The following guide utilizes docker and docker-compose to run select services required for Studio to function. It's our recommended setup. However, if you would rather install these services on your host, please follow the host-setup guide.
Note: If you are developing on Windows, it is recommended to use WSL (Windows Subsystem for Linux). Please follow the WSL setup guide for detailed instructions.
For detailed instructions on installing and configuring Volta, pyenv, and pyenv-virtualenv, please see the Prerequisites section in our Local Development with host guide.
For complete instructions on installing Python 3.10.13, creating and activating the virtual environment, and installing Studio’s Python dependencies, please refer to the Build Your Python Virtual Environment section in our Local Development with host guide.
If you run into an error with pip install
related to the grcpio
package, it is because it currently does not support M1 with the version for grcpio
Studio uses. In order to fix it, you will need to add the following environmental variables before running pip install
:
export GRPC_PYTHON_BUILD_SYSTEM_OPENSSL=1
export GRPC_PYTHON_BUILD_SYSTEM_ZLIB=1
export CFLAGS="-I/opt/homebrew/opt/openssl/include"
export LDFLAGS="-L/opt/homebrew/opt/openssl/lib"
The project requires Node 16.X
as the runtime and Yarn >= 1.22.22
as the package manager. We make use of Volta
to manage the same automatically. Please make sure you have volta installed and your shell configured to use volta. You can then install all the dependencies by running:
yarn install
Studio requires some background services to be running:
- Minio - a local S3 storage emulation
- PostgreSQL (postgres) - a relational database
- Redis - a fast key/value store useful for caching
- Celery - the task manager and executor, which relies on the Studio codebase
Generally speaking, you'll want to open a separate terminal/terminal-tab to run the services. With docker and docker-compose installed, running the above services is as easy as:
make run-services
The above command may take longer the first time it's run. It includes starting the celery
workers, and the other dependent services through docker, which can be done separately with the following two commands:
make dcservicesup
make devceleryworkers
To confirm that docker-based services are running, you should see three containers when executing docker ps
. For example:
> docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
e09c5c203b93 redis:6.0.9 "docker-entrypoint.s…" 51 seconds ago Up 49 seconds 0.0.0.0:6379->6379/tcp studio_vue-refactor_redis_1
6164371efb6b minio/minio "minio server /data" 51 seconds ago Up 49 seconds 0.0.0.0:9000->9000/tcp studio_vue-refactor_minio_1
c86bbfa3a59e postgres:12.10 "docker-entrypoint.s…" 51 seconds ago Up 49 seconds 0.0.0.0:5432->5432/tcp studio_vue-refactor_postgres_1
To stop the services, press Ctrl + C in the terminal where you ran make run-services
(or dcservicesup
). Once you've done that, you may run the following command to remove the docker containers (they will be recreated when you run run-services
or dcservicesup
again):
make dcservicesdown
With the services running, in a separate terminal/terminal-tab, we can now initialize the database for Studio development purposes. The command below will initialize the database tables, import constants, and a user account for development:
yarn run devsetup
With the services running, in a separate terminal/terminal-tab, and the database initialized, we can start the dev server:
yarn run devserver:hot # with Vue hot module reloading
# or
yarn run devserver # without hot module reloading
Either of the above commands will take a few moments to build the frontend. When it finishes, you can sign in with the account created by the yarn run devsetup
command:
- url:
http://localhost:8080/accounts/login/
- username:
[email protected]
- password:
a
Studio uses celery
for executing asynchronous tasks, which are integral to Studio's channel editing architecture. The celery service does not reload when there are Python changes like the Django devserver does, so it's often preferred to run it separately. If you are developing changes against a task or the celery configuration, you'll need to use make dcservicesup
to run only the docker-based services.
In a separate terminal/terminal-tab, run the following to start the service and press Ctrl + C to stop it:
make devceleryworkers
Stop and restart the above to reload your changes.