Hello I am currently using Python 3, BeautifulSoup 4 and, requests to scrape some information from supremenewyork.com UK. I have implemented a proxy script (that I know works) into the script. The only problem is that this website does not like programs to scrape this information automatically and so they have decided to scramble this script which I think makes it unusable as text.
My question: is there a way to get the text without using the .text thing and/or is there a way to get the script to read the text? and when it sees a special character like # to skip over it or to read the text when it sees & skip until it sees ;?
because basically how this website scrambles the text is by doing this. Here is an example, the text shown when you inspect element is:
supremetshirt
Which is supposed to say "supreme t-shirt" and so on (you get the idea, they don't use letters to scramble only numbers and special keys)
this is kind of highlighted in a box automatically when you inspect the element using a VPN on the UK supreme website, and is different than the text (which isn't highlighted at all). And whenever I run my script without the proxy code onto my local supremenewyork.com, It works fine (but only because of the code, not being scrambled on my local website and I want to pull this info from the UK website) any ideas? here is my code:
import requests
from bs4 import BeautifulSoup
categorys = ['jackets', 'shirts', 'tops_sweaters', 'sweatshirts', 'pants', 'shorts', 't-shirts', 'hats', 'bags', 'accessories', 'shoes', 'skate']
catNumb = 0
#use new proxy every so often for testing (will add something that pulls proxys and usses them for you.
UK_Proxy1 = '51.143.153.167:80'
proxies = {
'http': 'http://' + UK_Proxy1 + '',
'https': 'https://' + UK_Proxy1 + '',
}
for cat in categorys:
catStr = str(categorys[catNumb])
cUrl = 'http://www.supremenewyork.com/shop/all/' + catStr
proxy_script = requests.get(cUrl, proxies=proxies).text
bSoup = BeautifulSoup(proxy_script, 'lxml')
print('\n*******************"'+ catStr.upper() + '"*******************\n')
catNumb += 1
for item in bSoup.find_all('div', class_='inner-article'):
url = item.a['href']
alt = item.find('img')['alt']
req = requests.get('http://www.supremenewyork.com' + url)
item_soup = BeautifulSoup(req.text, 'lxml')
name = item_soup.find('h1', itemprop='name').text
#name = item_soup.find('h1', itemprop='name')
style = item_soup.find('p', itemprop='model').text
#style = item_soup.find('p', itemprop='model')
print (alt +(' --- ')+ name +(' --- ')+ style)
#print(alt)
#print(str(name))
#print (str(style))
When I run this script I get this error:
name = item_soup.find('h1', itemprop='name').text
AttributeError: 'NoneType' object has no attribute 'text'
And so what I did was I un-hash-tagged the stuff that is hash-tagged above, and hash-tagged the other stuff that is similar but different, and I get some kind of str error and so I tried the print(str(name)). I am able to print the alt fine (with every script, the alt is not scrambled), but when it comes to printing the name and style all it prints is a None under every alt code is printed.
I have been working on fixing this for days and have come up with no solutions. can anyone help me solve this?
I have solved my own answer using this solution:
thetable = soup5.find('div', class_='turbolink_scroller')
items = thetable.find_all('div', class_='inner-article')
for item in items:
alt = item.find('img')['alt']
name = item.h1.a.text
color = item.p.a.text
print(alt,' --- ', name, ' --- ',color)
Related
I'm trying to display the contents of the pdf by converting PDF into HTML using Adobe Acrobat 2021, extracting the paragraph structure, and post-processing. I saw a website whose only source is judgments as PDFs from the Supreme Court Website and displays them flawlessly. Does anybody have any idea how it's done?
My current flow is to convert the PDF into HTML to preserve the page layout and extract the text using Beautifulsoup.
Issues I'm currently facing:
Bulletin numbers are somehow dynamically calculated in the PDF and are tagged as
::before
on the browser. bs4 won't recognize it
Miss some paragraphs in between as some paragraphs are detected incorrectly
Table is detected as a table but some imperfections
PDF example : drive link
HTML from Adobe Acrobat : HTML file of the above PDF
This is my goal : Advocatekhoj
This is how accurate I'm expecting it to be.
Could someone please shed light on this? how-to(s) or any suggestions.
Note: I tried various PDF to HTML tools and the Adobe Acrobat was the best in detecting paragraph layout and preserving structure.
from bs4 import BeautifulSoup
from pprint import pprint
from os import listdir
from os.path import isfile, join
mypath = "sup_del_htmls/"
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
counter = 0
for f in onlyfiles:
print(counter)
with open("output_txt/"+f+".txt", 'w',encoding='utf-8') as txtfile:
with open(mypath+f, encoding='utf-8') as fp:
soup = BeautifulSoup(fp, "html.parser")
para_counter = 1
for li in soup.select("li"):
if li.find_parent("li"):
continue
full_para = ""
for para in li.select("p"):
for match in para.findAll('span'):
match.unwrap()
para_txt = para.get_text().replace("¶", "")
para_txt = para_txt.strip()
if para_txt.endswith(".") or para_txt.endswith(":") or para_txt.endswith(";") or para_txt.endswith(",") or para_txt.endswith('"') or para_txt.endswith("'"):
full_para += para_txt + "\n"
else:
full_para += para_txt + " "
txtfile.write(full_para)
txtfile.write("\n" + "--sep--" + "\n")
if li.find("table"):
tables = li.find_all("table")
for table in tables:
txtfile.write("--table--"+ "\n")
txtfile.write(str(table) + "\n")
txtfile.write("--sep--" + "\n")
reversed_end = []
for p in reversed(soup.select("p")):
if p.find_parent('li') or p.find_parent('ol'):
break
reversed_end.append(" ".join(p.text.split()))
if reversed_end!=[]:
for final_end in reversed(reversed_end):
txtfile.write(final_end + "\n")
txtfile.write("--sep--" + "\n")
The Result : output.txt
For the numbering with :before in css, you can try to extract the selector/s for the numbered items with a function like this
def getLctrSelectors(stsh):
stsh = stsh.get_text() if stsh else ''
ll_ids = list(set([
l.replace('>li', '> li').split('> li')[0].strip()
for l in stsh.splitlines() if l.strip()[:1] == '#'
and '> li' in l.replace('>li', '> li') and
'counter-increment' in l.split('{')[-1].split(':')[0]
]))
for i, l in enumerate(ll_ids):
sel = f'{l} > li > *:first-child'
ll_ids[i] = (sel, 1)
crl = [
ll for ll in stsh.splitlines() if ll.strip().startswith(l)
and 'counter-reset' in ll.split('{')[-1].split(':')[-2:][0]
][:1]
if not crl: continue
crl = crl[0].split('{')[-1].split('counter-reset')[-1].split(':')[-1]
crl = [w for w in crl.split(';')[0].split() if w.isdigit()]
ll_ids[i] = (sel, int(crl[-1]) if crl else 1)
return ll_ids
(It should take a style tag as input and return a list of selectors and starting counts - like [('#l1 > li > *:first-child', 3)] for your sample html.)
You can use it in your code to insert the numbers into the text in the bs4 tree:
soup = BeautifulSoup(fp, "html.parser")
for sel, ctStart in getLctrSelectors(soup.select_one('style')):
for i, lif in enumerate(soup.select(sel)):
lif.insert(0, f'{i + ctStart}. ')
para_counter = 1
### REST OF CODE ###
I'm not sure I can help you with paragraphs and tables issues... Are you sure the site uses the same pdfs as you have? (Or that they use pdfs at all rather than something closer to the original/raw data?) Your pdf itself looked rather different from its corresponding page on the site.
I have just came to an article called The 500 Greatest Songs of All Time and thought "oh that's cool I bet they also made a Spotify/Apple music list that I can follow". Well...they don't.
So in a nutshell, I wonder if it's possible to 1) scrap the website to extract the songs and 2) then do some kind of bulk upload to Spotify to create the list.
Songs' titles and authors are structured like this in the website:
Website screenshot. I have already tried to scrap the web with the importxml() formula in google sheets but with no success.
I understand the scrapping part is easier than the other and, as I am new to programming, I would be happy to manage to partially achieve this goal. I am sure this task can be achieved easily on python.
I feel like explaining everything would go beyond the scope here, so I tried to comment the code well enough.
1. Scrape the songs
I used python3 and selenium, their website doesn't block that.
Be sure to adjust your chromedriver path, and the output path of the .txt file at the bottom if necessary. Once it's done and you have your .txt file you can close it.
import time
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
s = Service(r'/Users/main/Desktop/chromedriver')
driver = webdriver.Chrome(service=s)
# just setting some vars, I used Xpath because I know that
top_500 = 'https://www.rollingstone.com/music/music-lists/best-songs-of-all-time-1224767/'
cookie_button_xpath = "// button [#id = 'onetrust-accept-btn-handler']"
div_containing_links_xpath = "// div [#id = 'pmc-gallery-list-nav-bar-render'] // child :: a"
song_names_xpath = "// article [#class = 'c-gallery-vertical-album'] / child :: h2"
links = []
songs = []
driver.get(top_500)
# accept cookies, give time to load
time.sleep(3)
cookie_btn = driver.find_element(By.XPATH, cookie_button_xpath)
cookie_btn.click()
time.sleep(1)
# extracting all the links since there are only 50 songs per page
links_to_next_pages = driver.find_elements(By.XPATH, div_containing_links_xpath)
for element in links_to_next_pages:
l = element.get_attribute('href')
links.append(l)
# extracting the songs, then going to next page and so on until we hit 500
counter = 1 # were starting with 1 here since links[0] is the current page we are already on
while True:
list = driver.find_elements(By.XPATH, song_names_xpath)
for element in list:
s = element.text
songs.append(s)
if len(songs) == 500:
break
driver.get(links[counter])
counter += 1
time.sleep(2)
# verify that there are no duplicates, if there were, something would be off
if len(songs) != len( set(songs) ):
print('you f***** up')
else:
print('seems fine')
with open('/Users/main/Desktop/output_songs.txt', 'w') as file:
file.writelines(line + '\n' for line in songs)
2. Prepare Spotify
Go to the Spotify Developer Dashboard and create an
account (use your Spotify acc).
Then create an app, call it whatever you want.
On your app click settings and whitelist http://localhost:8888/callback
On your app click "users and access" and add your Spotify account
Leave the tab open, we'll come back to it
3. Prepare Your Environment
You need Node.js so make sure that is installed on your machine
Download this from Spotifys GitHub
Unzip it, cd into the folder and run npm install
Go into the authorization_code folder and open app.js in a editor
Find var scope and append ' playlist-modify-public' to the string, this is so that your app can access you Spotify playlists, see here
Now go back to the app in your Spotify Developer Dashboard we'll need to copy the Client ID and the Client Secret into the var client_id and var client_secret respectively (in the app.js file). var redirect_uri will be
http://localhost:8888/callback - don't forget to save your changes.
4. Run the Spotify side of things
cd into the authorization_code folder and run app.js with node app.js (this is basically a server running on your PC)
Now if that works leave it running and go to http://localhost:8888, authorise your Spotify account there
There copy the full token, including the overflow, use inspect element to get it
Adjust the user_id and auth variables as well as the path to the output_songs.txt (at with open) in the following python script and run that, songs which are not found will be printed out at the end, give it a search with Google. They are usually on Spotify as well but Google seem to have the better search algorithm (surprised Pikachu face).
import requests
import re
import json
# this is NOT you display name, it's your user name!!
user_id = 'YOUR_USERNAME'
# paste your auth token from spotify; it can time out then you have to get a new one, so dont panic if you get a bunch of responses in the 400s after some time
auth = {"Authorization": "Bearer YOUR_AUTH_KEY_FROM_LOCALHOST"}
playlist = []
err_log = []
base_url = 'https://api.spotify.com/v1'
search_method = '/search'
with open('/Users/main/Desktop/output_songs.txt', 'r') as file:
songs = file.readlines()
# this querys spotify does some magic and then appends the tracks spotify uri to an array
def query_song_uris():
for n, entry in enumerate(songs):
x = re.findall(r"'([^']*)'", entry)
title_len = len(entry) - len(x[0]) - 4
title = x[0]
artist = entry[:title_len]
payload = {
'q': (entry),
'track:': (title),
'artist:': (artist),
'type': 'track',
'limit': 1
}
url = base_url + search_method
try:
r = requests.get(url, params=payload, headers=auth)
print('\nquerying spotify; ', r)
c = r.content.decode('UTF-8')
dic = json.loads(c)
track_uri = dic["tracks"]["items"][0]["uri"]
playlist.append(track_uri)
print(track_uri)
except:
err = f'\nNr. {(len(songs)-n)}: ' + f'{entry}'
err_log.append(err)
playlist.reverse()
query_song_uris()
# creates a playlist and returns playlist id
def create_playlist():
payload = {
"name": "Rolling Stone: Top 500 (All Time)",
"description": "music for old men xD with occasional hip hop appearences. just kidding"
}
url = base_url + f'/users/{user_id}/playlists'
r = requests.post(url, headers=auth, json=payload)
c = r.content.decode('UTF-8')
dic = json.loads(c)
print(f'\n\ncreating playlist #{dic["id"]}; ', r)
return dic["id"]
def add_to_playlist():
playlist_id = create_playlist()
while True:
if len(playlist) > 100:
p = playlist[:100]
else:
p = playlist
payload = {"uris": (p)}
url = base_url + f'/playlists/{playlist_id}/tracks'
r = requests.post(url, headers=auth, json=payload)
print(f'\nadding {len(p)} songs to playlist; ', r)
del playlist[ : len(p) ]
if len(playlist) == 0:
break
add_to_playlist()
print('\n\ncheck your spotify :)')
print("\n\n\nthese tracks didn't make it, check manually:\n")
for line in err_log:
print(line)
print('\n\n')
Done
If you don't want to run the code yourself, heres the playlist:
https://open.spotify.com/playlist/5fdLKYNFlA4XSvhEl36KXS
If you have trouble, everything from step 2 on is also described here in the Web API quick start or in general in the web API docs.
Regarding Apple Music
So Apple seems very closed up (surprise haha). What I found though is that you can query the i-Tunes store. Given response also contains a direct link to the song(s) on Apple music.
You might be able to go from there.
Get ISRC code from iTunes Search API (Apple music)
PS: undeniably regex is witchcraft, but y'all here got my back
I am working on my second Python scraper and keep running into the same problem. I would like to scrape the website shown in the code below. I would like to be ability to input parcel numbers and see if their Property Use Code matches. However, I am not sure if my scraper if finding the correct row in the table. Also, not sure how to use the if statement if the use code is not the 3730.
Any help would be appreciated.
from bs4 import BeautifulSoup
import requests
parcel = input("Parcel Number: ")
web = "https://mcassessor.maricopa.gov/mcs.php?q="
web_page = web+parcel
web_header={'User-Agent':'Mozilla/5.0(Macintosh;IntelMacOSX10_13_2)AppleWebKit/537.36(KHTML,likeGecko)Chrome/63.0.3239.132Safari/537.36'}
response=requests.get(web_page,headers=web_header,timeout=100)
soup=BeautifulSoup(response.content,'html.parser')
table=soup.find("td", class_="Property Use Code" )
first_row=table.find_all("td")[1]
if first_row is '3730':
print (parcel)
else:
print ('N/A')
There's no td with class "Property Use Code" in the html you're looking at - that is the text of a td. If you want to find that row, you can use
td = soup.find('td', text="Property Use Code")
and then, to get the next td in that row, you can use:
otherTd = td.find_next_sibling()
or, of you want them all:
otherTds = td.find_next_siblings()
It's not clear to me what you want to do with the values of these tds, but you'll want to use the text attribute to access them: your first_row is '3730' will always be False, because first_row is a bs4.element.Tag object here and '3730' is a str. You can, however, get useful information from otherTd.text == '3730'.
I'd like to obtain a list of all the titles of all Wikipedia articles. I know there are two possible ways to get content from a Wikimedia powered wiki. One would be the API and the other one would be a database dump.
I'd prefer not to download the wiki dump. First, it's huge, and second, I'm not really experienced with querying databases. The problem with the API on the other hand is that I couldn't figure out a way to only retrieve a list of the article titles and even if it would need > 4 mio requests which would probably get me blocked from any further requests anyway.
So my question is
Is there a way to obtain only the titles of Wikipedia articles via the API?
Is there a way to combine multiple request/queries into one? Or do I actually have to download a Wikipedia dump?
The allpages API module allows you to do just that. Its limit (when you set aplimit=max) is 500, so to query all 4.5M articles, you would need about 9000 requests.
But a dump is a better choice, because there are many different dumps, including all-titles-in-ns0 which, as its name suggests, contains exactly what you want (59 MB of gzipped text).
Right now, as per the current statistics the number of articles is around 5.8M.
To get the list of pages I did use the AllPages API. However, the number of pages I get is around 14.5M which is ~3 times of what I was expecting. I restricted myself to namespace 0 to get the list. Following is the sample code that I am using:
# get the list of all wikipedia pages (articles) -- English
import sys
from simplemediawiki import MediaWiki
listOfPagesFile = open("wikiListOfArticles_nonredirects.txt", "w")
wiki = MediaWiki('https://en.wikipedia.org/w/api.php')
continueParam = ''
requestObj = {}
requestObj['action'] = 'query'
requestObj['list'] = 'allpages'
requestObj['aplimit'] = 'max'
requestObj['apnamespace'] = '0'
pagelist = wiki.call(requestObj)
pagesInQuery = pagelist['query']['allpages']
for eachPage in pagesInQuery:
pageId = eachPage['pageid']
title = eachPage['title'].encode('utf-8')
writestr = str(pageId) + "; " + title + "\n"
listOfPagesFile.write(writestr)
numQueries = 1
while len(pagelist['query']['allpages']) > 0:
requestObj['apcontinue'] = pagelist["continue"]["apcontinue"]
pagelist = wiki.call(requestObj)
pagesInQuery = pagelist['query']['allpages']
for eachPage in pagesInQuery:
pageId = eachPage['pageid']
title = eachPage['title'].encode('utf-8')
writestr = str(pageId) + "; " + title + "\n"
listOfPagesFile.write(writestr)
# print writestr
numQueries += 1
if numQueries % 100 == 0:
print "Done with queries -- ", numQueries
print numQueries
listOfPagesFile.close()
The number of queries fired is around 28900, which results in approx. 14.5M names of the pages.
I also tried the all-titles link mentioned in the above answer. In that case as well I am getting around 14.5M pages.
I thought that this overestimate to the actual number of pages is because of the redirects, and did add the 'nonredirects' option to the request object:
requestObj['apfilterredir'] = 'nonredirects'
After doing that I get only 112340 number of pages. Which is too small as compared to 5.8M.
With the above code I was expecting roughly 5.8M pages, but that doesn't seem to be the case.
Is there any other option that I should be trying to get the actual (~5.8M) set of page names?
Here is an asynchronous program that will generate mediawiki pages titles:
async def wikimedia_titles(http, wiki="https://en.wikipedia.org/"):
log.debug('Started generating asynchronously wiki titles at {}', wiki)
# XXX: https://www.mediawiki.org/wiki/API:Allpages#Python
url = "{}/w/api.php".format(wiki)
params = {
"action": "query",
"format": "json",
"list": "allpages",
"apfilterredir": "nonredirects",
"apfrom": "",
}
while True:
content = await get(http, url, params=params)
if content is None:
continue
content = json.loads(content)
for page in content["query"]["allpages"]:
yield page["title"]
try:
apcontinue = content['continue']['apcontinue']
except KeyError:
return
else:
params["apfrom"] = apcontinue
I am a biologist trying to do computer science for research, so I may be a bit naïve. But I would like to a make a table containing information from a data frame, with a hyperlink in one of the columns. I imagine this needs to be an html document (?). I found this post this post describing how to put a hyperlink into a data frame and write it as an HTML file using googleVis. I would like to use this approach (it is the only one I know and seems to work well) except I would like to replace the actual URL with a description. The real motivation being that I would like to include many of these hyperlinks, and the links have long addresses which is difficult to read.
To be verbose, I essentially want to do what I did here where we read 'here' but 'here' points to
http:// stackoverflow.com/questions/8030208/exporting-table-in-r-to-html-with-hyperlinks
From your previous question, you can have another list which contains the titles of the URL's:
url=c('http://nytimes.com', 'http://cnn.com', 'http://www.weather.gov'))
urlTitles=c('NY Times', 'CNN', 'Weather'))
foo <- transform(foo, url = paste('<a href = ', shQuote(url), '>', urlTitles, '</a>'))
x = gvisTable(foo, options = list(allowHTML = TRUE))
plot(x)
Building on Jack's answer but consolidating from different threads:
library(googleVis)
library(R2HTML)
url <- c('http://nytimes.com', 'http://cnn.com', 'http://www.weather.gov')
urlTitles <- c('NY Times', 'CNN', 'Weather')
foo <- data.frame(a=c(1,2,3), b=c(4,5,6), url=url)
foo <- transform(foo, url = paste('<a href = ', shQuote(url), '>', urlTitles, '</a>'))
x <- gvisTable(foo, options = list(allowHTML = TRUE))
plot(x)