refactoring-exercise.md

clean-code-ml refactoring exercise

Pre-workshop setup

Please ensure you have the following:

• a GitHub account
• a CircleCI account
• an IDE (VS Code or PyCharm)
• Windows users:
  • Download Git Bash

Getting started

1. Fork repo
2. Clone repository: git clone https://github.com/YOUR_USERNAME/clean-code-ml
3. Run bin/setup.sh. This will install miniconda3 if it's not already installed, and install project-level dependencies specified in ./environment.yml

You're ready to roll! Here are some common commands that you can run in your dev workflow.

# activate virtual environment
source activate clean-code-ml

# deactivate virtual environment
conda deactivate

# run unit tests
nosetests

# run unit tests in watch mode and color output
nosetests --with-watch --rednose --nologcapture

# start jupyter notebook server
jupyter notebook
# Now you can visit localhost:8888 on your browser.

IDE configuration

Configure your IDE to use ~/miniconda3/envs/clean-code-ml/bin/python as the Python interpreter. Here are the instructions on how to do that in VS Code and PyCharm.

Once you've done that, you should be able to:

1. Get helpful auto-complete suggestions in your IDE as you type. If somehow that's not showing up, try restarting your code editor.
2. Let your IDE auto-format your code in a file. We've installed autopep8 using conda, and now your IDE can help you with the auto-formatting)
   • To do this in VS Code, hit Shift + ⌘ + F
3. Use other tools provided by your IDE.
   • For VS Code, hit F1 and type 'Python Refactor' and you can experiment with any of these commands (e.g. 'Sort Imports')

Attributions

The notebook which we use for the starting point of our refactoring exercise was adapted/modified from a Kaggle submission for the titanic competition.