Skip to content


Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?


Failed to load latest commit information.
Latest commit message
Commit time
January 17, 2020 11:57
March 7, 2023 12:16
January 31, 2020 15:09
January 17, 2020 11:57
November 30, 2021 14:34
January 17, 2020 11:57
January 17, 2020 11:57
January 17, 2020 11:57
January 17, 2020 11:57
March 6, 2023 15:36
November 19, 2019 12:05
December 13, 2022 13:11

debugpy - a debugger for Python

An implementation of the Debug Adapter Protocol for Python 3.

Build Status GitHub PyPI PyPI


OS Coverage
Windows Azure DevOps coverage
Linux Azure DevOps coverage
Mac Azure DevOps coverage

debugpy CLI Usage

Debugging a script file

To run a script file with debugging enabled, but without waiting for the client to attach (i.e. code starts executing immediately):

-m debugpy --listen localhost:5678

To wait until the client attaches before running your code, use the --wait-for-client switch.

-m debugpy --listen localhost:5678 --wait-for-client

The hostname passed to --listen specifies the interface on which the debug adapter will be listening for connections from DAP clients. It can be omitted, with only the port number specified:

-m debugpy --listen 5678 ...

in which case the default interface is

To be able to attach from another machine, make sure that the adapter is listening on a public interface - using will make it listen on all available interfaces:

-m debugpy --listen

This should only be done on secure networks, since anyone who can connect to the specified port can then execute arbitrary code within the debugged process.

To pass arguments to the script, just specify them after the filename. This works the same as with Python itself - everything up to the filename is processed by debugpy, but everything after that becomes sys.argv of the running process.

Debugging a module

To run a module, use the -m switch instead of filename:

-m debugpy --listen localhost:5678 -m mymodule

Same as with scripts, command line arguments can be passed to the module by specifying them after the module name. All other debugpy switches work identically in this mode; in particular, --wait-for-client can be used to block execution until the client attaches.

Attaching to a running process by ID

The following command injects the debugger into a process with a given PID that is running Python code. Once the command returns, a debugpy server is running within the process, as if that process was launched via -m debugpy itself.

-m debugpy --listen localhost:5678 --pid 12345

Ignoring subprocesses

The following command will ignore subprocesses started by the debugged process.

-m debugpy --listen localhost:5678 --pid 12345 --configure-subProcess False

debugpy Import usage

Enabling debugging

At the beginning of your script, import debugpy, and call debugpy.listen() to start the debug adapter, passing a (host, port) tuple as the first argument.

import debugpy
debugpy.listen(("localhost", 5678))

As with the --listen command line switch, hostname can be omitted, and defaults to "":


Waiting for the client to attach

Use the debugpy.wait_for_client() function to block program execution until the client is attached.

import debugpy
debugpy.wait_for_client()  # blocks execution until client is attached

breakpoint() function

Where available, debugpy supports the standard breakpoint() function for programmatic breakpoints. Use debugpy.breakpoint() function to get the same behavior when breakpoint() handler installed by debugpy is overridden by another handler. If the debugger is attached when either of these functions is invoked, it will pause execution on the calling line, as if it had a breakpoint set. If there's no client attached, the functions do nothing, and the code continues to execute normally.

import debugpy

while True:
    breakpoint()  # or debugpy.breakpoint()

Debugger logging

To enable debugger internal logging via CLI, the --log-to switch can be used:

-m debugpy --log-to path/to/logs ...

When using the API, the same can be done with debugpy.log_to():


In both cases, the environment variable DEBUGPY_LOG_DIR can also be set to the same effect.

When logging is enabled, debugpy will create several log files with names matching debugpy*.log in the specified directory, corresponding to different components of the debugger. When subprocess debugging is enabled, separate logs are created for every subprocess.