2. Writing the Setup Script¶
The setup script is the centre of all activity in building, distributing, and
installing modules using the Distutils. The main purpose of the setup script is
to describe your module distribution to the Distutils, so that the various
commands that operate on your modules do the right thing. As we saw in section
A Simple Example above, the setup script consists mainly of a call to
setup()
, and most information supplied to the Distutils by the module
developer is supplied as keyword arguments to setup()
.
Here’s a slightly more involved example, which we’ll follow for the next couple of sections: the Distutils” own setup script. (Keep in mind that although the Distutils are included with Python 1.6 and later, they also have an independent existence so that Python 1.5.2 users can use them to install other module distributions. The Distutils” own setup script, shown here, is used to install the package into Python 1.5.2.)
#!/usr/bin/env python
from distutils.core import setup
setup(name='Distutils',
version='1.0',
description='Python Distribution Utilities',
author='Greg Ward',
author_email='gward@python.net',
url='https://www.python.org/sigs/distutils-sig/',
packages=['distutils', 'distutils.command'],
)
There are only two differences between this and the trivial one-file distribution presented in section A Simple Example: more metadata, and the specification of pure Python modules by package, rather than by module. This is important since the Distutils consist of a couple of dozen modules split into (so far) two packages; an explicit list of every module would be tedious to generate and difficult to maintain. For more information on the additional meta-data, see section Additional meta-data.
Note that any pathnames (files or directories) supplied in the setup script should be written using the Unix convention, i.e. slash-separated. The Distutils will take care of converting this platform-neutral representation into whatever is appropriate on your current platform before actually using the pathname. This makes your setup script portable across operating systems, which of course is one of the major goals of the Distutils. In this spirit, all pathnames in this document are slash-separated.
This, of course, only applies to pathnames given to Distutils functions. If
you, for example, use standard Python functions such as glob.glob()
or
os.listdir()
to specify files, you should be careful to write portable
code instead of hardcoding path separators:
glob.glob(os.path.join('mydir', 'subdir', '*.html'))
os.listdir(os.path.join('mydir', 'subdir'))
2.1. Listing whole packages¶
The packages
option tells the Distutils to process (build, distribute,
install, etc.) all pure Python modules found in each package mentioned in the
packages
list. In order to do this, of course, there has to be a
correspondence between package names and directories in the filesystem. The
default correspondence is the most obvious one, i.e. package distutils
is
found in the directory distutils
relative to the distribution root.
Thus, when you say packages = ['foo']
in your setup script, you are
promising that the Distutils will find a file foo/__init__.py
(which
might be spelled differently on your system, but you get the idea) relative to
the directory where your setup script lives. If you break this promise, the
Distutils will issue a warning but still process the broken package anyway.
If you use a different convention to lay out your source directory, that’s no
problem: you just have to supply the package_dir
option to tell the
Distutils about your convention. For example, say you keep all Python source
under lib
, so that modules in the «root package» (i.e., not in any
package at all) are in lib
, modules in the foo
package are in
lib/foo
, and so forth. Then you would put
package_dir = {'': 'lib'}
in your setup script. The keys to this dictionary are package names, and an
empty package name stands for the root package. The values are directory names
relative to your distribution root. In this case, when you say packages =
['foo']
, you are promising that the file lib/foo/__init__.py
exists.
Another possible convention is to put the foo
package right in
lib
, the foo.bar
package in lib/bar
, etc. This would be
written in the setup script as
package_dir = {'foo': 'lib'}
A package: dir
entry in the package_dir
dictionary implicitly
applies to all packages below package, so the foo.bar
case is
automatically handled here. In this example, having packages = ['foo',
'foo.bar']
tells the Distutils to look for lib/__init__.py
and
lib/bar/__init__.py
. (Keep in mind that although package_dir
applies recursively, you must explicitly list all packages in
packages
: the Distutils will not recursively scan your source tree
looking for any directory with an __init__.py
file.)
2.2. Listing individual modules¶
For a small module distribution, you might prefer to list all modules rather than listing packages—especially the case of a single module that goes in the «root package» (i.e., no package at all). This simplest case was shown in section A Simple Example; here is a slightly more involved example:
py_modules = ['mod1', 'pkg.mod2']
This describes two modules, one of them in the «root» package, the other in the
pkg
package. Again, the default package/directory layout implies that
these two modules can be found in mod1.py
and pkg/mod2.py
, and
that pkg/__init__.py
exists as well. And again, you can override the
package/directory correspondence using the package_dir
option.
2.3. Describing extension modules¶
Just as writing Python extension modules is a bit more complicated than writing pure Python modules, describing them to the Distutils is a bit more complicated. Unlike pure modules, it’s not enough just to list modules or packages and expect the Distutils to go out and find the right files; you have to specify the extension name, source file(s), and any compile/link requirements (include directories, libraries to link with, etc.).
All of this is done through another keyword argument to setup()
, the
ext_modules
option. ext_modules
is just a list of
Extension
instances, each of which describes a
single extension module.
Suppose your distribution includes a single extension, called foo
and
implemented by foo.c
. If no additional instructions to the
compiler/linker are needed, describing this extension is quite simple:
Extension('foo', ['foo.c'])
The Extension
class can be imported from distutils.core
along
with setup()
. Thus, the setup script for a module distribution that
contains only this one extension and nothing else might be:
from distutils.core import setup, Extension
setup(name='foo',
version='1.0',
ext_modules=[Extension('foo', ['foo.c'])],
)
The Extension
class (actually, the underlying extension-building
machinery implemented by the build_ext command) supports a great deal
of flexibility in describing Python extensions, which is explained in the
following sections.
2.3.1. Extension names and packages¶
The first argument to the Extension
constructor is
always the name of the extension, including any package names. For example,
Extension('foo', ['src/foo1.c', 'src/foo2.c'])
describes an extension that lives in the root package, while
Extension('pkg.foo', ['src/foo1.c', 'src/foo2.c'])
describes the same extension in the pkg
package. The source files and
resulting object code are identical in both cases; the only difference is where
in the filesystem (and therefore where in Python’s namespace hierarchy) the
resulting extension lives.
If you have a number of extensions all in the same package (or all under the
same base package), use the ext_package
keyword argument to
setup()
. For example,
setup(...,
ext_package='pkg',
ext_modules=[Extension('foo', ['foo.c']),
Extension('subpkg.bar', ['bar.c'])],
)
will compile foo.c
to the extension pkg.foo
, and bar.c
to
pkg.subpkg.bar
.
2.3.2. Extension source files¶
The second argument to the Extension
constructor is
a list of source
files. Since the Distutils currently only support C, C++, and Objective-C
extensions, these are normally C/C++/Objective-C source files. (Be sure to use
appropriate extensions to distinguish C++ source files: .cc
and
.cpp
seem to be recognized by both Unix and Windows compilers.)
However, you can also include SWIG interface (.i
) files in the list; the
build_ext command knows how to deal with SWIG extensions: it will run
SWIG on the interface file and compile the resulting C/C++ file into your
extension.
This warning notwithstanding, options to SWIG can be currently passed like this:
setup(...,
ext_modules=[Extension('_foo', ['foo.i'],
swig_opts=['-modern', '-I../include'])],
py_modules=['foo'],
)
Or on the commandline like this:
> python setup.py build_ext --swig-opts="-modern -I../include"
On some platforms, you can include non-source files that are processed by the
compiler and included in your extension. Currently, this just means Windows
message text (.mc
) files and resource definition (.rc
) files for
Visual C++. These will be compiled to binary resource (.res
) files and
linked into the executable.
2.3.3. Preprocessor options¶
Three optional arguments to Extension
will help if
you need to specify include directories to search or preprocessor macros to
define/undefine: include_dirs
, define_macros
, and undef_macros
.
For example, if your extension requires header files in the include
directory under your distribution root, use the include_dirs
option:
Extension('foo', ['foo.c'], include_dirs=['include'])
You can specify absolute directories there; if you know that your extension will
only be built on Unix systems with X11R6 installed to /usr
, you can get
away with
Extension('foo', ['foo.c'], include_dirs=['/usr/include/X11'])
You should avoid this sort of non-portable usage if you plan to distribute your code: it’s probably better to write C code like
#include <X11/Xlib.h>
If you need to include header files from some other Python extension, you can
take advantage of the fact that header files are installed in a consistent way
by the Distutils install_headers command. For example, the Numerical
Python header files are installed (on a standard Unix installation) to
/usr/local/include/python1.5/Numerical
. (The exact location will differ
according to your platform and Python installation.) Since the Python include
directory—/usr/local/include/python1.5
in this case—is always
included in the search path when building Python extensions, the best approach
is to write C code like
#include <Numerical/arrayobject.h>
If you must put the Numerical
include directory right into your header
search path, though, you can find that directory using the Distutils
distutils.sysconfig
module:
from distutils.sysconfig import get_python_inc
incdir = os.path.join(get_python_inc(plat_specific=1), 'Numerical')
setup(...,
Extension(..., include_dirs=[incdir]),
)
Even though this is quite portable—it will work on any Python installation, regardless of platform—it’s probably easier to just write your C code in the sensible way.
You can define and undefine pre-processor macros with the define_macros
and
undef_macros
options. define_macros
takes a list of (name, value)
tuples, where name
is the name of the macro to define (a string) and
value
is its value: either a string or None
. (Defining a macro FOO
to None
is the equivalent of a bare #define FOO
in your C source: with
most compilers, this sets FOO
to the string 1
.) undef_macros
is
just a list of macros to undefine.
For example:
Extension(...,
define_macros=[('NDEBUG', '1'),
('HAVE_STRFTIME', None)],
undef_macros=['HAVE_FOO', 'HAVE_BAR'])
is the equivalent of having this at the top of every C source file:
#define NDEBUG 1
#define HAVE_STRFTIME
#undef HAVE_FOO
#undef HAVE_BAR
2.3.4. Library options¶
You can also specify the libraries to link against when building your extension,
and the directories to search for those libraries. The libraries
option is
a list of libraries to link against, library_dirs
is a list of directories
to search for libraries at link-time, and runtime_library_dirs
is a list of
directories to search for shared (dynamically loaded) libraries at run-time.
For example, if you need to link against libraries known to be in the standard library search path on target systems
Extension(...,
libraries=['gdbm', 'readline'])
If you need to link with libraries in a non-standard location, you’ll have to
include the location in library_dirs
:
Extension(...,
library_dirs=['/usr/X11R6/lib'],
libraries=['X11', 'Xt'])
(Again, this sort of non-portable construct should be avoided if you intend to distribute your code.)
2.3.5. Other options¶
There are still some other options which can be used to handle special cases.
The optional
option is a boolean; if it is true,
a build failure in the extension will not abort the build process, but
instead simply not install the failing extension.
The extra_objects
option is a list of object files to be passed to the
linker. These files must not have extensions, as the default extension for the
compiler is used.
extra_compile_args
and extra_link_args
can be used to
specify additional command line options for the respective compiler and linker
command lines.
export_symbols
is only useful on Windows. It can contain a list of
symbols (functions or variables) to be exported. This option is not needed when
building compiled extensions: Distutils will automatically add initmodule
to the list of exported symbols.
The depends
option is a list of files that the extension depends on
(for example header files). The build command will call the compiler on the
sources to rebuild extension if any on this files has been modified since the
previous build.
2.4. Relationships between Distributions and Packages¶
A distribution may relate to packages in three specific ways:
It can require packages or modules.
It can provide packages or modules.
It can obsolete packages or modules.
These relationships can be specified using keyword arguments to the
distutils.core.setup()
function.
Dependencies on other Python modules and packages can be specified by supplying
the requires keyword argument to setup()
. The value must be a list of
strings. Each string specifies a package that is required, and optionally what
versions are sufficient.
To specify that any version of a module or package is required, the string
should consist entirely of the module or package name. Examples include
'mymodule'
and 'xml.parsers.expat'
.
If specific versions are required, a sequence of qualifiers can be supplied in parentheses. Each qualifier may consist of a comparison operator and a version number. The accepted comparison operators are:
< > ==
<= >= !=
These can be combined by using multiple qualifiers separated by commas (and optional whitespace). In this case, all of the qualifiers must be matched; a logical AND is used to combine the evaluations.
Let’s look at a bunch of examples:
Requires Expression |
Explanation |
---|---|
|
Only version |
|
Any version after |
Now that we can specify dependencies, we also need to be able to specify what we
provide that other distributions can require. This is done using the provides
keyword argument to setup()
. The value for this keyword is a list of
strings, each of which names a Python module or package, and optionally
identifies the version. If the version is not specified, it is assumed to match
that of the distribution.
Some examples:
Provides Expression |
Explanation |
---|---|
|
Provide |
|
Provide |
A package can declare that it obsoletes other packages using the obsoletes keyword argument. The value for this is similar to that of the requires keyword: a list of strings giving module or package specifiers. Each specifier consists of a module or package name optionally followed by one or more version qualifiers. Version qualifiers are given in parentheses after the module or package name.
The versions identified by the qualifiers are those that are obsoleted by the distribution being described. If no qualifiers are given, all versions of the named module or package are understood to be obsoleted.
2.5. Installing Scripts¶
So far we have been dealing with pure and non-pure Python modules, which are usually not run by themselves but imported by scripts.
Scripts are files containing Python source code, intended to be started from the
command line. Scripts don’t require Distutils to do anything very complicated.
The only clever feature is that if the first line of the script starts with
#!
and contains the word «python», the Distutils will adjust the first line
to refer to the current interpreter location. By default, it is replaced with
the current interpreter location. The --executable
(or -e
)
option will allow the interpreter path to be explicitly overridden.
The scripts
option simply is a list of files to be handled in this
way. From the PyXML setup script:
setup(...,
scripts=['scripts/xmlproc_parse', 'scripts/xmlproc_val']
)
Distinto en la versión 3.1: All the scripts will also be added to the MANIFEST
file if no template is
provided. See Specifying the files to distribute.
2.6. Installing Package Data¶
Often, additional files need to be installed into a package. These files are often data that’s closely related to the package’s implementation, or text files containing documentation that might be of interest to programmers using the package. These files are called package data.
Package data can be added to packages using the package_data
keyword
argument to the setup()
function. The value must be a mapping from
package name to a list of relative path names that should be copied into the
package. The paths are interpreted as relative to the directory containing the
package (information from the package_dir
mapping is used if appropriate);
that is, the files are expected to be part of the package in the source
directories. They may contain glob patterns as well.
The path names may contain directory portions; any necessary directories will be created in the installation.
For example, if a package should contain a subdirectory with several data files, the files can be arranged like this in the source tree:
setup.py
src/
mypkg/
__init__.py
module.py
data/
tables.dat
spoons.dat
forks.dat
The corresponding call to setup()
might be:
setup(...,
packages=['mypkg'],
package_dir={'mypkg': 'src/mypkg'},
package_data={'mypkg': ['data/*.dat']},
)
Distinto en la versión 3.1: All the files that match package_data
will be added to the MANIFEST
file if no template is provided. See Specifying the files to distribute.
2.7. Installing Additional Files¶
The data_files
option can be used to specify additional files needed
by the module distribution: configuration files, message catalogs, data files,
anything which doesn’t fit in the previous categories.
data_files
specifies a sequence of (directory, files) pairs in the
following way:
setup(...,
data_files=[('bitmaps', ['bm/b1.gif', 'bm/b2.gif']),
('config', ['cfg/data.cfg'])],
)
Each (directory, files) pair in the sequence specifies the installation directory and the files to install there.
Each file name in files is interpreted relative to the setup.py
script at the top of the package source distribution. Note that you can
specify the directory where the data files will be installed, but you cannot
rename the data files themselves.
The directory should be a relative path. It is interpreted relative to the
installation prefix (Python’s sys.prefix
for system installations;
site.USER_BASE
for user installations). Distutils allows directory to be
an absolute installation path, but this is discouraged since it is
incompatible with the wheel packaging format. No directory information from
files is used to determine the final location of the installed file; only
the name of the file is used.
You can specify the data_files
options as a simple sequence of files
without specifying a target directory, but this is not recommended, and the
install command will print a warning in this case. To install data
files directly in the target directory, an empty string should be given as the
directory.
Distinto en la versión 3.1: All the files that match data_files
will be added to the MANIFEST
file if no template is provided. See Specifying the files to distribute.
2.8. Additional meta-data¶
The setup script may include additional meta-data beyond the name and version. This information includes:
Meta-Data |
Description |
Value |
Notes |
---|---|---|---|
|
name of the package |
short string |
(1) |
|
version of this release |
short string |
(1)(2) |
|
package author’s name |
short string |
(3) |
|
email address of the package author |
email address |
(3) |
|
package maintainer’s name |
short string |
(3) |
|
email address of the package maintainer |
email address |
(3) |
|
home page for the package |
URL |
(1) |
|
short, summary description of the package |
short string |
|
|
longer description of the package |
long string |
(4) |
|
location where the package may be downloaded |
URL |
|
|
a list of classifiers |
list of strings |
(6)(7) |
|
a list of platforms |
list of strings |
(6)(8) |
|
a list of keywords |
list of strings |
(6)(8) |
|
license for the package |
short string |
(5) |
Notes:
These fields are required.
It is recommended that versions take the form major.minor[.patch[.sub]].
Either the author or the maintainer must be identified. If maintainer is provided, distutils lists it as the author in
PKG-INFO
.The
long_description
field is used by PyPI when you publish a package, to build its project page.The
license
field is a text indicating the license covering the package where the license is not a selection from the «License» Trove classifiers. See theClassifier
field. Notice that there’s alicence
distribution option which is deprecated but still acts as an alias forlicense
.This field must be a list.
The valid classifiers are listed on PyPI.
To preserve backward compatibility, this field also accepts a string. If you pass a comma-separated string
'foo, bar'
, it will be converted to['foo', 'bar']
, Otherwise, it will be converted to a list of one string.
- “short string”
A single line of text, not more than 200 characters.
- “long string”
Multiple lines of plain text in reStructuredText format (see http://docutils.sourceforge.net/).
- “list of strings”
See below.
Encoding the version information is an art in itself. Python packages generally adhere to the version format major.minor[.patch][sub]. The major number is 0 for initial, experimental releases of software. It is incremented for releases that represent major milestones in a package. The minor number is incremented when important new features are added to the package. The patch number increments when bug-fix releases are made. Additional trailing version information is sometimes used to indicate sub-releases. These are «a1,a2,…,aN» (for alpha releases, where functionality and API may change), «b1,b2,…,bN» (for beta releases, which only fix bugs) and «pr1,pr2,…,prN» (for final pre-release release testing). Some examples:
- 0.1.0
the first, experimental release of a package
- 1.0.1a2
the second alpha release of the first patch version of 1.0
classifiers
must be specified in a list:
setup(...,
classifiers=[
'Development Status :: 4 - Beta',
'Environment :: Console',
'Environment :: Web Environment',
'Intended Audience :: End Users/Desktop',
'Intended Audience :: Developers',
'Intended Audience :: System Administrators',
'License :: OSI Approved :: Python Software Foundation License',
'Operating System :: MacOS :: MacOS X',
'Operating System :: Microsoft :: Windows',
'Operating System :: POSIX',
'Programming Language :: Python',
'Topic :: Communications :: Email',
'Topic :: Office/Business',
'Topic :: Software Development :: Bug Tracking',
],
)
Distinto en la versión 3.7: setup
now warns when classifiers
, keywords
or platforms
fields are not specified as a list or a string.
2.9. Debugging the setup script¶
Sometimes things go wrong, and the setup script doesn’t do what the developer wants.
Distutils catches any exceptions when running the setup script, and print a simple error message before the script is terminated. The motivation for this behaviour is to not confuse administrators who don’t know much about Python and are trying to install a package. If they get a big long traceback from deep inside the guts of Distutils, they may think the package or the Python installation is broken because they don’t read all the way down to the bottom and see that it’s a permission problem.
On the other hand, this doesn’t help the developer to find the cause of the
failure. For this purpose, the DISTUTILS_DEBUG
environment variable can be set
to anything except an empty string, and distutils will now print detailed
information about what it is doing, dump the full traceback when an exception
occurs, and print the whole command line when an external program (like a C
compiler) fails.