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How to extract hidden html content with scrapy?

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.

Extracting links from website with selenium bs4 and python

Okay so.
The heading might seem like this question has already been asked but I had no luck finding an answer for it.
I need help with making link extracting program with python.
Actually It works. It finds all <a> elements on a webpage. Takes their href="" and puts it in an array. Then it exports it in csv file. Which is what I want.
But I can't get a hold of one thing.
The website is dynamic so I am using the Selenium webdriver to get JavaScript results.
The code for the program is pretty simple. I open a website with webdriver and then get its content. Then I get all links with
results = driver.find_elements_by_tag_name('a')
Then I loop through results with for loop and get href with
result.get_attribute("href")
I store results in an array and then print them out.
But the problem is that I can't get the name of the links.
This leads to Google
Is there any way to get 'This leads to Google' string.
I need it for every link that is stored in an array.
Thank you for your time
UPDATE!!!!!
As it seems it only gets dynamic links. I just notice this. This is really strange now. For hard coded items, it returns an empty string. For a dynamic link, it returns its name.

Okay. So. The answer is that instad of using .text you shoud use get_attribute("textContent"). Works better than get_attribute("innerHTML")
Thanks KunduK for this answer. You saved my day :)

How do I obtain data, with scrapy, in a web page in which I do not see that there is the code I want to scrape

I'm trying to get the names of the users and the content of the comments that exist on this page:
User and text that I need to extract:
When I test the extraction with the chrome plugin Xpath helper, I am getting the user names with the statement:
//*[#id="livefyre"]/div/div/div/div/article/div/header/a/span
and the comments, I get them with:
//*[#id="livefyre"]/div/div/div/div/article/div/section/div/p
When I do the test in the scrapy console, with the query:
response.xpath(//*[#id="livefyre"]/div/div/div/div/article/div/section/div/p).extract()
I get a [];
I've also tried with:
response.xpath (//*[#id="livefyre"]/div/div/div/div/article/div/section/div/p.text()).extract()
The same thing happens with my code.
Verifying the code of the page, I see that all those comments do not exist in the html code.
When I inspect the page, for example, I see the comment text:
But when, I check the html code of the page I do not see anything
:
Where am I making a mistake?
Thanks for help.

As you stated, there isn't any comment in the code of page, that mean website is being rendered through javascript, There are two ways you can scrape these kind of websites
First,
use scrapy-splash to render javascript
second,
find the api/network call that brings the comments, mock that request in scrapy to get your data.

Scraping webpage generated by javascript

I have a problem getting javascript content into HTML to use it for scripting. I used multiple methods as phantomjs or python QT library and they all get most of the content in nicely but the problem is that there are javascript buttons inside the page like this:
Pls see screenshot here
Now when I load this page from a script these buttons won't default to any value so I am getting back 0 for all SELL/NEUTRAL/BUY values below. Is there a way to set these values when you load the page from a script?
Example page with all the values is: https://www.tradingview.com/symbols/NEBLBTC/technicals/
Any help would be greatly appreciated.

If you are trying to achieve this with scrapy or with derivation of cURL or urrlib I am afraid that you can't do this. Python has another external packages such selenium that allow you to interact with the javascript of the page, but the problem with selenium is too slow, if you want something similar to scrapy you could check how the site works (as i can see it works through ajax or websockets) and fetch the info that you want through urllib, like you would do with an API.
Please let me know if you understand me or i misunderstood your question

I used seleneum which was perfect for this job, it is indeed slow but fits my purpose. I also used the seleneum firefox plugin to generate the python script as it was very challenging to find where exactly in the code as the button I had to press.

Python - Scrapy ecommerce website

I'm trying to scrape the price of this product
http://www.asos.com/au/fila/fila-vintage-plus-ringer-t-shirt-with-small-logo-in-green/prd/9065343?clr=green&SearchQuery=&cid=7616&gridcolumn=2&gridrow=1&gridsize=4&pge=1&pgesize=72&totalstyles=4699
With the following code but it returns an empty array
response.xpath('//*[#id="product-price"]/div/span[2]/text()').extract()
Any help is appreciated, Thanks.

Because the site is dynamic(this is what I got when I use view(response) command in scrapy shell:
As you can see, the price info doesn't come out.
Solutions:
1. splash.
2. selenium+phantomJS
It might help also by checking this answer:Empty List From Scrapy When Using Xpath to Extract Values

The price is later added by the browser which renders the page using javascript code found in the html. If you disable javascript in your browser, you would notice that the page would look a bit different. Also, take a look at the page source, usually that's unaltered, to see that the tag you're looking for doesn't exist (yet).
Scrapy doesn't execute any javascript code. It receives the plain html and that's what you have to work with.
If you want to extract data from pages which look the same as in the browser, I recommend using an headless browser like Splash (if you're already using scrapy): https://github.com/scrapinghub/splash
You can programaticaly tell it to download your page, render it and select the data points you're interested in.
The other way is to check for the request made to the Asos API which asks for the product data. In your case, for this product:
http://www.asos.com/api/product/catalogue/v2/stockprice?productIds=9065343&currency=AUD&keyStoreDataversion=0ggz8b-4.1&store=AU
I got this url by taking a look at all the XMLHttpRequest (XHR) requests sent in the Network tab found in Developers Tools (on Google Chrome).

You can try to find JSON inside HTML (using regular expression) and parse it:
json_string = response.xpath('//script[contains(., "function (view) {")]/text()').re_first( r'view\(\'([^\']+)' )
data = json.loads(json_string)
price = data["price"]["current"]