This web application analyzes a user's twitter account and displays various visualizations. It is made using tweepy api, plotly, flask and implementeed on heroku.
Installing tweepy, the twitter api for python.
pip install tweepy
Installing plotly, a powerful visualization tool.
pip install plotly
You also need to create a Twitter Developer account and get consumer key and access token.
The tweepy.API.user_timeline() function returns the last 20 tweets of a user. To get more tweets, we need to use the tweepy.Cursor() function.
The user_timeline() function returns a list of Status objects. The Status object contains a json element which has all the data related to the particular tweet.
For this application, we will use the text, source, created_at, lang, retweeted, is_quote_status and in_reply_to_screen_name attributes of the status object.
This application uses plotly to visualize the data gethered from the twitter api.
We need to convert the plotly graph to json and use the Plotly javascript to display the visualizations in the html file.
To deploy the application on heroku, we need to create a free heroku account first. A useful tutorial to get started wih heroku can be found here.
Once, heroku is set up and all the files needed to deply the app on heroku are ready, use the following commands to deply the app.
> heroku create
> git push heroku master
> heroku ps:scale web=1
> herou open