Debugging Python with VS Code

The Python extension supports debugging of a number of types of Python applications. For a short walkthrough of basic debugging, see Tutorial - Configure and run the debugger.

To familiarize yourself with VS Code's general debugging capabilities, such as examining local variables, the watch window, arguments, breakpoints, and more, review VS Code debugging. This present article addresses only those considerations that are specific to Python, mainly Python-specific debugging configurations.

Initializing Python debugging configurations

The behavior of the VS Code debugger when working with Python is driven by a configuration. Configurations are defined in a launch.json file that's stored in a .vscode folder in your workspace.

To initialize debug configurations, first select the Debug View in the sidebar:

If you don't yet have any configurations defined, you'll see "No Configurations" in the drop-down list, and a dot on the settings icon:

To generate a launch.json file with Python configurations, do the following steps:

1. Select the settings button (circled in the image above) or use the Debug > Open configurations menu command.

2. In the list of debuggers that appears, select Python. (You can also use Python Experimental if you'd like, which is work in progress. See Issue 538 (GitHub).)

3. The Python extension then creates and opens a launch.json file that contains number of pre-defined configurations.

You can always open launch.json from the Explorer, or use the Debug View settings icon. You're also free to add any other configurations you want. It's often helpful in a project to create a configuration that runs a specific startup file. For example, if you always want to always launch startup.py whenever you start the debugger, create a configuration entry as follows:

{
    "name": "Python: startup.py",
    "type": "python",
    "request": "launch",
    "program": "${workspaceFolder}/startup.py",
},

The details of configuration properties are covered later in this article under Standard configuration and options. Additional configurations are also described in this article under Debugging specific app types.

Choose a configuration

To select a debugging configuration, select the Debug View in the sidebar, then select an option of your choice from the drop-down list:

While debugging, the Status Bar shows the current configuration on the lower left, with the current debugging interpreter to the right. Selecting the configuration brings up the list from which you can choose a different configuration:

By default, the debugger uses the same python.pythonPath workspace setting as for other features of VS Code. To use a different interpreter for debugging specifically, set the value for pythonPath in the applicable debugger configuration. Alternately, select the named interpreter on the Status Bar to select a different one.

Note: The debugger settings don't support relative paths, including when relying on the main python.pythonPath setting. To work around this, use an environment variable, or create a variable such as ${workspaceFolder} that resolves to your project folder, then use that variable in the path, as in "python.pythonPath": "${workspaceFolder}/venv/bin/python".

Standard configuration and options

Standard configuration for launch.json:

{
    "name": "Python: Current File",
    "type": "python",
    "request": "launch",
    "program": "${file}",
}

Custom configurations for various settings are described in the following sections.

name

Provides the name for the debug configuration that appears in the VS Code drop-down list.

type

Identifies the type of debugger to use; leave this set to python for Python code.

request

Specifies the mode in which to start debugging:

• launch: start the debugger on the file specified in program
• attach: attach the debugger to an already running process. See Remote debugging for an example.

program

Provides the fully qualified path to the python program's entry module (startup file). The value ${file}, often used in default configurations, uses the currently active file in the editor. By specifying a specific startup file, you can always be sure of launching your program with the same entry point regardless of which files are open. For example:

"program": "/Users/Me/Projects/PokemonGo-Bot/pokemongo_bot/event_handlers/__init__.py",

You can also rely on a relative path from the workspace root. For example, if the root is /Users/Me/Projects/PokemonGo-Bot then you can use the following:

"program": "${workspaceFolder}/pokemongo_bot/event_handlers/__init__.py",

pythonPath

Points to the Python interpreter to be used for debugging, which can be a folder containing a Python interpreter. The value can use variables like ${workspaceFolder} and ${workspaceFolder}/.venv.

If not specified, this setting defaults to the interpreter identified in the python.pythonPath setting, which is equivalent to using the value ${config:python.pythonPath}. To use a different interpreter, specify its path instead.

You can specify platform-specific paths by placing pythonPath within a parent object named osx, windows, or linux. For example, the configuration for PySpark uses the following values:

"osx": {
    "pythonPath": "^\"\\${env:SPARK_HOME}/bin/spark-submit\""
},
"windows": {
    "pythonPath": "^\"\\${env:SPARK_HOME}/bin/spark-submit.cmd\""
},
"linux": {
    "pythonPath": "^\"\\${env:SPARK_HOME}/bin/spark-submit\""
},

Alternately, you can use a custom environment variable that's defined on each platform to contain the full path to the Python interpreter to use, so that no additional folder paths are needed.

args

Specifies arguments to pass to the Python program. Each argument should be contained within quotes, for example:

"args": [
    "--quiet", "--norepeat"
],

stopOnEntry

When set to true, breaks the debugger at the first line of the program being debugged. If omitted (the default) or set to false, the debugger runs the program to the first breakpoint.

console

Specifies how program output is displayed.

cwd

Specifies the current working directory for the debugger, which is the base folder for any relative paths used in code. If omitted, defaults to ${workspaceFolder} (the folder open in VS Code).

As an example, say ${workspaceFolder} contains a py_code folder containing app.py, and a data folder containing salaries.csv. If you start the debugger on py_code/app.py, then the relative paths to the data file vary depending on the value of cwd:

debugOptions

An array of additional options that may contain the following:

env

Sets optional environment variables for the debugger process beyond system environment variables, which the debugger always inherits.

envFile

Optional path to a file that contains environment variable definitions. See Configuring Python environments - environment variable definitions file.

Remote debugging

Remote debugging allows you to step through a program locally within VS Code while it runs on a remote computer. It is not necessary to install VS Code on the remote computer.

1. Both computers: make sure that identical source code is available.

2. Both computers: install ptvsd 3.0.0 using pip3 install ptvsd==3.0.0 (Mac/Linux) or pip install ptvsd==3.0.0 (Windows). Version 3.0.0 is specifically required; later versions are not yet supported.

3. Remote computer: open the port you wish to use for debugging in the appropriate firewall or other networking configuration.

4. Remote computer: in the source code, add the following lines, replacing my_secret with a passphrase that you'll use to authenticate remote debugging, and replacing address with the remote computer's IP address and port number (IP address 1.2.3.4 is shown here for illustration only).

   import ptvsd
   
   # Allow other computers to attach to ptvsd at this IP address and port, using the secret
   ptvsd.enable_attach("my_secret", address = ('1.2.3.4', 3000))
   
   # Pause the program until a remote debugger is attached
   ptvsd.wait_for_attach()
   

   The IP address used in enable_attach should be the remote computer's private IP address, if applicable (Linux VMs on Azure, for example, have both a public and private address). If you use the public IP address, you might see the error "Cannot assign requested address".

5. Local computer: in the source code, add a commented-out copy of the same code added on the remote computer. Adding these lines makes sure that the source code on both computers matches line by line.

   #import ptvsd
   
   # Allow other computers to attach to ptvsd at this IP address and port, using the secret
   #ptvsd.enable_attach("my_secret", address = ('1.2.3.4', 3000))
   
   # Pause the program until a remote debugger is attached
   #ptvsd.wait_for_attach()
   

6. Local computer: switch to Debug View in VS Code, select the Python: Attach configuration, then select the settings (gear) icon to open launch.json to that configuration.

7. Local computer: Modify the configuration so that remoteRoot provide the location of the program on the remote computer's file system. Also modify host, port, and secret to match the values in the ptvsd.enable_attach call added to the source code, except that you need to use the remote computer's public IP address for host. You might also change name to specifically identify the configuration. For example:

   {
       "name": "Python Attach (Remote Debug 1.2.3.4)",
       "type": "python",
       "request": "attach",
       "localRoot": "${workspaceFolder}",
       "remoteRoot": "c:\\py\\hello",  // Set to the program location on the remote computer.
       //"remoteRoot": "~/hello",      // Linux example
       "port": 3000,                   // Set to the remote port
       "secret": "my_secret",          // Set to your specific secret
       "host": "1.2.3.4"               // Set to your remote host's public IP address
   }
   

   *Tip: If the remoteRoot path is the same as the local computer, you can use ${workspaceFolder} as the value for remoteRoot.

8. Remote computer: start the program from the command line, which should pause on the ptvsd.wait_for_attach() call. Note that you don't run the program inside a debugger like VS Code. The ptvsd library is providing the remote debugging capabilities directly.

9. Local computer: set a breakpoint in the code where you want to start debugging.

   Tip: setting a single breakpoint on the statement immediately following the ptvsd.wait_for_attach() line may not work. Set at least one other breakpoint on another statement.

10. Local computer: start the VS Code debugger using the modified Python Attach configuration. VS Code should stop on your locally-set breakpoints, allowing you to step through the code, examine variables, and perform all other debugging actions. Expressions that you enter in the Debug Console are run on the remote computer as well.

    Text output to stdout, as from print statements, appear on both computers. Other output, such as graphical plots from a package like matplotlib, however, appear only on the remote computer.

11. During remote debugging, the debugging toolbar appears as below:

    

    On this toolbar, the disconnect button (⇧F5 (Windows, Linux Shift+F5)) stops the debugger and allows the remote program to run to completion. The restart button (⇧⌘F5 (Windows, Linux Ctrl+Shift+F5)) restarts the debugger on the local computer but does not restart the remote program. You use the restart button only when you've already restarted the remote program and need to reattach the debugger.

Debugging over SSH

In some cases you may want or need to use a secure connection to the remote computer when debugging. On Windows computers, you may need to install OpenSSH to have the ssh command.

On the remote computer:

1. Enable port forwarding by opening the sshd_config config file (found under /etc/ssh/ on Linux and under %programfiles(x86)%/openssh/etc on Windows) and modifying the following setting:

   AllowTcpForwarding yes
   

2. Start the program and let it wait at the ptvsd.wait_for_attach() call as described in the previous section.

On the local computer:

1. Run ssh -L sourceport:localhost:destinationport user@remoteaddress using a selected port for destinationport and the appropriate username and the remote computer's IP address in user@remoteaddress. For example, to use port 3000 on IP address 1.2.3.4, the command would be ssh -L 3000:localhost:3000 user@1.2.3.4.

2. Verify that you can see a prompt in the SSH session.

3. In VS Code, set the port in the debug configuration of launch.json to match the port used in the ssh command.

4. Launch the program and attach the debugger as described in the previous section.

Debugging specific app types

The configuration drop-down provides a variety of different options for general app types:

Specific steps are also needed for remote debugging and Google App Engine. For details on debugging unit tests (including nosetest), see Unit testing.

To debug an app that requires administrator privileges, use "console": "externalTerminal" and include "Sudo" in debugOptions.

Flask debugging

{
    "name": "Python: Flask (0.11.x or later)",
    "type": "python",
    "request": "launch",
    "module": "flask",
    "env": {
        "FLASK_APP": "app.py"
    },
    "args": [
        "run",
        "--no-debugger",
        "--no-reload"
    ]
},

As you can see, this configuration specifies "env": {"FLASK_APP": "app.py"} and "args": ["run", "--no-debugger","--no-reload"]. The "module": "flask" property is used instead of program. (You may see "FLASK_APP": "${workspaceFolder}/app.py" in the env property, in which case modify the configuration to refer to only the filename. Otherwise you may see "Cannot import module C" errors where C is a drive letter.)

If you want to run Flask's development server in development mode, use the following configuration:

{
    "name": "Python: Flask (development mode)",
    "type": "python",
    "request": "launch",
    "module": "flask",
    "env": {
        "FLASK_APP": "app.py",
        "FLASK_ENV": "development"
    },
    "args": [
        "run"
    ]
},

Google App Engine debugging

Google App Engine launches an app by itself, so launching it in the VS Code debugger isn't directly possible. What's required instead is to use ptvsd in the app and then launch Google App Engine in a mode that allows VS Code to attach its debugger.

1. Download ptvsd and extract its files into a ptvsd folder in your working folder. (If using a different folder, modify the path in the pydev_startup.py file created in step 4).

2. Create a tasks.json file with the following contents:

   {
       "version": "2.0.0",
       "tasks": [
           {
               "label": "Launch Google App Engine",
               "command": "python",
               "type": "shell",
               "args": [
                   "/usr/local/google_appengine/dev_appserver.py",
                   "--python_startup_script=${workspaceFolder}/pydev_startup.py",
                   "--automatic_restart=no",
                   "--max_module_instances=default:1",
                   "${workspaceFolder}/app.yaml"
               ]
           }
       ]
   }
   

3. On Windows and Linux, replace the first item in args with the path to wherever Google App Engine is installed (the path shown in the source code above is for macOS).

4. Create a file named pydev_startup.py in your project root with the following contents, modified as noted:

   import sys
   import os
   
   #Assuming that pdvsd is located in the working folder
   sys.path.append(os.getcwd())
   
   import ptvsd
   # Modify the secret and port number as desired; you're debugging locally so the values don't matter.
   # However, be sure the port is not blocked on your computer.
   ptvsd.enable_attach(secret = 'gae', address = ('0.0.0.0', 3000))
   
   #The debug server has started and you can now use VS Code to attach to the application for debugging
   print("Google App Engine has started, ready to attach the debugger")
   

5. Create a launch.json configuring using the Attach (Remote Debug) configuration as a template. Make sure the secret and port values match what's in the source code above.

6. Add "preLaunchTask": "python" to launch.json.

7. From the Command Palette, run the Run Build Task command. This opens the Tasks output window where you see various messages.

8. Once you see the message "Google App Engine has started, ready to attach the debugger", start the VS Code debugger using the remote debugging configuration.

9. Set breakpoints where you want, then start the browser to start the app.

Troubleshooting

There are many reasons why the debugger may not work. Oftentimes the debug console reveals specific causes, but two specific reasons are as follows:

• The path to the python executable is incorrect: check the value of pythonPath in your user settings.

• Invalid expressions in the watch window (see example below): clear all expressions from the Watch window and restart the debugger.

  Traceback (most recent call last):
    File ".../visualstudio_py_debugger.py", line 1646, in loop
      cmd()
    File ".../visualstudio_py_debugger.py", line 1918, in command_execute_code
      thread.run_on_thread(text, cur_frame, eid, frame_kind, repr_kind)
    File ".../visualstudio_py_debugger.py", line 1246, in run_on_thread
      self.schedule_work(lambda : self.run_locally(text, cur_frame, execution_id, frame_kind, repr_kind))
    File ".../visualstudio_py_debugger.py", line 1238, in schedule_work
      self.unblock()
    File ".../visualstudio_py_debugger.py", line 1234, in unblock
      self._block_lock.release()
  RuntimeError: release unlocked lock
  

Next steps

• Python environments - Control which Python interpreter is used for editing and debugging.
• Unit testing - Configure unit test environments and discover, run, and debug tests.
• Settings reference - Explore the full range of Python-related settings in VS Code.
• General debugging - Learn about the debugging features of VS Code.