**Note**: The first time you start your stack, it might take a minute for it to be ready. While the backend waits for the database to be ready and configures everything. You can check the logs to monitor it.
If your Docker is not running in `localhost` (the URLs above wouldn't work) check the sections below on **Development with Docker Toolbox** and **Development with a custom IP**.
#### Deploy the stack locally
If you want to run the docker stack locally on swarm
During development, you can change Docker Compose settings that will only affect the local development environment, in the file `docker-compose.override.yml`.
The changes to that file only affect the local development environment, not the production environment. So, you can add "temporary" changes that help the development workflow.
For example, the directory with the backend code is mounted as a Docker "host volume", mapping the code you change live to the directory inside the container. That allows you to test your changes right away, without having to build the Docker image again. It should only be done during development, for production, you should build the Docker image with a recent version of the backend code. But during development, it allows you to iterate very fast.
There is also a command override that runs `/start-reload.sh` (included in the base image) instead of the default `/start.sh` (also included in the base image). It starts a single server process (instead of multiple, as would be for production) and reloads the process whenever the code changes. Have in mind that if you have a syntax error and save the Python file, it will break and exit, and the container will stop. After that, you can restart the container by fixing the error and running again:
```console
$ docker-compose up -d
```
There is also a commented out `command` override, you can uncomment it and comment the default one. It makes the backend container run a process that does "nothing", but keeps the container alive. That allows you to get inside your running container and execute commands inside, for example a Python interpreter to test installed dependencies, or start the development server that reloads when it detects changes, or start a Jupyter Notebook session.
To get inside the container with a `bash` session you can start the stack with: