/pyflame2

🔥 Pyflame: A Ptracing Profiler For Python

Primary LanguageC++Apache License 2.0Apache-2.0

Pyflame: A Ptracing Profiler For Python

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Pyflame is a high performance profiling tool that generates flame graphs for Python. Pyflame is implemented in C++, and uses the Linux ptrace(2) system call to collect profiling information. It can take snapshots of the Python call stack without explicit instrumentation, meaning you can profile a program without modifying its source code. Pyflame is capable of profiling embedded Python interpreters like uWSGI. It fully supports profiling multi-threaded Python programs.

Pyflame usually introduces significantly less overhead than the builtin profile (or cProfile) modules, and emits richer profiling data. The profiling overhead is low enough that you can use it to profile live processes in production.

Full Documentation: https://pyflame.readthedocs.io

pyflame

Quickstart

Building And Installing

For Debian/Ubuntu, install the following:

# Install build dependencies on Debian or Ubuntu.
sudo apt-get install autoconf automake autotools-dev g++ pkg-config python-dev python3-dev libtool make

Once you have the build dependencies installed:

./autogen.sh
./configure
make

The make command will produce an executable at src/pyflame that you can run and use.

Or you can use docker to build pyflame

sudo docker build --tag pyflame .
sudo docker run -it -v $(pwd):/root/pyflame pyflame /bin/bash -c "cd /root/pyflame;./autogen.sh;./configure;make"

This will also produce the executable at src/pyflame, which support py2.6/2.7/3.4/3.5/3.6/3.7

Optionally, if you have virtualenv installed, you can test the executable you produced using make check.

Using Pyflame

The full documentation for using Pyflame is here. But here's a quick guide:

# Attach to PID 12345 and profile it for 1 second
pyflame -p 12345

# Attach to PID 768 and profile it for 5 seconds, sampling every 0.01 seconds
pyflame -s 5 -r 0.01 -p 768

# Run py.test against tests/, emitting sample data to prof.txt
pyflame -o prof.txt -t py.test tests/

In all of these cases you will get flame graph data on stdout (or to a file if you used -o). This data is in the format expected by flamegraph.pl, which you can find here.

FAQ

The full FAQ is here.

What's The Deal With (idle) Time?

Full answer here. tl;dr: use the -x flag to suppress (idle) output.

What About These Ptrace Errors?

See here.

How Do I Profile Threaded Applications?

Use the --threads option.

Is There A Way To Just Dump Stack Traces?

Yes, use the -d option.