I am trying to automate a test case wherein I first login to a website and then modify a drop down. I have automated the part until where I reach the correct page. The issue is, this drop down option is part of a table. The table has many similar elements. Also a few table tags are used as the first column is locked and others are horizontally scrollable. I am finding it very difficult to locate the correct drop down option to click.
When I check in the developer options, the drown modification is actually a POST request.
I know we can use API testing with pytest, but is it possible to integrate this within existing selenium framework?
Can I create a framework where in test_navigate will navigate me to the necessary page (pure selenium). Then test_modify_dropdown will use api call to send the POST request and modify the option. And then i can continue with further test_three?
All this in pytest by the way.
You should simply be able to use the python requests module. A post request could look like this:
import requests
url = "url/for/your/api"
myobj = {'somekey': 'somevalue'} #json in request payload
x = requests.post(url, json = myobj)
print(x.text) #and/or get whatever data you want from the response.
Related
I'm new to webscraping and I wanted to retrieve all the wins and losses within this season of the NHL. Now this url works fine: https://www.nhl.com/scores ... but the problem arises when I want to go back to previous dates like so: https://www.nhl.com/scores/2022-09-24 ... this is the url that shows up when I interact with the buttons in that first url. you can see for yourself. I know i'm missing something here but to me it's not as obvious. please enlighten me.
I then tried to see if there was a way to use https://www.nhl.com/scores/ to obtain the information I require but I am having trouble accessing that data.
I'd recommend not using the URLs to access a specific date's data and instead take a look at the Fetch/XHR requests in your browser's dev tools -> Network activity to see what kinds of API calls are being made whenever you click on a date. Then you can make a call directly to that API endpoint within your python script and parse the JSON response
You can use the requests library for this: https://requests.readthedocs.io/en/latest/
I'm using scrapy (on PyCharm v2020.1.3) to build a spider that crawls this webpage: "https://www.woolworths.com.au/shop/browse/drinks/cordials-juices-iced-teas/iced-teas", i want to extract the products names, and the breadcrumb in a list format, and save the results in a csv file.
I tried the following code but it returns empty brackets [] , after i've inspected the html code i discovred that the content is hidden in angularjs format.
If someone has a solution for that it would be great
Thank you
import scrapy
class ProductsSpider(scrapy.Spider):
name = 'products'
start_urls = ['https://www.woolworths.com.au/shop/browse/drinks/cordials-juices-iced-teas/iced-teas']
def parse(self, response):
product = response.css('a.shelfProductTile-descriptionLink::text').extract()
yield "productnames"
You won't be able to get the desired products through parsing the HTML. It is heavily javascript orientated and therefore scrapy wont parse this.
The simplest way to get the product names, I'm not sure what you mean by breadcrumbs is to re-engineer the HTTP requests. The woolworths website generates the product details via an API. If we can mimick the request the browser makes to obtain that product information we can get the information in a nice neat format.
First you have to set within settings.py ROBOTSTXT_OBEY = False. Becareful about protracted scrapes of this data because your IP will probably get banned at some point.
Code Example
import scrapy
class TestSpider(scrapy.Spider):
name = 'test'
allowed_domains = ['woolworths.com']
data = {
'excludeUnavailable': 'true',
'source': 'RR-Best Sellers'}
def start_requests(self):
url = 'https://www.woolworths.com.au/apis/ui/products/58520,341057,305224,70660,208073,69391,69418,65416,305227,305084,305223,427068,201688,427069,341058,305195,201689,317793,714860,57624'
yield scrapy.Request(url=url,meta=self.data,callback=self.parse)
def parse(self, response):
data = response.json()
for a in data:
yield {
'name': a['Name'],
}
Explanation
We start of with our defined url in start_requests. This URL is the specific URL of the API woolworth uses to obtain information for iced tea. For any other link on woolworths the part of the URL after /products/ will be specific to that part of the website.
The reason why we're using this, is because using browser activity is slow and prone to being brittle. This is fast and the information we can get is usually highly structured much better for scraping.
So how do we get the URL you may be asking ? You need to inspect the page, and find the correct request. If you click on network tools and then reload the website. You'll see a bunch of requests. Usually the largest sized request is the one with all the data. Clicking that and clicking preview gives you a box on the right hand side. This gives all the details of the products.
In this next image, you can see a preview of the product data
We can then get the request URL and anything else from this request.
I will often copy this request as a CURL (Bash Command) as seen here
And enter it into curl.trillworks.com. This can convert CURL to python. Giving you a nice formatted headers and any other data needed to mimick the request.
Now putting this into jupyter and playing about, you actually only need the params NOT the headers which is much better.
So back to the code. We do a request, using meta argument we can pass on the data, remember because it's outside the function we have to use self.data and then specifying the callback to parse.
We can use the response.json() method to convert the JSON object to a set of python dictionaries corresponding to each product. YOU MUST have scrapy V2.2 to use this method. Other you could use data = json.loads(response.text), but you'll have put to import json at the top of the script.
From the preview and playing about with the json in requests we can see these python dictionaries are actually within a list and so we can use a for loop to loop round each product, which is what we are doing here.
We then yield a dictionary to extract the data, a refers to each products which is it's own dictionary and a['Name'] refers to that specific python dictionary key 'Name' and giving us the correct value. To get a better feel for this, I always use requests package in jupyter to figure out the correct way to get the data I want.
The only thing left to do is to use scrapy crawl test -o products.csv to output this to a CSV file.
I can't really help you more than this until you specify any other data you want from this page. Please remember that you're going against what the site wants you to scrape, but also any other pages on that website you will need to find out the specific URL to the API to get those products. I have given you the way to do this, I suggest if you want to automate this it would be worth your while trying to struggle with this. We are hear to help but an attempt on your part is how you're going to learn coding.
Additional Information on the Approach of Dynamic Content
There is a wealth of information on this topic. Here are some guidelines to think about when looking at javascript orientated websites. The default is you should try re-engineer the requests the browser makes to load the pages information. This is what the javascript in this site and many other sites is doing, it's providing a dynamic way without reloading the page to display new information by making an HTTP request. If we can mimic that request, we can get the information we desire. This is the most efficent way to get dynamic content.
In order of preference
Re-engineering the HTTP requests
Scrapy-splash
Scrapy_selenium
importing selenium package into your scripts
Scrapy-splash is slightly better than the selenium package, as it pre-renders the page, giving you access to the selectors with the data. Selenium is slow, prone to errors but will allow you to mimic browser activity.
There are multiple ways to include selenium into your scripts see down below as an overview.
Recommended Reading/Research
Look at the scrapy documentation with regard to dynamic content here
This will give you an overview of the steps to handling dynamic content. I will say generally speaking selenium should be thought of as a last resort. It's pretty inefficient when doing larger scale scraping.
If you are consider adding in the selenium package into your script. This might be the lower barrier of entry to getting your script working but not necessarily that efficient. At the end of the day scrapy is a framework but there is a lot of flexibility in adding in 3rd party packages. The spider scripts are just a python class importing the scrapy architecture in the background. As long as you're mindful of the response and translating some of the selenium to work with scrapy, you should be able to input selenium into your scripts. I would this solution is probably the least efficient though.
Consider using scrapy-splash, splash pre-renders the page and allows for you to add in javascript execution. Docs are here and a good article from scrapinghub here
Scrapy-selenium is a package with a custom scrapy downloader middleware that allows you to do selenium actions and execute javascript. Docs here You'll need to have a play around to get the login in procedure from this, it doesn't have the same level of detail as the selenium package itself.
I work with python and data mine some content which I categorize into different categories.
Then I go to a specific webpage and submit manually the results.
Is there a way to automate the process? I guess this is a "form-submit" thread but I haven't seen any relevant module in Python. Can you suggest me something?
Selenium Webdriver is the most popular way to drive web pages, but Python also has beautifulsoup; Either library will work.
If you want make this automatic yo have to see which params are send in the form and make a request with this params to the endpoint but directly from your python app, or search a package that simulate a browser and fill the form, but I think that the correct way is making the request directly from your app
So I've scraped websites before, but this time I am stumped. I am attempting to search for a person on Biography.com and retrieve his/her biography. But whenever I search the site using urllib2 and query the URL: http://www.biography.com/search/ I get a blank page with no data in it.
When I look into the source generated in the browser by clicking View Source, I still do not see any data. When I use Chrome's developer tools, I find some data but still no links leading to the biography.
I have tried changing the User Agent, adding referrers, using cookies in Python but to no avail. If someone could help me out with this task it would be really helpful.
I am planning to use this text for my NLP project and worst case, I'll have to manually copy-paste the text. But I hope it doesn't come to that.
Chrome/Chromium's Developer Tools (or Firebug) is definitely your friend here. I can see that the initial search on Biography's site is made via a call to a Google API, e.g.
https://www.googleapis.com/customsearch/v1?q=Barack%20Obama&key=AIzaSyCMGfdDaSfjqv5zYoS0mTJnOT3e9MURWkU&cx=011223861749738482324%3Aijiqp2ioyxw&num=8&callback=angular.callbacks._0
The search term I used is in the q= part of the query string: q=Barack%20Obama.
This returns JSON inside of which there is a key link with the value of the article of interest's URL.
"link": "http://www.biography.com/people/barack-obama-12782369"
Visiting that page shows me that this is generated by a request to:
http://api.saymedia-content.com/:apiproxy-anon/content-sites/cs01a33b78d5c5860e/content-customs/#published/#by-custom-type/ContentPerson/#by-slug/barack-obama-12782369
which returns JSON containing HTML.
So, replacing the last part of the link barack-obama-12782369 with the relevant info for the person of interest in the saymedia-content link may well pull out what you want.
To implement:
You'll need to use urllib2 (or requests) to do the search via their Google API call, using urllib2.urlopen(url) or requests.get(url). Replace the Barack%20Obama with a URL escaped search string, e.g. Bill%20Clinton.
Parse the JSON using Python's json module to extract the string that gives you the http://www.biography.com/people link. From this, extract the part of this link of interest (as barack-obama-12782369 above).
Use urllib2 or requests to do a saymedia-content API request replacing barack-obama-12782369 after #by-slug/ with whatever you extract from 2; i.e. do another urllib2.urlopen on this URL.
Parse the JSON from the response of this second request to extract the content you want.
(Caveat: This is provided that there are no session-based strings in those two API calls that might expire.)
Alternatively, you can use Selenium to visit the website, do the search and then extract the content.
You will most likely need to manually copy and paste, as biography.com is a completely javascript-based site, so it can't be scraped with traditional methods.
You can discover an api url with httpfox (firefox addon). f.e. http://www.biography.com/.api/item/search?config=published&query=marx
brings you a json you can process searching for /people/ to retrive biography links.
Or you can use an screen crawler like selenium
I am trying to retrieve query results on sites based on ajax like www.snapbird.org using Python. Since it doesn't show in the page source, I am not sure how to proceed.
I am a Python newbie and hence it would be great if I could get a pointer in the right direction.
I am also open to some other approach to the task if that is easier
This is going to be complex but as a start, ppen firebug and find the URL that gets called when the AJAX request is handled. You can call that directly in your Python program and parse the output.
You could use Selenium's Python client driver to parse the page source. I usually use this in conjunction with PyQuery to make web scraping easier.
Here's the basic tutorial for Selenium's Python driver. Be sure to follow the instructions for Selenium version 2 instead of version 1 (unless you're using version 1 for some reason).
You could also configure chrome/firefox to an HTTP proxy and then log/extract the necessary content with the proxy. I've tinkered with python proxies to save/log the requests/content based on content-type or URI globs.
For other projects I've written site-specific javascript bookmarklets which poll for new data and then POST it to my server (by dynamically creating both a form and iframe, and setting myform.target=myiframe;
Other javascript scripts/bookmarklets simulate a user interacting with sites, so instead of polling every few seconds the javascript automates clicking buttons and form submissions, etc. These scripts are always very site-specific of course but they've been hugely useful for me, especially when iterating over all the paginated results for a given search.
Here is a stripped down version of walking over a list of "paginated" results and preparing to send the data off to my server (which then further parses it with BeautifulSoup). In particular this was designed for Youtube's Sent/Inbox messages.
var tables = [];
function process_and_repeat(){
if(!(inbox && inbox.message_pane_ && inbox.message_pane_.innerHTML)){
alert("We've got no data!");
}
if(inbox.message_pane_.innerHTML.indexOf('<table') === 0)
{
tables.push(inbox.message_pane_.innerHTML);
inbox.next_page();
setTimeout("process_and_repeat()",3000);
}
else{
alert("Fininshed, [" + tables.length + " processed]");
document.write('<form action=http://curl.sente.cc method=POST><textarea name=sent.html>'+escape(tables.join('\n'))+'</textarea><input type=submit></form>')
}
}
process_and_repeat(); // now we wait and watch as all the paginated pages are viewed :)
This is a stripped down example without any fancy iframes/non-essentials which just add complexity.
Adding to what Liam said, Selenium is a great tool, too, which has aided in my various scraping needs. I'd be more than happy to help you out with this if you'd like.
One easy solution might be using a browser like Mechanize. So you can browse site, follow links, make searches and nearly everything that you can do with a browser with user interface.
But for a very sepcific job, you may not even need a such library, you can use urllib and urllib2 python libraries to make a connection and read response... You can use Firebug to see data structure of a search and response body. Then use urllib to make a request with relevant parameters...
With an example...
I made a search with joyvalencia and check the request url with firebug to see:
http://api.twitter.com/1/statuses/user_timeline.json?screen_name=joyvalencia&count=100&page=2&include_rts=true&callback=twitterlib1321017083330
So calling this url with urllib2.urlopen() will be the same with making the query on Snapbird. Response body is:
twitterlib1321017083330([{"id_str":"131548107799396357","place":null,"geo":null,"in_reply_to_user_id_str":null,"coordinates":.......
When you use urlopen() and read the response, the upper string is what you get... Then you can use json library of python to read the data and parse it to a pythonic data structure...