In my current project I had a task to use twitter API. Twitter uses OAuth for authentication, which is pretty dreary. To avoid fiddling with it all the time, I've moved authentication to decorator, now it looks like this:
@twitter_api
def tweet_hello(request, api):
api.update_status('hello')# ...Decorator checks if key is available, and, if needed - initiates authentication. User is redirected to twitter, grants permission and is redirected back to site, to the same place where he left off. If key is available - nothing happens, just view is launched as usual.
It's convenient that there's no need for additional twitter settings in user profile.
tweepy is used as an API wrapper.
def twitter_api(view):
def wrapped(request, args, *kwargs):
callback_url = absolute_url(oauth_endpoint)
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET, callback_url)
if 'twitter_access_token' in request.session:
key, secret = request.session['twitter_access_token']
auth.set_access_token(key, secret)
return view(request, api=tweepy.API(auth), *args, **kwargs)
request.session['twitter_action'] = request.path
redirect_url = auth.get_authorization_url()
request.session['twitter_request_token'] = (auth.request_token.key, auth.request_token.secret)
return redirect(redirect_url)
return wrapped
def oauth_endpoint(request):
callback_url = absolute_url(oauth_endpoint)
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET, callback_url)
key, secret = request.session.pop('twitter_request_token')
auth.set_request_token(key, secret)
verifier = request.REQUEST.get('oauth_verifier')
auth.get_access_token(verifier)
request.session['twitter_access_token'] = (auth.access_token.key, auth.access_token.secret)
return redirect(request.session.pop('twitter_action'))- of course, you need to wrap everything in try..except blocks and process errors accordingly
absolute_urlshould return full url, with http://- apart from
request.pathyou can also storePOSTandGET. - path can be passed as an argument to
callback_url
Subscribe for the news and updates
Test analysis is an essential and crucial activity in the testing process. A well-organized test analysis provides an adequate level of confidence in the overall effectiveness of the testing and contributes to the delivery of high-quality software.
We have reviewed the top web frameworks for server and client-side development and compared their pros and cons. Find out which one can be a great fit for your next project.
Django ORM is a very abstract and flexible API. But if you do not know exactly how it works, you will likely end up with slow and heavy views, if you have not already. So, this article provides practical solutions to N+1 and high loading time issues. For clarity, I will create a simple view that demonstrates common ORM query problems and shows frequently used practices.
Learn how to use "OR" and "AND" queries efficiently in Django without using database models Q. Enhance your query-building skills. Dive in now.
It appears that not everyone knows that in python you can create classes dynamically without metaclasses. I'll show an example of how to do it.So we've learned how to use custom QuerySet to chain requests:Article.objects.old().public()Now we need to make it work for related objects:user.articles.old().public()This is done using use_for_related_fields, but it needs a little trick.
Usually users' profiles are stored in single model. When there are multiple user types, separation is made by some field like user_type.Situation is a little more complicated when different data is needed for each user type.In this article I'll describe how I solve this task.