Skip to main content

Import C++ files directly from Python!

Project description

Import C or C++ files directly from Python!

Let’s try it out. First, if you’re on Linux or OS X, install with the terminal command pip install cppimport.

Most cppimport users combine it with pybind11, but you can use a range of methods to create your Python extensions. Raw C extensions, Boost.Python, SWIG all work. Let’s look at a simple C++ extension:

/*cppimport
<%
setup_pybind11(cfg)
%>
*/
#include <pybind11/pybind11.h>

namespace py = pybind11;

int square(int x) {
    return x * x;
}

PYBIND11_PLUGIN(somecode) {
    pybind11::module m("somecode", "auto-compiled c++ extension");
    m.def("square", &square);
    return m.ptr();
}

Save this code as somecode.cpp.

Open a python interpreter and run these lines [1]:

>>> import cppimport
>>> somecode = cppimport.imp("somecode") #This will pause for a moment to compile the module
>>> somecode.square(9)
81

I’m a big fan of the workflow that this enables, where you can edit both C++ files and Python and recompilation happens transparently.

I want things to be even easier! (Python import hook)

Modify the first section of the .cpp file and add “cppimport” on the first line of the file. This MUST be on the first line. This is explained further down.

/*cppimport
<%
setup_pybind11(cfg)
%>
*/

Then import the file using the import hook:

>>> import cppimport.import_hook
>>> import somecode #This will pause for a moment to compile the module
>>> somecode.square(9)
81

What’s actually going on?

The technical description: cppimport looks for a C or C++ source file that matches the requested module. If such a file exists, the file is first run through the Mako templating system. The compilation options produced by the Mako pass are then use to compile the file as a Python extension. The extension (shared library) that is produced is placed in the same folder as the C++ source file. Then, the extension is loaded.

Simpler language please: Sometimes Python just isn’t fast enough. Or you have existing code in a C++ library. So, you write a Python extension module, a library of compiled code. I recommend pybind11 for C++ to Python bindings or cffi for C to Python bindings. I’ve done this a lot over the years. But, I discovered that my productivity goes through the floor when my development process goes from Edit -> Test in just Python to Edit -> Compile -> Test in Python plus C++. So, cppimport combines the process of compiling and importing an extension in Python so that you can type modulename = cppimport.imp("modulename") and not have to worry about multiple steps. Internally, cppimport looks for a file modulename.cpp. If one is found, it’s run through the Mako templating system to gather compiler options, then it’s compiled and loaded as an extension module.

Note that because of the Mako pre-processing, the comments around the configuration block may be omitted.

Recompilation only happens when necessary:

Compilation should only happen the first time the module is imported. The C++ source is compared with a checksum on each import to determine if the file has changed. Additional dependencies (header files!) can be tracked by adding to the Mako header:

cfg['dependencies'] = ['file1.h', 'file2.h']

I need to set the compiler or linker args!

cfg['linker_args'] = ['...']
cfg['compiler_args'] = ['...']
cfg['libraries'] = ['...']
cfg['include_dirs'] = ['...']

For example, to use C++11, add:

<%
cfg['compiler_args'] = ['-std=c++11']
%>

I want multiple source files for one extension!

cfg['sources'] = ['...']

I need more output!

Calling cppimport.set_quiet(False) will result in output that will be helpful in debugging compile errors.

Sometimes I need to force a rebuild even when the checksum matches

Call cppimport.force_rebuild() before running cppimport.imp(...).

I want incremental compiles on extensions with multiple sources.

(For the uninitiated, incremental compilation involves only recompiling those source files that have changed or include headers that have changed.)

cppimport is built on top of the setuptools and distutils, the standard library for python packaging and distribution. Unfortunately, setuptools does not support incremental compilation. I recommend following the suggestions on this SO answer. That is:

  1. Use ccache to (massively) reduce the cost of rebuilds

  2. Enable parallel compilation. This can be done with cfg['parallel'] = True in the C++ file’s configuration header.

I need information about filepaths in my module configuration code!

The module name is available as the fullname variable and the C++ module file is available as filepath. For example,

<%
module_dir = os.path.dirname(filepath)
%>

Why does the import hook need “cppimport” on the first line of the .cpp file?

Modifying the Python import system is a global modification and thus affects all imports from any other package. As a result, to avoid accidentally breaking another package, the import hook uses an “opt in” system where C and C++ files can specify they are meant to be used with cppimport by having a comment including the phrase “cppimport” on the first line of the file.

Windows?

I don’t know if cppimport works on Windows. If you’re on Windows, try it out and I’ll happily accept a pull request for any issues that you fix. I have reports that cppimport works on Windows with Python 3.6 and Visual C++ 2015 Build Tools.

cppimport uses the MIT License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cppimport-18.1.10.tar.gz (4.2 MB view details)

Uploaded Source

File details

Details for the file cppimport-18.1.10.tar.gz.

File metadata

File hashes

Hashes for cppimport-18.1.10.tar.gz
Algorithm Hash digest
SHA256 c3390059ffcf5e06f698703822a63ef936ae5e5424fb3e8b0fee088cdc667d0d
MD5 210b6c60c8d7fac3504af59685316ad9
BLAKE2b-256 4dcf690066fd4bcf36599497e2a0b22fcfefa35b0bd1c8924b74a42f3f41e12e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page