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PyStack

Print the stack trace of a running Python process, or of a Python core dump.

PyStack is a tool that uses forbidden magic to let you inspect the stack frames of a running Python process or a Python core dump, helping you quickly and easily learn what it's doing (or what it was doing when it crashed) without having to interpret nasty CPython internals.

What PyStack can do

PyStack has the following amazing features:

💻 Works with both running processes and core dump files.
🧵 Shows if each thread currently holds the Python GIL, is waiting to acquire it, or is currently dropping it.
🗑️ Shows if a thread is running a garbage collection cycle.
🐍 Optionally shows native function calls, as well as Python ones. In this mode, PyStack prints the native stack trace (C/C++/Rust function calls), except that the calls to Python callables are replaced with frames showing the Python code being executed, instead of showing the internal C code the interpreter used to make the call.
🔍 Automatically demangles symbols shown in the native stack.
📈 Includes calls to inlined functions in the native stack whenever enough debug information is available.
🔍 Optionally shows the values of local variables and function arguments in Python stack frames.
🔒 Safe to use on running processes. PyStack does not modify any memory or execute any code in a process that is running. It simply attaches just long enough to read some of the process's memory.
⚡ Optionally, it can perform a Python stack analysis without pausing the process at all. This minimizes impact to the debugged process, at the cost of potentially failing due to data races.
🚀 Super fast! It can analyze core files 10x faster than general-purpose tools like GDB.
🎯 Even works with aggressively optimized Python interpreter binaries.
🔍 Even works with Python interpreters' binaries that do not have symbols or debug information (Python stack only).
💥 Tolerates memory corruption well. Even if the process crashed due to memory corruption, PyStack can usually reconstruct the stack.
💼 Self-contained: it does not depend on external tools or programs other than the Python interpreter used to run PyStack itself.

What platforms are supported?

At this time only Linux is supported.

Building from source

If you wish to build PyStack from source, you need the following binary dependencies in your system:

libdw
libelf

Note that sometimes both libraries are provided together as part of a distribution's elfutils package.

Check your package manager on how to install these dependencies (e.g., apt-get install libdw-dev libelf-dev in Debian-based systems). Note that you may need to tell the compiler where to find the header and library files of the dependencies for the build to succeed. If pkg-config is available (e.g. apt-get install pkg-config on Debian-based systems), it will automatically be used to locate the libraries and configure the correct build flags. Check your distribution's documentation to determine the location of the header and library files or for more detailed information. When building on Alpine Linux (or any other distribution that doesn't use glibc) you'll need elfutils 0.188 or newer. You may need to build this from source if your distribution's package manager doesn't have it.

Once you have these binary dependencies installed, you can clone the repository and follow the typical build process for Python libraries:

git clone git@github.com:bloomberg/pystack.git pystack
cd pystack
python3 -m venv ../pystack-env/  # just an example, put this wherever you want
source ../pystack-env/bin/activate
python3 -m pip install --upgrade pip
python3 -m pip install -e .
python3 -m pip install -r requirements-test.txt -r requirements-extra.txt

This will install PyStack in the virtual environment in development mode (the -e of the last pip install command), and then install the Python libraries needed to test it, lint it, and generate its documentation.

If you plan to contribute back, you should install the pre-commit hooks:

pre-commit install

This will ensure that your contribution passes our linting checks.

Documentation

You can find the full documentation here.

Usage

PyStack uses distinct subcommands for analyzing running processes and core dump files.

usage: pystack [-h] [-v] [--no-color] {remote,core} ...

Get Python stack trace of a remote process

options:
  -h, --help     show this help message and exit
  -v, --verbose
  --no-color     Deactivate colored output

commands:
  {remote,core}  What should be analyzed by PyStack (use <command> --help for a command-specific help section).
    remote       Analyze a remote process given its PID
    core         Analyze a core dump file given its location and the executable

Analyzing running processes

The remote command is used to analyze the status of a running (remote) process. The analysis is always done in a safe and non-intrusive way, as no code is loaded in the memory space of the process under analysis and no memory is modified in the remote process. This makes analysis using PyStack a great option even for those services and applications that are running in environments where the running process must not be impacted in any way (other than being temporarily paused, though --no-block can avoid even that). There are several options available:

usage: pystack remote [-h] [-v] [--no-color] [--no-block] [--native] [--native-all] [--locals] [--exhaustive] pid

positional arguments:
  pid            The PID of the remote process

options:
  -h, --help     show this help message and exit
  -v, --verbose
  --no-color     Deactivate colored output
  --no-block     do not block the process when inspecting its memory
  --native       Include the native (C) frames in the resulting stack trace
  --native-all   Include native (C) frames from threads not registered with the interpreter (implies --native)
  --locals       Show local variables for each frame in the stack trace
  --exhaustive   Use all possible methods to obtain the Python stack info (may be slow)

To use PyStack, you just need to provide the PID of the process:

$ pystack remote 112
Traceback for thread 112 [] (most recent call last):
    (Python) File "/test.py", line 17, in <module>
        first_func()
    (Python) File "/test.py", line 6, in first_func
        second_func()
    (Python) File "/test.py", line 10, in second_func
        third_func()
    (Python) File "/test.py", line 14, in third_func
        time.sleep(1000)

Analyzing core dumps

The core subcommand is used to analyze the status of a core dump file. Analyzing core files is very similar to analyzing processes but there are some differences, as the core file does not contain the totality of the memory that was valid when the program was live. In most cases, this makes no difference, as PyStack will try to adapt automatically. However, in some cases, you will need to specify extra command line options to help PyStack locate the information it needs. When analyzing cores, there are several options available:

usage: pystack core [-h] [-v] [--no-color] [--native] [--native-all] [--locals] [--exhaustive] [--lib-search-path LIB_SEARCH_PATH | --lib-search-root LIB_SEARCH_ROOT] core [executable]

positional arguments:
  core                  The path to the core file
  executable            (Optional) The path to the executable of the core file

options:
  -h, --help            show this help message and exit
  -v, --verbose
  --no-color            Deactivate colored output
  --native              Include the native (C) frames in the resulting stack trace
  --native-all          Include native (C) frames from threads not registered with the interpreter (implies --native)
  --locals              Show local variables for each frame in the stack trace
  --exhaustive          Use all possible methods to obtain the Python stack info (may be slow)
  --lib-search-path LIB_SEARCH_PATH
                        List of paths to search for shared libraries loaded in the core. Paths must be separated by the ':' character
  --lib-search-root LIB_SEARCH_ROOT
                        Root directory to search recursively for shared libraries loaded into the core.

In most cases, you just need to provide the location of the core to use PyStack with core dump files:

$ pystack core ./the_core_file
Using executable found in the core file: /usr/bin/python3.8

Core file information:
state: t zombie: True niceness: 0
pid: 570 ppid: 1 sid: 1
uid: 0 gid: 0 pgrp: 570
executable: python3.8 arguments: python3.8

The process died due receiving signal SIGSTOP
Traceback for thread 570 [] (most recent call last):
    (Python) File "/test.py", line 19, in <module>
        first_func({1: None}, [1,2,3])
    (Python) File "/test.py", line 7, in first_func
        second_func(x, y)
    (Python) File "/test.py", line 12, in second_func
        third_func(x, y)
    (Python) File "/test.py", line 16, in third_func
        time.sleep(1000)

Pystack

Install / Use

README