Configure an interpreter using Docker Compose
Professional feature: download PyCharm Professional to try.
Preparing an example
Press Ctrl+Alt+S to open the IDE settings and select . Ensure that the Enable Django Support checkbox is selected. Then click OK to close the project settings.
Download the project archive from GitHub, unpack it, and save it on the local drive.
Select from the main menu and specify the path to the downloaded project.
PyCharm can suggest creating a virtual environment based on the project requirements recorded in the requirements.txt file.
Click OK to create an environment.
Adding files for Docker and Docker Compose
In the Project tool window, right-click the project root and select from the context menu. Enter the filename: Dockerfile.
Copy and paste the following code in the Dockerfile file:
FROM python:3.6.7 WORKDIR /app # By copying over requirements first, we make sure that Docker will cache # our installed requirements rather than reinstall them on every build COPY requirements.txt /app/requirements.txt RUN pip install -r requirements.txt # Now copy in our code, and run it COPY . /app EXPOSE 8000 CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]Then right-click the project root again, select from the context menu, and create the docker-compose.yml file.
Copy and paste the following code into the docker-compose.yml file.
version: '2' services: web: build: . ports: - "8000:8000" volumes: - .:/app links: - db db: image: "postgres:9.6" ports: - "5432:5432" environment: POSTGRES_PASSWORD: hunter2tip
If needed, you can use variable substitution in the docker-compose.yml file, for example:
db: image: "postgres:${POSTGRES_VERSION}"This file defines two services:
webanddb, and links them together.
Configuring Docker
Press Ctrl+Alt+S to open the IDE settings and select .
Click
to create a Docker server. Accept the suggested default values:macOSWindows
note
The Path mappings settings are not available on Linux. So, if you want to map some directories on a virtual machine to some path on your local Linux machine, you will have to do it manually.
Click OK to save changes.
Configuring Docker Compose as a remote interpreter
Ensure that you have downloaded and installed Python on your computer.
Do one of the following:
Click the Python Interpreter selector and choose Add New Interpreter.
Press Ctrl+Alt+S to open the project Settings/Preferences and go to . Click the Add Interpreter link next to the list of the available interpreters.
Select On Docker Compose from the list of the available interpreter types.
In the New Target: Docker dialog, specify the docker server and the docker-compose.yml file. Also select the service.
Optionally, specify environment variables.
Wait until PyCharm creates and configures a new target:
Next, select an interpreter to use in the container. You can select any virtual environment that is already configured in the container or select a system interpreter.
Using the Docker tool window
Since you've configured Docker, the Services tool window appears at the bottom of PyCharm's main window. You can click 
in the gutter next to the services group to launch db and web services.
Running your application under Docker-Compose
To execute a Django application, run a migration. Select from the main menu and enter
migrate:
(See Run tasks of manage.py for details.)
Run the Django server run/debug configuration. To do that, from the main menu select . In the dialog that opens click
and select Django Server:
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.
To run the newly created configuration, select from the main menu.
tip
If you are using the Docker Machine, use the machine's IP address instead.
With the run/debug configuration created, you can also debug your application under Docker Compose. To do that, set a breakpoint (for a Django application, you can set it in a template) and from the main menu select , or just click 
next to the run/debug configuration drop-down with the RunDjangoApp run/debug configuration selected.
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