Attaching to a running process#

Memray allows you to attach to a running process and to observe the allocations it performs once you’ve attached. This doesn’t allow you to see where memory was allocated before you attached to the process, but it does allow you to observe or record future allocations. This can be useful if an application is continuing to request more memory than you think it should need, and you want to figure out why. It can also be useful for observing the allocation patterns of a long running process once the process has already completed any initial warm up steps that it needs to do.

Basic Usage#

The general form of the attach subcommand is:

memray attach [options] <pid>

The only required argument for memray attach is a process ID to attempt to attach to. You must be able to attach a debugger to that process, and that process must be a Python process, and the Memray package must be installed in the environment that the process is running in. That is, memray attach will execute the Python statement import memray in the process being attached to, and that import must succeed for attaching to work.

By default this will open a live mode TUI showing the allocations that the process performs after you’ve attached, but you can instead provide the name of a capture file to write to with the -o option, allowing you to analyze the captured allocations with any Memray reporter you’d like. You can also provide most of the options that memray run accepts. See the CLI reference for details.

If you use the -o option, the process will continue recording allocations to the capture file even after memray attach has returned. Otherwise, allocations are tracked only for as long as the live mode TUI continues running. Once you quit the TUI, the attached process will stop tracking allocations. If you later reattach to the same process, it will start from a clean slate, and will not be aware of any allocations seen during your first TUI session.

Debugger Privileges#

Memray leverages a debugger for attaching to the process. It is compatible with both gdb and lldb, but one or the other must be installed in order for memray attach to work. Only a super user (either root, or a user with the CAP_SYS_PTRACE capability) can attach to processes run by another user. Further, security settings on modern Linux systems typically prevent a regular user from attaching even to their own processes. You can loosen that restriction by writing 0 to /proc/sys/kernel/yama/ptrace_scope as root, allowing any user to attach to their own processes. When running a Docker container, you can use --cap-add=SYS_PTRACE to allow attaching to processes within the container.


Allowing arbitrary processes to be traced is insecure, as it provides an easy vector for privilege escalation within a remote code execution attack. Be sure to consider the security implications before you choose to grant regular users the ability to attach to processes.

In some cases (like MacOS), the debugger may require you to authenticate with your username and password in order to attach to a process. In that case it is possible that a window will pop up asking for your password or for biometric authentication.


memray attach works by injecting executable code into a running process. We’ve tried to do this in the safest way possible, but we can’t guarantee that there aren’t edge cases where this might crash or deadlock the process that you’re attempting to attach to, depending on what it’s doing at the point when we attach. We advise only using this as a debugging tool on development machines.

If you attach to a Python 3.7 or Python 3.8 process that has never imported the threading module, the attached process will show an error when the interpreter finishes running the main script. This is due to a known bug that was not fixed until Python 3.9. From Python 3.9 onwards there will be no error on exit, but the interpreter will assign the wrong name to the main thread if threading is later imported by the script. That should not have any major effect on the behavior of the program.

If you do find some case where memray attach either doesn’t work or causes a crash or deadlock, we want to hear about it! Please file a bug report explaining what went wrong. If the issue is reproducible, please try running memray attach with the --verbose flag, which outputs a lot of extra debugging information, including the output of the debugger session that was used to inject our code into the remote process. If the process crashed and left a core file, please include a stack trace of all of the threads in the process, so that we can understand what state it was in when we tried to attach. You can show all threads’ stacks using thread apply all bt in gdb or thread backtrace all in lldb.

CLI Reference#

usage: memray attach [-h] [-o FILE] [-f] [--native] [--follow-fork] [--trace-python-allocators] [--compress-on-exit | --no-compress] [--method {auto,gdb,lldb}] [-v] pid

Positional Arguments#


Remote pid to attach to

Named Arguments#

-o, --output

Capture allocations into the given file instead of starting a live tracking session

-f, --force

If the output file already exists, overwrite it

Default: False


Track native (C/C++) stack frames as well

Default: False


Record allocations in child processes forked from the tracked script

Default: False


Record allocations made by the Pymalloc allocator

Default: False


Compress the resulting file using lz4 after tracking completes

Default: True


Do not compress the resulting file using lz4

Default: False


Possible choices: auto, gdb, lldb

Method to use for injecting code into the process to track

Default: “auto”

-v, --verbose

Print verbose debugging information.

Default: False

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