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Bandersnatch Project

Read the Documentation for information on how to get started.

Deployed App

Tech Stack

  • Logic: Python3
  • API Framework: Flask
  • Templates: Jinja2
  • Structure: HTML5
  • Styling: CSS3
  • Database: MongoDB
  • Graphs: Altair
  • Machine Learning: Scikit
  • Hosting: Heroku

Provided Code

  • HTML Templates
  • CSS Styles
  • API Framework
  • Miscellaneous Helper Files
  • Sprint Specific Documentation

Primary Features by URL

  • /: Splash Page
  • /data: Tabular Data
  • /view: Dynamic Visualizations
  • /model: Interactive Machine Learning Model

Primary Goals

For best results, complete each sprint in order, before going on to the next sprint.

  1. Sprint 1: Database Operations
    • Develop a database interface class
    • Create random data
    • Populate the database with at least 1000 datapoints
  2. Sprint 2: Dynamic Visualizations
    • Notebook exploration
    • Chart function
    • API integration
  3. Sprint 3: Machine Learning Model
    • Notebook exploration
    • Machine Learning interface class
    • Model serialization (save and open)
    • API model integration

Stretch Goals

  • Use ElephantSQL instead of MongoDB
  • Use Plotly instead of Altair
  • Use PyTorch instead of Scikit
  • Use FastAPI instead of Flask
  • Add the ability for the user to reset & reseed the database
  • Add the ability for the user to re-train the machine learning model
  • Add the ability for the user to download a working serialized model and dataset
  • Add authentication to sensitive pages
  • Use a different set of features to train the model
  • Use your own dataset entirely

OS Specific Notes: Gunicorn is not Windows compatible!

  • Windows users should not use the run.sh shell script, as it depends on gunicorn.
  • Windows users should use py -m app.main to start the app with Flask acting as the server.
  • Windows users may need to download the wheel for fortuna dependency. and follow its README
  • Mac and Linux users can use ./run.sh script or type the command directly python3 -m gunicorn app.main:APP.
  • Feel free to modify the shell scripts to suit your needs, these are intended to run locally.
  • In any case you should not modify the Procfile, this is the run script for the remote server.