Update PyCharm
By default, PyCharm is configured to check for updates automatically and notify you when a new version is available. Updates are usually patch-based : they are applied to the existing installation and only require you to restart the IDE. However, sometimes patch updates are not available, and a new version of PyCharm must be installed.
When PyCharm updates to a new major release, it opens the What’s New in PyCharm tab in the editor with information about the changes, improvements, and fixes. To open this tab manually, select Help | What’s New in PyCharm .
If PyCharm does not have HTTP access outside your local network, it will not be able to check for updates and apply patches. In this case, you have to download new versions of the IDE and install them manually as described in Standalone installation. On macOS, you can delete the outdated version of PyCharm from Application and then drag the newly installed version to Application .
Toolbox App
If you installed PyCharm using the Toolbox App, it will suggest that you update the IDE when a new version is available.
Automatically update all managed tools
- Open the Toolbox App and click the Toolbox App menu icon in the top right corner.
- In the Toolbox App Settings dialog, expand Tools and select Update all tools automatically .
If you disable this option, you will need to click Update next to any instance when a newer version comes out.
You can also configure the update policy for every managed IDE instance separately.
Configure the update policy for a specific instance
- Open the Toolbox App, click next to the relevant IDE instance, and select Settings .
- In the instance settings dialog, select the update channel to use for this IDE instance:
- Release : Update only to stable releases that are recommended for production.
- Early Access Program : Includes updates to release candidates , beta releases, and EAP builds, which are not recommended for production and include feature previews.
Standalone instance
If you installed PyCharm manually, the standalone IDE instance will manage its own updates. It will notify you when a new version is available (show you a notification in the Event Log tool window). You can choose to update the current instance, download and install the new version as a separate instance, postpone the notification, or ignore the update entirely.
On Linux, it is not recommended to manually update an existing standalone PyCharm installation to a newer major version. You should always extract the downloaded tarball to a clean directory. For more information, refer to Standalone installation.
If you installed PyCharm using root privileges, you should use the same level of privileges to update the IDE.
Configure the update policy
To manage the PyCharm update policy, open Settings Control+Alt+S and select Appearance & Behavior | System Settings | Updates .
If the IDE instance is managed by the Toolbox App, these settings will affect only plugin updates.
The Updates page contains the following settings:
Check IDE updates for
Select whether you want PyCharm to check for updates automatically and choose an update channel.
- Early Access Program : Provides all updates, including major version EAP builds and minor version Preview builds. This channel is not recommended for production development. PyCharm can be updated only to a minor Preview version, but not to a major EAP build. For example, you can update PyCharm 2021.1.1 to 2021.1.2 , but not to 2021.2 EAP . The 2021.2 EAP version in this case will be installed as an additional instance. EAP versions can be updated to both newer EAP and stable PyCharm versions. If an EAP version is updated to a stable version at some point, the name of the original installation directory does not change.
- Beta Releases or Public Previews : Includes stable releases, release candidates, and beta releases. Some updates in this channel may contain minor bugs and feature previews.
- Stable Releases : Includes only stable releases that are recommended for production.
You can choose the update channel only if you are using a stable version . For EAP builds, the channel is always set to Early Access Program .
Check for plugin updates
Select whether you want PyCharm to check for new versions of plugins automatically.
Check for Updates
Check for updates immediately.
Alternatively, go to Help | Check for Updates on Windows or Linux, or PyCharm | Check for Updates on macOS.
Manage ignored updates…
Show the list of updates that were ignored. These updates will not be suggested until you remove them from the list of ignored updates.
If you remove several updates from the ignored list, only the most recent will be offered for download when you check for updates.
Show What’s New in the editor after an IDE update
Open a tab with information about new features and improvements after a major IDE update.
Snap package
If you installed PyCharm as a snap package, it will manage updates automatically. All snaps are updated automatically in the background every day. You can also get the latest version of all snaps manually at any time by running the following command:
sudo snap refresh
Or if you want to update only the PyCharm snap:
Install, uninstall, and upgrade packages
PyCharm provides methods for installing, uninstalling, and upgrading Python packages for a particular Python interpreter. It means that each project has its own set of packages, which is considered a best practice for Python dependency management. By default, PyCharm uses pip to manage project packages. For Conda environments you can use the conda package manager.
In PyCharm, you can preview and manage packages in the Python Packages tool window and in the Python interpreter Settings .
Manage packages in the Python Packages tool window
This tool window is available in PyCharm 2021.1 and later
The Python Packages tool window provides the quickest and neat way to preview and install packages for the currently selected Python interpreter. This window is enabled by default, and you can find it in the lower group of the tool windows. At any time you can open it using the main menu: View | Tool Windows | Python Packages .
The Python Packages tool window shows installed packages and the packages available in the PyPI and Conda package repositories. Use the Search field to filter out the list of the available packages.
You can preview package documentation in the documentation area, or you can click the Documentation link and open the corresponding resource in a browser.
To delete an installed package, click in the upper-right corner of the Python Package tool window.
Install packages from repositories
- Start typing the package name in the Search field of the Python Package tool window. You should be able to see the number of the matching packages.
- Expand the list of the available versions in the upper-right corner of the tool window. Select the required version or keep it the latest.
- Click the Install with pip or Install with conda button next to the version list. Once PyCharm notifies you about successful installation, you should see the package in the list of the installed packages.
- If needed, click and provide a path to any custom repository you want to install from.
Manage package repositories
- To specify a custom repository, including devpi or PyPi, click on the Python Packages toolbar.
- In the Python Packages Repositories dialog, click to add a new repository. If no authorization is required, for example, in the case of a local repository, type the target URL and click OK .
- If you want to install Python packages from a repository that requires HTTP authorization, click Basic HTTP and type the repository URL and the login credentials. Click OK to complete the task.
Once the repository is added, it appears in the list of the repositories in the Python Packages tool window.
Install packages from Version Control System
- Click the Add Package link on the Python Packages toolbar and select From Version Control .
- Specify a path to the target git repository. For more information, refer to pip documentation for more information about supported path formats.
- Select Install as editable (-e) if you want to install a project in editable mode (for example, setuptools develop mode ).
Install packages from a local machine
- Click the Add Package link on the Python Packages toolbar and select From Disk .
- Specify a path to the package directory or an archive ( zip or whl ).
Manage packages in the Python interpreter settings
To manage Python packages for the Python interpreter, select the Python Interpreter page in the project Settings or select Interpreter Settings in the Python Interpreter selector on the Status bar .
If you select a Python interpreter with the configured Conda environment, the Use Conda Package Manager toggle appears in the packages area toolbar.
Use this toggle to install and upgrade packages from Conda package repositories. This toggle is enabled by default for Conda environments.
Install a package
- Click the button on the package toolbar.
- In the Available Packages dialog that opens, preview the list of the available packages and type the name of the package to install in the Search field.
- If required, select the following checkboxes:
- Specify version : if this checkbox is selected, you can select the desired version from the list of available versions. By default, the latest version is taken.
- Options : If this checkbox is selected, you can type the pip install command-line options in the text field.
- Install to user’s site packages directory : If this checkbox is left cleared (by default), then the packages will be installed into the current interpreter package directory. If the checkbox is selected, the packages will be installed into the specified directory. This option is not available for Conda environments.
- Select the target package and click Install Package .
If you’ve got any or error messages, consult the Troubleshooting guide for a solution.
Uninstall a package
- In the list of the packages, select the packages to be removed.
- Click Uninstall (). The selected packages are removed from the interpreter.
PyCharm smartly tracks the status of packages and recognizes outdated versions by showing 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 upgrading 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 .
Upgrade a package
- In the list of the packages, select the package to be upgraded.
- Click Upgrade ( ). The selected packages are upgraded to the latest available versions.
- Click OK to complete upgrading.
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 .
If you’re accustomed to installing packages from the command line, you can proceed with your workflow using the Terminal.
Reuse installed packages
- Create a new virtual environment and install packages that you want to be used in other projects. Then you can specify this virtual environment as a Python interpreter for the target project and all the needed packages will be available.
- In the Terminal window execute the following command: pip freeze > requirements.txt Then add the created requirements.txt file to the target project and PyCharm will prompt you to install the packages listed in the file.
How to change version of Python in PyCharm
I wanted to make Discord bot (should I even write this here), but it’s said that I need Python 3.6, not Python 3.7 that I have. How can I change from Python 3.7 to Python 3.6 to make something like that ?
183k 19 19 gold badges 134 134 silver badges 249 249 bronze badges
asked Aug 26, 2018 at 23:20
929 2 2 gold badges 8 8 silver badges 16 16 bronze badges
you just need to change the Python Interpreter used for the project. Edit configurations/Python interpreter.
Aug 26, 2018 at 23:22
. and install Python 3.6 if it’s not already done
Aug 26, 2018 at 23:25
how does one downgrade pycharm version?
Aug 17, 2022 at 13:49
2 Answers 2
First make sure you have Python 3.6 installed.
Then Go to File > Settings > Project:* > Project Interpreter , then select your interpreter under the Project Interpreter drop down.
If its still not there, you can also press the settings cog button on the right side of the drop down and select add . Select System Interpreter from the left side, then select the interpreter from there. When you press ok , the interpreter will be available to be selected.
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
- 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
- Press Control+Alt+S to open the IDE settings and then select Project | Python Interpreter .
- Click the drop-down and select the desired Python interpreter:
- 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:
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
- Press Control+Alt+S to open the IDE settings and then select Project | Python Interpreter .
- Expand the list of the available interpreters and click Show All .
- 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 .
The Python interpreter name specified in the Name field, becomes visible in the list of available interpreters. Click OK to apply the changes. 
Remove a Python interpreter
If you no longer need a Python interpreter for a project, you can remove it from the project settings.
- Do one of the following:
- Press Control+Alt+S to open the IDE settings and then select Project | Python Interpreter .
- Click the Python Interpreter selector and choose Interpreter Settings .
- Expand the list of the available interpreters and click Show All .
- Choose the interpreter that you want to remove and click .
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
- 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.
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 Add Local Interpreter .
- In the left-hand pane of the Add Python Interpreter dialog, select System Interpreter .
- 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.
You 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: 
As prompted, consider using a virtual environment for your project. - Click OK to complete the task.
Create a virtualenv environment
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 Add Local Interpreter .
- In the left-hand pane of the Add Python Interpreter dialog, select Virtualenv Environment .
- 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
- 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.
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 Add Local Interpreter .
- In the left-hand pane of the Add Python Interpreter dialog, select Conda Environment .
- 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
- Choose the desired environment from the list.
The selected conda environment will be reused for the current project.
Create a pipenv environment
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 Add Local Interpreter .
- In the left-hand pane of the Add Python Interpreter dialog, select Pipenv Environment .
- Choose the base interpreter from the list, or click and find the desired Python executable in your file system.
- 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.
- 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 paste it in the Pipenv executable field.
- 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
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 Add Local Interpreter .
- In the left-hand pane of the Add Python Interpreter dialog, select Poetry Environment .
- 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 Poetry executable field, 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.
Configure a WSL interpreter
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 WSL .
- Wait until PyCharm detects Linux on your machine and completes introspection. Press Next to proceed:
- 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 .
For 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
- 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.
- Make sure that the Vagrant plugin is enabled.
- 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.
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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.
Clik Create to complete the task.Configure an interpreter using SSH
- Ensure that there is an SSH server running on a remote host, since PyCharm runs remote interpreters via ssh-sessions.
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 SSH .
- Select an option to create a new SSH connection, then specify server information (host, port, and username).
Alternatively, 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:
- Click, disable the Visible only for this project checkbox, and fill in the required fields:
- 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:
- Click next to the list of configurations:
- In the next dialog window, provide the authentication details to connect to the target server.
Select 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.
You can create a new virtual 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.
- 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
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 Docker .
- 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.
For 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. - 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.
Build a Docker image Select Build and change the default values in the Dockerfile and Context folder fields if necessary. 
If 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
Configure an interpreter using Docker Compose
- Do one of the following:
- Click the Python Interpreter selector and choose Add New Interpreter .
- Press Control+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 Docker Compose .
- Select an existing Docker configuration in the Server dropdown. Alternatively, select Create new 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. For 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.
- In Configuration files , specify the docker-compose.yml file. Also select the service.
Optionally, specify environment variables and edit the Compose project name in Project name . - Wait until PyCharm creates and configures a new target:
- Next, 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.
- 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.
- 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).
- 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.
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.