You can use this library to get the text of any user's Tweets trivially.
Very useful for making markov chains.
>>> from twitter_scraper import get_tweets >>> for tweet in get_tweets('kennethreitz', pages=1): >>> print(tweet['text']) P.S. your API is a user interface s3monkey just hit 100 github stars! Thanks, y’all! I’m not sure what this /dev/fd/5 business is, but it’s driving me up the wall. …
It appears you can ask for up to 25 pages of tweets reliably (~486 tweets).
If you're interested in financially supporting Kenneth Reitz open source, consider visiting this link. Your support helps tremendously with sustainability of motivation, as Open Source is no longer part of my day job.
First, install markovify:
$ pipenv install markovify
>>> import markovify >>> tweets = '\n'.join([t['text'] for t in get_tweets('kennethreitz', pages=25)]) >>> text_model = markovify.Text(tweets) >>> print(text_model.make_short_sentence(140)) Wtf you can’t use APFS on a prototype for “django-heroku”, which does a lot out of me.
$ pipenv install twitter-scraper
Only Python 3.6+ is supported
$ python test.py