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Scrapy and possibilities available

I’m looking into web scraping /crawling possibilities and have been reading up on the Scrapy program. I was wondering if anyone knows if it’s possible to input instructions into the script so that once it’s visited the url it can then choose pre-selected dates from a calendar on the website. ?
End result is for this to be used for price comparisons on sites such as Trivago. I’m hoping I can get the program to select certain criteria such as dates once on the website like a human would.
Thanks,
Alex

In theory for a website like Trivago you can use the URL to set the dates you want to query but you will need to research user agents and proxies because otherwise your IP will get blacklisted really fast.

Website is denying access when requesting content

I am trying to collect the news history for a stock from a website using python.
The news load as you scroll down, so a number of requests are necessary for each stock.
After a few requests the website denies access, even after specifying the User-Agent and even after making it vary with each request. I also tried pausing the execution for a few seconds between requests. Nothing works.
Does anybody know how to go around this?

In case somebody else runs into this issue, the package "fake-useragent" seems to provide a solution.
I simply randomized the user agent before each request.
The website continues to deny access, albeit just seldom, and one can bypass this with a simple loop.
(The same answer was deleted a few days ago because I included a link to the package. I think my answer is more helpful to whomever runs into this issue in the future than previous answers to similar questions and all of your stupid comments.)

Can I scrape all URL results using Python from a google search without getting blocked?

I realize that versions of this question have been asked and I spent several hours the other day trying a number of strategies.
What I would like to is use python to scrape all of the URLs from a google search that I can use in a separate script to do text analysis of a large corpus (news sites mainly). This seems relatively straightforward, but none of the attempts I've tried have worked properly.
This is as close as I got:
from google import search
for url in search('site:cbc.ca "kinder morgan" and "trans mountain" and protest*', stop=100):
print(url)
This returned about 300 URLs before I got kicked. An actual search using these parameters provides about 1000 results and I'd like all of them.
First: is this possible? Second: does anyone have any suggestions to do this? I basically just want a txt file of all the URLs that I can use in another script.

It seems that this package uses screen scraping to retrieve search results from google, so it doesn't play well with Google's Terms of Service which could be the reason why you've been blocked.
The relevant clause in Google's Terms of Service:
Don’t misuse our Services. For example, don’t interfere with our Services or try to access them using a method other than the interface and the instructions that we provide. You may use our Services only as permitted by law, including applicable export and re-export control laws and regulations. We may suspend or stop providing our Services to you if you do not comply with our terms or policies or if we are investigating suspected misconduct.
I haven't been able to find a definite number, but it seems like their limit for the number of search queries a day is rather strict too - at 100 search queries / day on their JSON Custom Search API documentation here.
Nonetheless, there's no harm trying out other alternatives to see if they work better:
BeautifulSoup
Scrapy
ParseHub - this one is not in code, but is a useful piece of software with good documentation. Link to their tutorial on how to scrape a list of URLs.

Screen scraping with Python/Scrapy/Urllib2 seems to be blocked

To help me learn Python, I decided to screen scrape the football commentaries from the ESPNFC website from the 'live' page (such as here).
It was working up until a day ago but having finally sorted some things out, I went to test it and the only piece of commentary I got back was [u'Commentary Not Available'].
Does anyone have any idea how they are doing this, and any easy and quick ways around? I am using Scrapy/Xpath and Urllib2.
Edit//
for game_id in processQueue:
data_text = getInformation(game_id)
clean_events_dict = getEvents(data_text)
break
Doesn't work the same as
i = getInformation(369186)
j = getEvents(i)
In the first sample, processQueue is a list with game_ids in. The first one of these is given to the script to start scraping. This is broken out of before it has a chance to move on to another game_id
In the second sample I use a single game id.
The first one fails and the second one works and I have absolutely no idea why. Any ideas?

There's a few things you can try, assuming you can still access the data from your browser. Bear in mind, however, that web site operators generally are within their rights to block you; this is why projects that rely on the scraping of a single site are a risky proposition. Here they are:
Delay a few seconds between each scrape
Delay a random number of seconds between each scrape
Accept cookies during your scraping session
Run JavaScript during your session (not possible with Scrapy as far as I know)
Share the scraping load between several IP ranges
There are other strategies which, I generally argue, are less ethical:
Modify your User Agent string to make your scraper look like a browser
I suggest in this answer here that scrapers should be set up to obey robots.txt. However, if you program your scraper to be well-behaved, site operators will have fewer reasons to go to the trouble of blocking you. The most frequent errors I see in this Stack Overflow tag are simply that scrapers are being run far too fast, and they are accidentally causing a (minor) denial of service. So, try slowing down your scrapes first, and see if that helps.

Parsing from a website -- source code does not contain the info I need

I'm a little new to web crawlers and such, though I've been programming for a year already. So please bear with me as I try to explain my problem here.
I'm parsing info from Yahoo! News, and I've managed to get most of what I want, but there's a little portion that has stumped me.
For example: http://news.yahoo.com/record-nm-blaze-test-forest-management-225730172.html
I want to get the numbers beside the thumbs up and thumbs down icons in the comments. When I use "Inspect Element" in my Chrome browser, I can clearly see the things that I have to look for - namely, an em tag under the div class 'ugccmt-rate'. However, I'm not able to find this in my python program. In trying to track down the root of the problem, I clicked to view source of the page, and it seems that this tag is not there. Do you guys know how I should approach this problem? Does this have something to do with the javascript on the page that displays the info only after it runs? I'd appreciate some pointers in the right direction.
Thanks.

The page is being generated via JavaScript.
Check if there is a mobile version of the website first. If not, check for any APIs or RSS/Atom feeds. If there's nothing else, you'll either have to manually figure out what the JavaScript is loading and from where, or use Selenium to automate a browser that renders the JavaScript for you for parsing.

Using the Web Console in Firefox you can pretty easily see what requests the page is actually making as it runs its scripts, and figure out what URI returns the data you want. Then you can request that URI directly in your Python script and tease the data out of it. It is probably in a format that Python already has a library to parse, such as JSON.
Yahoo! may have some stuff on their server side to try to prevent you from accessing these data files in a script, such as checking the browser (user-agent header), cookies, or referrer. These can all be faked with enough perseverance, but you should take their existence as a sign that you should tread lightly. (They may also limit the number of requests you can make in a given time period, which is impossible to get around.)