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Pycharm configure python interpreter
Pycharm configure python interpreter












pycharm configure python interpreter
  1. #Pycharm configure python interpreter how to#
  2. #Pycharm configure python interpreter apk#
  3. #Pycharm configure python interpreter install#
  4. #Pycharm configure python interpreter code#

In our case we want to migrate our migrations so just type migrate and the magic happen. This will open a new tab at the bottom of your IDE where you can execute directly the commands. In the menu Tools you have now a Run manage.py Task option. Running manage.py command for an application hosted in a docker is quite heavy, you have everytime to run docker-compose exec YourServiceWeb python3 manage.py YourCommand

pycharm configure python interpreter

If you click on Run you dockers will be automatically mounted and you application is accessible.

pycharm configure python interpreter

Then click on ok and the configuration is done. In the top bar of your IDE you should see a Add configuration button:Ĭlick on it, then on the blue '+' sign and select Django Server, finally fill the informations needed and select the interpreter we created previously as project interpreter: Now the interpreter is ready, we have to tell Pycharm to use this interpreter for this project. You can now apply the settings and go back to your IDE main window. On the new window, select docker-compose, and select your docker-compose.yml file as a configuration file, then in service select web:Ĭlick on ok and continue in the settings, going to Languages & Frameworks > Django. For that open the settings ( File > Settings on windows, P圜harm > preferences on Mac OS) and open the python interpreter section in your project.Ĭlick on the three dots on the right then add We will configure Pycharm to use our docker as a python interpreter. We can fix that in the terminal but let's configure Pycharm and do it through the IDE. Now everything is ready but if you run your docker compose you will have an error because the database is empty. 'ENGINE': 'django.db.backends.postgresql', We will as well make some modification on our settings file (my_blog/ settings.py): ĪLLOWED_HOSTS = #to allow access in local

#Pycharm configure python interpreter how to#

The object is not about dockerizing an application but how to configure Pycharm. Same than for the Dockerfile you probably understand this file.

pycharm configure python interpreter

Image: "postgres:latest" container_name: MyDb At the root of the project, create a file docker-compose.yml: version: '3' services: Setup the docker compose fileĪs we will have two dockers to run together, we will need docker-compose to manage them. For PostgreSQL, we don't need a Dockerfile, the official image will be enough for us. This Dockerfile will create the docker which will run our python interpreter. I suppose you understand this file as we explained it in the tutorial about deployment.

#Pycharm configure python interpreter install#

RUN pip install -upgrade pip COPY requirements.txt /app/requirements.txtĬMD

#Pycharm configure python interpreter apk#

RUN apk update & apk add postgresql-dev gcc python3-dev musl-dev Then create a file named Dockerfile: FROM python: 3.8. If you don't know what I'm talking about, you can have a look on the tutorial " Deploying an application Django with PostgreSQL and Docker. We will start with cloning the application and create a dockerfile for our python docker.

#Pycharm configure python interpreter code#

We want now to have a docker for PostgreSQL, another docker for the python interpreter, we want also the data from the database to be persistent and finally to have access to the code to edit it. You can use the project we created in the tutorial " First steps with Django" The environmentīefore starting the configuration, you'll need to install few dependencies on your computer: Today we will see how to configure a project in our new IDE. Pycharm is one of the most used python IDE in the world, and implemented docker as development environment. Using docker as a development environment decrease also the time needed for a new developer to be ready to code. That way every developer will work on the same environment, regardless of their operating system. To be sure every developer work with the same controlled development environment, more and more teams use docker.














Pycharm configure python interpreter