requests.get('https://codedamn.com')

print(res.text)
print(res.status_code)
import requests

# Make a request to https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/
# Store the result in 'res' variable
res = requests.get(
    'https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/')
txt = res.text
status = res.status_code

print(txt, status)
# print the result
from bs4 import BeautifulSoup

page = requests.get("https://codedamn.com")
soup = BeautifulSoup(page.content, 'html.parser')
title = soup.title.text # gets you the text of the <title>(...)</title>
import requests
from bs4 import BeautifulSoup

# Make a request to https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Extract title of page
page_title = soup.title.text

# print the result
print(page_title)
import requests
from bs4 import BeautifulSoup

# Make a request
page = requests.get(
    "https://codedamn.com")
soup = BeautifulSoup(page.content, 'html.parser')

# Extract title of page
page_title = soup.title.text

# Extract body of page
page_body = soup.body

# Extract head of page
page_head = soup.head

# print the result
print(page_body, page_head)
import requests
from bs4 import BeautifulSoup

# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Extract title of page
page_title = soup.title

# Extract body of page
page_body = soup.body

# Extract head of page
page_head = soup.head

# print the result
print(page_title, page_head)
import requests
from bs4 import BeautifulSoup

# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Extract first <h1>(...)</h1> text
first_h1 = soup.select('h1')[0].text
import requests
from bs4 import BeautifulSoup
# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Create all_h1_tags as empty list
all_h1_tags = []

# Set all_h1_tags to all h1 tags of the soup
for element in soup.select('h1'):
    all_h1_tags.append(element.text)

# Create seventh_p_text and set it to 7th p element text of the page
seventh_p_text = soup.select('p')[6].text

print(all_h1_tags, seventh_p_text)
info = {
   "title": 'Asus AsusPro Adv...   '.strip(),
   "review": '2 reviews\n\n\n'.strip()
}
import requests
from bs4 import BeautifulSoup
# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Create top_items as empty list
top_items = []

# Extract and store in top_items according to instructions on the left
products = soup.select('div.thumbnail')
for elem in products:
    title = elem.select('h4 > a.title')[0].text
    review_label = elem.select('div.ratings')[0].text
    info = {
        "title": title.strip(),
        "review": review_label.strip()
    }
    top_items.append(info)

print(top_items)
import requests
from bs4 import BeautifulSoup
# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Create top_items as empty list
image_data = []

# Extract and store in top_items according to instructions on the left
images = soup.select('img')
for image in images:
    src = image.get('src')
    alt = image.get('alt')
    image_data.append({"src": src, "alt": alt})

print(image_data)
info = {
   "href": "<link here>",
   "text": "<link text here>"
}
import requests
from bs4 import BeautifulSoup
# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Create top_items as empty list
all_links = []

# Extract and store in top_items according to instructions on the left
links = soup.select('a')
for ahref in links:
    text = ahref.text
    text = text.strip() if text is not None else ''

    href = ahref.get('href')
    href = href.strip() if href is not None else ''
    all_links.append({"href": href, "text": text})

print(all_links)
import requests
from bs4 import BeautifulSoup
import csv
# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

all_products = []

products = soup.select('div.thumbnail')
for product in products:
    # TODO: Work
    print("Work on product here")


keys = all_products[0].keys()

with open('products.csv', 'w', newline='') as output_file:
    dict_writer = csv.DictWriter(output_file, keys)
    dict_writer.writeheader()
    dict_writer.writerows(all_products)
import requests
from bs4 import BeautifulSoup
import csv
# Make a request
page = requests.get(
    "https://codedamn-classrooms.github.io/webscraper-python-codedamn-classroom-website/")
soup = BeautifulSoup(page.content, 'html.parser')

# Create top_items as empty list
all_products = []

# Extract and store in top_items according to instructions on the left
products = soup.select('div.thumbnail')
for product in products:
    name = product.select('h4 > a')[0].text.strip()
    description = product.select('p.description')[0].text.strip()
    price = product.select('h4.price')[0].text.strip()
    reviews = product.select('div.ratings')[0].text.strip()
    image = product.select('img')[0].get('src')

    all_products.append({
        "name": name,
        "description": description,
        "price": price,
        "reviews": reviews,
        "image": image
    })


keys = all_products[0].keys()

with open('products.csv', 'w', newline='') as output_file:
    dict_writer = csv.DictWriter(output_file, keys)
    dict_writer.writeheader()
    dict_writer.writerows(all_products)

Python Tutorial: Web Scraping with Scrapy (8 Code Examples)

price. upc. image_url. url. In code, this is how you create a new Item class in Scrapy: from scrapy import Item, Field class BookItem (Item): title = Field () price = Field () upc = Field () image_url = Field () url = Field () As you can see in the code snippet, you need to import two Scrapy objects: Item and Field.

virtualenv env
source env/bin/activate
pip install scrapy
scrapy startproject bookscraper
📦bookscraper
 ┣ 📂bookscraper
 ┃ ┣ 📂spiders
 ┃ ┃ ┗ 📜bookscraper.py
 ┃ ┣ 📜items.py
 ┃ ┣ 📜middlewares.py
 ┃ ┣ 📜pipelines.py
 ┃ ┗ 📜settings.py
 ┗ 📜scrapy.cfg
from scrapy import Item, Field
class BookItem(Item):
    title = Field()
    price = Field()
    upc = Field()
    image_url = Field()
    url = Field()
touch bookscraper.py
from scrapy.spiders import CrawlSpider, Rule
from scrapy.linkextractors import LinkExtractor
from bookscraper.items import BookItem

class BookScraper(CrawlSpider):
    name = "bookscraper"
    start_urls = ["http://books.toscrape.com/"]

    rules = (
        Rule(LinkExtractor(restrict_css=".nav-list > li > ul > li > a"), follow=True),
        Rule(LinkExtractor(restrict_css=".product_pod > h3 > a"), callback="parse_book")
    )

    def parse_book(self, response):
        book_item = BookItem()

        book_item["image_url"] = response.urljoin(response.css(".item.active > img::attr(src)").get())
        book_item["title"] = response.css(".col-sm-6.product_main > h1::text").get()
        book_item["price"] = response.css(".price_color::text").get()
        book_item["upc"] = response.css(".table.table-striped > tr:nth-child(1) > td::text").get()
        book_item["url"] = response.url
        return book_item
scrapy crawl bookscraper
{'image_url': 'http://books.toscrape.com/media/cache/0f/76/0f76b00ea914ced1822d8ac3480c485f.jpg',
 'price': '£12.61',
 'title': 'The Third Wave: An Entrepreneur’s Vision of the Future',
 'upc': '3bebf34ee9330cbd',
 'url': 'http://books.toscrape.com/catalogue/the-third-wave-an-entrepreneurs-vision-of-the-future_862/index.html'}
2022-05-01 18:46:18 [scrapy.core.scraper] DEBUG: Scraped from <200 http://books.toscrape.com/catalogue/shoe-dog-a-memoir-by-the-creator-of-nike_831/index.html>
{'image_url': 'http://books.toscrape.com/media/cache/fc/21/fc21d144c7289e5b1cb133e01a925126.jpg',
 'price': '£23.99',
 'title': 'Shoe Dog: A Memoir by the Creator of NIKE',
 'upc': '0e0dcc3339602b28',
 'url': 'http://books.toscrape.com/catalogue/shoe-dog-a-memoir-by-the-creator-of-nike_831/index.html'}
2022-05-01 18:46:18 [scrapy.core.scraper] DEBUG: Scraped from <200 http://books.toscrape.com/catalogue/the-10-entrepreneur-live-your-startup-dream-without-quitting-your-day-job_836/index.html>
{'image_url': 'http://books.toscrape.com/media/cache/50/4b/504b1891508614ff9393563f69d66c95.jpg',
 'price': '£27.55',
 'title': 'The 10% Entrepreneur: Live Your Startup Dream Without Quitting Your '
          'Day Job',
 'upc': '56e4f9eab2e8e674',
 'url': 'http://books.toscrape.com/catalogue/the-10-entrepreneur-live-your-startup-dream-without-quitting-your-day-job_836/index.html'}
2022-05-01 18:46:18 [scrapy.core.scraper] DEBUG: Scraped from <200 http://books.toscrape.com/catalogue/far-from-true-promise-falls-trilogy-2_320/index.html>
{'image_url': 'http://books.toscrape.com/media/cache/9c/aa/9caacda3ff43984447ee22712e7e9ca9.jpg',
 'price': '£34.93',
 'title': 'Far From True (Promise Falls Trilogy #2)',
 'upc': 'ad15a9a139919918',
 'url': 'http://books.toscrape.com/catalogue/far-from-true-promise-falls-trilogy-2_320/index.html'}
2022-05-01 18:46:18 [scrapy.core.scraper] DEBUG: Scraped from <200 http://books.toscrape.com/catalogue/the-travelers_285/index.html>
{'image_url': 'http://books.toscrape.com/media/cache/42/a3/42a345bdcb3e13d5922ff79cd1c07d0e.jpg',
 'price': '£15.77',
 'title': 'The Travelers',
 'upc': '2b685187f55c5d31',
 'url': 'http://books.toscrape.com/catalogue/the-travelers_285/index.html'}
2022-05-01 18:46:18 [scrapy.core.scraper] DEBUG: Scraped from <200 http://books.toscrape.com/catalogue/the-bone-hunters-lexy-vaughan-steven-macaulay-2_343/index.html>
{'image_url': 'http://books.toscrape.com/media/cache/8d/1f/8d1f11673fbe46f47f27b9a4c8efbf8a.jpg',
 'price': '£59.71',
 'title': 'The Bone Hunters (Lexy Vaughan & Steven Macaulay #2)',
 'upc': '9c4d061c1e2fe6bf',
 'url': 'http://books.toscrape.com/catalogue/the-bone-hunters-lexy-vaughan-steven-macaulay-2_343/index.html'}

Python web scraping tutorial (with examples)

URL change using. EC.url_changes() New opened window using. EC.new_window_is_opened() Changes in title using: EC.title_is() If you have any page redirections, you can see if there is a change in title or URL to check for it. There are many conditions to check for; we just take an example to show you how much power you have. …

$ pip install beautifulsoup4
from bs4 import BeautifulSoup
$ python myfile.py
from urllib.request import urlopen

from bs4 import BeautifulSoup

html = urlopen("https://www.python.org/")

res = BeautifulSoup(html.read(),"html5lib");

print(res.title)
from urllib.request import urlopen

from urllib.error import HTTPError

from bs4 import BeautifulSoup

try:

    html = urlopen("https://www.python.org/")

except HTTPError as e:

    print(e)

else:

    res = BeautifulSoup(html.read(),"html5lib")

    print(res.title)
from urllib.request import urlopen

from urllib.error import HTTPError

from urllib.error import URLError

from bs4 import BeautifulSoup

try:

    html = urlopen("https://www.python.org/")

except HTTPError as e:

    print(e)

except URLError:

    print("Server down or incorrect domain")

else:

    res = BeautifulSoup(html.read(),"html5lib")

    print(res.titles)
from urllib.request import urlopen

from urllib.error import HTTPError

from urllib.error import URLError

from bs4 import BeautifulSoup

try:

    html = urlopen("https://www.python.org/")

except HTTPError as e:

    print(e)

except URLError:

    print("Server down or incorrect domain")

else:

    res = BeautifulSoup(html.read(),"html5lib")

    if res.title is None:

        print("Tag not found")

    else:

        print(res.title)
tags = res.findAll("h2", {"class": "widget-title"})
from urllib.request import urlopen

from urllib.error import HTTPError

from urllib.error import URLError

from bs4 import BeautifulSoup

try:

    html = urlopen("https://www.python.org/")

except HTTPError as e:

    print(e)

except URLError:

    print("Server down or incorrect domain")

else:

    res = BeautifulSoup(html.read(),"html5lib")

    tags = res.findAll("h2", {"class": "widget-title"})

    for tag in tags:

        print(tag.getText())
tags = res.findAll("span", "a" "img")
tags = res.findAll("a", {"class": ["url", "readmorebtn"]})
tags = res.findAll(text="Python Programming Basics with Examples")
tags = res.span.findAll("a")
tag = res.find("nav", {"id": "site-navigation"}).select("a")[3]
import re

tags = res.findAll("img", {"src": re.compile("\.\./uploads/photo_.*\.png")})
$ pip install selenium
from selenium import webdriver

browser = webdriver.Chrome()

browser.get("https://www.python.org/")

nav = browser.find_element_by_id("mainnav")

print(nav.text)
from selenium import webdriver

browser = webdriver.PhantomJS()

browser.get("https://www.python.org/")

print(browser.find_element_by_class_name("introduction").text)

browser.close()
browser.find_element_by_id("id")

browser.find_element_by_css_selector("#id")

browser.find_element_by_link_text("Click Here")

browser.find_element_by_name("Home")
browser.find_elements_by_id("id")

browser.find_elements_by_css_selector("#id")

browser.find_elements_by_link_text("Click Here")

browser.find_elements_by_name("Home")
from selenium import webdriver

from bs4 import BeautifulSoup

browser = webdriver.PhantomJS()

browser.get("https://www.python.org/")

page = BeautifulSoup(browser.page_source,"html5lib")

links = page.findAll("a")

for link in links:

    print(link)

browser.close()
from selenium import webdriver

browser = webdriver.PhantomJS()

browser.get("https://developer.mozilla.org/en-US/docs/Web/HTML/Element/iframe")

iframe = browser.find_element_by_tag_name("iframe")

browser.switch_to.default_content()

browser.switch_to.frame(iframe)

iframe_source = browser.page_source

print(iframe_source) #returns iframe source

print(browser.current_url) #returns iframe URL
from urllib.request import urlopen

from urllib.error import HTTPError

from urllib.error import URLError

from bs4 import BeautifulSoup

try:

html = urlopen("https://developer.mozilla.org/en-US/docs/Web/HTML/Element/iframe")

except HTTPError as e:

print(e)

except URLError:

print("Server down or incorrect domain")

else:

res = BeautifulSoup(html.read(), "html5lib")

tag = res.find("iframe")

print(tag['src']) #URl of iframe ready for scraping
from selenium import webdriver

import time

browser = webdriver.PhantomJS()

browser.get("https://www.w3schools.com/xml/ajax_intro.asp")

browser.find_element_by_tag_name("button").click()

time.sleep(2)     #Explicit wait

browser.get_screenshot_as_file("image.png")

browser.close()
from selenium import webdriver

from selenium.webdriver.common.by import By

from selenium.webdriver.support.ui import WebDriverWait

from selenium.webdriver.support import expected_conditions as EC

browser = webdriver.PhantomJS()

browser.get("https://resttesttest.com/")

browser.find_element_by_id("submitajax").click()

try:

    element = WebDriverWait(browser, 10).until(EC.text_to_be_present_in_element((By.ID, "statuspre"),"HTTP 200 OK"))

finally:

    browser.get_screenshot_as_file("image.png")

browser.close()
EC.url_changes()
EC.new_window_is_opened()
EC.title_is()
from selenium import webdriver

browser = webdriver.PhantomJS()

browser.get("https://likegeeks.com/")

print(browser.get_cookies())
from selenium import webdriver

browser = webdriver.PhantomJS()

browser.get("https://likegeeks.com/")

browser.delete_all_cookies()
Host https://www.google.com/
Connection keep-alive
Accept text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8
User-Agent Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/
39.0.2171.95 Safari/537.36
Referrer https://www.google.com/
Accept-Encoding gzip, deflate, sdch
Accept-Language en-US,en;q=0.8
Accept-Encoding identity
User-Agent Python-urllib/3.4
import time

time.sleep(3)
from urllib2 import Request

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