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, or Condavirtual environment. A virtual environment consists of a base interpreter and 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 your Python interpreter either using the Python Interpreter selector or in the project Settings/Preferences.
Change 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:
Change the Python interpreter in the project settings
Press Ctrl+Alt+S to open the IDE settings and select Project <project name> | Python Interpreter.
Expand the list of the available interpreters and click the Show All link. Alternatively, click the icon and select 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When PyCharm stops supporting any of the outdated Python versions, the corresponding Python interpreter is marked as unsupported.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 local content with the target server. Mind a notification balloon in the lower-right corner. You can click one of the links to perform the following actions:
Auto-upload files to the server
Synchronize files and then enable auto-uploading
Modify a Python interpreter
Press Ctrl+Alt+S to open the IDE settings and select Project <project name> | Python Interpreter.
Expand the list of the available interpreters and click the Show All link. Alternatively, click the icon and select Show All.
Select the target interpreter and click Edit.
You can specify an alternative interpreter name for the selected interpreter. The Python interpreter name specified in the Name field, becomes visible in the list of available interpreters. Click OK to apply the changes.
For remote interpreters (that are available in PyCharm Professional) you can modify configuration parameters.
Press Ctrl+Alt+S to open the project Settings/Preferences and go to Project <project name> | Python Interpreter. Then click the icon and select Add.
Choose the interpreter type to add and perform the specific settings:
In the left-hand pane of the Add Python Interpreter dialog, select Virtualenv Environment. The following actions depend on whether the virtual environment existed before.
If New environment is selected:
Specify the location of the new virtual environment in the text field, or click and find location in your file system. Note that the directory where the new virtual environment should be located, must be empty!
Choose the base interpreter from the list, or click and find a Python executable in the your file system.
If PyCharm detects no Python on your machine, it provides two options: to download the latest Python versions from python.org or to specify a path to the Python executable (in case of non-standard installation).
Select the Inherit global site-packages checkbox if you want that 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.
Select the Make available to all projects checkbox if you want to reuse this environment when creating Python interpreters in PyCharm.
If Existing environment is selected:
Expand the Interpreter list and select any of the existing interpreters. Alternatively, click and specify a path to the Python executable in your file system, for example, C:\Python36\python.exe.
Select the Make available to all projects checkbox if you want to reuse this environment when creating Python interpreters in PyCharm.
If you have added the user base’s 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.
Click OK to complete the task.
If you have not modified the PATH variable, PyCharm shows an error message: Pipenv executable is not found. Discover the proper executable path as described in the pipenv installation procedure and enter the target string in the Pipenv executable field, for example: C:\Users\jetbrains\AppData\Roaming\Python\Python37\Scripts\pipenv.exe (Windows) or /Users/jetbrains/.local/bin/pipenv (macOS).
Click OK to save the changes and complete the task.
In the left-hand pane of the Add Python Interpreter dialog, select Conda Environment. The following actions depend on whether the Conda environment existed before.
If New environment is selected:
Specify the location of the new Conda environment in the text field, or click and find location in your file system. Note that the directory where the new Conda environment should be located, must be empty!
Select the Python version from the list.
Specify the location of the Conda executable file in the text field, or click and find location in the Conda installation directory. You're basically looking for a path that you've used when installing Conda on your machine.
Select the Make available to all projects checkbox if you want to reuse this environment when creating Python interpreters in PyCharm.
If Existing environment is selected:
Expand the Interpreter list and select any of the existing interpreters. Alternatively, click and specify a path to the Conda executable in your file system, for example, C:\Users\jetbrains\Anaconda3\python.exe.
Select the Make available to all projects checkbox if you want to reuse this environment when creating Python interpreters in PyCharm.
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 and click OK.
If PyCharm detects no Python on your machine, it provides two options: to download the latest Python versions from python.org or to specify a path to the Python executable (in case of non-standard installation).
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 Next to proceed with the final configuration step.
In the next dialog window, verify the path to the desired Python interpreter. You can accept default, or specify a different one. You have to configure the path mappings between your local project and the server. To do that, click next to the Sync folders field and enter the path to the local project folder and the path to the folder on the remote server.
You can also select the lowest checkbox to enable automatic upload of the local changes to the remote server.
Select the Linux distribution and specify the path to the python executable in the selected Linux distribution. Typically, you should be looking for wsl.exe but you can specify any non default WSL distro.
In the dialog that opens, select the Docker option, from the drop-down lists select the Docker server (if the server is missing, click New...), and specify the image name: python:latest.
Python interpreter path should have the default value:
In the dialog that opens, select the Docker Compose option, from the drop-down lists select the Docker server, Docker Compose service (here web), configuration file (here docker-compose.yml) and Python interpreter path (here python).
Why we've chosen web? This choice is explained by the fact, that after configuring a Docker-Compose-based interpreter, we'll be able to create regular run configurations that will alter the behavior of the container we selected. Therefore, if we want to debug the code in a container, that's the one we should select here.
Next, wait while PyCharm starts your Docker Compose configuration to scan and index:
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.
Setting the default interpreter
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.
icon and select Show All. 
and find location in your file system. Note that the directory where the new virtual environment should be located, must be empty!
and in the Select Python Interpreter dialog that opens, choose the desired Python executable and click OK.
and suggests to upgrade it.