## Summary
- Created app dirs and set as constants in the top-level init.
- Renamed _config_values_main to training_config.py and renamed the ConfigValuesMain class to TrainingConfig.
- Moved training_config.py to src/primaite/config/training_config.py
- Renamed all training config yaml file keys to make creating an instance of TrainingConfig easier.
- Moved action_type and num_steps over to the training config.
- Decoupled the training config and lay down config.
- Refactored main.py so that it can be ran from CLI and can take a training config path and a lay down config path.
- Refactored all outputs so that they save to the session dir.
- Added some necessary setup scripts that handle creating app dirs, fronting example config files to the user, fronting demo notebooks to the user, performing clean-up in between installations etc.
- Added functions that attempt to retrieve the file path of users example config files that have been fronted by the primaite setup.
- Added logging config and a getLogger function in the top-level init.
- Refactored all logs entries logged to use a logger using the primaite logging config.
- Added basic typer CLI for doing things like setup, viewing logs, viewing primaite version, running a basic session.
- Updated test to use new features and config structures.
- Made tests log to temp directory
- typer==0.9.0 added to pyproject.toml
- Refactored documentation and included APi docs, dependencies.
- Make files now re-build autosummary and deps file.
- Added typer and platformdirs to deps in pyproject.toml.
- Made root_is_pure = True in setup.py as platform/python specific wheels don't need to be built but the option is there should we need to.
## Test process
- Added an e2e test for primaite.main.run func.
- Added legacy config file conversion tests
- added
## Checklist
- [X] This PR is linked to a **work item**
- [X] I have performed **self-review** of the code
- [X] I have written **tests** for any new functionality added with this PR
- [X] I have updated the **documentation** if this PR changes or adds functionality
- [X] I have run **pre-commit** checks for code style
Related work items: #915
## Summary:
Split the ticket into two task
Task 1: Fixed the resetting operating state to set compromised or overwhelmed services or operating system back to a good state. Added a reset count that switches the node into a good state.
Task 2: Created a "SHUTTING DOWN" operating state to last for a (configurable) and a "BOOTING" operating state to last for a (configurable).
## Test process
First test was to test the reset changes the node to a good state when its set to a COMPROMISED state. The last two test makes sure that the node boots and shutdowns correctly.
## Checklist
- [x] This PR is linked to a **work item**
- [x] I have performed **self-review** of the code
- [x] I have written **tests** for any new functionality added with this PR
- [x] I have updated the **documentation** if this PR changes or adds functionality
- [x] I have run **pre-commit** checks for code style
Related work items: #898, #1438
## Summary
This PR implements a new module called `observations` within `primaite.environment`.
The module is able to keep track of the observation space and to generate observations for the blue agent. It builds the observation space from components. Each component can be configured by supplying parameters at instantiation. For example, the Link Traffic Levels component lets the user customise how many levels there should be.
Note: If a space contains multiple components, they are combined into a 'gym.spaces.Tuple' Space. This is not compatible with some learning agents so we may need to add the options to flatten the observation space.
## Test process
I was able to run the main script with a single-component obs space. I also wrote several unit and integration tests for the new functionality.
## Checklist
- [x] This PR is linked to a **work item**
- [x] I have performed **self-review** of the code
- [x] I have written **tests** for any new functionality added with this PR
- [x] I have updated the **documentation** if this PR changes or adds functionality
- [x] I have run **pre-commit** checks for code style
If you review this, please check the linked tickets and make sure you agree that this PR addresses them fully.
Related work items: #886, #924, #1468, #1469
## Summary
To do this, I have altered `primaite_env` to add the changes from ADSP branch for implementing the `ANY` action space.
It impacts `NODE` and `ACL` action spaces in `primaite_env.py` as all three of them are now discrete action spaces, using dictionary keys to represent different valid actions a node can take on each step.
Previously they were multi-discrete where a single action would look like this `[1,2,1,0]`.
Now an action looks like this, a dictionary entry `{.. 5: [1,2,1,0] ... }` whereby the new action is `5` for example.
It changes the `enums.py` where I added the `ANY` into `ActionType`.
I have also added a package from the ADSP branch agents to add the file utils.py. The file contains functions used by primaite_env.py to decide and check valid actions a node can take and removes the ones which are unnecessary and invalid. This is done for all three types, `NODE`, `ACL` and `ANY`.
## Test process
I have written an unit test in `test_single_action_space.py` which checks the new action space for an `ANY` laydown config has both types of actions in the `action_space` dictionary stored by the environment.
I have written an integration tests to check an agent is carrying out both `NODE` and `ACL` actions in a single episode, where I have hard coded the agent to do two specific things on two different steps.
On one step, I tell the `computer_1` node to turn off one of the nodes and on the other step it creates an ACL rule denying communication between `computer_1` and `switch_1` nodes.
## Checklist
- [X] This PR is linked to a **work item**
- [X] I have performed **self-review** of the code
- [X] I have written **tests** for any new functionality added with this PR
- [X] I have updated the **documentation** if this PR changes or adds functionality
- [X] I have run **pre-commit** checks for code style
Related work items: #893, #1429
- make files now re-build autosummary and deps file.
- Added typer and platformdirs to deps in pyproject.toml.
- Made root_is_pure = True in setup.py as platform/python specific wheels don't need to be built but the option is there should we need to.
-
Added an e2e test for primaite.main.run func.
- renamed _config_values_main to training_config.py and renamed the ConfigValuesMain class to TrainingConfig.
Moved training_config.py to src/primaite/config/training_config.py
- Renamed all training config yaml file keys to make creating an instance of TrainingConfig easier.
Moved action_type and num_steps over to the training config.
- Decoupled the training config and lay down config.
- Refactored main.py so that it can be ran from CLI and can take a training config path and a lay down config path.
- refactored all outputs so that they save to the session dir.
- Added some necessary setup scripts that handle creating app dirs, fronting example config files to the user, fronting demo notebooks to the user, performing clean-up in between installations etc.
- Added functions that attempt to retrieve the file path of users example config files that have been fronted by the primaite setup.
- Added logging config and a getLogger function in the top-level init.
- Refactored all logs entries logged to use a logger using the primaite logging config.
- Added basic typer CLI for doing things like setup, viewing logs, viewing primaite version, running a basic session.
- Updated test to use new features and config structures.
- Began updating docs. More to do here.
This PR fixes some minor issues that I found in the main.py script. Namely:
1. The first observation was always all zeroes when using a generic agent. This is because the `update_environment_obs()` method is not called automatically and is only called by `env.reset()`.
2. The config yaml is never closed as the close function of the file reader was only referenced but never called.
Related work items: #1441
Check out the linked bug ticket to understand the issue.
The fix was very simple- just changing which variable is passed to the reward calculation funciton.
Related work items: #1442
