1.4 Development tool installation

Many of the projects in this book are focused on data analysis. The tooling for data analysis is often easiest to install with the conda tool. This isn’t a requirement, and readers familiar with the PIP tool will often be able to build their working environments without the help of the conda tool.

We suggest the following tools:

• Conda for installing and configuring each project’s unique virtual environment.

• Sphinx for writing documentation.

• Behave for acceptance tests.

• Pytest for unit tests. The pytest-cov plug-in can help to compute test coverage.

• Pip-Tool for building a few working files from the pyproject.toml project definition.

• Tox for running the suite of tests.

• Mypy for static analysis of the type annotations.

• Flake8 for static analysis of code, in general, to make sure it follows a consistent style.

One of the deliverables is the pyproject.toml file. This has all of the metadata about the project in a single place. It lists packages...