I'm trying to pull data from a website which is dynamically updated (every few hours or so), it is a website of a transport service and it has a few pages/tabs.
all i managed so far is to pull only the first page no matter what i try.
so i can't pull the data of the other tabs.
the code:
from bs4 import BeautifulSoup, SoupStrainer
import requests
import pandas as pd
# For establishing connection
proxies = {'http': 'http:...'}
url = 'http://yit.maya-tour.co.il/yit-pass/Drop_Report.aspx?client_code=2660&coordinator_code=2669'
page = requests.get(url, proxies=proxies)
data = page.text
soup = BeautifulSoup(data, "lxml")
for link in soup.find_all('a'):
print(link.get('href'))
html = requests.get(url, proxies=proxies).text
df_list = pd.read_html(html)
df = df_list[1]
df.to_csv('my data.csv')
i also tried doing it by parsing the html source code, but only got the first page as well, any ideas??
you should extract the first page's hyperlinks and use it in your code!(if there is no hyperlinks, put other urls in the loop like below)
import pandas as pd
df_list = []
//call each page here. i assume you have page number at the end of main url
for p in range(1, n):
url = 'http://yit.maya-tour.co.il/yit-pass/Drop_Report.aspx?client_code=2660& coordinator_code=2669?pNumber=%d' %p
df_list.append(pd.read_html(url)[0])
df = pd.concat(df_list)
print(df)
df.to_csv('my data.csv')
Every 15 seconds the webpage is calling the javasscript code below:
function __doPostBack(eventTarget, eventArgument) {
if (!theForm.onsubmit || (theForm.onsubmit() != false)) {
theForm.__EVENTTARGET.value = eventTarget;
theForm.__EVENTARGUMENT.value = eventArgument;
theForm.submit();
}
}
Open your browser dev tools and put a breakpoint in this function. After you understand the arguments that are submitted by the code, use requests (or other http client) to submit the form from your python code.
Related
I'm trying to use pagination to request multiple pages of rent listing from zillow. Otherwise I'm limited to the first page only. However, my code seems to load the first page only even if I specify specific pages manually.
# Rent
import requests
from bs4 import BeautifulSoup as soup
import json
url = 'https://www.zillow.com/torrance-ca/rentals'
params = {
'q': {"pagination":{"currentPage": 1},"isMapVisible":False,"filterState":{"fore":{"value":False},"mf":{"value":False},"ah":{"value":True},"auc":{"value":False},"nc":{"value":False},"fr":{"value":True},"land":{"value":False},"manu":{"value":False},"fsbo":{"value":False},"cmsn":{"value":False},"fsba":{"value":False}},"isListVisible":True}
}
headers = {
# headers were copied from network tab on developer tools in chrome
}
html = requests.get(url=url,headers=headers, params=params)
html.status_code
bsobj = soup(html.content, 'lxml')
for script in bsobj.find_all('script'):
inner_text_with_string = str(script.string)
if inner_text_with_string[:18] == '<!--{"queryState":':
my_query = inner_text_with_string
my_query = my_query.strip('><!-')
data = json.loads(my_query)
data = data['cat1']['searchResults']['listResults']
print(data)
This returns about 40 listings. However, if I change "pagination":{"currentPage": 1} to "pagination":{"currentPage": 2}, it returns the same listings! It's as if the pagination parameter isn't recognized.
I believe these are the correct parameters, as I took them straight from the url string query and used http://urlprettyprint.com/ to make it pretty.
Any thoughts on what I'm doing wrong?
Using the params argument with requests is sending the wrong data, you can confirm this by printing response.url. what i would do is use urllib.parse.urlencode:
from urllib.parse import urlencode
...
html = requests.get(url=f"{url}?{urlencode(params)}", headers=headers)
how to get access to this API:
import requests
url = 'https://b2c-api-premiumlabel-production.azurewebsites.net/api/b2c/page/menu?id_loja=2691'
print(requests.get(url))
I'm trying to retrieve data from this site via API, I found the url above and I can see its data , however I can't seem to get it right because I'm running into code 403.
This is the website url:
https://www.nagumo.com.br/osasco-lj46-osasco-ayrosa-rua-avestruz/departamentos
I'm trying to retrieve items category, they are visible for me, but I'm unable to take them.
Later I'll use these categories to iterate over products API.
API Category
Obs: please be gentle it's my first post here =]
To get the data as you shown in your image the following headers and endpoint are needed:
import requests
headers = {
'sm-token': '{"IdLoja":2691,"IdRede":884}',
'User-Agent': 'Mozilla/5.0',
'Referer': 'https://www.nagumo.com.br/osasco-lj46-osasco-ayrosa-rua-avestruz/departamentos',
}
params = {
'id_loja': '2691',
}
r = requests.get('https://www.nagumo.com.br/api/b2c/page/menu', params=params, headers=headers)
r.json()
Not sure exactly what your issue is here.
Bu if you want to see the content of the response and not just the 200/400 reponses. You need to add '.content' to your print.
Eg.
#Create Session
s = requests.Session()
#Example Connection Variables, probably not required for your use case.
setCookieUrl = 'https://www...'
HeadersJson = {'Accept-Language':'en-us'}
bodyJson = {"__type":"xxx","applicationName":"xxx","userID":"User01","password":"password2021"}
#Get Request
p = s.get(otherUrl, json=otherBodyJson, headers=otherHeadersJson)
print(p) #Print response (200 etc)
#print(p.headers)
#print(p.content) #Print the content of the response.
#print(s.cookies)
I'm also new here haha, but besides this requests library, you'll also need another one like beautiful soup for what you're trying to do.
bs4 installation: https:https://www.crummy.com/software/BeautifulSoup/bs4/doc/#installing-beautiful-soup
Once you install it and import it, it's just continuing what you were doing to actively get your data.
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
this gets the entire HTML content of the page, and so, you can get your data from this page based on their css selectors like this:
site_data = soup.select('selector')
site_data is an array of things with that 'selector', so a simple for loop and an array to add your items in would suffice (as an example, getting links for each book on a bookstore site)
For example, if i was trying to get links from a site:
import requests
from bs4 import BeautifulSoup
sites = []
URL = 'https://b2c-api-premiumlabel-production.azurewebsites.net/api/b2c/page/menu?id_loja=2691'
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
links = soup.select("a") # list of all items with this selector
for link in links:
sites.append(link)
Also, a helpful tip is when you inspect the page (right click and at the bottom press 'inspect'), you can see the code for the page. Go to the HTML and find the data you want and right click it and select copy -> copy selector. This will make it really easy for you to get the data you want on that site.
helpful sites:
https://oxylabs.io/blog/python-web-scraping
https://realpython.com/beautiful-soup-web-scraper-python/
I've been trying to scrape Bandcamp fan pages to get a list of the albums they have purchased and I'm having trouble efficiently doing it. I wrote something with Selenium but it's mildly slow so I'd like to learn a solution that'd maybe send a POST request to the site and parse the JSON from there.
Here's a sample collection page: https://bandcamp.com/nhoward
Here's the Selenium code:
def scrapeFanCollection(url):
browser = getBrowser()
setattr(threadLocal, 'browser', browser)
#Go to url
browser.get(url)
try:
#Click show more button
browser.find_element_by_class_name('show-more').click()
#Wait two seconds
time.sleep(2)
#Scroll to the bottom loading full collection
scroll(browser, 2)
except Exception:
pass
#Return full album collection
soup_a = BeautifulSoup(browser.page_source, 'lxml', parse_only=SoupStrainer('a', {"class": "item-link"}))
#Empty array
urls = []
# Looping through all the a elements in the page source
for item in soup_a.find_all('a', {"class": "item-link"}):
url = item.get('href')
if(url != None):
urls.append(url)
return urls
The API can be accessed as follows:
$ curl -X POST -H "Content-Type: Application/JSON" -d \
'{"fan_id":82985,"older_than_token":"1586531374:1498564527:a::","count":10000}' \
https://bandcamp.com/api/fancollection/1/collection_items
I didn't encounter a scenario where a "older_than_token" was stale, so the problem boils down to getting the "fan_id" given a URL.
This information is located in a blob in the id="pagedata" element.
>>> import json
>>> import requests
>>> from bs4 import BeautifulSoup
>>> res = requests.get("https://www.bandcamp.com/ggorlen")
>>> soup = BeautifulSoup(res.text, "lxml")
>>> user = json.loads(soup.find(id="pagedata")["data-blob"])
>>> user["fan_data"]["fan_id"]
82985
Putting it all together (building upon this answer):
import json
import requests
from bs4 import BeautifulSoup
fan_page_url = "https://www.bandcamp.com/ggorlen"
collection_items_url = "https://bandcamp.com/api/fancollection/1/collection_items"
res = requests.get(fan_page_url)
soup = BeautifulSoup(res.text, "lxml")
user = json.loads(soup.find(id="pagedata")["data-blob"])
data = {
"fan_id": user["fan_data"]["fan_id"],
"older_than_token": user["wishlist_data"]["last_token"],
"count": 10000,
}
res = requests.post(collection_items_url, json=data)
collection = res.json()
for item in collection["items"][:10]:
print(item["album_title"], item["item_url"])
I'm using user["wishlist_data"]["last_token"] which has the same format as the "older_than_token" just in case this matters.
In order to get the entire collection i changed the previous code from
"older_than_token": user["wishlist_data"]["last_token"]
to
user["collection_data"]["last_token"]
which contained the right token
Unfortunately for you, this particular Bandcamp site doesn't seem to make any HTTP API call to fetch the list of albums. You can check that by using your browser developer tools, Network tab, click on XHR filter. The only call being made seems to be fetching your collection details.
Currently doing web-scraping for the first time trying to grab and compile a list of completed Katas from my CodeWars profile. You can view the completed problems without being logged in but it does not display your solutions unless you have logged in to that specific account.
Here is an inspect preview of the page display when logged in and the relevant divs I'm trying to scrape:
The url for that page is https://www.codewars.com/users/User_Name/completed_solutions
with User_Name replaced by an actual username.
The log-in page is: https://www.codewars.com/users/sign_in
I have attempted to get the divs with the class "list-item solutions" in two different ways now which I'll write:
#attempt 1
import requests
from bs4 import BeautifulSoup
login_url = "https://www.codewars.com/users/sign_in"
end_url = "https://www.codewars.com/users/Ash-Ozen/completed_solutions"
with requests.session() as sesh:
result = sesh.get(login_url)
soup = BeautifulSoup(result.content, "html.parser")
token = soup.find("input", {"name": "authenticity_token"})["value"]
payload = {
"user[email]": "ph#gmail.com",
"user[password]": "phpass>",
"authenticity_token": str(token),
}
result = sesh.post(login_url, data=payload) #this logs me in?
page = sesh.get(end_url) #This navigates me to the target page?
soup = BeautifulSoup(page.content, "html.parser")
print(soup.prettify()) # some debugging
# Examining the print statement shows that the "list-item solutions" is not
# there. Checking page.url shows the correct url(https://www.codewars.com/users/Ash-Ozen/completed_solutions).
solutions = soup.findAll("div", class_="list-item solutions")
# solutions yields an empty list.
and
#attempt 2
from robobrowser import RoboBrowser
from bs4 import BeautifulSoup
browser = RoboBrowser(history=True)
browser.open("https://www.codewars.com/users/sign_in")
form = browser.get_form()
form["user[email]"].value = "phmail#gmail.com"
form["user[password]"].value = "phpass"
browser.submit_form(form) #think robobrowser handles the crfs token for me?
browser.open("https://www.codewars.com/users/Ash-Ozen/completed_solutions")
r = browser.parsed()
soup = BeautifulSoup(str(r[0]), "html.parser")
solutions = soup.find_all("div", class_="list-item solutions")
print(solutions) # returns empty list
No idea how/what to debug from here to get it working.
Edit: My initial thoughts about what is going wrong is that, after performing either post I get redirected to the dashboard (behavior after logging in successfully) but it seems that when trying to get the final url I end up with the non-logged-in version of the page.
For last few days I am trying to scrap the following website (link pasted below) which has a few excels and pdfs available in a table. I am able to do it for the home page successfully. There are total 59 pages from which these excels/ pdfs have to be scrapped. In most of the websites I have seen till now there is a query parameter which is available in the site url which changes as you move from one page to another. In this case, we have a _doPostBack function probably because of which the URL remains the same on every page you go to. I looked at multiple solutions and posts which are suggesting to see the parameters of post call and use them but I am not able to make sense of the parameters which are provided in post call (this is the first time I am scrapping a website).
Can someone please suggest some resource which can help me write a code which helps me in moving from one page to another using python. The details are as follows:
Website link - http://accord.fairfactories.org/ffcweb/Web/ManageSuppliers/InspectionReportsEnglish.aspx
My current code which extracts the CAP excel sheet from the home page (this is working perfect and is provided just for reference)
from urllib.request import urlopen
from urllib.request import urlretrieve
from bs4 import BeautifulSoup
import re
import urllib
Base = "http://accord.fairfactories.org/ffcweb/Web"
html = urlopen("http://accord.fairfactories.org/ffcweb/Web/ManageSuppliers/InspectionReportsEnglish.aspx")
bs = BeautifulSoup(html)
name = bs.findAll("td", {"class":"column_style_right column_style_left"})
i = 1
for link in bs.findAll("a", {"id":re.compile("CAP(?!\w)")}):
if 'href' in link.attrs:
name = str(i)+".xlsx"
a = link.attrs['href']
b = a.strip("..")
c = Base+b
urlretrieve(c, name)
i = i+1
Please let me know if I have missed anything while providing the information and please don't rate me -ve else I won't be able to ask any questions further
For aspx sites, you need to look for things like __EVENTTARGET, __EVENTVALIDATION etc.. and post those parameters with each request, this will get all the pages and using requests with bs4:
import requests
from bs4 import BeautifulSoup
from urlparse import urljoin # python 3 use from urllib.parse import urljoin
# All the keys need values set bar __EVENTTARGET, that stays the same.
data = {
"__EVENTTARGET": "gvFlex",
"__VIEWSTATE": "",
"__VIEWSTATEGENERATOR": "",
"__VIEWSTATEENCRYPTED": "",
"__EVENTVALIDATION": ""}
def validate(soup, data):
for k in data:
# update post values in data.
if k != "__EVENTTARGET":
data[k] = soup.select_one("#{}".format(k))["value"]
def get_all_excel():
base = "http://accord.fairfactories.org/ffcweb/Web"
url = "http://accord.fairfactories.org/ffcweb/Web/ManageSuppliers/InspectionReportsEnglish.aspx"
with requests.Session() as s:
# Add a user agent for each subsequent request.
s.headers.update({"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:47.0) Gecko/20100101 Firefox/47.0"})
r = s.get(url)
bs = BeautifulSoup(r.content, "lxml")
# get links from initial page.
for xcl in bs.select("a[id*=CAP]"):
yield urljoin(base, xcl["href"])
# need to re-validate the post data in our dict for each request.
validate(bs, data)
last = bs.select_one("a[href*=Page$Last]")
i = 2
# keep going until the last page button is not visible
while last:
# Increase the counter to set the target to the next page
data["__EVENTARGUMENT"] = "Page${}".format(i)
r = s.post(url, data=data)
bs = BeautifulSoup(r.content, "lxml")
for xcl in bs.select("a[id*=CAP]"):
yield urljoin(base, xcl["href"])
last = bs.select_one("a[href*=Page$Last]")
# again re-validate for next request
validate(bs, data)
i += 1
for x in (get_all_excel()):
print(x)
If we run it on the first three pages, you can see we get the data you want:
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9965
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9552
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10650
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11969
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10086
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10905
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10840
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9229
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11310
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9178
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9614
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9734
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10063
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10871
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9468
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9799
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9278
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=12252
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9342
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9966
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11595
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9652
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10271
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10365
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10087
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9967
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11740
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=12375
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11643
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10952
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=12013
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9810
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10953
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10038
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9664
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=12256
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9262
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9210
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9968
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9811
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11610
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9455
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11899
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10273
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9766
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9969
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10088
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10366
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9393
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9813
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11795
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9814
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11273
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=12187
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10954
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9556
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11709
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9676
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10251
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10602
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10089
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9908
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10358
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9469
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11333
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9238
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9816
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9817
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10736
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10622
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9394
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9818
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=10592
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=9395
http://accord.fairfactories.org/Utilities/DownloadFile.aspx?id=11271