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 Condavirtual environment. A virtual environment consists of a base interpreter and the installed packages.
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.
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 select Project <project name> | Python Interpreter.
Expand the list of the available interpreters and click Show All.
Select the target interpreter.
When PyCharm stops supporting any of the outdated Python versions, the corresponding Python interpreter is marked as unsupported.
When you change 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 perform one of the following actions:
Auto-upload files to the server
Synchronize files and then enable auto-uploading
Modify a Python interpreter
Press Control+Alt+S to open the IDE settings and select Project <project name> | 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.
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 select Project <project name> | Python Interpreter.
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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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 field, type the fully-qualified path to the required interpreter executable, 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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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 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.
Once all the steps are done, the new pipenv environment is set for your project and the packages listed in the Pipfile are installed.
If you open a project with a Pipfile file added but no any interpreter configured, PyCharm offers you to use Pipenv environment.
If you select this option, PyCharm sets pipenv for you automatically. Alternatively, you can click Configure Python interpreter to follow the standard workflow.
Similarly, when you open a project with a Pipfile file in PyCharm for the very first time, for example, by checking it out from the Version Control, the Pipenv virtual environment will be configured automatically.
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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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 PyCharm doesn't detect the poetry executable, specify the following path in the Poetry executable field, replacing jetbrains with your username:
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 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. SFTP support is required for copying helpers to the server.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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.
In the next field, PyCharm will display the path to the Python executable. Press "Next" to proceed.
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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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:
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
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.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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 Server dropdown.
Alternatively, select Create new and perform the following steps to create a new Docker configuration:
Create a Docker configuration
Click New 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, see 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, see 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 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.
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
You can provide several arguments separated by spaces.
Wait for PyCharm to connect to the Docker daemon and complete the container introspection.
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.
Click OK.
The configured remote interpreter is added to the list.
Press Control+Alt+S to open Settings and go to Project: <project name> | 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 New 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, see 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, see 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.
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.
In PyCharm, you can specify an interpreter that will be automatically set for all newly created projects.
From the main menu, select 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.
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and in the Select Python Interpreter dialog that opens, choose the desired Python executable.
and find the desired Python executable in your file system.
to browse for it.
, disable the Visible only for this project checkbox, and fill in the required fields:
to add a new interpreter. Click OK to save the changes.
and suggests to upgrade it.