Develop Reference

Python web scraping script does not find element by css selector

I'm trying to get this web scraper to get current electricity price from this website, it's in finnish but it's right under "Hinta nyt". https://sahko.tk/
Here's my code:
import requests
from bs4 import BeautifulSoup
url = "https://sahko.tk/"
element_selector = ""
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
elements = soup.find_all(element_selector)
if len(elements) == 0:
print("No element found with selector '%s'" % element_selector)
else:
element_text = elements[0].text
print(element_text)
I left the element_selector to empty because what ever I tried it just did not work. I'm not even sure if I'm on the right tracks.

The data you see is embedded inside <script> in that page. To parse the current price you can use next example:
import re
import json
import requests
url = "https://sahko.tk/"
data = requests.get(url).text
data = re.search(r"function prices_today\(\)\{var t= (.*?});", data).group(1)
data = json.loads(data)
print("Hinta nyt", data["now"], "snt/kWh")
Prints:
Hinta nyt 33.27 snt/kWh

Python Web Scraping - How to scrape this type of site?

Okay, so I need to scrape the following webpage: https://www.programmableweb.com/category/all/apis?deadpool=1
It's a list of APIs. There are approx 22,000 APIs to scrape.
I need to:
1) Get the URL of each API in the table (pages 1-889), and also to scrape the following info:
API name
Description
Category
Submitted
2) I then need to scrape a bunch of information from each URL.
3) Export the data to a CSV
The thing is, I’m a bit lost of how to think about this project. From what I can see, there are no AJAX calls been made to populate the table, which means I’m going to have to parse the HTML directly (right?)
In my head, the logic would be something like this:
Use the requests & BS4 libraries to scrape the table
Then, somehow grab the HREF from every row
Access that HREF, scrape the data, move onto the next one
Rinse and repeat for all table rows.
Am I on the right track, is this possible with requests & BS4?
Here's are some screenshots of what I've been trying to explain.
Thank you SOO much for any help. This is hurting my head haha

Here we go using requests, BeautifulSoup and pandas:
import requests
from bs4 import BeautifulSoup
import pandas as pd
url = 'https://www.programmableweb.com/category/all/apis?deadpool=1&page='
num = int(input('How Many Page to Parse?> '))
print('please wait....')
name = []
desc = []
cat = []
sub = []
for i in range(0, num):
r = requests.get(f"{url}{i}")
soup = BeautifulSoup(r.text, 'html.parser')
for item1 in soup.findAll('td', attrs={'class': 'views-field views-field-title col-md-3'}):
name.append(item1.text)
for item2 in soup.findAll('td', attrs={'class': 'views-field views-field-search-api-excerpt views-field-field-api-description hidden-xs visible-md visible-sm col-md-8'}):
desc.append(item2.text)
for item3 in soup.findAll('td', attrs={'class': 'views-field views-field-field-article-primary-category'}):
cat.append(item3.text)
for item4 in soup.findAll('td', attrs={'class': 'views-field views-field-created'}):
sub.append(item4.text)
result = []
for item in zip(name, desc, cat, sub):
result.append(item)
df = pd.DataFrame(
result, columns=['API Name', 'Description', 'Category', 'Submitted'])
df.to_csv('output.csv')
print('Task Completed, Result saved to output.csv file.')
Result can be viewed online: Check Here
Output Simple:
Now For href parsing:
import requests
from bs4 import BeautifulSoup
import pandas as pd
url = 'https://www.programmableweb.com/category/all/apis?deadpool=0&page='
num = int(input('How Many Page to Parse?> '))
print('please wait....')
links = []
for i in range(0, num):
r = requests.get(f"{url}{i}")
soup = BeautifulSoup(r.text, 'html.parser')
for link in soup.findAll('td', attrs={'class': 'views-field views-field-title col-md-3'}):
for href in link.findAll('a'):
result = 'https://www.programmableweb.com'+href.get('href')
links.append(result)
spans = []
for link in links:
r = requests.get(link)
soup = soup = BeautifulSoup(r.text, 'html.parser')
span = [span.text for span in soup.select('div.field span')]
spans.append(span)
data = []
for item in spans:
data.append(item)
df = pd.DataFrame(data)
df.to_csv('data.csv')
print('Task Completed, Result saved to data.csv file.')
Check Result Online: Here
Sample View is Below:
In Case if you want those 2 csv files together so here's the code:
import pandas as pd
a = pd.read_csv("output.csv")
b = pd.read_csv("data.csv")
merged = a.merge(b)
merged.to_csv("final.csv", index=False)
Online Result: Here

You should read more about scraping if you are going to pursue it .
from bs4 import BeautifulSoup
import csv , os , requests
from urllib import parse
def SaveAsCsv(list_of_rows):
try:
with open('data.csv', mode='a', newline='', encoding='utf-8') as outfile:
csv.writer(outfile).writerow(list_of_rows)
except PermissionError:
print("Please make sure data.csv is closed\n")
if os.path.isfile('data.csv') and os.access('data.csv', os.R_OK):
print("File data.csv Already exists \n")
else:
SaveAsCsv([ 'api_name','api_link','api_desc','api_cat'])
BaseUrl = 'https://www.programmableweb.com/category/all/apis?deadpool=1&page={}'
for i in range(1, 890):
print('## Getting Page {} out of 889'.format(i))
url = BaseUrl.format(i)
res = requests.get(url)
soup = BeautifulSoup(res.text,'html.parser')
table_rows = soup.select('div.view-content > table[class="views-table cols-4 table"] > tbody tr')
for row in table_rows:
tds = row.select('td')
api_name = tds[0].text.strip()
api_link = parse.urljoin(url, tds[0].find('a').get('href'))
api_desc = tds[1].text.strip()
api_cat = tds[2].text.strip() if len(tds) >= 3 else ''
SaveAsCsv([api_name,api_link,api_desc,api_cat])

How to scrape embedded integers on a website

I'm trying to scrape the number of likes for the datasets available on this website.
I've been unable to workout a way of reliably identifying and scraping the relationship between the dataset title and the like integer:
as it is embedded in the HTML as below:
I have used a scraper previously to get information about the resource urls. In that case I was able to capture the last child a of parent h3 with a parent having class .dataset-item.
I would like to adapt my existing code to scrape the number of likes for each resource in the catalogue, rather than the URLs. Below is the code for the url scraper I used:
from bs4 import BeautifulSoup as bs
import requests
import csv
from urllib.parse import urlparse
json_api_links = []
data_sets = []
def get_links(s, url, css_selector):
r = s.get(url)
soup = bs(r.content, 'lxml')
base = '{uri.scheme}://{uri.netloc}'.format(uri=urlparse(url))
links = [base + item['href'] if item['href'][0] == '/' else item['href'] for item in soup.select(css_selector)]
return links
results = []
#debug = []
with requests.Session() as s:
for page in range(1,2): #set number of pages
links = get_links(s, 'https://data.nsw.gov.au/data/dataset?page={}'.format(page), '.dataset-item h3 a:last-child')
for link in links:
data = get_links(s, link, '[href*="/api/3/action/package_show?id="]')
json_api_links.append(data)
#debug.append((link, data))
resources = list(set([item.replace('opendata','') for sublist in json_api_links for item in sublist])) #can just leave as set
for link in resources:
try:
r = s.get(link).json() #entire package info
data_sets.append(r)
title = r['result']['title'] #certain items
if 'resources' in r['result']:
urls = ' , '.join([item['url'] for item in r['result']['resources']])
else:
urls = 'N/A'
except:
title = 'N/A'
urls = 'N/A'
results.append((title, urls))
with open('data.csv','w', newline='') as f:
w = csv.writer(f)
w.writerow(['Title','Resource Url'])
for row in results:
w.writerow(row)
My desired output would appear like this:

The approach is pretty straight forward. Your given website contains required elements in a list Tag. And what you need to do, is to get source code of that <li> tag, and just fetch Heading, which has a certain class and Same goes for like count.
The catch in like count is, the text comprises of some noise. To fix that, you can use regular expression to extract digits ('\d+') from given input of likes count. Following code gives desired result:
from bs4 import BeautifulSoup as soup
import requests
import re
import pandas as pd
source = requests.get('https://data.nsw.gov.au/data/dataset')
sp = soup(source.text,'lxml')
element = sp.find_all('li',{'class':"dataset-item"})
heading = []
likeList = []
for i in element:
try:
header = i.find('a',{'class':"searchpartnership-url-analytics"})
heading.append(header.text)
except:
header = i.find('a')
heading.append(header.text)
like = i.find('span',{'id':'likes-count'})
likeList.append(re.findall('\d+',like.text)[0])
dict = {'Title': heading, 'Likes': likeList}
df = pd.DataFrame(dict,index=False)
print(df)
Hope it helped!

You could use the following.
I am using a css selector with Or syntax to retrieve title and likes as one list (as every publication has both). I then use slicing to separate titles from likes.
from bs4 import BeautifulSoup as bs
import requests
import csv
def get_titles_and_likes(s, url, css_selector):
r = s.get(url)
soup = bs(r.content, 'lxml')
info = [item.text.strip() for item in soup.select(css_selector)]
titles = info[::2]
likes = info[1::2]
return list(zip(titles,likes))
results = []
with requests.Session() as s:
for page in range(1,10): #set number of pages
data = get_titles_and_likes(s, 'https://data.nsw.gov.au/data/dataset?page={}'.format(page), '.dataset-heading .searchpartnership-url-analytics, .dataset-heading [href*="/data/dataset"], .dataset-item #likes-count')
results.append(data)
results = [i for item in results for i in item]
with open(r'data.csv','w', newline='') as f:
w = csv.writer(f)
w.writerow(['Title','Likes'])
for row in results:
w.writerow(row)

BeautifulSoup loop fails to capture content

My BeautifulSoup scraper loops through a list of URLs and captures one of my criteria ('month_year') as desired. But each 'li' tag in the second loop merely extracts details for the first instance on the page.
The 'month_year' doesn't change for a given URL, and that's fine. But 'broadcast' should return different details for each 'li' tag.
Any advice for a novice?
import csv
from bs4 import BeautifulSoup
from urllib.request import urlopen
contents = []
with open('monthly_list.csv','r') as csvf:
urls = csv.reader(csvf)
for url in urls:
page = urlopen(url[0]).read()
tunes = BeautifulSoup(page, 'html.parser')
playlist = tunes.find('ul', class_='content-container row')
daily_URLs_data = open('daily_URLs_2007-2018.csv', 'a')
for li in playlist.find_all('div', class_='description'):
month_year = tunes.find('div', class_='resultsHeader').text
broadcast = playlist.h3.a
print (month_year)
print (broadcast)
csv_writer.writerow([month_year, broadcast])

How do I simultaneously scrape two pages and produce two distinct lists within one nested 'for-loop'?

I'm scraping from two URLs that have the same DOM structure, and so I'm trying to find a way to scrape both of them at the same time.
The only caveat is that the data scraped from both these pages need to end up on distinctly named lists.
To explain with example, here is what I've tried:
import os
import requests
from bs4 import BeautifulSoup as bs
urls = ['https://www.basketball-reference.com/leaders/ws_career.html',
'https://www.basketball-reference.com/leaders/ws_per_48_career.html',]
ws_list = []
ws48_list = []
categories = [ws_list, ws48_list]
for url in urls:
response = requests.get(url, headers=headers)
soup = bs(response.content, 'html.parser')
section = soup.find('table', class_='stats_table')
for a in section.find_all('a'):
player_name = a.text
for cat_list in categories:
cat_list.append(player_name)
print(ws48_list)
print(ws_list)
This ends up printing two identical lists when I was shooting for 2 lists unique to its page.
How do I accomplish this? Would it be better practice to code it another way?

Instead of trying to append to already existing lists. Just create new ones. Make a function to do the scrape and pass each url in turn to it.
import os
import requests
from bs4 import BeautifulSoup as bs
urls = ['https://www.basketball-reference.com/leaders/ws_career.html',
'https://www.basketball-reference.com/leaders/ws_per_48_career.html',]
def parse_page(url, headers={}):
response = requests.get(url, headers=headers)
soup = bs(response.content, 'html.parser')
section = soup.find('table', class_='stats_table')
return [a.text for a in section.find_all('a')]
ws_list, ws48_list = [parse_page(url) for url in urls]
print('ws_list = %r' % ws_list)
print('ws8_list = %r' % ws48_list)

Just add them to the appropriate list and the problem is solved?
for i, url in enumerate(urls):
response = requests.get(url)
soup = bs(response.content, 'html.parser')
section = soup.find('table', class_='stats_table')
for a in section.find_all('a'):
player_name = a.text
categories[i].append(player_name)
print(ws48_list)
print(ws_list)

You can use a function to define your scraping logic, then just call it for your urls.
import os
import requests
from bs4 import BeautifulSoup as bs
def scrape(url):
response = requests.get(url)
soup = bs(response.content, 'html.parser')
section = soup.find('table', class_='stats_table')
names = []
for a in section.find_all('a'):
player_name = a.text
names.append(player_name)
return names
ws_list = scrape('https://www.basketball-reference.com/leaders/ws_career.html')
ws48_list = scrape('https://www.basketball-reference.com/leaders/ws_per_48_career.html')
print(ws_list)
print(ws48_list)