Is there a way to iterate through a page's archives where the format is
'http://base_url/page=#' - where # is 2-nth page number?
Ideally I'd like to deploy my scraper on every successive page after 'base_url'
is the a function or for loop in python where the base_url would be iterated through like:
page = i in range(nth)
base_url ='http://base_url/page={}'
e.g. http://www.businessinsider.com/?page=3 vs. http://www.businessinsider.com/
You can just request each page like so:
# python 2
from urllib2 import urlopen
# python 3
from urllib.request import urlopen
base_url = "http://example.com/"
# request page 1 through 10
n = 10
for i in range(1, n+1):
if (i == 1):
# handle first page
response = urlopen(base_url)
response = urlopen(base_url + "?page=%d" % i)
data = response.read()
# handle data here
EDIT: urlopen() returns an HTTPResponse or addinfourl object (depending on your Python version) - you need to call .read() on that to get the string of data. (I've updated my example code above, too).
Related
Hi i want to crawl XHR request url which has JSON feed but when i change query paramater page value to 2 or any other it retrieve data from page 1 but when i did the same in browser it shows data according to its page.
enter code here
import json
import requests
url = 'https://www.daraz.pk/computer-graphic-cards/?'
params_dict = {}
params_dict['ajax']= 'true'
params_dict['page']= 1
params_dict['spm'] = 'a2a0e.home.cate_2_9.1.35e349378NoL6f'
res = requests.get(url, params=params_dict)
data = json.loads(res.text)
res.url # url changes but content is same of page 1
info = data.get('mods').get('listItems')
for i in info:
print(i['name'])
I think how the data is being returned has issues. I modified the call slightly by looping over the pages.
Looking at the data returned, it seems that some products are being returned on multiple pages even in the UI.
for page_num in range(1, 7):
res = requests.get('https://www.daraz.pk/computer-graphic-cards/?ajax=true&page=' + str(page_num)).json()
info = res.get('mods').get('listItems')
for i in info:
print('%s:%s:%s---------%s' % (i['itemId'],i['sellerName'],i['skuId'],i['name']))
print('----------------------- PAGE %s ------------------------------------------' % (page_num))
Data returned from this code snippet is linked here.
I'm looking for some library or libraries in Python to:
a) log in a web site,
b) find all links to some media files (let us say having "download" in their URLs), and
c) download each file efficiently directly to the hard drive (without loading the whole media file into RAM).
Thanks
You can use the broadly used requests module (more than 35k stars on github), and BeautifulSoup. The former handles session cookies, redirections, encodings, compression and more transparently. The later finds parts in the HTML code and has an easy-to-remember syntax, e.g. [] for properties of HTML tags.
It follows a complete example in Python 3.5.2 for a web site that you can scrap without a JavaScript engine (otherwise you can use Selenium), and downloading sequentially some links with download in its URL.
import shutil
import sys
import requests
from bs4 import BeautifulSoup
""" Requirements: beautifulsoup4, requests """
SCHEMA_DOMAIN = 'https://exmaple.com'
URL = SCHEMA_DOMAIN + '/house.php/' # this is the log-in URL
# here are the name property of the input fields in the log-in form.
KEYS = ['login[_csrf_token]',
'login[login]',
'login[password]']
client = requests.session()
request = client.get(URL)
soup = BeautifulSoup(request.text, features="html.parser")
data = {KEYS[0]: soup.find('input', dict(name=KEYS[0]))['value'],
KEYS[1]: 'my_username',
KEYS[2]: 'my_password'}
# The first argument here is the URL of the action property of the log-in form
request = client.post(SCHEMA_DOMAIN + '/house.php/user/login',
data=data,
headers=dict(Referer=URL))
soup = BeautifulSoup(request.text, features="html.parser")
generator = ((tag['href'], tag.string)
for tag in soup.find_all('a')
if 'download' in tag['href'])
for url, name in generator:
with client.get(SCHEMA_DOMAIN + url, stream=True) as request:
if request.status_code == 200:
with open(name, 'wb') as output:
request.raw.decode_content = True
shutil.copyfileobj(request.raw, output)
else:
print('status code was {} for {}'.format(request.status_code,
name),
file=sys.stderr)
You can use the mechanize module to log into websites like so:
import mechanize
br = mechanize.Browser()
br.set_handle_robots(False)
br.open("http://www.example.com")
br.select_form(nr=0) #Pass parameters to uniquely identify login form if needed
br['username'] = '...'
br['password'] = '...'
result = br.submit().read()
Use bs4 to parse this response and find all the hyperlinks in the page like so:
from bs4 import BeautifulSoup
import re
soup = BeautifulSoup(result, "lxml")
links = []
for link in soup.findAll('a'):
links.append(link.get('href'))
You can use re to further narrow down the links you need from all the links present in the response webpage, which are media links (.mp3, .mp4, .jpg, etc) in your case.
Finally, use requests module to stream the media files so that they don't take up too much memory like so:
response = requests.get(url, stream=True) #URL here is the media URL
handle = open(target_path, "wb")
for chunk in response.iter_content(chunk_size=512):
if chunk: # filter out keep-alive new chunks
handle.write(chunk)
handle.close()
when the stream attribute of get() is set to True, the content does not immediately start downloading to RAM, instead the response behaves like an iterable, which you can iterate over in chunks of size chunk_size in the loop right after the get() statement. Before moving on to the next chunk, you can write the previous chunk to memory hence ensuring that the data isn't stored in RAM.
You will have to put this last chunk of code in a loop if you want to download media of every link in the links list.
You will probably have to end up making some changes to this code to make it work as I haven't tested it for your use case myself, but hopefully this gives a blueprint to work off of.
So I am trying to create a program that gets all the urls on a google webpage search, and returns a list of them all in order of where they are on that page. So if its the top url on a google search page for "random", this link, then the first item in the list that should be returned should be "https://www.random.org/". This is due to it being the first link when you search random on google in the source code. I am using urllib3 and the re module because I do not really know how to use beautiful soup or lxml but if you can do this in beautiful soup and/or lxml that would also be fine. This is my code so far:
import urllib.request
import re
def find(start,end):
urls = []
with open('data.txt', 'r') as myFile:
pass # Needs to append the every instance of all urls between the start and end inputs in data.txt
# Returns all instances of urls between the start and end paramaters in data.txt
return urls
def parse(query):
# Creates the url with the query
url = 'https://www.google.com/search?q=' + query
# Gets past googles attempt to block parsing
headers = {}
headers['User-Agent'] = "Mozilla/5.0 (X11; Linux i686) AppleWebKit/537.17 (KHTML, like Gecko) Chrome/24.0.1312.27 Safari/537.17"
# Fetches data
req = urllib.request.Request(url, headers = headers)
resp = urllib.request.urlopen(req)
respData = resp.read()
# Saves the source code in a txt file
saveFile = open('data.txt','w')
saveFile.write(str(respData))
saveFile.close()
# Finds the urls and returns them
newUrl = find('<h3 class="r"><a href="','"')
return newUrl
print(parse("random"))
PROBLEM: My problem is making the find() function work, I am not sure how to get the urls from the source code saved in data.txt and the variable respData, I want to do make this efficient so I was thinking of using regular expressions. However I am not sure how to get it to get the urls from the source code based on where the url starts (the class bit which is a parameter for the find function) and where it starts (the inverted comma which is another parameter for the find function).
SIMPLIFIED PROBLEM: Given some text data how would you create a list with all instances of some text in data between two strings start and finish. And how would you make this efficient for a large amount of data stored in data and then apply that to the find() function in my original code.
NOTE: Using python 3.6.3 therefore, I'm not using urllib2 instead urllib3. And if it is going to to take a long time to get every url on a google search webpage the first 10 urls are fine.
With beautiful soup, after urlopen
from bs4 import BeautifulSoup
#code snip
resp = urllib.request.urlopen(req)
soup = BeautifulSoup(resp)
for x in soup.findAll('a', {"class": "r"}):
print(x)
I have not tested, but this is how you do the search in Beautiful soup
On a side note, using Regex to parse html can be tricky when going it alone. Better to use Beautiful Soap 4 or Scrapy to handle the parsing for you.
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
This is probably a very simple task, but I cannot find any help. I have a website that takes the form www.xyz.com/somestuff/ID. I have a list of the IDs I need information from. I was hoping to have a simple script to go one the site and download the (complete) web page for each ID in a simple form ID_whatever_the_default_save_name_is in a specific folder.
Can I run a simple python script to do this for me? I can do it by hand, it is only 75 different pages, but I was hoping to use this to learn how to do things like this in the future.
Mechanize is a great package for crawling the web with python. A simple example for your issue would be:
import mechanize
br = mechanize.Browser()
response = br.open("www.xyz.com/somestuff/ID")
print response
This simply grabs your url and prints the response from the server.
This can be done simply in python using the urllib module. Here is a simple example in Python 3:
import urllib.request
url = 'www.xyz.com/somestuff/ID'
req = urllib.request.Request(url)
page = urllib.request.urlopen(req)
src = page.readall()
print(src)
For more info on the urllib module -> http://docs.python.org/3.3/library/urllib.html
Do you want just the html code for the website? If so, just create a url variable with the host site and add the page number as you go. I'll do this for an example with http://www.notalwaysright.com
import urllib.request
url = "http://www.notalwaysright.com/page/"
for x in range(1, 71):
newurl = url + x
response = urllib.request.urlopen(newurl)
with open("Page/" + x, "a") as p:
p.writelines(reponse.read())