Как поменять интерпретатор в pycharm
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Как поменять интерпретатор в pycharm

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Configure an interpreter using Docker Compose

This functionality relies on the Django plugin, which is bundled and enabled in PyCharm by default. If the relevant features aren’t available, make sure that you didn’t disable the plugin.

  1. Press Ctrl+Alt+S to open the IDE settings and then select Plugins .
  2. Open the Installed tab, find the Django plugin, and select the checkbox next to the plugin name.

Prerequisites

Make sure that the following prerequisites are met:

  • You have stable Internet connection, so that PyCharm can download and run busybox:latest (the latest version of the BusyBox Docker Official Image). Once you have successfully configured an interpreter using Docker, you can go offline.
  • Docker is installed. You can install Docker on the various platforms, but here we’ll use the macOS installation. Note that you might want to repeat this tutorial on different platforms; then use Docker installations for Windows and Linux (Ubuntu, other distributions-related instructions are available as well).
  • 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 IDE settings Ctrl+Alt+S as described in Install plugins. In the Settings dialog ( Ctrl+Alt+S ) , select Build, Execution, Deployment | Docker , and select Docker for under Connect to Docker daemon with . For example, if you are on macOS, select Docker for Mac . See more detail in Docker settings.

Note that you cannot install any Python packages into Docker-based project interpreters.

Prepare an example

Let’s use a Django application with a PostgreSQL database running in a separate container.

  1. On the Welcome screen, click Get from VCS .
  2. In the Get from Version Control dialog, specify the URL of the remote repository and click Clone .
  3. PyCharm suggests creating a virtual environment based on the project requirements recorded in the requirements.txt file. Creating a virtual environmentClick OK to create an environment.
  4. Another hint that IDE provides is detecting a data source. Click Connect to Database to set up the database. Detecting a datasourceYou might need to download missing drivers and check the rest of the configuration options: Configuring a datasource

With this done, your example is ready, and you can start configuring docker containers.

For this Django application, let’s create two containers: one for the database, and one for the application itself. The Docker Compose will link the two containers together.

Add files for Docker and Docker Compose

  1. In the Project tool window, right-click the project root and select New | File from the context menu. Enter the filename: Dockerfile .
  2. 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»]

version: ‘2’ services: web: build: . ports: — «8000:8000» volumes: — .:/app links: — db db: image: «postgres:9.6» ports: — «5432:5432» environment: POSTGRES_PASSWORD: hunter2

If needed, you can use variable substitution in the docker-compose.yml file, for example:
db: image: «postgres:$«

Configure Docker

Now that you have prepared the example, let’s configure Docker.

Docker settings

  1. Press Ctrl+Alt+S to open the IDE settings and then select Build, Execution, Deployment | Docker .
  2. Click to create a Docker server. Accept the suggested default values: If you installed Docker in a custom location, you may need to specify the paths to the Docker CLI executables. 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.

Configure Docker Compose as a remote interpreter

Let’s now define a remote interpreter based on Docker Compose.

  1. Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  2. Select On Docker Compose .
  3. Select Docker configuration in the Server dropdown.
  4. Specify the docker-compose.yml file in Configuration files and select the service. Creating a new Docker Compose targetOptionally, specify environment variables and edit the Compose project name.
  5. Wait until PyCharm creates and configures a new target: Configuring a Docker Compose target
  6. Select an interpreter to use in the container. You can choose any virtualenv or conda environment that is already configured in the container, or select a system interpreter. Selecting a system interpreter for a Docker target
  7. Click OK . The configured remote interpreter is added to the list.

Use the Docker tool window

When you have configured Docker, the Services tool window appears at the bottom of PyCharm’s main window. You can click docker-compose up in the gutter next to the services group to launch db and web services.

Docker window

Refer to Docker for more details on managing docker containers in the Services tool windows.

Configure database credentials

Modify the DATABASES section of the settings.py file in your Django project to add database configuration details:

Run the application

  1. Select Tools | Run ‘manage.py’ task from the main menu and enter migrate to run a migration and execute a Django application.
  2. Create a Run/Debug configuration for the Django server. To do that, select Run | Edit Configurations from the main menu. In the Run/Debug Configurations dialog, click Add New Configuration and select Django Server . Run/Debug configuration for a Django server
  3. Set the Host field to 0.0.0.0 to ensure that the Docker container is open to external requests. To allow the server to start at this address, add 0.0.0.0 to the ALLOWED_HOSTS list in settings.py .
  4. To run the newly created configuration, select Run | Run ‘RunDjangoApp’ from the main menu. Docker compose run

To see the output in your web browser, go to http://localhost:8000:

Django application output

If you are using the Docker Machine, use the machine’s IP address instead.

You can also create Run/Debug Configurations for Django tests.

Debug the application

With the Run/Debug configuration created, you can also debug your application.

  1. Set a breakpoint (for a Django application, you can set it in a template).
  2. Do one of the following:
    • Select Run | Debug ‘RunDjangoApp’ from the main menu.
    • Click Debug next to the Run/Debug configuration drop-down with the RunDjangoApp configuration selected.

For more information about debugging application in a container, refer to Debugging in a Docker container.

как изменить версию python base interpreter в существующем окружении в pycharm?

Есть окружение, созданное автоматически pycharm’ом, в нем используется интерпретатор python версии 3.8 32bit, который расположен в папке Scripts\python.exe. При попытке воспользоваться новым интерпретатором python версии 3.9 64bit, pycharm вынуждает создать новое окружение, что очень не хотелось бы: во-первых, необходимо устанавливать библиотеки заново, во-вторых, размножать эти окружения, поддерживать обновления библиотек в каждом из этих окружений, и занимать кучу места на диске. Есть ли способ изменить версию интерпретатора в существующем окружении? если нет, то почему? введите сюда описание изображения введите сюда описание изображения

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Никита Солоницын
задан 3 ноя 2020 в 21:15
Никита Солоницын Никита Солоницын
41 1 1 серебряный знак 6 6 бронзовых знаков

2 ответа 2

Сортировка: Сброс на вариант по умолчанию

Если коротко, то нельзя поменять версию интерпретатора в существующем virtualenv-е.

Во-первых, пакеты могут зависеть от версии интерпретатора. Во-вторых, некоторые пакеты компилируемые. Они зависят от заголовочных файлов конкретной версии и линкуются с ней. Замена интерпретатора их сломает.

Так что, даже если бы это было возможно, все равно придется переустанавливать эти пакеты. И, поверьте, лучше сделать окружение с нуля чем иметь кучу трудноуловимых проблем с совместимостью. Тем более что с нуля и не нужно.

Обычно зачем вам может понадобиться работать одновременно с несколькими версиями — это тестирование того, что приложение поддерживает их обе. Но для этого есть инструмент получше — tox.

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ответ дан 3 ноя 2020 в 22:21
Roman-Stop RU aggression in UA Roman-Stop RU aggression in UA
23.6k 1 1 золотой знак 19 19 серебряных знаков 30 30 бронзовых знаков

Нашел ответ=) Подход venv в Python 3 обладает преимуществом, которое вынуждает вас использовать определенную версию интерпретатора Python 3, который будет использован для создания виртуальной среды. Таким образом, вы избегаете недоразумений при выяснении, какая инсталляция Python базируется в новой виртуальной среде. [https://python-scripts.com/virtualenv][1]

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ответ дан 3 ноя 2020 в 21:31
Никита Солоницын Никита Солоницын
41 1 1 серебряный знак 6 6 бронзовых знаков
Ничего не понятно.
3 ноя 2020 в 21:51

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Configure a Python interpreter

To work with your Python code in PyCharm, you need to configure at least one Python interpreter. You can use a system interpreter that is available with your Python installation. You can also create a Virtualenv, pipenv, Poetry, or conda virtual environment . A virtual environment consists of a base interpreter and the installed packages.

With PyCharm Professional , you can also configure interpreters to execute your Python code on remote environments by using SSH, Vagrant, Docker, Docker Compose, or WSL (only for Windows).

When you configure a Python interpreter , you need to specify the path to the Python executable in your system. So, before configuring a Python interpreter, you need to ensure that you’ve downloaded Python and installed it in your system and you’re aware of a path to it.

You can create several Python interpreters based on the same Python executable. This is helpful when you need to create different virtual environments for developing different types of applications. For example, you can create one virtual environment based on Python 3.6 to develop Django applications and another virtual environment based on the same Python 3.6 to work with scientific libraries.

Python interpreters can be configured for a new project or for the current project (you can create a new interpreter or use one of the existing interpreters).

Configuring an existing Python interpreter

At any time, you can switch the Python interpreter either by using the Python Interpreter selector or in Settings .

Switch the Python interpreter using the Python Interpreter selector

Project interpreter selector

  • The Python Interpreter selector is located on the status bar. It is the most convenient and quickest way to switch the Python interpreter. Just click it and select the target interpreter:

Switch the Python interpreter in the IDE settings

View interpreters

  1. Press Ctrl+Alt+S to open the IDE settings and then select Project | Python Interpreter .
  2. Click the drop-down and select the desired Python interpreter:
  3. If it’s not on the list, click Show All . Then select the desired interpreter in the left pane and click OK . When PyCharm stops supporting any of the outdated Python versions, the corresponding Python interpreter is marked as unsupported.

When you change the project interpreter and select an SSH interpreter, you might need to synchronize the local content with the target server. Mind a notification balloon in the lower-right corner:

Sync local files with the deployment server

You can choose to enable the automatic uploading of files to the server:

  • Click Auto-upload files to start uploading on the next save.
  • Click Sync and auto-upload files to immediately sync the files and upload them on every save in future.

Modify a Python interpreter

  1. Press Ctrl+Alt+S to open the IDE settings and then select Project | Python Interpreter .
  2. Expand the list of the available interpreters and click Show All . Show all available interpreters
  3. You can modify the path to the Python executable in the Interpreter path field. When the Associate this virtual environment with the current project checkbox is enabled, the interpeter is available only in the current PyCharm project. To change the interpreter name, select the target interpreter and click . Edit iconThe Python interpreter name specified in the Name field, becomes visible in the list of available interpreters. Click OK to apply the changes. Edit interpreter settings

Remove a Python interpreter

If you no longer need a Python interpreter for a project, you can remove it from the project settings.

  1. Do one of the following:
    • Press Ctrl+Alt+S to open the IDE settings and then select Project | Python Interpreter .
    • Click the Python Interpreter selector and choose Interpreter Settings .
  2. Expand the list of the available interpreters and click Show All . Show all available interpreters
  3. Choose the interpreter that you want to remove and click . Remove a Python interpreter

Creating a new Python interpreter

Configuring local Python interpreters

To configure a local Python interpreter for the current project, follow one of the procedures below:

Configure a system interpreter

  1. Ensure that you have downloaded and installed Python on your computer. Installing Python on Windows from Microsoft Store If you are on Windows, you can download Python from the Microsoft Store and install it as a Python interpreter. Once the Python application is downloaded from the Microsoft Store, it becomes available in the list of the Python executables. Note that interpreters added from the Microsoft Store installations come with some limitations. Because of restrictions on Microsoft Store apps, Python scripts may not have full write access to shared locations such as TEMP and the registry.
  2. Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  3. Select Add Local Interpreter .
  4. In the left-hand pane of the Add Python Interpreter dialog, select System Interpreter . Adding a system interpreter
  5. In the Interpreter drop-down, select one of the Python interpreters that have been installed in your system, or click and in the Select Python Interpreter dialog that opens, choose the desired Python executable. Selecting the Python executableYou will need admin privileges to install, remove, and upgrade packages for the system interpreter. When attempting to install an interpreter package through an intention action, you might receive the following error message: System Interpreter warning messageAs prompted, consider using a virtual environment for your project.
  6. Click OK to complete the task.

Create a virtualenv environment

Creating a virtual environment

  1. Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  2. Select Add Local Interpreter .
  3. In the left-hand pane of the Add Python Interpreter dialog, select Virtualenv Environment .
  4. The following actions depend on whether you want to create a new virtual environment or to use an existing one. New virtual environment
    • Specify the location of the new virtual environment in the Location field, or click and browse for the desired location in your file system. The directory for the new virtual environment should be empty.
    • Choose the base interpreter from the list, or click and find the desired Python executable in your file system.
    • Select the Inherit global site-packages checkbox if you want all packages installed in the global Python on your machine to be added to the virtual environment you’re going to create. This checkbox corresponds to the —system-site-packages option of the virtualenv tool.

    Existing virtual environment

    • Choose the desired interpreter from the list.
    • If the desired interpreter is not on the list, click , and then browse for the desired Python executable (for example, venv/bin/python on macOS or venv\Scripts\python.exe on Windows).

The selected virtual environment will be reused for the current project.

If PyCharm displays the Invalid environment warning, it means that the specified Python binary cannot be found in the file system, or the Python version is not supported. Check the Python path and install a new version, if needed.

Create a conda environment

New Conda environment

  1. Ensure that Anaconda or Miniconda is downloaded and installed on your computer, and you’re aware of a path to its executable file. For more information, refer to the installation instructions.
  2. Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  3. Select Add Local Interpreter .
  4. In the left-hand pane of the Add Python Interpreter dialog, select Conda Environment .
  5. The following actions depend on whether you want to create a new conda environment or to use an existing one. New conda environment
    • Select the Python version from the list.
    • Normally, PyCharm will detect conda installation. Otherwise, specify the location of the conda executable, or click to browse for it.
    • Specify the environment name.

    Existing conda environment

    • Select the environment from the list.

The selected conda environment will be reused for the current project.

Create a pipenv environment

Adding a Pipenv environment

  1. Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  2. Select Add Local Interpreter .
  3. In the left-hand pane of the Add Python Interpreter dialog, select Pipenv Environment .
  4. Choose the base interpreter from the list, or click and find the desired Python executable in your file system.
  5. If your project contains Pipfile , you can choose whether you want to install the packages listed in it by enabling or disabling the Install packages from Pipfile checkbox. By default, the checkbox is enabled.
  6. If you have added the base binary directory to your PATH environmental variable, you don’t need to set any additional options: the path to the pipenv executable will be autodetected. If the pipenv executable is not found, follow the pipenv installation procedure to discover the executable path, and then specify it in the dialog.
  7. Click OK to complete the task.

When you have set the pipenv virtual environment as a Python interpreter, all available packages are added from the source defined in Pipfile . The packages are installed, removed, and updated in the list of the packages through pipenv rather than through pip.

Create a Poetry environment

creating a poetry environment

  1. Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  2. Select Add Local Interpreter .
  3. In the left-hand pane of the Add Python Interpreter dialog, select Poetry Environment .
  4. The following actions depend on whether you want to create a new Poetry environment or to use an existing one. New Poetry environment
    • Select Poetry Environment .
    • Choose the base interpreter from the list, or click and find the desired Python executable in your file system.
    • If your project contains pyproject.toml , you can choose whether you want to install the packages listed in it by enabling or disabling the Install packages from pyproject.toml checkbox. By default, the checkbox is enabled.
    • If PyCharm doesn’t detect the poetry executable, specify the following path in the dialog, replacing jetbrains with your username:

/Users/jetbrains/Library/Application Support/pypoetry/venv/bin/poetry
C:\Users\jetbrains\AppData\Roaming\pypoetry\venv\Scripts\poetry.exe
/home/jetbrains/.local/bin/poetry

  • Make sure that the project directory contains a pyproject.toml file.
  • Select Existing environment . Then expand the Interpreter list and choose the desired interpreter.
  • If the desired interpreter is not on the list, click, and then browse for the Python executable within the previously configured Poetry environment.

The selected Poetry environment will be reused for the current project.

Configuring remote Python interpreters

When a remote Python interpreter is added, at first the PyCharm helpers are copied to the remote host. PyCharm helpers are needed to run remotely the packaging tasks, debugger, tests and other PyCharm features.

Next, the skeletons for binary libraries are generated and copied locally. Also, all the Python library sources are collected from the Python paths on a remote host and copied locally along with the generated skeletons. Storing skeletons and all Python library sources locally is required for resolve and completion to work correctly.

PyCharm checks the remote helpers version on every remote run, so if you update your PyCharm version, the new helpers will be uploaded automatically, and you don’t need to recreate remote interpreter.

You can only add a remote interpreter for your Project . A remote interpreter cannot be set as the default interpreter for a Workspace .

Configure a WSL interpreter

  1. Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  2. Select On WSL .
  3. Wait until PyCharm detects Linux on your machine and completes introspection. Click Next to proceed: Detecting Linux
  4. In the left-hand pane of the dialog, select the type of the WSL interpreter you want to create: Virtual Environment , Conda Environment , or System Interpreter . New WSL interpreterFor a system interpreter, just provide the path to the Python executable in the selected Linux distribution. For virtual and conda environments, you can provide a path to a Python executable of an existing environment in the selected Linux distribution or create a new environment based on the specified Python.

Once done, the new interpreter will be added to your project, and the default mnt mappings will be set.

Configure an interpreter using Vagrant

  1. Ensure that the following prerequisites are met (outside of PyCharm):
    • One of supported Vagrant providers is installed on your computer.
    • Vagrant is installed on your computer, and all the necessary infrastructure is created.
    • The parent folders of the following executable files have been added to the system PATH variable:
      • vagrant.bat or vagrant from your Vagrant installation. This should be done automatically by the installer.
      • VBoxManage.exe or VBoxManage from your Oracle’s VirtualBox installation.
    • The required virtual boxes are created.
  2. Make sure that the Vagrant plugin is enabled.
  3. Ensure that you have properly initiated and started Vagrant. Basically, you need to open the Terminal window and execute the following commands:

$ vagrant init ubuntu/trusty64
$ vagrant up

For more information, refer to Vagrant documentation.

  • Do one of the following:
    • Click the Python Interpreter selector and choose Add New Interpreter .
    • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
    • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
  • Select On Vagrant .
  • Specify the path to the Vagrant instance folder in Vagrant Instance Folder . Wait until you see a link in Vagrant Host URL .
  • In the New Target: Vagrant dialog, click the browse icon next to the Vagrant Instance Folder field, and specify the desired Vagrant instance folder. This results in showing the link to Vagrant Host URL . Specifying the Vagrant instance folder
  • In the next field, PyCharm will display the path to the Python executable. Press «Next» to proceed. Python executable is discovered
  • You can create a virtual environment (venv or conda) or use a system Python interpreter for the target Vagrant instance. Note that virtual environment must be configured and available in the specified Vagrant instance folder. Otherwise, the corresponding lists will be empty. Virtual environment on a target Vagrant instanceClik Create to complete the task.
  • Configure an interpreter using SSH

    1. Ensure that there is an SSH server running on a remote host, since PyCharm runs remote interpreters via ssh-sessions.
    2. Do one of the following:
      • Click the Python Interpreter selector and choose Add New Interpreter .
      • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
      • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
    3. Select On SSH .
    4. Select an option to create a new SSH connection, then specify server information (host, port, and username). adding an interpreter via SSHAlternatively, you can select Existing and choose any available SSH configuration from the list. To create a new SSH configuration, follow the steps below: Creating an SSH configuration
      • Click next to the list of configurations: Add new SSH configuration
      • Click, disable the Visible only for this project checkbox, and fill in the required fields: Adding new SSH configuration
      • Once done, the newly created SSH configuration will appear in the list of available configurations. It will also become available in the SSH Deployment Configurations settings. Click Next to proceed: Connecting to SSH server
    5. In the next dialog window, provide the authentication details to connect to the target server. specifying authentication detailsSelect Password or Key pair (OpenSSH or PuTTY) and enter your password or passphrase. If Key pair (OpenSSH or PuTTY) is selected, specify:
      • Private key : location of the file with a private key
      • Passphrase : similar to a password, it serves to encrypt the private key.

    Click Next to proceed.

  • Wait until PyCharm completes the introspection of the SSH server. SSH server introspection
  • In the next dialog, select a type of Python environment to configure on the SSH server. Selecting a Python environmentYou can create a new virtual environment or сonda environment, select an existing one, or use a system interpreter.
    • Select the Inherit global site-packages checkbox if you want all packages installed in the global Python on your machine to be added to the virtual environment you’re going to create. This checkbox corresponds to the —system-site-packages option of the virtualenv tool.
    • If you need to execute your Python code on the SSH server as a sudo user, enable the Execute code with root privileges via sudo checkbox.
    • You can configure the path mappings between your local project and the server. To do that, click the Browse icon in the Sync folders field and enter the path to the local project folder and the path to the folder on the remote server.

    Click Create to complete adding the interpreter.

    Configure an interpreter using Docker

    1. Do one of the following:
      • Click the Python Interpreter selector and choose Add New Interpreter .
      • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
      • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
    2. Select On Docker .
    3. Select an existing Docker configuration in the Docker server dropdown. Alternatively, click and perform the following steps to create a new Docker configuration: Create a Docker configuration Click to add a Docker configuration and specify how to connect to the Docker daemon. The connection settings depend on your Docker version and operating system. For more information, refer to Docker connection settings. The Connection successful message should appear at the bottom of the dialog. Docker connection settingsFor more information about mapping local paths to the virtual machine running the Docker daemon when using Docker on Windows or macOS, refer to Virtual machine path mappings for Windows and macOS hosts. You will not be able to use volumes and bind mounts for directories outside of the mapped local path. This table is not available on a Linux host, where Docker runs natively and you can mount any directory to the container.
    4. The following actions depend on whether you want to pull a pre-built image from a Docker registry or to build an image locally from a Dockerfile. Pull a Docker image Select Pull or use existing and specify the tag of the desired image in the Image tag field. Creating a Docker interpreter by pulling an imageBuild a Docker image Select Build and change the default values in the Dockerfile and Context folder fields if necessary. Creating a Docker interpreter by building an imageIf required, expand the Optional section and specify the following:
    Image tag Specify an optional name and tag for the built image. This can be helpful for referring to the image in the future. If you leave the field blank, the image will have only a random unique identifier.
    Build options Set supported docker build options. For example, you can specify metadata for the built image with the —label option.
    Build args Specify the values for build-time variables that can be accessed like regular environment variables during the build process but do not persist in the intermediate or final images. This is similar to using the —build-args option with the docker build command. These variables must be defined in the Dockerfile with the ARG instruction. For example, you can define a variable for the version of the base image that you are going to use:

    ARG PY_VERSION=latest FROM python:$PY_VERSION

    The PY_VERSION variable in this case will default to latest and the Dockerfile will produce an image with the latest available version of Python, unless you redefine it as a build-time argument. If you set, PY_VERSION=3.10 , Docker will pull python:3.10 instead, which will run a container with Python version 3.10. Redefining the PY_VERSION argument is similar to setting the following command-line option:

    —build-arg PY_VERSION=3.10

  • Wait for PyCharm to connect to the Docker daemon and complete the container introspection. Docker container introspection is completed
  • Next, select an interpreter to use in the Docker container. You can choose any virtualenv or conda environment that is already configured in the container or select a system interpreter. Selecting a system interpreter for a Docker target
  • Click OK . The configured remote interpreter is added to the list.
  • Configure an interpreter using Docker Compose

    1. Do one of the following:
      • Click the Python Interpreter selector and choose Add New Interpreter .
      • Press Ctrl+Alt+S to open Settings and go to Project: | Python Interpreter . Click the Add Interpreter link next to the list of the available interpreters.
      • Click the Python Interpreter selector and choose Interpreter Settings . Click the Add Interpreter link next to the list of the available interpreters.
    2. Select On Docker Compose .
    3. Select Docker configuration in the Server dropdown.
    4. Specify the docker-compose.yml file in Configuration files and select the service. Creating a new Docker Compose targetOptionally, specify environment variables and edit the Compose project name.
    5. Wait until PyCharm creates and configures a new target: Configuring a Docker Compose target
    6. Select an interpreter to use in the container. You can choose any virtualenv or conda environment that is already configured in the container, or select a system interpreter. Selecting a system interpreter for a Docker target
    7. Click OK . The configured remote interpreter is added to the list.

    Setting the default interpreter

    In PyCharm, you can specify an interpreter that will be automatically set for all newly created projects.

    1. Go to File | New Projects Setup | Settings for New Projects (on Window and Linux) or File | New Projects Setup | Preferences for New Projects (on macOS).
    2. Select Python Interpreter settings. Then either choose an existing interpreter from the Python interpreter list of click to add a new interpreter. Click OK to save the changes. The change will become effective for all newly created projects in PyCharm.

    Managing interpreter packages

    For each interpreter, you can install, upgrade, and delete Python packages. By default, PyCharm uses pip to manage project packages. For conda environments you can use the conda package manager.

    Managing packages

    PyCharm smartly tracks the status of packages and recognizes outdated versions by showing the number of the currently installed package version (column Version ), and the latest available version (column Latest version ). When a newer version of a package is detected, PyCharm marks it with the arrow sign and suggests to upgrade it.

    By default, the Latest version column shows only stable versions of the packages. If you want to extend the scope of the latest available versions to any pre-release versions (such as beta or release candidate ), click Show early releases .

    You can upgrade several packages at once. Hold Cmd (macOS) or Ctrl on (Unix or Windows), left-click to select several items in the list of packages, and then click Upgrade .

    See the detailed instructions:

    • How to install a package
    • How to upgrade the package
    • How to uninstall the package

    If you are looking for a more convenient way to search for Python packages, preview the documentation, and manage Python package repositories, try the Python Packages tool window. For more information, refer to Manage packages in the Python Packages tool window.

    Как выбрать интерпретатор python в PyCharm?

    Доброго времени. Не понимаю, почему PyCharm не видит другие версии питона, хотя они установлены и именно из настроек самого PyCharm видны, а при создании конфигурации для проекта их уже нет.
    sMdli5f.pngGiB02fU.png

    Что я делаю не так?

    • Вопрос задан более трёх лет назад
    • 10266 просмотров

    Комментировать
    Решения вопроса 1

    sim3x

    Смотрите в настройках проекта, а не настройках тестов

    в сеттингах ищите django и название своего проекта

    Settings
    Project >:
    — Project interpreter

    Ответ написан более трёх лет назад
    Нравится 1 2 комментария

    artgrosvil

    Илья Трусов @artgrosvil Автор вопроса

    Выбрал, но всё равно в проекте используется Python3.5
    V1vFYYN.pngTu9ogXT.png XIzCEJU.png

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