Configure an interpreter using Docker Compose
Make sure that the following prerequisites are met:
You have a stable Internet connection.
To operate with Docker you need the busybox image be available on your machine. Ensure that you have a stable Internet connection, so that PyCharm can download and run
busybox:latest. Once you have successfully configured Docker, you can go offline.
Docker is installed. You can install Docker on the various platforms, but here we'll use the Windows installation.
Before you start working with Docker, make sure that the Docker plugin is enabled. The plugin is bundled with PyCharm and is activated by default. If the plugin is not activated, enable it on the Plugins page of the Settings/Preferences dialog Ctrl+Alt+S as described in Manage plugins.
If you are using Docker for Windows, enable the Expose daemon on tcp://localhost:2375 without TLS option in the General section of your Docker settings.
Note that you cannot install any Python packages into Docker-based project interpreters.
Preparing an example
We could have actually repeated the same example as was used for Docker, but for Docker Compose it makes no sense - too simple...
To show a realistic example of a Docker Compose application, we'll use a Django application with a PostgreSQL database running in a separate container. Get the project from GitHub, and open it in PyCharm ( ).
For this Django application, we should create two containers: one for a database, and one for the application itself. We'll use the Docker Compose to link the two containers together.
Adding files for Docker and Docker Compose
In the Project tool window, right-click the project root and choose Dockerfile) and enter the following code:Alt+Insert, enter the filename (here
Next, repeat the same steps for the docker-compose.yml file and enter the following code:
Let's look at the docker-compose.yml file. This file defines 2 services:
db, and links them together.
Now that we've prepared our example, let's configure Docker.
To do that, open Settings dialog (Ctrl+Alt+S or click on the main toolbar) and click the Docker page under the Build, Execution, Deployment node. Click to create a Docker server.
Accept the suggested default values:
For macOS, select Docker for Mac to connect to the Docker daemon.
Next, apply changes.
Configuring Docker Compose as a remote interpreter
Let's now define a remote interpreter based on Docker-Compose.
Ensure that you have downloaded and installed Python on your computer.
Open the Add Python Interpreter dialog by either way:
When you're in the Editor, the most convenient way is to use the Python Interpreter widget in the . Click the widget and select
If you are in the Settings/Preferences dialogCtrl+Alt+S, select . Click the icon and select Add.
In the dialog that opens, select the Docker Compose option, from the drop-down lists select the Docker server, Docker Compose service (here
web), configuration file (here
docker-compose.yml)and image name (here
Why we've chosen
web? This choice is explained by the fact, that after configuring a Docker-Compose-based interpreter, we'll be able to create regular run configurations that will alter the behavior of the container we selected. Therefore, if we want to debug the code in a container, that's the one we should select here. All other containers in the compose file will always be started together with this one, but you won't be able to affect their behavior from PyCharm - they'll always behave as if you started them with the command
docker-compose up from the command line.
Next, wait while PyCharm starts your Docker-Compose configuration to scan and index:
Using the Docker tool window
Since we've configured Docker, the Services tool window button appears at the bottom of PyCharm's main window. Click this button and see your container running:
Configuring database credentials
DATABASES section of the settings.py file in your Django project to add database configuration details:
Running your application under Docker-Compose
First, as we are executing a Django application, we must run a migration.
To do that, choose
(See Run tasks of manage.py for details.)
Next, create an ordinary Django server run/debug configuration. To do that, from the main menu choose Django Server:; in the dialog that opens click and select
The only thing you should pay attention to, is that Host field must be set to 0.0.0.0 - to make sure that we listen to requests coming from outside the Docker container.
Launch this configuration ():
To see output in your web browser, go to http://localhost:8000 (in the address bar, change 0.0.0.0 to localhost):
Let's summarize what has been done with the help of PyCharm:
We downloaded a Django application from GitHub and opened it.
We added specific Docker Compose files to our project.
We configured a remote interpreter based on Docker Compose.
We ran our Django application in the Docker Compose container.