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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.

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.

Python - Beautiful Soup to grab emails from website

I've been trying to figure out a simple way to run through a set of URLs that lead to pages that all have the same layout. We figured out that one issue is that in the original list the URLs are http but then they redirect to https. I am not sure if that then causes a problem in trying to pull the information from the page. I can see the structure of the page when I use Inspector in Chrome, but when I try to set up the code to grab relevant links I come up empty (literally). The most general code I have been using is:
soup = BeautifulSoup(urllib2.urlopen('https://ngcproject.org/program/algirls').read())
links = SoupStrainer('a')
print links
which yields:
a|{}
Given that I'm new to this I've been trying to work with anything that I think might work. I also tried:
mail = soup.find(attrs={'class':'tc-connect-details_send-email'}).a['href']
and
spans = soup.find_all('span', {'class' : 'tc-connect-details_send-email'})
lines = [span.get_text() for span in spans]
print lines
but these don't yield anything either.
I am assuming that it's an issue with my code and not one that the data are hidden from being scraped. Ideally I want to have the data passed to a CSV file for each URL I scrape but right now I need to be able to confirm that the code is actually grabbing the right information. Any suggestions welcome!

If you press CTRL+U on Google Chrome or Right click > view source.
You'll see that the page is rendered by using javascript or other.
urllib is not going to be able to display/download what you're looking for.
You'll have to use automated browser (Selenium - most popular) and you can use it with Google Chrome / Firefox or a headless browser (PhantomJS).
You can then get the information from Selenium and store it then manipulate it in anyway you see fit.

Scraping Biography.com using urllib2

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

web scraping a problem site

I'm trying to scrape some information from a web site, but am having trouble reading the relevant pages. The pages seem to first send a basic setup, then more detailed info. My download attempts only seem to capture the basic setup. I've tried urllib and mechanize so far.
Firefox and Chrome have no trouble displaying the pages, although I can't see the parts I want when I view page source.
A sample url is https://personal.vanguard.com/us/funds/snapshot?FundId=0542&FundIntExt=INT
I'd like, for example, average maturity and average duration from the lower right of the page. The problem isn't extracting that info from the page, it's downloading the page so that I can extract the info.

The page uses JavaScript to load the data. Firefox and Chrome are only working because you have JavaScript enabled - try disabling it and you'll get a mostly empty page.
Python isn't going to be able to do this by itself - your best compromise would be to control a real browser (Internet Explorer is easiest, if you're on Windows) from Python using something like Pamie.

The website loads the data via ajax. Firebug shows the ajax calls. For the given page, the data is loaded from https://personal.vanguard.com/us/JSP/Funds/VGITab/VGIFundOverviewTabContent.jsf?FundIntExt=INT&FundId=0542
See the corresponding javascript code on the original page:
<script>populator = new Populator({parentId:
"profileForm:vanguardFundTabBox:tab0",execOnLoad:true,
populatorUrl:"/us/JSP/Funds/VGITab/VGIFundOverviewTabContent.jsf?FundIntExt=INT&FundId=0542",
inline:fals e,type:"once"});
</script>

The reason why is because it's performing AJAX calls after it loads. You will need to account for searching out those URLs to scrape it's content as well.

As RichieHindle mentioned, your best bet on Windows is to use the WebBrowser class to create an instance of an IE rendering engine and then use that to browse the site.
The class gives you full access to the DOM tree, so you can do whatever you want with it.
http://msdn.microsoft.com/en-us/library/system.windows.forms.webbrowser(loband).aspx