We Keep Coding

How can I plug this section of code into my BeautifulSoup script?

I am new to Python and Beautiful Soup. My project I am working on is a script which scrapes the pages inside of the hyperlinks on this page:
https://bitinfocharts.com/top-100-richest-dogecoin-addresses-2.html
Currently, the script has a filter which will only scrape the pages which have a "Last Out" date which is past a certain date.
I am trying to add an additional filter to the script, which does the following:
Scrape the "Profit from price change:" section on the page inside hyperlink (Example page: https://bitinfocharts.com/dogecoin/address/D8WhgsmFUkf4imvsrwYjdhXL45LPz3bS1S
Convert the profit into a float
Compare the profit to a variable called "goal" which has a float assigned to it.
If the profit is greater or equal to goal, then scrape the contents of the page. If the profit is NOT greater or equal to the goal, do not scrape the webpage, and continue the script.
Here is the snippet of code I am using to try and do this:
#Get the profit
sections = soup.find_all(class_='table-striped')
for section in sections:
oldprofit = section.find_all('td')[11].text
removetext = oldprofit.replace('USD', '')
removetext = removetext.replace(' ', '')
removetext = removetext.replace(',', '')
profit = float(removetext)
# Compare profit to goal
goal = float(50000)
if profit >= goal
Basically, what I am trying to do is run an if statement on a value on the webpage, and if the statement is true, then scrape the webpage. If the if statement is false, then do not scrape the page and continue the code.
Here is the entire script that I am trying to plug this into:
import csv
import requests
from bs4 import BeautifulSoup as bs
from datetime import datetime
headers = []
datarows = []
# define 1-1-2020 as a datetime object
after_date = datetime(2020, 1, 1)
with requests.Session() as s:
s.headers = {"User-Agent": "Safari/537.36"}
r = s.get('https://bitinfocharts.com/top-100-richest-dogecoin-addresses-2.html')
soup = bs(r.content, 'lxml')
# select all tr elements (minus the first one, which is the header)
table_elements = soup.select('tr')[1:]
address_links = []
for element in table_elements:
children = element.contents # get children of table element
url = children[1].a['href']
last_out_str = children[8].text
# check to make sure the date field isn't empty
if last_out_str != "":
# load date into datetime object for comparison (second part is defining the layout of the date as years-months-days hour:minute:second timezone)
last_out = datetime.strptime(last_out_str, "%Y-%m-%d %H:%M:%S %Z")
# if check to see if the date is after 2020/1/1
if last_out > after_date:
address_links.append(url)
for url in address_links:
r = s.get(url)
soup = bs(r.content, 'lxml')
table = soup.find(id="table_maina")
#Get the Doge Address for the filename
item = soup.find('h1').text
newitem = item.replace('Dogecoin', '')
finalitem = newitem.replace('Address', '')
#Get the profit
sections = soup.find_all(class_='table-striped')
for section in sections:
oldprofit = section.find_all('td')[11].text
removetext = oldprofit.replace('USD', '')
removetext = removetext.replace(' ', '')
removetext = removetext.replace(',', '')
profit = float(removetext)
# Compare profit to goal
goal = float(50000)
if profit >= goal
if table:
for row in table.find_all('tr'):
heads = row.find_all('th')
if heads:
headers = [th.text for th in heads]
else:
datarows.append([td.text for td in row.find_all('td')])
fcsv = csv.writer(open(f'{finalitem}.csv', 'w', newline=''))
fcsv.writerow(headers)
fcsv.writerows(datarows)
I am familiar with if statements however I this unsure how to plug this into the existing code and have it accomplish what I am trying to do. If anyone has any advice I would greatly appreciate it. Thank you.

From my understanding, it seems like all that you are asking is how to have the script continue if it fails that criteria in which case you need to just do
if profit < goal:
continue
Though the for loop in your snippet is only using the final value of profit, if there are other profit values that you need to look at those values are not being evaluated.

web-scrape: get H4 attributes & href

I am trying to web-scrape a website. But I can get access to the attributes of some fields.
here is the code i used:
import urllib3
from bs4 import BeautifulSoup
import pandas as pd
scrap_list = pd.DataFrame()
for path in range(10): # scroll over the categories
for path in range(10): # scroll over the pages
url = 'https://www.samehgroup.com/index.php?route=product/category'+str(page)+'&'+'path='+ str(path)
req = urllib3.PoolManager()
res = req.request('GET', URL)
soup = BeautifulSoup(res.data, 'html.parser')
soup.findAll('h4', {'class': 'caption'})
# extract names
scrap_name = [i.text.strip() for i in soup.findAll('h2', {'class': 'caption'})]
scrap_list['product_name']=pd.DataFrame(scrap_name,columns =['Item_name'])
# extract prices
scrap_list['product_price'] = [i.text.strip() for i in soup.findAll('div', {'class': 'price'})]
product_price=pd.DataFrame(scrap_price,columns =['Item_price'])
I want an output that provides me with each product and its price. I still can't get that right.
Any help would be very much appreciated.

I think the problem here was looping through the website pages. I got the code below working by first making a list of urls containing numbered 'paths' corresponding to pages on the website. Then looping through this list and applying a page number to the url.
If you wanted to only get all the products from a certain page, this page can be selected from the urlist and by index.
from bs4 import BeautifulSoup
import requests
import pandas as pd
import time
urlist = [] #create list of usable url's to iterate through,
for i in range(1,10): # 9 pages equal to pages on website
urlist.append('https://www.samehgroup.com/index.php?route=product/category&path=' + str(i))
namelist = []
newprice = []
for urlunf in urlist: #first loop to get 'path'
for n in range(100): #second loop to get 'pages'. set at 100 to cover website max page at 93
try: #try catches when pages containing products run out.
url = urlunf + '&page=' + str(n)
page = requests.get(url).text
soup = BeautifulSoup(page, 'html')
products = soup.find_all('div', class_='caption')
for prod in products: #loops over returned list of products for names and prices
name = prod.find('h4').text
newp = prod.find('p', class_='price').find('span', class_='price-new').text
namelist.append(name) #append data to list outside of loop
newprice.append(newp)
time.sleep(2)
except AttributeError: #if there are no more products it will move to next page
pass
df = pd.DataFrame() #create df and add scraped data
df['name'] = namelist
df['price'] = newprice

How do I filter a list through a formatted web scraping for loop

I have a list of basketball players that I want to pass through a web scraping for loop I've already set up. The list of players is a list of the 2011 NBA Draft picks. I want to loop through each player and get their college stats from their final year in college. The problem is some drafted players did not go to college and therefore do not have a url formatted in their name so every time I pass in even one player that did not play in college the whole code gets an error. I have tried including "pass" and "continue" but nothing seems to work. This is the closest I gotten so far:
from bs4 import BeautifulSoup
import requests
import pandas as pd
headers = {'User Agent':'Mozilla/5.0'}
players = [
'kyrie-irving','derrick-williams','enes-kanter',
'tristan-thompson','jonas-valanciunas','jan-vesely',
'bismack-biyombo','brandon-knight','kemba-walker,
'jimmer-fredette','klay-thompson'
]
#the full list of players goes on for a total of 60 players, this is just the first handful
player_stats = []
for player in players:
url = (f'https://www.sports-reference.com/cbb/players/{player}-1.html')
res = requests.get(url)
#if player in url:
#continue
#else:
#print("This player has no college stats")
#Including this if else statement makes the error say header is not defined. When not included, the error says NoneType object is not iterable
soup = BeautifulSoup(res.content, 'lxml')
header = [th.getText() for th in soup.findAll('tr', limit = 2)[0].findAll('th')]
rows = soup.findAll('tr')
player_stats.append([td.getText() for td in soup.find('tr', id ='players_per_game.2011')])
player_stats
graph = pd.DataFrame(player_stats, columns = header)

You can do 1 of 2 things:
check the response status code. 200 is successful response, anything else is an error. Problem with that is some site will have a valid html page to say "invalid page", so you could still get a successful 200 response.
Just use try/except. If it fails, continue to the next item in the list
Because of that issue with option 1, go with option 2 here. Also, have you considered using pandas to parse the table? It's a little easier to do (and uses BeautifulSoup under the hood)?
Lastly, you're going to need to do a little more logic with this. There are multiple college players "Derrick William". I suspect you're not meaning https://www.sports-reference.com/cbb/players/derrick-williams-1.html. So you need to figure out how to work that out.
from bs4 import BeautifulSoup
import requests
import pandas as pd
headers = {'User Agent':'Mozilla/5.0'}
players = [
'kyrie-irving','derrick-williams','enes-kanter',
'tristan-thompson','jonas-valanciunas','jan-vesely',
'bismack-biyombo','brandon-knight','kemba-walker',
'jimmer-fredette','klay-thompson'
]
#the full list of players goes on for a total of 60 players, this is just the first handful
player_stats = []
for player in players:
url = (f'https://www.sports-reference.com/cbb/players/{player}-1.html')
res = requests.get(url)
try:
soup = BeautifulSoup(res.content, 'lxml')
header = [th.getText() for th in soup.findAll('tr', limit = 2)[0].findAll('th')]
rows = soup.findAll('tr')
player_stats.append([td.getText() for td in soup.find('tr', id ='players_per_game.2011')])
player_stats
except:
print("%s has no college stats" %player)
graph = pd.DataFrame(player_stats, columns = header)
With Pandas:
graph = pd.DataFrame()
for player in players:
try:
url = (f'https://www.sports-reference.com/cbb/players/{player}-1.html')
df = pd.read_html(url)[0]
cols = list(df.columns)
df = df.iloc[-2][cols]
df['Player'] = player
graph = graph.append(df).reset_index(drop=True)
graph = graph[['Player'] + cols]
except:
print("%s has no college stats" %player)

BeautifulSoup use select multiple times

My problem is related to this answer.
I have following code:
import urllib.request
from bs4 import BeautifulSoup
time = 0
html = urllib.request.urlopen("https://www.kramerav.com/de/Product/VM-2N").read()
html2 = urllib.request.urlopen("https://www.kramerav.com/de/Product/SDIA-IN2-F16").read()
try:
div = str(BeautifulSoup(html).select("div.large-image")[0])
if(str(BeautifulSoup(html).select("div.large-image")[1]) != ""):
div += str(BeautifulSoup(html).select("div.large-image")[1])
time = time + 1
except IndexError:
div = ""
time = time + 1
finally:
print(str(time) + div)
The site of the variable html has 2 div-classes named "large-image". The site of the variable html2 only has 1.
With html the program works as intended. But if I switch to html2 the variable div is going to be completely empty.
I would like to save the 1 div-class rather than saving nothing. How could I archieve this?

the variable div is going to be completely empty.
That's because your error handler assigned it the empty string.
Please don't use subscripts, conditionals, and handlers in that way. It would be more natural to iterate over the results of select() with for, building up a result list (or string).
Also, you should create soup = BeautifulSoup(html) just once, as that can be a fairly expensive operation, since it carefully parses a potentially long web page. With that, you could build up a list of HTML fragments with:
images = [image
for image in soup.select('div.large-image')]
Or if for some reason you're not fond list comprehensions, you could equivalently write:
images = []
for image in soup.select('div.large-image'):
images.append(image)
and then get the required html with div = '\n'.join(images).

You can concatenate all items inside for loop
all_divs = soup.select("div.large-image")
for item in all_divs:
div += str(item)
time += 1
or using join()
time = len(all_divs)
div = ''.join(str(item) for item in all_divs)
You can also write in file directly inside for loop and you get to row
for item in all_divs:
csv_writer.writerow( [str(item).strip()] )
time += 1
Working example
import urllib.request
from bs4 import BeautifulSoup
import csv
div = ""
time = 0
f = open('output.csv', 'w')
csv_writer = csv.writer(f)
all_urls = [
"https://www.kramerav.com/de/Product/VM-2N",
"https://www.kramerav.com/de/Product/SDIA-IN2-F16",
]
for url in all_urls:
print('url:', url)
html = urllib.request.urlopen(url).read()
try:
soup = BeautifulSoup(html)
all_divs = soup.select("div.large-image")
for item in all_divs:
div += str(item)
time += 1
# or
time = len(all_divs)
div = ''.join(str(item) for item in all_divs)
# or
for item in all_divs:
#div += str(item)
#time += 1
csv_writer.writerow( [time, str(item).strip()] )
except IndexError as ex:
print('Error:', ex)
time += 1
finally:
print(time, div)
f.close()

How can I loop scraping data for multiple pages in a website using python and beautifulsoup4

I am trying to scrape data from the PGA.com website to get a table of all of the golf courses in the United States. In my CSV table I want to include the Name of the golf course ,Address ,Ownership ,Website , Phone number. With this data I would like to geocode it and place into a map and have a local copy on my computer
I utilized Python and Beautiful Soup4 to extract my data. I have reached as far to extract the data and import it into a CSV but I am now having a problem of scraping data from multiple pages on the PGA website. I want to extract ALL THE GOLF COURSES but my script is limited only to one page I want to loop it in away that it will capture all data for golf courses from all pages found in the PGA site. There are about 18000 gold courses and 900 pages to capture data
Attached below is my script. I need help on creating code that will capture ALL data from the PGA website and not just one site but multiple. In this manner it will provide me with all the data of gold courses in the United States.
Here is my script below:
import csv
import requests
from bs4 import BeautifulSoup
url = "http://www.pga.com/golf-courses/search?searchbox=Course+Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0"
r = requests.get(url)
soup = BeautifulSoup(r.content)
g_data1=soup.find_all("div",{"class":"views-field-nothing-1"})
g_data2=soup.find_all("div",{"class":"views-field-nothing"})
courses_list=[]
for item in g_data2:
try:
name=item.contents[1].find_all("div",{"class":"views-field-title"})[0].text
except:
name=''
try:
address1=item.contents[1].find_all("div",{"class":"views-field-address"})[0].text
except:
address1=''
try:
address2=item.contents[1].find_all("div",{"class":"views-field-city-state-zip"})[0].text
except:
address2=''
try:
website=item.contents[1].find_all("div",{"class":"views-field-website"})[0].text
except:
website=''
try:
Phonenumber=item.contents[1].find_all("div",{"class":"views-field-work-phone"})[0].text
except:
Phonenumber=''
course=[name,address1,address2,website,Phonenumber]
courses_list.append(course)
with open ('filename5.csv','wb') as file:
writer=csv.writer(file)
for row in courses_list:
writer.writerow(row)
#for item in g_data1:
#try:
#print item.contents[1].find_all("div",{"class":"views-field-counter"})[0].text
#except:
#pass
#try:
#print item.contents[1].find_all("div",{"class":"views-field-course-type"})[0].text
#except:
#pass
#for item in g_data2:
#try:
#print item.contents[1].find_all("div",{"class":"views-field-title"})[0].text
#except:
#pass
#try:
#print item.contents[1].find_all("div",{"class":"views-field-address"})[0].text
#except:
#pass
#try:
#print item.contents[1].find_all("div",{"class":"views-field-city-state-zip"})[0].text
#except:
#pass
This script only captures 20 at a time and I want to capture all in one script which account for 18000 golf courses and 900 pages to scrape form.

The PGA website's search have multiple pages, the url follows the pattern:
http://www.pga.com/golf-courses/search?page=1 # Additional info after page parameter here
this means you can read the content of the page, then change the value of page by 1, and read the the next page.... and so on.
import csv
import requests
from bs4 import BeautifulSoup
for i in range(907): # Number of pages plus one
url = "http://www.pga.com/golf-courses/search?page={}&searchbox=Course+Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0".format(i)
r = requests.get(url)
soup = BeautifulSoup(r.content)
# Your code for each individual page here

if you still read this post , you can try this code too....
from urllib.request import urlopen
from bs4 import BeautifulSoup
file = "Details.csv"
f = open(file, "w")
Headers = "Name,Address,City,Phone,Website\n"
f.write(Headers)
for page in range(1,5):
url = "http://www.pga.com/golf-courses/search?page={}&searchbox=Course%20Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0".format(page)
html = urlopen(url)
soup = BeautifulSoup(html,"html.parser")
Title = soup.find_all("div", {"class":"views-field-nothing"})
for i in Title:
try:
name = i.find("div", {"class":"views-field-title"}).get_text()
address = i.find("div", {"class":"views-field-address"}).get_text()
city = i.find("div", {"class":"views-field-city-state-zip"}).get_text()
phone = i.find("div", {"class":"views-field-work-phone"}).get_text()
website = i.find("div", {"class":"views-field-website"}).get_text()
print(name, address, city, phone, website)
f.write("{}".format(name).replace(",","|")+ ",{}".format(address)+ ",{}".format(city).replace(",", " ")+ ",{}".format(phone) + ",{}".format(website) + "\n")
except: AttributeError
f.close()
where it is written range(1,5) just change that with 0,to the last page , and you will get all details in CSV, i tried very hard to get your data in proper format but it's hard:).

You're putting a link to a single page, it's not going to iterate through each one on its own.
Page 1:
url = "http://www.pga.com/golf-courses/search?searchbox=Course+Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0"
Page 2:
http://www.pga.com/golf-courses/search?page=1&searchbox=Course%20Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0
Page 907:
http://www.pga.com/golf-courses/search?page=906&searchbox=Course%20Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0
Since you're running for page 1 you'll only get 20. You'll need to create a loop that'll run through each page.
You can start off by creating a function that does one page then iterate that function.
Right after the search? in the url, starting at page 2, page=1 begins increasing until page 907 where it's page=906.

I noticed that the first solution had a repetition of the first instance, that is because the 0 page and 1 page is the same page. This is resolved by specifying the start page in the range function. Example below...
for i in range(1, 907): #Number of pages plus one
url = "http://www.pga.com/golf-courses/search?page={}&searchbox=Course+Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0".format(i)
r = requests.get(url)
soup = BeautifulSoup(r.content, "html5lib") #Can use whichever parser you prefer
# Your code for each individual page here

Had this same exact problem and the solutions above did not work. I solved mine by accounting for cookies. A requests session helps. Create a session and it'll pull all the pages you need by inserting a cookie to all the numbered pages.
import csv
import requests
from bs4 import BeautifulSoup
url = "http://www.pga.com/golf-courses/search?searchbox=Course+Name&searchbox_zip=ZIP&distance=50&price_range=0&course_type=both&has_events=0"
s = requests.Session()
r = s.get(url)

The PGA website has changed this question has been asked.
It seems they organize all courses by: State > City > Course
In light of this change and the popularity of this question, here's how I'd solve this problem today.
Step 1 - Import everything we'll need:
import time
import random
from gazpacho import Soup # https://github.com/maxhumber/gazpacho
from tqdm import tqdm # to keep track of progress
Step 2 - Scrape all the state URL endpoints:
URL = "https://www.pga.com"
def get_state_urls():
soup = Soup.get(URL + "/play")
a_tags = soup.find("ul", {"data-cy": "states"}, mode="first").find("a")
state_urls = [URL + a.attrs['href'] for a in a_tags]
return state_urls
state_urls = get_state_urls()
Step 3 - Write a function to scrape all the city links:
def get_state_cities(state_url):
soup = Soup.get(state_url)
a_tags = soup.find("ul", {"data-cy": "city-list"}).find("a")
state_cities = [URL + a.attrs['href'] for a in a_tags]
return state_cities
state_url = state_urls[0]
city_links = get_state_cities(state_url)
Step 4 - Write a function to scrape all of the courses:
def get_courses(city_link):
soup = Soup.get(city_link)
courses = soup.find("div", {"class": "MuiGrid-root MuiGrid-item MuiGrid-grid-xs-12 MuiGrid-grid-md-6"}, mode="all")
return courses
city_link = city_links[0]
courses = get_courses(city_link)
Step 5 - Write a function to parse all the useful info about a course:
def parse_course(course):
return {
"name": course.find("h5", mode="first").text,
"address": course.find("div", {'class': "jss332"}, mode="first").strip(),
"url": course.find("a", mode="first").attrs["href"]
}
course = courses[0]
parse_course(course)
Step 6 - Loop through everything and save:
all_courses = []
for state_url in tqdm(state_urls):
city_links = get_state_cities(state_url)
time.sleep(random.uniform(1, 10) / 10)
for city_link in city_links:
courses = get_courses(city_link)
time.sleep(random.uniform(1, 10) / 10)
for course in courses:
info = parse_course(course)
all_courses.append(info)