Do not hang around in Pythran code base without your developer guide! It is the compass that will guide you in the code jungle!
This document is a never ending work-in-progress draft. Please contribute!
Pythran can be configured with a rc file. An example is found in pythran/pythran.cfg. Look at it! To customize it:
$> cp pythran/pythran.cfg ~/.pythranrc
In particular, you may want to add -g -O0
to the cxxflags
.
All Python code must be conform to the PEP 8, and the flake8
command must not
yield any message when run on our database. Additionally, avoid backslashes,
and try to make your code as concise as possible.
$> flake8 pythran/.py pythran//.py –exclude=”pythran/tests/test.py,__init__.py”
C++ code use spaces (no tabs) and a tab width of 4.
Listing the top level directory yields the following entries:
PyPI
entries
and such.If you’re reading this document, you know what it’s all about! MANUAL
is the user documentation and DEVGUIDE
is the developer documentation.
Use make
from this directory to produce the static website.
pythran
uses the unittest
module and the pytest package to manage test cases. The whole
validation suite is run through the command:
$> python -m pytest pythran/tests
To run it faster we use the pytest
extension xdist, the test suite will run using all
available cores. Otherwise it might run very slowly, something like four
hours on a decent laptop :’(.
Note that it is possible to use the pytest
module to pass a subset of the
test suite:
$> pytest -n 8 pythran/tests/test_list.py
runs all the tests found in pythran/tests/test_list.py
.
Only compiler tests can be check using test filtering:
$> pytest -n 8 pythran/tests -m "not module"
There are two kinds of tests in pythran
:
unit tests that test a specific feature of the implementation. Such tests
are listed as method of a class deriving from test_env.TestEnv
and must
call the run_test(function_to_translate, *effective_parameters,
**name_to_signature)
method [1]. It translates function_to_translate
into a native function using the type annotations given in the
name_to_signature
dictionary, runs both the python and the native
version with effective_parameters
as arguments and asserts the results
are the same.
[1] | See examples in |
test cases that are just plain python modules to be converted in native
module by pythran
. It is used to test complex situations, codes or
benchmarks found on the web etc. They are just translated, not run. These
test cases lie in pythran/tests/cases/
and are listed in
pythran/tests/test_cases.py
.
The C++ code generated by pythran
relies on a specific back-end,
pythonic
. It is a set of headers that mimics Python’s intrinsics and
collections behavior in C++. It lies in pythran/pythonic/
. There is one
directory per module, e.g. pythran/pythonic/numpy
for the numpy
module,
and one file per function, e.g. pythran/pythonic/numpy/ones.hpp
for the
numpy.ones
function. Type definitions are stored in the seperate
pythran/pythonic/types
directory, one header per type. Each function header
must be #includ
-able independently, i.e. it itself includes all the type
and function definition it needs. This helps keeping compilation time low.
All Pythran functions and types live in the pythonic
namespace. Each extra
module defines a new namespace, like pythonic::math
or
pythonic::random
, and each type is defined in the pythonic::types
namespace. The DECLARE_FUNCTOR
and DEFINE_FUNCTOR
macros from
pythonic/utils/functor.hpp
is commonly used to convert functions into
functors and put them into the mandatory functor
namespace.
The pythonic runtime can be used without Python support, so it is important to
protect all Python-specific stuff inside ENABLE_PYTHON_MODULE
guard.
All methods are represented by functions in Pythran. The associated
pseudo-modules are prefixed and suffixed by a double underscore __
, as in
pythran/pythonic/__list__
.
Stand-alone algorithms are put into pythran/tests/cases
. They must be valid
Pythran input (including spec annotations). To be taken into account by the
validation suite, they must be listed in pythran/tests/test_cases.py
. To be
taken into account by the benchmarking suite, they must have a line starting
with the #runas
directive. Check pythran/tests/matmul.py
for a complete
example.
To run the benchmark suite, one can rely on:
$> python setup.py bench --mode=<mode>
where <mode> is one among:
setup.py
.All measurements are made using the timeit
module. The number of iterations
is customizable through the --nb-iter
switch.
Add support for a new module: | |
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Add a new analysis: | |
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Push changes into the holy trunk: | |
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