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99 lines
3.1 KiB
99 lines
3.1 KiB
Benchmark
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=========
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The following is the result of a synthetic benchmark comparing both compilation
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time and module size of pybind11 against Boost.Python. A detailed report about a
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Boost.Python to pybind11 conversion of a real project is available here: [#f1]_.
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.. [#f1] http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf
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Setup
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-----
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A python script (see the ``docs/benchmark.py`` file) was used to generate a set
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of files with dummy classes whose count increases for each successive benchmark
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(between 1 and 2048 classes in powers of two). Each class has four methods with
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a randomly generated signature with a return value and four arguments. (There
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was no particular reason for this setup other than the desire to generate many
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unique function signatures whose count could be controlled in a simple way.)
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Here is an example of the binding code for one class:
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.. code-block:: cpp
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...
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class cl034 {
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public:
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cl279 *fn_000(cl084 *, cl057 *, cl065 *, cl042 *);
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cl025 *fn_001(cl098 *, cl262 *, cl414 *, cl121 *);
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cl085 *fn_002(cl445 *, cl297 *, cl145 *, cl421 *);
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cl470 *fn_003(cl200 *, cl323 *, cl332 *, cl492 *);
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};
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...
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PYBIND11_PLUGIN(example) {
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py::module m("example");
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...
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py::class_<cl034>(m, "cl034")
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.def("fn_000", &cl034::fn_000)
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.def("fn_001", &cl034::fn_001)
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.def("fn_002", &cl034::fn_002)
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.def("fn_003", &cl034::fn_003)
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...
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return m.ptr();
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}
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The Boost.Python version looks almost identical except that a return value
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policy had to be specified as an argument to ``def()``. For both libraries,
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compilation was done with
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.. code-block:: bash
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Apple LLVM version 7.0.2 (clang-700.1.81)
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and the following compilation flags
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.. code-block:: bash
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g++ -Os -shared -rdynamic -undefined dynamic_lookup -fvisibility=hidden -std=c++14
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Compilation time
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----------------
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The following log-log plot shows how the compilation time grows for an
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increasing number of class and function declarations. pybind11 includes many
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fewer headers, which initially leads to shorter compilation times, but the
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performance is ultimately fairly similar (pybind11 is 19.8 seconds faster for
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the largest largest file with 2048 classes and a total of 8192 methods -- a
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modest **1.2x** speedup relative to Boost.Python, which required 116.35
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seconds).
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.. only:: not latex
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.. image:: pybind11_vs_boost_python1.svg
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.. only:: latex
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.. image:: pybind11_vs_boost_python1.png
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Module size
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-----------
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Differences between the two libraries become much more pronounced when
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considering the file size of the generated Python plugin: for the largest file,
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the binary generated by Boost.Python required 16.8 MiB, which was **2.17
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times** / **9.1 megabytes** larger than the output generated by pybind11. For
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very small inputs, Boost.Python has an edge in the plot below -- however, note
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that it stores many definitions in an external library, whose size was not
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included here, hence the comparison is slightly shifted in Boost.Python's
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favor.
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.. only:: not latex
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.. image:: pybind11_vs_boost_python2.svg
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.. only:: latex
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.. image:: pybind11_vs_boost_python2.png
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