Data Visualization DSL

Access the powerful data-processing and visualization capabilities of the python ecosystem as well as programmatic dynamic updating using a friendly syntax.

Development

Getting started

In order to start developing the project, follow these simple steps:

1. Clone the repository if you haven't already
2. In the root project directory, run make init (Make should be installed). Follow the output of this script closely and make sure you perform and required actions.
3. When this is done, you should have a Python virtual environment set up directly in the project. You can use the command make run to run the main program.
4. Have fun!

JetBrains IDE setup (Tested for IntelliJ)

It might be useful to run, test, and debug the program through the IDE. To set up JetBrains configurations with the correct environment, follow these steps:

1. Open the project normally in the IDE.
2. In project structure (File > Project Structure on Mac), go to the SDKs tab under Platform Settings.
3. Click the + button to add an SDK. Select "Add Python SDK".
4. From the list of options, select "Pipenv Environment". Check that the base interpreter path points to a valid Python 3.8 installation, and "Install packages from Pipfile" is checked. Click OK and wait for the process to complete.
5. Go to the Project tab and make sure Project SDK is set to "Pipenv (cpsc410_project1_team17) Python 3.8.5". In Modules , click cpsc410_project1_team17. In the Dependencies tab, make sure Module SDK is set to "Project SDK Pipenv ". Click OK.
6. When editing a Python file, if you see an option to "Use Pipenv Interpreter", click it, and click install from Pipfile.

Create a run configuration

1. Click "ADD CONFIGURATION". Click + and select "Python" from the list.
2. Call the configuration "Main". For the main script, select main.py in the root project directory. Check the box for "Use SDK of module" (the module should be cpsc410_project1_team17). Click OK.

Create a testing configuration

1. Click "ADD CONFIGURATION". Click + and select "Python tests / Unittests" from the list.
2. Call the configuration "Tests" and select "Custom" as the target.
3. In the Additional Arguments field, past the following:

discover -s tests -p "test_*.py"

Choose to use the SDK of the main module as before. Click OK.

FAQ

1. How do I add source code?

   Simply edit or add python files to those found in the code directory.

2. How do I add tests?

   Add test cases to the files in the test directory where appropriate. See the unittest docs for more info. If you need to add a new test file, it should be placed directly in the tests directory and have a name starting with "test_".

3. How do I add dependencies?

   Ideally, consult with the team and Dev Lead first. To add to the project, run pipenv install <package> from the root directory and make sure everybody runs make-update upon getting the new Pipfile.

4. What tools do we use? Python (obviously) for our central logic, numpy for numerical computations, PyQtGraph for visualization.

Git Procedure:

• Create new branches for functionality that you're working on
• Commit and push to the branch (make sure you run tests first!)
• Create a pull request to master when you're ready
  • Try to keep pull requests small
  • Squash commits into one if your pull request includes multiple
  • Pull requests require at least one approver to be merged in