dashAI 0.2.0

Prepare the environment

1. Install the LTS node version.

2. Install Yarn package manager following the instructions located on the yarn getting started page.

3. Move to DashAI/front and Install the project packages using yarn:

$ cd DashAI/front
$ yarn install

Running the frontend

Move to DashAI/front if you are not on that route:

$ cd DashAI/front

Then, launch the front-end development server by running the following command:

$ yarn start

If you want to launch the front-end test server (without launching the backend) with dummy data, run:

$ yarn json-server

Linting and formatting

The project uses as default linter eslint with the react/recommended, standard-with-typescript` and prettier` styles.

To manually run the linter, move to DashAI/front and run:

$ yarn eslint src

The project uses prettier as default formatter.

To format the code manually, move to DashAI/front and execute:

$ yarn prettier --write src

Build the frontend

Execute from DashAI/front:

$ yarn build

Prepare the environment

First, set the python enviroment using conda:

Then, move to DashAI/back

$ cd DashAI/back

Later, install the requirements:

$ pip install pip-tools
$ pip-sync requirements.txt requirements-dev.txt

Running the Backend

There are three ways to run DashAI:

1. By executing DashAI as a module:

$ python -m DashAI

2. Or, installing the default build:

$ pip install .
$ dashai

If you chose the second way, remember to install it each time you make changes.

Setting the local execution path

With the –local-path option you can determine where DashAI will save its local files, such as datasets, experiments, runs and others. The following example shows how to set the folder in the local .DashAI directory:

$ python -m DashAI --local-path "~/.DashAI"

Setting the logging level

Through the –logging_level parameter, you can set which logging level the DashAI backend server will have.

$ python -m DashAI --logging-level INFO

The possible levels available are: DEBUG, INFO, WARNING, ERROR, CRITICAL.

Note that the –logging-level not only affects the DashAI loggers, but also the datasets (which is set to the same level as DashAI) and the SQLAlchemy (which is only activated when logging level is DEBUG).

Checking Available Options

You can check all available options through the command:

$ python -m DashAI --help

Execute tests

DashAI uses pytest to perform the backend tests. To execute the backend tests

1. Move to DashAI/back

$ cd DashAI/back

2. Run:

$ pytest tests/

Linting and formatting

The project uses as default backend linter ruff:

To manually run the linter, move to DashAI/back and execute:

$ ruff .

The project uses black as default formatter.

To manually format the code, move to DashAI/back and execute:

$ black .