GDPractice is a complete solution for creating interactive coding practices in the Godot engine.
After iterating over solutions for interactive practices, which we first open-sourced in Learn GDScript from Zero, we went back to the drawing board to create a more robust and flexible solution with Godot 4. GDPractice is the result of that work. It's already used in Learn 2D Gamedev From Zero with Godot 4 to teach game development to high school students and aspiring developers worldwide.
- Requirements and checks: You can register requirements and checks to validate the user's work. Requirements are prerequisites needed for your practice tests to run that help avoid errors if learners remove or rename properties, functions, etc. Checks are the actual tests that validate the user's work. The framework provides a simple API to create common checks and requirements.
- Test space: To make practices suitable for teaching gamedev, writing unit tests that check the learner's code is not enough. A lot of production game code is not designed to be testable with unit tests. What if you want to check that the player is looking at the mouse each frame or that entering an area triggers a particular animation? GDPractice allows you to apply parameters of the learner's code to the solution at runtime, capture state from both the solution and the practice copy, and compare the two over time to validate the learner's work.
- Simulate and display simulated input: You can simulate input events required to test the user's work deterministically*. GDPractice captures these events and displays them to the learner.
- Build system:
- The framework generates practice starter files based on the solution, so there's a single source of truth for each practice. It supports diffing scenes, scripts, and other resources.
- You can generate two projects from a single Godot project: a workbook project for the user to complete the practices and a solution project with the correct solutions. It allows teachers to control the solutions and distribute the workbook projects to students.
- Change any project settings when generating workbook projects. For example, you can remove all input actions from the workbook project if the practice requires the learner to create them.
- Hides addon files: GDPractice hides the addons/ and other files from the user in the workbook project to offer them a more streamlined experience browsing the project. The files are hidden from the FileSystem dock and quick picker dialogs.
* Note that the practices' behavior can vary a little depending on the system, the learner's framerate, and input devices.
You can copy three of the addons/ in this repository to your project to use GDPractice:
addons/gdpractice/
addons/gdquest_sparkly_bag
addons/gdquest_theme_utils
The first addon is the framework itself, and the last two are little code libraries used by GDPractice and some other open-source technologies we maintain, like GDTour, the interactive Godot tutorial framework.
The repository also comes with gdplug, a powerful tool to manage add-ons in your Godot projects and download them from open-source repositories. You can use it to add GDPractice or any other Godot addon to your project. First, copy the addons/gdplug/
folder to your project, then create a file named plug.gd
at the root of your Godot project with the following content:
#!/usr/bin/env -S godot --headless --script
extends "res://addons/gd-plug/plug.gd"
func _plugging() -> void:
plug(
"[email protected]:GDQuest/GDPractice.git",
{include = ["addons/gdpractice", "addons/gdquest_sparkly_bag", "addons/gdquest_theme_utils"]},
)
Then, run the following command in your terminal to download the addons:
godot --headless --script plug.gd update
Due to our current workload, we still have limited documentation for GDPractice. However, several example practices are in the practice_solutions/
folder of this repository.
A limitation of Godot is that we do not have a great system to register entry points or hooks to tell an add-on what configuration to use. So we rely on having GDScript files at specific paths to make GDPractice work:
res://practice_solutions/metadata.gd
: This file should extend theres://addons/gdpractice/metadata.gd
class. It's used to register and list the practices in your project.res://practice_solutions/build_settings.gd
: This file is optional. It's used to override the default build settings. Open theres://addons/gdpractice/build_settings.gd
file to see the available settings you can override.res://practice_solutions/diff.gd
: This file is optional. It's used to edit the project settings at build time. For example, you can remove all input actions from the workbook project if the course or some practices require students to create them.
To build the workbook and solution projects, you can use the build.gd
script in the res://addons/gdpractice/
folder. Run the script with godot --headless --script addons/gdpractice/build.gd -- --help
to get its documentation and all the options.
To build, and for practices to work, the system requires you to create a practice metadata file at the path res://practice_solutions/metadata.gd
. This file should extend the class res://addons/gdpractice/metadata.gd
.
You can control the settings applied at build time by creating a file named res://practice_solutions/build_settings.gd
. This file should extend the res://addons/gdpractice/build_settings.gd
class.
Open the res://addons/gdpractice/build_settings.gd
file to see the available settings you can override.
You can edit the project settings (the project.godot
file) at build time by creating a script named diff.gd
in the res://practice_solutions/
folder.
This is useful for removing or adding input actions, changing the project's main scene, or changing the project settings in the workbook and solution projects.
The project settings are used as the reference for the solution project, and the diff.gd
script is applied when generating the workbook project.
For example, this code snippet removes all input actions from the workbook, except for the ui_*
actions included by default by Godot.
static func edit_project_configuration() -> void:
const INPUT_KEY := "input/%s"
for action in InputMap.get_actions():
if action.begins_with("ui"):
continue
ProjectSettings.set_setting(INPUT_KEY % action, null)
ProjectSettings.save()
Every practice has a script named test.gd that extends the built-in script tester/test.gd. This script is responsible for running the practice tests. The test.gd script exposes a few virtual functions it calls in preparation before running the checks.
The testing system waits for nodes in the tree to be ready before running the tests. It ensures that the practice and solution are initialized before collecting data.
The system runs the following functions in order and in relatively rapid succession:
_build_requirements()
: checks pre-requisites before running other functions._setup_state()
: used to harmonize the properties of the student practice and solution scene._setup_populate_test_space()
: used to collect data from the running practice and solution scene._build_checks()
: creates unit tests used to test student code.
Here's some more detail. Two functions are provided to build requirements and checks:
_build_requirements()
: This function is called before the practice starts running. It should check if the practice has all the necessary variables, functions, signal connections, and so on to run without errors. For example, you can use this to check if a node or property exists in the student practice so that you can safely access it without error later on. If the requirements are not met, the other functions will not run to avoid errors. To add requirements, addRequirement
objects to therequirements
array._build_checks()
: This function is called after the practice has run for a moment. It should be used to check if the practice is behaving as expected. If the checks fail, the practice will be marked as failed. To add checks, createCheck
objects and add them to thechecks
array.
Two functions allow the practice system to capture data from the practice and solution:
_setup_state()
: This async function is called before the practice starts running, once all nodes are ready in the scene tree. It should be used to copy the state of the practice to the solution. Use this to ensure that the practice and solution start with the same properties. For example, you can copy the speed or health of a character from the practice to the solution._setup_populate_test_space()
: This async function is called right after_setup_state()
. It should be used to capture data from the practice and solution. Use this to collect the state of the practice and the solution during the practice. For example, you can capture the position of a character in the practice and solution to compare them later.
The two functions above run one after the other and are separated just for conceptual clarity.
The needs of practice tests are very different, so the data you collect and how you collect it is entirely up to you. You collect all the data you need in _setup_populate_test_space()
. You can store the data however you want, though I recommend using the provided _test_space
array. Some helper functions in the Test
class make it easier to check the data later on.
To store data from multiple frames, use await
in the _setup_populate_test_space()
function. This will allow you to run code over multiple frames. For example, you can use the following code to store the position of a character in the practice and solution over ten frames:
func _setup_populate_test_space() -> void:
for i in range(10):
var data := {
"practice_global_position": _practice.global_position,
"solution_global_position": _solution.global_position
}
_test_space.append(data)
await get_tree().physics_frame
I prefer using an inner class to store the data, to get static typing, and to make it easier to access the data later on. Here's the same example using an inner class:
class TestData:
var practice_global_position := Vector2.ZERO
var solution_global_position := Vector2.ZERO
func _setup_populate_test_space() -> void:
for i in range(10):
var data := TestData.new()
data.practice_global_position = _practice.global_position
data.solution_global_position = _solution.global_position
_test_space.append(data)
await get_tree().physics_frame
Alternatively, the test script provides the method _connect_timed()
to collect data over some time. Here's a typical example: collecting frame data over one second:
func _setup_populate_test_space() -> void:
await _connect_timed(1.0, get_tree().process_frame, _populate_test_space)
func _populate_test_space() -> void:
var data := TestData.new()
data.practice_global_position = _practice.global_position
data.solution_global_position = _solution.global_position
_test_space.append(data)
One key difference between game dev practices and usual interactive programming exercises is that we simulate player input and need to ensure that the student code accounts for this input.
Godot has two main ways to check for player input:
- Polling in the
_process()
and_physics_process()
functions. - Using the
_input()
functions with input events.
Similarly, we use two different approaches to inject and simulate inputs depending on the approach used by the practice:
- Polling: We can simulate player input in the processing loop by calling
Input.action_press()
andInput.action_release()
. - Input events: We can simulate player input by creating an
InputEvent
object and callingInput.parse_input_event()
.
The following example simulates the player moving to the right for 0.3 seconds and collecting data in the test space.
func _setup_populate_test_space() -> void:
Input.action_press("move_right")
await _connect_timed(0.3, get_tree().process_frame, _populate_test_space)
Input.action_release("move_right")
func _populate_test_space() -> void:
_test_space.append({
"practice_position": _practice.position,
"solution_position": _practice.position,
})
For input events, it's different as we need to create an InputEvent
object and call Input.parse_input_event()
. We use them more for one-time events like mouse clicks or key presses. Here's an example of simulating pressing the space bar:
func _setup_populate_test_space() -> void:
var event = InputEventKey.new()
event.scancode = KEY_SPACE
event.pressed = true
Input.parse_input_event(event)
# ... collect data
In some cases, the instantiated scenes in the workbook project practices may appear to point to the solution scenes instead of the files in the res://practices/
folder.
This can be due to a cache problem in the Godot editor. To fix this, you can try the following:
- Close the Godot editor.
- Delete the
.godot/
folder in the project directory. - Open the Godot editor and reload the project.
You can also open the .tscn
files of generated practices in a text editor and ensure the paths to the scenes are correct.