## Benchmarking with `hyperfine`

We use `hyperfine` to benchmark, especially comparing before and after to see the impact of a change: https://github.com/sharkdp/hyperfine.

When benchmarking, you must decide if you care about cold cache performance vs. warm cache (or both). If cold, use `--no-pantsd --no-process-execution-local-cache`. If warm, use hyperfine's option `--warmup=1`.

For example:

## Profiling with PySpy (TODO)

## Identifying the impact of Python's GIL (on macOS)

## Obtaining Full Thread Backtraces

Pants runs as a Python program that calls into a native Rust library. In debugging locking and deadlock issues, it is useful to capture dumps of the thread stacks in order to figure out where a deadlock may be occurring.

One-time setup:

1. Ensure that gdb is installed.

   • Ubuntu: `sudo apt install gdb`

2. Ensure that the kernel is configured to allow debuggers to attach to processes that are not in the same parent/child process hierarchy.

   • `echo 0 | sudo tee /proc/sys/kernel/yama/ptrace_scope`

   • To make the change permanent, add a file to /etc/sysctl.d named `99-ptrace.conf` with contents `kernel.yama.ptrace_scope = 0`. **Note: This is a security exposure if you are not normally debugging processes across the process hierarchy.**

3. Ensure that the debug info for your system Python binary is installed.

   • Ubuntu: `sudo apt install python3-dbg`

Dumping thread stacks:

1. Find the pants binary (which may include pantsd if pantsd is enabled).

   • Run: `ps -ef | grep pants`

2. Invoke gdb with the python binary and the process ID:

   • Run: `gdb /path/to/python/binary PROCESS_ID`

3. Enable logging to write the thread dump to `gdb.txt`: `set logging on`

4. Dump all thread backtraces: `thread apply all bt`

5. If you use pyenv to mange your Python install, a gdb script will exist in the same directory as the Python binary. Source it into gdb:

   • `source ~/.pyenv/versions/3.8.5/bin/python3.8-gdb.py` (if using version 3.8.5)

6. Dump all Python stacks: `thread apply all py-bt`