Problem Solving with Algorithms and Data Structures using Python

By Brad Miller and David Ranum, Luther College.

Textbook provided for free by Runestone Academy. Consider supporting them.

Project Setup

Jupyter Notebooks (*.ipynb files)

If you don't yet have an environment to run jupyter notebooks, you may choose to install miniconda. You can follow the instructions from Vancouver DataJam which will include installing the libraries needed for some of my solutions to the exercises (e.g. pandas, matplotlib).

After conda is installed, terminals will have the conda base environment activated by default. To disable this behaviour, run conda config --set auto_activate_base false.

Opening the Jupyter Notebooks

1. Activate the conda base environment, if not yet activated: conda activate
2. Run jupyter notebook
3. Navigate to the location of the notebook you want to open!
   • Searching the internet for jupyter notebook basics will give you lots of resources to get started on Jupyter notebooks.
4. When you're done, press Control-C to stop the notebook server
5. Deactivate conda: conda deactivate

Virtual Environment

You don't need to use virtual environments to run the solutions as long as you have python paths set up, and the necessary packages installed (e.g. pytest if you are interested in running the tests)

I'm using a virtual environment because I prefer not to use a global installation of pytest, which is what I use to run my tests.

Workflow with the Virtual Environment

1. Create a virtual environment: `virtualenv --prompt "(pythonds3) " .venv

2. Activate environment: source .venv/bin/activate

3. pip-install all the things

   • pip install [package] OR
   • pip install -r requirements.txt

4. (noting for my own sake) After installing new packages, export current environment configuration file: pip freeze > requirements.txt

5. Deactivate environment: deactivate

Tests

I use pytest to run my tests.