Installing Python Modules (Legacy version)

Author:

Greg Ward

Note

The entire distutils package has been deprecated and will be removed in Python 3.12. This documentation is retained as a reference only, and will be removed with the package. See the What’s New entry for more information.

See also

Installing Python Modules

The up to date module installation documentation. For regular Python usage, you almost certainly want that document rather than this one.

Note

This document is being retained solely until the setuptools documentation at https://setuptools.readthedocs.io/en/latest/setuptools.html independently covers all of the relevant information currently included here.

Note

This guide only covers the basic tools for building and distributing extensions that are provided as part of this version of Python. Third party tools offer easier to use and more secure alternatives. Refer to the quick recommendations section in the Python Packaging User Guide for more information.

Introduction

In Python 2.0, the distutils API was first added to the standard library. This provided Linux distro maintainers with a standard way of converting Python projects into Linux distro packages, and system administrators with a standard way of installing them directly onto target systems.

In the many years since Python 2.0 was released, tightly coupling the build system and package installer to the language runtime release cycle has turned out to be problematic, and it is now recommended that projects use the pip package installer and the setuptools build system, rather than using distutils directly.

See Installing Python Modules and Distributing Python Modules for more details.

This legacy documentation is being retained only until we’re confident that the setuptools documentation covers everything needed.

Distutils based source distributions

If you download a module source distribution, you can tell pretty quickly if it was packaged and distributed in the standard way, i.e. using the Distutils. First, the distribution’s name and version number will be featured prominently in the name of the downloaded archive, e.g. foo-1.0.tar.gz or widget-0.9.7.zip. Next, the archive will unpack into a similarly named directory: foo-1.0 or widget-0.9.7. Additionally, the distribution will contain a setup script setup.py, and a file named README.txt or possibly just README, which should explain that building and installing the module distribution is a simple matter of running one command from a terminal:

python setup.py install

For Windows, this command should be run from a command prompt window (Start ‣ Accessories):

setup.py install

If all these things are true, then you already know how to build and install the modules you’ve just downloaded: Run the command above. Unless you need to install things in a non-standard way or customize the build process, you don’t really need this manual. Or rather, the above command is everything you need to get out of this manual.

Standard Build and Install

As described in section Distutils based source distributions, building and installing a module distribution using the Distutils is usually one simple command to run from a terminal:

python setup.py install

Platform variations

You should always run the setup command from the distribution root directory, i.e. the top-level subdirectory that the module source distribution unpacks into. For example, if you’ve just downloaded a module source distribution foo-1.0.tar.gz onto a Unix system, the normal thing to do is:

gunzip -c foo-1.0.tar.gz | tar xf -    # unpacks into directory foo-1.0
cd foo-1.0
python setup.py install

On Windows, you’d probably download foo-1.0.zip. If you downloaded the archive file to C:\Temp, then it would unpack into C:\Temp\foo-1.0; you can use either an archive manipulator with a graphical user interface (such as WinZip) or a command-line tool (such as unzip or pkunzip) to unpack the archive. Then, open a command prompt window and run:

cd c:\Temp\foo-1.0
python setup.py install

Splitting the job up

Running setup.py install builds and installs all modules in one run. If you prefer to work incrementally—especially useful if you want to customize the build process, or if things are going wrong—you can use the setup script to do one thing at a time. This is particularly helpful when the build and install will be done by different users—for example, you might want to build a module distribution and hand it off to a system administrator for installation (or do it yourself, with super-user privileges).

For example, you can build everything in one step, and then install everything in a second step, by invoking the setup script twice:

python setup.py build
python setup.py install

If you do this, you will notice that running the install command first runs the build command, which—in this case—quickly notices that it has nothing to do, since everything in the build directory is up-to-date.

You may not need this ability to break things down often if all you do is install modules downloaded off the ‘net, but it’s very handy for more advanced tasks. If you get into distributing your own Python modules and extensions, you’ll run lots of individual Distutils commands on their own.

How building works

As implied above, the build command is responsible for putting the files to install into a build directory. By default, this is build under the distribution root; if you’re excessively concerned with speed, or want to keep the source tree pristine, you can change the build directory with the --build-base option. For example:

python setup.py build --build-base=/path/to/pybuild/foo-1.0

(Or you could do this permanently with a directive in your system or personal Distutils configuration file; see section Distutils Configuration Files.) Normally, this isn’t necessary.

The default layout for the build tree is as follows:

--- build/ --- lib/
or
--- build/ --- lib.<plat>/
               temp.<plat>/

where <plat> expands to a brief description of the current OS/hardware platform and Python version. The first form, with just a lib directory, is used for “pure module distributions”—that is, module distributions that include only pure Python modules. If a module distribution contains any extensions (modules written in C/C++), then the second form, with two <plat> directories, is used. In that case, the temp.plat directory holds temporary files generated by the compile/link process that don’t actually get installed. In either case, the lib (or lib.plat) directory contains all Python modules (pure Python and extensions) that will be installed.

In the future, more directories will be added to handle Python scripts, documentation, binary executables, and whatever else is needed to handle the job of installing Python modules and applications.

How installation works

After the build command runs (whether you run it explicitly, or the install command does it for you), the work of the install command is relatively simple: all it has to do is copy everything under build/lib (or build/lib.plat) to your chosen installation directory.

If you don’t choose an installation directory—i.e., if you just run setup.py install—then the install command installs to the standard location for third-party Python modules. This location varies by platform and by how you built/installed Python itself. On Unix (and macOS, which is also Unix-based), it also depends on whether the module distribution being installed is pure Python or contains extensions (“non-pure”):

Platform

Standard installation location

Default value

Notes

Unix (pure)

prefix/lib/pythonX.Y/site-packages

/usr/local/lib/pythonX.Y/site-packages

(1)

Unix (non-pure)

exec-prefix/lib/pythonX.Y/site-packages

/usr/local/lib/pythonX.Y/site-packages

(1)

Windows

prefix\Lib\site-packages

C:\PythonXY\Lib\site-packages

(2)

Notes:

  1. Most Linux distributions include Python as a standard part of the system, so prefix and exec-prefix are usually both /usr on Linux. If you build Python yourself on Linux (or any Unix-like system), the default prefix and exec-prefix are /usr/local.

  2. The default installation directory on Windows was C:\Program Files\Python under Python 1.6a1, 1.5.2, and earlier.

prefix and exec-prefix stand for the directories that Python is installed to, and where it finds its libraries at run-time. They are always the same under Windows, and very often the same under Unix and macOS. You can find out what your Python installation uses for prefix and exec-prefix by running Python in interactive mode and typing a few simple commands. Under Unix, just type python at the shell prompt. Under Windows, choose Start ‣ Programs ‣ Python X.Y ‣ Python (command line). Once the interpreter is started, you type Python code at the prompt. For example, on my Linux system, I type the three Python statements shown below, and get the output as shown, to find out my prefix and exec-prefix:

Python 2.4 (#26, Aug  7 2004, 17:19:02)
Type "help", "copyright", "credits" or "license" for more information.
>>> import sys
>>> sys.prefix
'/usr'
>>> sys.exec_prefix
'/usr'

A few other placeholders are used in this document: X.Y stands for the version of Python, for example 3.2; abiflags will be replaced by the value of sys.abiflags or the empty string for platforms which don’t define ABI flags; distname will be replaced by the name of the module distribution being installed. Dots and capitalization are important in the paths; for example, a value that uses python3.2 on UNIX will typically use Python32 on Windows.

If you don’t want to install modules to the standard location, or if you don’t have permission to write there, then you need to read about alternate installations in section Alternate Installation. If you want to customize your installation directories more heavily, see section Custom Installation on custom installations.

Alternate Installation

Often, it is necessary or desirable to install modules to a location other than the standard location for third-party Python modules. For example, on a Unix system you might not have permission to write to the standard third-party module directory. Or you might wish to try out a module before making it a standard part of your local Python installation. This is especially true when upgrading a distribution already present: you want to make sure your existing base of scripts still works with the new version before actually upgrading.

The Distutils install command is designed to make installing module distributions to an alternate location simple and painless. The basic idea is that you supply a base directory for the installation, and the install command picks a set of directories (called an installation scheme) under this base directory in which to install files. The details differ across platforms, so read whichever of the following sections applies to you.

Note that the various alternate installation schemes are mutually exclusive: you can pass --user, or --home, or --prefix and --exec-prefix, or --install-base and --install-platbase, but you can’t mix from these groups.

Alternate installation: the user scheme

This scheme is designed to be the most convenient solution for users that don’t have write permission to the global site-packages directory or don’t want to install into it. It is enabled with a simple option:

python setup.py install --user

Files will be installed into subdirectories of site.USER_BASE (written as userbase hereafter). This scheme installs pure Python modules and extension modules in the same location (also known as site.USER_SITE). Here are the values for UNIX, including macOS:

Type of file

Installation directory

modules

userbase/lib/pythonX.Y/site-packages

scripts

userbase/bin

data

userbase

C headers

userbase/include/pythonX.Yabiflags/distname

And here are the values used on Windows:

Type of file

Installation directory

modules

userbase\PythonXY\site-packages

scripts

userbase\PythonXY\Scripts

data

userbase

C headers

userbase\PythonXY\Include{distname}

The advantage of using this scheme compared to the other ones described below is that the user site-packages directory is under normal conditions always included in sys.path (see site for more information), which means that there is no additional step to perform after running the setup.py script to finalize the installation.

The build_ext command also has a --user option to add userbase/include to the compiler search path for header files and userbase/lib to the compiler search path for libraries as well as to the runtime search path for shared C libraries (rpath).

Alternate installation: the home scheme

The idea behind the “home scheme” is that you build and maintain a personal stash of Python modules. This scheme’s name is derived from the idea of a “home” directory on Unix, since it’s not unusual for a Unix user to make their home directory have a layout similar to /usr/ or /usr/local/. This scheme can be used by anyone, regardless of the operating system they are installing for.

Installing a new module distribution is as simple as

python setup.py install --home=<dir>

where you can supply any directory you like for the --home option. On Unix, lazy typists can just type a tilde (~); the install command will expand this to your home directory:

python setup.py install --home=~

To make Python find the distributions installed with this scheme, you may have to modify Python’s search path or edit sitecustomize (see site) to call site.addsitedir() or edit sys.path.

The --home option defines the installation base directory. Files are installed to the following directories under the installation base as follows:

Type of file

Installation directory

modules

home/lib/python

scripts

home/bin

data

home

C headers

home/include/python/distname

(Mentally replace slashes with backslashes if you’re on Windows.)

Alternate installation: Unix (the prefix scheme)

The “prefix scheme” is useful when you wish to use one Python installation to perform the build/install (i.e., to run the setup script), but install modules into the third-party module directory of a different Python installation (or something that looks like a different Python installation). If this sounds a trifle unusual, it is—that’s why the user and home schemes come before. However, there are at least two known cases where the prefix scheme will be useful.

First, consider that many Linux distributions put Python in /usr, rather than the more traditional /usr/local. This is entirely appropriate, since in those cases Python is part of “the system” rather than a local add-on. However, if you are installing Python modules from source, you probably want them to go in /usr/local/lib/python2.X rather than /usr/lib/python2.X. This can be done with

/usr/bin/python setup.py install --prefix=/usr/local

Another possibility is a network filesystem where the name used to write to a remote directory is different from the name used to read it: for example, the Python interpreter accessed as /usr/local/bin/python might search for modules in /usr/local/lib/python2.X, but those modules would have to be installed to, say, /mnt/@server/export/lib/python2.X. This could be done with

/usr/local/bin/python setup.py install --prefix=/mnt/@server/export

In either case, the --prefix option defines the installation base, and the --exec-prefix option defines the platform-specific installation base, which is used for platform-specific files. (Currently, this just means non-pure module distributions, but could be expanded to C libraries, binary executables, etc.) If --exec-prefix is not supplied, it defaults to --prefix. Files are installed as follows:

Type of file

Installation directory

Python modules

prefix/lib/pythonX.Y/site-packages

extension modules

exec-prefix/lib/pythonX.Y/site-packages

scripts

prefix/bin

data

prefix

C headers

prefix/include/pythonX.Yabiflags/distname

There is no requirement that --prefix or --exec-prefix actually point to an alternate Python installation; if the directories listed above do not already exist, they are created at installation time.

Incidentally, the real reason the prefix scheme is important is simply that a standard Unix installation uses the prefix scheme, but with --prefix and --exec-prefix supplied by Python itself as sys.prefix and sys.exec_prefix. Thus, you might think you’ll never use the prefix scheme, but every time you run python setup.py install without any other options, you’re using it.

Note that installing extensions to an alternate Python installation has no effect on how those extensions are built: in particular, the Python header files (Python.h and friends) installed with the Python interpreter used to run the setup script will be used in compiling extensions. It is your responsibility to ensure that the interpreter used to run extensions installed in this way is compatible with the interpreter used to build them. The best way to do this is to ensure that the two interpreters are the same version of Python (possibly different builds, or possibly copies of the same build). (Of course, if your --prefix and --exec-prefix don’t even point to an alternate Python installation, this is immaterial.)

Alternate installation: Windows (the prefix scheme)

Windows has no concept of a user’s home directory, and since the standard Python installation under Windows is simpler than under Unix, the --prefix option has traditionally been used to install additional packages in separate locations on Windows.

python setup.py install --prefix="\Temp\Python"

to install modules to the \Temp\Python directory on the current drive.

The installation base is defined by the --prefix option; the --exec-prefix option is not supported under Windows, which means that pure Python modules and extension modules are installed into the same location. Files are installed as follows:

Type of file

Installation directory

modules

prefix\Lib\site-packages

scripts

prefix\Scripts

data

prefix

C headers

prefix\Include{distname}

Custom Installation

Sometimes, the alternate installation schemes described in section Alternate Installation just don’t do what you want. You might want to tweak just one or two directories while keeping everything under the same base directory, or you might want to completely redefine the installation scheme. In either case, you’re creating a custom installation scheme.

To create a custom installation scheme, you start with one of the alternate schemes and override some of the installation directories used for the various types of files, using these options:

Type of file

Override option

Python modules

--install-purelib

extension modules

--install-platlib

all modules

--install-lib

scripts

--install-scripts

data

--install-data

C headers

--install-headers

These override options can be relative, absolute, or explicitly defined in terms of one of the installation base directories. (There are two installation base directories, and they are normally the same—they only differ when you use the Unix “prefix scheme” and supply different --prefix and --exec-prefix options; using --install-lib will override values computed or given for --install-purelib and --install-platlib, and is recommended for schemes that don’t make a difference between Python and extension modules.)

For example, say you’re installing a module distribution to your home directory under Unix—but you want scripts to go in ~/scripts rather than ~/bin. As you might expect, you can override this directory with the --install-scripts option; in this case, it makes most sense to supply a relative path, which will be interpreted relative to the installation base directory (your home directory, in this case):

python setup.py install --home=~ --install-scripts=scripts

Another Unix example: suppose your Python installation was built and installed with a prefix of /usr/local/python, so under a standard installation scripts will wind up in /usr/local/python/bin. If you want them in /usr/local/bin instead, you would supply this absolute directory for the --install-scripts option:

python setup.py install --install-scripts=/usr/local/bin

(This performs an installation using the “prefix scheme”, where the prefix is whatever your Python interpreter was installed with— /usr/local/python in this case.)

If you maintain Python on Windows, you might want third-party modules to live in a subdirectory of prefix, rather than right in prefix itself. This is almost as easy as customizing the script installation directory—you just have to remember that there are two types of modules to worry about, Python and extension modules, which can conveniently be both controlled by one option:

python setup.py install --install-lib=Site

The specified installation directory is relative to prefix. Of course, you also have to ensure that this directory is in Python’s module search path, such as by putting a .pth file in a site directory (see site). See section Modifying Python’s Search Path to find out how to modify Python’s search path.

If you want to define an entire installation scheme, you just have to supply all of the installation directory options. The recommended way to do this is to supply relative paths; for example, if you want to maintain all Python module-related files under python in your home directory, and you want a separate directory for each platform that you use your home directory from, you might define the following installation scheme:

python setup.py install --home=~ \
                        --install-purelib=python/lib \
                        --install-platlib=python/lib.$PLAT \
                        --install-scripts=python/scripts
                        --install-data=python/data

or, equivalently,

python setup.py install --home=~/python \
                        --install-purelib=lib \
                        --install-platlib='lib.$PLAT' \
                        --install-scripts=scripts
                        --install-data=data

$PLAT is not (necessarily) an environment variable—it will be expanded by the Distutils as it parses your command line options, just as it does when parsing your configuration file(s).

Obviously, specifying the entire installation scheme every time you install a new module distribution would be very tedious. Thus, you can put these options into your Distutils config file (see section Distutils Configuration Files):

[install]
install-base=$HOME
install-purelib=python/lib
install-platlib=python/lib.$PLAT
install-scripts=python/scripts
install-data=python/data

or, equivalently,

[install]
install-base=$HOME/python
install-purelib=lib
install-platlib=lib.$PLAT
install-scripts=scripts
install-data=data

Note that these two are not equivalent if you supply a different installation base directory when you run the setup script. For example,

python setup.py install --install-base=/tmp

would install pure modules to /tmp/python/lib in the first case, and to /tmp/lib in the second case. (For the second case, you probably want to supply an installation base of /tmp/python.)

You probably noticed the use of $HOME and $PLAT in the sample configuration file input. These are Distutils configuration variables, which bear a strong resemblance to environment variables. In fact, you can use environment variables in config files on platforms that have such a notion but the Distutils additionally define a few extra variables that may not be in your environment, such as $PLAT. (And of course, on systems that don’t have environment variables, such as Mac OS 9, the configuration variables supplied by the Distutils are the only ones you can use.) See section Distutils Configuration Files for details.

Note

When a virtual environment is activated, any options that change the installation path will be ignored from all distutils configuration files to prevent inadvertently installing projects outside of the virtual environment.

Modifying Python’s Search Path

When the Python interpreter executes an import statement, it searches for both Python code and extension modules along a search path. A default value for the path is configured into the Python binary when the interpreter is built. You can determine the path by importing the sys module and printing the value of sys.path.

$ python
Python 2.2 (#11, Oct  3 2002, 13:31:27)
[GCC 2.96 20000731 (Red Hat Linux 7.3 2.96-112)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import sys
>>> sys.path
['', '/usr/local/lib/python2.3', '/usr/local/lib/python2.3/plat-linux2',
 '/usr/local/lib/python2.3/lib-tk', '/usr/local/lib/python2.3/lib-dynload',
 '/usr/local/lib/python2.3/site-packages']
>>>

The null string in sys.path represents the current working directory.

The expected convention for locally installed packages is to put them in the .../site-packages/ directory, but you may want to install Python modules into some arbitrary directory. For example, your site may have a convention of keeping all software related to the web server under /www. Add-on Python modules might then belong in /www/python, and in order to import them, this directory must be added to sys.path. There are several different ways to add the directory.

The most convenient way is to add a path configuration file to a directory that’s already on Python’s path, usually to the .../site-packages/ directory. Path configuration files have an extension of .pth, and each line must contain a single path that will be appended to sys.path. (Because the new paths are appended to sys.path, modules in the added directories will not override standard modules. This means you can’t use this mechanism for installing fixed versions of standard modules.)

Paths can be absolute or relative, in which case they’re relative to the directory containing the .pth file. See the documentation of the site module for more information.

A slightly less convenient way is to edit the site.py file in Python’s standard library, and modify sys.path. site.py is automatically imported when the Python interpreter is executed, unless the -S switch is supplied to suppress this behaviour. So you could simply edit site.py and add two lines to it:

import sys
sys.path.append('/www/python/')

However, if you reinstall the same major version of Python (perhaps when upgrading from 2.2 to 2.2.2, for example) site.py will be overwritten by the stock version. You’d have to remember that it was modified and save a copy before doing the installation.

There are two environment variables that can modify sys.path. PYTHONHOME sets an alternate value for the prefix of the Python installation. For example, if PYTHONHOME is set to /www/python, the search path will be set to ['', '/www/python/lib/pythonX.Y/', '/www/python/lib/pythonX.Y/plat-linux2', ...].

The PYTHONPATH variable can be set to a list of paths that will be added to the beginning of sys.path. For example, if PYTHONPATH is set to /www/python:/opt/py, the search path will begin with ['/www/python', '/opt/py']. (Note that directories must exist in order to be added to sys.path; the site module removes paths that don’t exist.)

Finally, sys.path is just a regular Python list, so any Python application can modify it by adding or removing entries.

Distutils Configuration Files

As mentioned above, you can use Distutils configuration files to record personal or site preferences for any Distutils options. That is, any option to any command can be stored in one of two or three (depending on your platform) configuration files, which will be consulted before the command-line is parsed. This means that configuration files will override default values, and the command-line will in turn override configuration files. Furthermore, if multiple configuration files apply, values from “earlier” files are overridden by “later” files.

Location and names of config files

The names and locations of the configuration files vary slightly across platforms. On Unix and macOS, the three configuration files (in the order they are processed) are:

Type of file

Location and filename

Notes

system

prefix/lib/pythonver/distutils/distutils.cfg

(1)

personal

$HOME/.pydistutils.cfg

(2)

local

setup.cfg

(3)

And on Windows, the configuration files are:

Type of file

Location and filename

Notes

system

prefix\Lib\distutils\distutils.cfg

(4)

personal

%HOME%\pydistutils.cfg

(5)

local

setup.cfg

(3)

On all platforms, the “personal” file can be temporarily disabled by passing the --no-user-cfg option.

Notes:

  1. Strictly speaking, the system-wide configuration file lives in the directory where the Distutils are installed; under Python 1.6 and later on Unix, this is as shown. For Python 1.5.2, the Distutils will normally be installed to prefix/lib/python1.5/site-packages/distutils, so the system configuration file should be put there under Python 1.5.2.

  2. On Unix, if the HOME environment variable is not defined, the user’s home directory will be determined with the getpwuid() function from the standard pwd module. This is done by the os.path.expanduser() function used by Distutils.

  3. I.e., in the current directory (usually the location of the setup script).

  4. (See also note (1).) Under Python 1.6 and later, Python’s default “installation prefix” is C:\Python, so the system configuration file is normally C:\Python\Lib\distutils\distutils.cfg. Under Python 1.5.2, the default prefix was C:\Program Files\Python, and the Distutils were not part of the standard library—so the system configuration file would be C:\Program Files\Python\distutils\distutils.cfg in a standard Python 1.5.2 installation under Windows.

  5. On Windows, if the HOME environment variable is not defined, USERPROFILE then HOMEDRIVE and HOMEPATH will be tried. This is done by the os.path.expanduser() function used by Distutils.

Syntax of config files

The Distutils configuration files all have the same syntax. The config files are grouped into sections. There is one section for each Distutils command, plus a global section for global options that affect every command. Each section consists of one option per line, specified as option=value.

For example, the following is a complete config file that just forces all commands to run quietly by default:

[global]
verbose=0

If this is installed as the system config file, it will affect all processing of any Python module distribution by any user on the current system. If it is installed as your personal config file (on systems that support them), it will affect only module distributions processed by you. And if it is used as the setup.cfg for a particular module distribution, it affects only that distribution.

You could override the default “build base” directory and make the build* commands always forcibly rebuild all files with the following:

[build]
build-base=blib
force=1

which corresponds to the command-line arguments

python setup.py build --build-base=blib --force

except that including the build command on the command-line means that command will be run. Including a particular command in config files has no such implication; it only means that if the command is run, the options in the config file will apply. (Or if other commands that derive values from it are run, they will use the values in the config file.)

You can find out the complete list of options for any command using the --help option, e.g.:

python setup.py build --help

and you can find out the complete list of global options by using --help without a command:

python setup.py --help

See also the “Reference” section of the “Distributing Python Modules” manual.

Building Extensions: Tips and Tricks

Whenever possible, the Distutils try to use the configuration information made available by the Python interpreter used to run the setup.py script. For example, the same compiler and linker flags used to compile Python will also be used for compiling extensions. Usually this will work well, but in complicated situations this might be inappropriate. This section discusses how to override the usual Distutils behaviour.

Tweaking compiler/linker flags

Compiling a Python extension written in C or C++ will sometimes require specifying custom flags for the compiler and linker in order to use a particular library or produce a special kind of object code. This is especially true if the extension hasn’t been tested on your platform, or if you’re trying to cross-compile Python.

In the most general case, the extension author might have foreseen that compiling the extensions would be complicated, and provided a Setup file for you to edit. This will likely only be done if the module distribution contains many separate extension modules, or if they often require elaborate sets of compiler flags in order to work.

A Setup file, if present, is parsed in order to get a list of extensions to build. Each line in a Setup describes a single module. Lines have the following structure:

module ... [sourcefile ...] [cpparg ...] [library ...]

Let’s examine each of the fields in turn.

  • module is the name of the extension module to be built, and should be a valid Python identifier. You can’t just change this in order to rename a module (edits to the source code would also be needed), so this should be left alone.

  • sourcefile is anything that’s likely to be a source code file, at least judging by the filename. Filenames ending in .c are assumed to be written in C, filenames ending in .C, .cc, and .c++ are assumed to be C++, and filenames ending in .m or .mm are assumed to be in Objective C.

  • cpparg is an argument for the C preprocessor, and is anything starting with -I, -D, -U or -C.

  • library is anything ending in .a or beginning with -l or -L.

If a particular platform requires a special library on your platform, you can add it by editing the Setup file and running python setup.py build. For example, if the module defined by the line

foo foomodule.c

must be linked with the math library libm.a on your platform, simply add -lm to the line:

foo foomodule.c -lm

Arbitrary switches intended for the compiler or the linker can be supplied with the -Xcompiler arg and -Xlinker arg options:

foo foomodule.c -Xcompiler -o32 -Xlinker -shared -lm

The next option after -Xcompiler and -Xlinker will be appended to the proper command line, so in the above example the compiler will be passed the -o32 option, and the linker will be passed -shared. If a compiler option requires an argument, you’ll have to supply multiple -Xcompiler options; for example, to pass -x c++ the Setup file would have to contain -Xcompiler -x -Xcompiler c++.

Compiler flags can also be supplied through setting the CFLAGS environment variable. If set, the contents of CFLAGS will be added to the compiler flags specified in the Setup file.

Using non-Microsoft compilers on Windows

Borland/CodeGear C++

This subsection describes the necessary steps to use Distutils with the Borland C++ compiler version 5.5. First you have to know that Borland’s object file format (OMF) is different from the format used by the Python version you can download from the Python or ActiveState web site. (Python is built with Microsoft Visual C++, which uses COFF as the object file format.) For this reason you have to convert Python’s library python25.lib into the Borland format. You can do this as follows:

coff2omf python25.lib python25_bcpp.lib

The coff2omf program comes with the Borland compiler. The file python25.lib is in the Libs directory of your Python installation. If your extension uses other libraries (zlib, …) you have to convert them too.

The converted files have to reside in the same directories as the normal libraries.

How does Distutils manage to use these libraries with their changed names? If the extension needs a library (eg. foo) Distutils checks first if it finds a library with suffix _bcpp (eg. foo_bcpp.lib) and then uses this library. In the case it doesn’t find such a special library it uses the default name (foo.lib.) [1]

To let Distutils compile your extension with Borland C++ you now have to type:

python setup.py build --compiler=bcpp

If you want to use the Borland C++ compiler as the default, you could specify this in your personal or system-wide configuration file for Distutils (see section Distutils Configuration Files.)

See also

C++Builder Compiler

Information about the free C++ compiler from Borland, including links to the download pages.

Creating Python Extensions Using Borland’s Free Compiler

Document describing how to use Borland’s free command-line C++ compiler to build Python.

GNU C / Cygwin / MinGW

This section describes the necessary steps to use Distutils with the GNU C/C++ compilers in their Cygwin and MinGW distributions. [2] For a Python interpreter that was built with Cygwin, everything should work without any of these following steps.

Not all extensions can be built with MinGW or Cygwin, but many can. Extensions most likely to not work are those that use C++ or depend on Microsoft Visual C extensions.

To let Distutils compile your extension with Cygwin you have to type:

python setup.py build --compiler=cygwin

and for Cygwin in no-cygwin mode [3] or for MinGW type:

python setup.py build --compiler=mingw32

If you want to use any of these options/compilers as default, you should consider writing it in your personal or system-wide configuration file for Distutils (see section Distutils Configuration Files.)

Older Versions of Python and MinGW

The following instructions only apply if you’re using a version of Python inferior to 2.4.1 with a MinGW inferior to 3.0.0 (with binutils-2.13.90-20030111-1).

These compilers require some special libraries. This task is more complex than for Borland’s C++, because there is no program to convert the library. First you have to create a list of symbols which the Python DLL exports. (You can find a good program for this task at https://sourceforge.net/projects/mingw/files/MinGW/Extension/pexports/).

pexports python25.dll >python25.def

The location of an installed python25.dll will depend on the installation options and the version and language of Windows. In a “just for me” installation, it will appear in the root of the installation directory. In a shared installation, it will be located in the system directory.

Then you can create from these information an import library for gcc.

/cygwin/bin/dlltool --dllname python25.dll --def python25.def --output-lib libpython25.a

The resulting library has to be placed in the same directory as python25.lib. (Should be the libs directory under your Python installation directory.)

If your extension uses other libraries (zlib,…) you might have to convert them too. The converted files have to reside in the same directories as the normal libraries do.

See also

Building Python modules on MS Windows platform with MinGW

Information about building the required libraries for the MinGW environment.

Footnotes