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docs\contributing.rst (1956, 2019-12-03)
docs\faq.rst (6902, 2019-12-03)
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docs\index.rst (2266, 2019-12-03)
docs\installation.rst (3777, 2019-12-03)
docs\man.md (3942, 2019-12-03)
docs\pyflame.man (4529, 2019-12-03)
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# Pyflame: A Ptracing Profiler For Python [](https://travis-ci.org/uber/pyflame) [](http://pyflame.readthedocs.io/en/latest/?badge=latest) [](https://copr.fedorainfracloud.org/coprs/eklitzke/pyflame/) (This project is deprecated and not maintained.) Pyflame is a high performance profiling tool that generates [flame graphs](http://www.brendangregg.com/flamegraphs.html) for Python. Pyflame is implemented in C++, and uses the Linux [ptrace(2)](http://man7.org/linux/man-pages/man2/ptrace.2.html) 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](https://uwsgi-docs.readthedocs.io/en/latest/). 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  ## Quickstart ### Building And Installing For Debian/Ubuntu, install the following: ```bash # 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: ```bash ./autogen.sh ./configure make ``` The `make` command will produce an executable at `src/pyflame` that you can run and use. 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](https://pyflame.readthedocs.io/en/latest/usage.html). But here's a quick guide: ```bash # 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](https://github.com/brendangregg/FlameGraph). ## FAQ The full FAQ is [here](https://pyflame.readthedocs.io/en/latest/faq.html). ### What's The Deal With (idle) Time? Full answer [here](https://pyflame.readthedocs.io/en/latest/faq.html#what-is-idle-time). tl;dr: use the `-x` flag to suppress (idle) output. ### What About These Ptrace Errors? See [here](https://pyflame.readthedocs.io/en/latest/faq.html#what-are-these-ptrace-permissions-errors). ### How Do I Profile Threaded Applications? Use the `--threads` option. ### Is There A Way To Just Dump Stack Traces? Yes, use the `-d` option.

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