A tool that can be used to keep track of time spent on projects.

1. Install Miniconda.

   Miniconda is the recommended environment for development. Miniconda is a minimal distribution of Conda, a cross-platform package management and environment management tool for Python projects.

2. Open a terminal and ensure the conda base environment is activated.

3. Install Anaconda Project: conda install anaconda-project

   Anaconda Project is the recommended task runner, and is installable using conda. Anaconda Project allows for multiple Conda environments to be defined in a single file, each with their own associated package dependencies. Commands can be associated with specific environments, and can be tailored to different platforms. Anaconda Project also assists with environment setup and cross-platform environment variables, among other things.

4. (Optional) Prepare the default environment: anaconda-project run install

   The default environment contains all development, debug, and testing dependencies, in addition to useful development tools (such as linters, formatters, and Jupyter Notebook).

The project is built on the Django framework. It is backed by the PostgreSQL database.

• Pass --fail-fast to fail execution immediately as soon as a test fails.
• Pass --parallel to run tests in parallel.

When starting the test server, a few useful flags:

• Pass --noinput to wipe the test database without a user prompt
• Pass --addrport to use a different port e.g. running the dev and test server side by side

For running robot:

• Pass -d to write Robot output files to a directory of your choice.
• Pass -v to pass variables to Robot.
  • -v BROWSER:<browser> will change the browser Robot uses to test the application. Examples of valid browsers are:
    • firefox
    • headlessfirefox
    • chrome
    • headlesschrome
  • -v DRIVER_SPEED_SECS:<seconds> will speed up or slow down test execution
  • -v SERVER_PORT:<port> to change the port Robot uses to access the application. Useful if running a dev and test server side-by-side.

The application-debug environment adds django-debug-toolbar to the application runtime. To use it, set the DJANGO_SETTINGS_MODULE environment variable to ProjectTime.config.settings-debug, then run the following command:

anaconda-project run --env-spec application-debug manage.py runserver

• For PyPi: anaconda-project run setup.py sdist bdist_wheel
• For Conda: anaconda-project run conda build -c conda-forge conda-recipe

When interacting with Django from a Jupyter notebook, Django must be manually configured first:

import os
import django

os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'ProjectTime.config.settings')
os.environ.setdefault('DJANGO_ALLOW_ASYNC_UNSAFE', 'true')
django.setup()