This project is intended to help you tie together some important concepts and technologies from the 12-day course, including Git, Flask, JSON, Pandas, Requests, Heroku, and Bokeh for visualization.
The repository contains a basic template for a Flask configuration that will work on Heroku.
A finished example that demonstrates some basic functionality.
-
Git clone the existing template repository.
-
Procfile
,requirements.txt
,conda-requirements.txt
, andruntime.txt
contain some default settings. -
There is some boilerplate HTML in
templates/
-
Create Heroku application with
heroku create <app_name>
or leave blank to auto-generate a name. -
(Suggested) Use the conda buildpack. If you choose not to, put all requirements into
requirements.txt
heroku config:add BUILDPACK_URL=https://github.com/kennethreitz/conda-buildpack.git
-
Question: What are the pros and cons of using conda vs. pip?
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Deploy to Heroku:
git push heroku master
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You should be able to see your site at
https://<app_name>.herokuapp.com
-
A useful reference is the Heroku quickstart guide.
- Use the
requests
library to grab some data from a public API. This will often be in JSON format, in which casesimplejson
will be useful. - Build in some interactivity by having the user submit a form which determines which data is requested.
- Create a
pandas
dataframe with the data.
- Create a Bokeh plot from the dataframe.
- Consult the Bokeh documentation and examples.
- Make the plot visible on your website through embedded HTML or other methods - this is where Flask comes in to manage the interactivity and display the desired content.
- Some good references for Flask: This article, especially the links in "Starting off", and this tutorial.