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is a collection of enhancements to the Python (for Python 2.3.5 and up on most platforms; 64-bit platforms require a minimum of Python 2.4) that allow you to more easily build and distribute Python packages, especially ones that have dependencies on other packages.
Packages built and distributed using look to the user like ordinary Python packages based on the . Your users don't need to install or even know about setuptools in order to use them, and you don't have to include the entire setuptools package in your distributions. By including just a single bootstrap module (an 8K .py file), your package will automatically download and install if the user is building your package from source and doesn't have a suitable version already installed.
Feature Highlights:
In addition to the PyPI downloads, the development version of is available from the Python SVN sandbox, and in-development versions of the 0.6 branch are available as well.
Please follow the EasyInstall Installation Instructions to install the current stable version of setuptools. In particular, be sure to read the section on Custom Installation Locations if you are installing anywhere other than Python's directory.
If you want the current in-development version of setuptools, you should first install a stable version, and then run:
ez_setup.py setuptools==dev
This will download and install the latest development (i.e. unstable) version of setuptools from the Python Subversion sandbox.
For basic use of setuptools, just import things from setuptools instead of the distutils. Here's a minimal setup script using setuptools:
from setuptools import setup, find_packages setup( name = "HelloWorld", version = "0.1", packages = find_packages(), )
As you can see, it doesn't take much to use setuptools in a project. Just by doing the above, this project will be able to produce eggs, upload to PyPI, and automatically include all packages in the directory where the setup.py lives. See the Command Reference section below to see what commands you can give to this setup script.
Of course, before you release your project to PyPI, you'll want to add a bit more information to your setup script to help people find or learn about your project. And maybe your project will have grown by then to include a few dependencies, and perhaps some data files and scripts:
from setuptools import setup, find_packages
setup(
name = "HelloWorld",
version = "0.1",
packages = find_packages(),
scripts = ['say_hello.py'],
# Project uses reStructuredText, so ensure that the docutils get
# installed or upgraded on the target machine
install_requires = ['docutils>=0.3'],
package_data = {
# If any package contains *.txt or *.rst files, include them:
'': ['*.txt', '*.rst'],
# And include any *.msg files found in the 'hello' package, too:
'hello': ['*.msg'],
}
# metadata for upload to PyPI
author = "Me",
author_email = "me@example.com",
description = "This is an Example Package",
license = "PSF",
keywords = "hello world example examples",
url = "http://example.com/HelloWorld/", # project home page, if any
# could also include long_description, download_url, classifiers, etc.
)
In the sections that follow, we'll explain what most of these arguments do (except for the metadata ones), and the various ways you might use them in your own project(s).
Setuptools can work well with most versioning schemes; there are, however, a few special things to watch out for, in order to ensure that setuptools and EasyInstall can always tell what version of your package is newer than another version. Knowing these things will also help you correctly specify what versions of other projects your project depends on.
A version consists of an alternating series of release numbers and pre-release or post-release tags. A release number is a series of digits punctuated by dots, such as or . Each series of digits is treated numerically, so releases and are different ways to spell the same release number, denoting the first subrelease of release 2. But is the tenth subrelease of release 2, and so is a different and newer release from or . Leading zeros within a series of digits are also ignored, so is the same as , and different from .
Following a release number, you can have either a pre-release or post-release tag. Pre-release tags make a version be considered older than the version they are appended to. So, revision is newer than revision , which in turn is newer than or . Postrelease tags make a version be considered newer than the version they are appended to. So, revisions like and are newer than , but are older than (which has a higher release number).
A pre-release tag is a series of letters that are alphabetically before "final". Some examples of prerelease tags would include , , , , , and so on. You do not have to place a dot before the prerelease tag if it's immediately after a number, but it's okay to do so if you prefer. Thus, and both represent release candidate 1 of version , and are treated as identical by setuptools.
In addition, there are three special prerelease tags that are treated as if they were the letter : , , and . So, version , and are all the exact same version as , and are treated as identical by setuptools.
A post-release tag is either a series of letters that are alphabetically greater than or equal to "final", or a dash (). Post-release tags are generally used to separate patch numbers, port numbers, build numbers, revision numbers, or date stamps from the release number. For example, the version might denote Subversion revision 1263 of a post-release patch of version . Or you might use to denote a date-stamped post-release.
Notice that after each pre or post-release tag, you are free to place another release number, followed again by more pre- or post-release tags. For example, could denote Subversion revision 41475 of the in- development version of the ninth alpha of release 0.6. Notice that is a pre-release tag, so this version is a lower version number than , which would be the actual ninth alpha of release 0.6. But the is a post-release tag, so this version is newer than .
For the most part, setuptools' interpretation of version numbers is intuitive, but here are a few tips that will keep you out of trouble in the corner cases:
Don't use or any other character than as a separator, unless you really want a post-release. Remember that means you've already released , whereas and are candidates you're putting out before . If you accidentally distribute copies of a post-release that you meant to be a pre-release, the only safe fix is to bump your main release number (e.g. to ) and re-release the project.
Don't stick adjoining pre-release tags together without a dot or number between them. Version is the prerelease of , not a development pre-release of . Use instead, as in , or separate the prerelease tags with a number, as in . , , and even are identical versions from setuptools' point of view, so you can use whatever scheme you prefer.
If you want to be certain that your chosen numbering scheme works the way you think it will, you can use the function to compare different version numbers:
>>> from pkg_resources import parse_version
>>> parse_version('1.9.a.dev') == parse_version('1.9a0dev')
True
>>> parse_version('2.1-rc2') < parse_version('2.1')
False
>>> parse_version('0.6a9dev-r41475') < parse_version('0.6a9')
True
Once you've decided on a version numbering scheme for your project, you can have setuptools automatically tag your in-development releases with various pre- or post-release tags. See the following sections for more details:
The following keyword arguments to are added or changed by . All of them are optional; you do not have to supply them unless you need the associated feature.
A string or list of strings specifying what other distributions need to be present in order for the setup script to run. will attempt to obtain these (even going so far as to download them using ) before processing the rest of the setup script or commands. This argument is needed if you are using distutils extensions as part of your build process; for example, extensions that process setup() arguments and turn them into EGG-INFO metadata files.
(Note: projects listed in will NOT be automatically installed on the system where the setup script is being run. They are simply downloaded to the setup directory if they're not locally available already. If you want them to be installed, as well as being available when the setup script is run, you should add them to and .)
A string naming a subclass (or a package or module containing one or more of them, or a method of such a subclass), or naming a function that can be called with no arguments and returns a . If the named suite is a module, and the module has an function, it is called and the results are added to the tests to be run. If the named suite is a package, any submodules and subpackages are recursively added to the overall test suite.
Specifying this argument enables use of the test command to run the specified test suite, e.g. via . See the section on the test command below for more details.
If you would like to use a different way of finding tests to run than what setuptools normally uses, you can specify a module name and class name in this argument. The named class must be instantiable with no arguments, and its instances must support the method as defined in the Python module's class. Setuptools will pass only one test "name" in the names argument: the value supplied for the argument. The loader you specify may interpret this string in any way it likes, as there are no restrictions on what may be contained in a string.
The module name and class name must be separated by a . The default value of this argument is . If you want to use the default behavior, you can specify as your argument instead. This will prevent automatic scanning of submodules and subpackages.
The module and class you specify here may be contained in another package, as long as you use the option to ensure that the package containing the loader class is available when the command is run.
A list of strings naming resources that should be extracted together, if any of them is needed, or if any C extensions included in the project are imported. This argument is only useful if the project will be installed as a zipfile, and there is a need to have all of the listed resources be extracted to the filesystem as a unit. Resources listed here should be '/'-separated paths, relative to the source root, so to list a resource in package , you would include the string in this argument.
If you only need to obtain resources one at a time, or you don't have any C extensions that access other files in the project (such as data files or shared libraries), you probably do NOT need this argument and shouldn't mess with it. For more details on how this argument works, see the section below on Automatic Resource Extraction.
For simple projects, it's usually easy enough to manually add packages to the argument of . However, for very large projects (Twisted, PEAK, Zope, Chandler, etc.), it can be a big burden to keep the package list updated. That's what is for.
takes a source directory, and a list of package names or patterns to exclude. If omitted, the source directory defaults to the same directory as the setup script. Some projects use a or directory as the root of their source tree, and those projects would of course use or as the first argument to . (And such projects also need something like in their arguments, but that's just a normal distutils thing.)
Anyway, walks the target directory, and finds Python packages by looking for files. It then filters the list of packages using the exclusion patterns.
Exclusion patterns are package names, optionally including wildcards. For example, will exclude all packages whose last name part is . Or, will also exclude any subpackages of packages named , but it still won't exclude a top-level package or the children thereof. In fact, if you really want no packages at all, you'll need something like this:
find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"])
in order to cover all the bases. Really, the exclusion patterns are intended to cover simpler use cases than this, like excluding a single, specified package and its subpackages.
Regardless of the target directory or exclusions, the function returns a list of package names suitable for use as the argument to , and so is usually the easiest way to set that argument in your setup script. Especially since it frees you from having to remember to modify your setup script whenever your project grows additional top-level packages or subpackages.
Packaging and installing scripts can be a bit awkward with the distutils. For one thing, there's no easy way to have a script's filename match local conventions on both Windows and POSIX platforms. For another, you often have to create a separate file just for the "main" script, when your actual "main" is a function in a module somewhere. And even in Python 2.4, using the option only works for actual files that aren't installed in a package.
fixes all of these problems by automatically generating scripts for you with the correct extension, and on Windows it will even create an file so that users don't have to change their settings. The way to use this feature is to define "entry points" in your setup script that indicate what function the generated script should import and run. For example, to create two console scripts called and , and a GUI script called , you might do something like this:
setup(
# other arguments here...
entry_points = {
'console_scripts': [
'foo = my_package.some_module:main_func',
'bar = other_module:some_func',
],
'gui_scripts': [
'baz = my_package_gui.start_func',
]
}
)
When this project is installed on non-Windows platforms (using "setup.py install", "setup.py develop", or by using EasyInstall), a set of , , and scripts will be installed that import and from the specified modules. The functions you specify are called with no arguments, and their return value is passed to , so you can return an errorlevel or message to print to stderr.
On Windows, a set of , , and launchers are created, alongside a set of , , and files. The wrappers find and execute the right version of Python to run the or file.
You may define as many "console script" and "gui script" entry points as you like, and each one can optionally specify "extras" that it depends on, that will be added to when the script is run. For more information on "extras", see the section below on Declaring Extras. For more information on "entry points" in general, see the section below on Dynamic Discovery of Services and Plugins.
Occasionally, there are situations where it's desirable to make an file directly executable. You can do this by including an entry point such as the following:
setup(
# other arguments here...
entry_points = {
'setuptools.installation': [
'eggsecutable = my_package.some_module:main_func',
]
}
)
Any eggs built from the above setup script will include a short excecutable prelude that imports and calls from . The prelude can be run on Unix-like platforms (including Mac and Linux) by invoking the egg with , or by enabling execute permissions on the file. For the executable prelude to run, the appropriate version of Python must be available via the environment variable, under its "long" name. That is, if the egg is built for Python 2.3, there must be a executable present in a directory on .
This feature is primarily intended to support bootstrapping the installation of setuptools itself on non-Windows platforms, but may also be useful for other projects as well.
IMPORTANT NOTE: Eggs with an "eggsecutable" header cannot be renamed, or invoked via symlinks. They must be invoked using their original filename, in order to ensure that, once running, will know what project and version is in use. The header script will check this and exit with an error if the file has been renamed or is invoked via a symlink that changes its base name.
supports automatically installing dependencies when a package is installed, and including information about dependencies in Python Eggs (so that package management tools like EasyInstall can use the information).
and use a common syntax for specifying a project's required dependencies. This syntax consists of a project's PyPI name, optionally followed by a comma-separated list of "extras" in square brackets, optionally followed by a comma-separated list of version specifiers. A version specifier is one of the operators , , , , or , followed by a version identifier. Tokens may be separated by whitespace, but any whitespace or nonstandard characters within a project name or version identifier must be replaced with .
Version specifiers for a given project are internally sorted into ascending version order, and used to establish what ranges of versions are acceptable. Adjacent redundant conditions are also consolidated (e.g. becomes , and becomes ). versions are excised from the ranges they fall within. A project's version is then checked for membership in the resulting ranges. (Note that providing conflicting conditions for the same version (e.g. "<2,>=2" or "==2,!=2") is meaningless and may therefore produce bizarre results.)
Here are some example requirement specifiers:
docutils >= 0.3 # comment lines and \ continuations are allowed in requirement strings BazSpam ==1.1, ==1.2, ==1.3, ==1.4, ==1.5, \ ==1.6, ==1.7 # and so are line-end comments PEAK[FastCGI, reST]>=0.5a4 setuptools==0.5a7
The simplest way to include requirement specifiers is to use the argument to . It takes a string or list of strings containing requirement specifiers. If you include more than one requirement in a string, each requirement must begin on a new line.
This has three effects:
Note, by the way, that if you declare your dependencies in , you do not need to use the function in your scripts or modules, as long as you either install the project or use to do development work on it. (See "Development Mode" below for more details on using .)
If your project depends on packages that aren't registered in PyPI, you may still be able to depend on them, as long as they are available for download as an egg, in the standard distutils format, or as a single file. You just need to add some URLs to the argument to .
The URLs must be either:
In general, it's better to link to web pages, because it is usually less complex to update a web page than to release a new version of your project. You can also use a SourceForge link in the case where a package you depend on is distributed via SourceForge.
If you depend on a package that's distributed as a single file, you must include an suffix to the URL, to give a project name and version number. (Be sure to escape any dashes in the name or version by replacing them with underscores.) EasyInstall will recognize this suffix and automatically create a trivial to wrap the single file as an egg.
The option takes the form of a list of URL strings. For example, the below will cause EasyInstall to search the specified page for eggs or source distributions, if the package's dependencies aren't already installed:
setup( ... dependency_links = [ "http://peak.telecommunity.com/snapshots/" ], )
Sometimes a project has "recommended" dependencies, that are not required for all uses of the project. For example, a project might offer optional PDF output if ReportLab is installed, and reStructuredText support if docutils is installed. These optional features are called "extras", and setuptools allows you to define their requirements as well. In this way, other projects that require these optional features can force the additional requirements to be installed, by naming the desired extras in their .
For example, let's say that Project A offers optional PDF and reST support:
setup(
name="Project-A",
...
extras_require = {
'PDF': ["ReportLab>=1.2", "RXP"],
'reST': ["docutils>=0.3"],
}
)
As you can see, the argument takes a dictionary mapping names of "extra" features, to strings or lists of strings describing those features' requirements. These requirements will not be automatically installed unless another package depends on them (directly or indirectly) by including the desired "extras" in square brackets after the associated project name. (Or if the extras were listed in a requirement spec on the EasyInstall command line.)
Extras can be used by a project's entry points to specify dynamic dependencies. For example, if Project A includes a "rst2pdf" script, it might declare it like this, so that the "PDF" requirements are only resolved if the "rst2pdf" script is run:
setup(
name="Project-A",
...
entry_points = {
'console_scripts':
['rst2pdf = project_a.tools.pdfgen [PDF]'],
['rst2html = project_a.tools.htmlgen'],
# more script entry points ...
}
)
Projects can also use another project's extras when specifying dependencies. For example, if project B needs "project A" with PDF support installed, it might declare the dependency like this:
setup( name="Project-B", install_requires = ["Project-A[PDF]"], ... )
This will cause ReportLab to be installed along with project A, if project B is installed -- even if project A was already installed. In this way, a project can encapsulate groups of optional "downstream dependencies" under a feature name, so that packages that depend on it don't have to know what the downstream dependencies are. If a later version of Project A builds in PDF support and no longer needs ReportLab, or if it ends up needing other dependencies besides ReportLab in order to provide PDF support, Project B's setup information does not need to change, but the right packages will still be installed if needed.
Note, by the way, that if a project ends up not needing any other packages to support a feature, it should keep an empty requirements list for that feature in its argument, so that packages depending on that feature don't break (due to an invalid feature name). For example, if Project A above builds in PDF support and no longer needs ReportLab, it could change its setup to this:
setup(
name="Project-A",
...
extras_require = {
'PDF': [],
'reST': ["docutils>=0.3"],
}
)
so that Package B doesn't have to remove the from its requirement specifier.
The distutils have traditionally allowed installation of "data files", which are placed in a platform-specific location. However, the most common use case for data files distributed with a package is for use by the package, usually by including the data files in the package directory.
Setuptools offers three ways to specify data files to be included in your packages. First, you can simply use the keyword, e.g.:
from setuptools import setup, find_packages setup( ... include_package_data = True )
This tells setuptools to install any data files it finds in your packages. The data files must be under CVS or Subversion control, or else they must be specified via the distutils' file. (They can also be tracked by another revision control system, using an appropriate plugin. See the section below on Adding Support for Other Revision Control Systems for information on how to write such plugins.)
If you want finer-grained control over what files are included (for example, if you have documentation files in your package directories and want to exclude them from installation), then you can also use the keyword, e.g.:
from setuptools import setup, find_packages
setup(
...
package_data = {
# If any package contains *.txt or *.rst files, include them:
'': ['*.txt', '*.rst'],
# And include any *.msg files found in the 'hello' package, too:
'hello': ['*.msg'],
}
)
The argument is a dictionary that maps from package names to lists of glob patterns. The globs may include subdirectory names, if the data files are contained in a subdirectory of the package. For example, if the package tree looks like this:
setup.py src/ mypkg/ __init__.py mypkg.txt data/ somefile.dat otherdata.dat
The setuptools setup file might look like this:
from setuptools import setup, find_packages
setup(
...
packages = find_packages('src'), # include all packages under src
package_dir = {'':'src'}, # tell distutils packages are under src
package_data = {
# If any package contains *.txt files, include them:
'': ['*.txt'],
# And include any *.dat files found in the 'data' subdirectory
# of the 'mypkg' package, also:
'mypkg': ['data/*.dat'],
}
)
Notice that if you list patterns in under the empty string, these patterns are used to find files in every package, even ones that also have their own patterns listed. Thus, in the above example, the file gets included even though it's not listed in the patterns for .
Also notice that if you use paths, you must use a forward slash () as the path separator, even if you are on Windows. Setuptools automatically converts slashes to appropriate platform-specific separators at build time.
(Note: although the argument was previously only available in , it was also added to the Python package as of Python 2.4; there is some documentation for the feature available on the python.org website.)
Sometimes, the or options alone aren't sufficient to precisely define what files you want included. For example, you may want to include package README files in your revision control system and source distributions, but exclude them from being installed. So, setuptools offers an option as well, that allows you to do things like this:
from setuptools import setup, find_packages
setup(
...
packages = find_packages('src'), # include all packages under src
package_dir = {'':'src'}, # tell distutils packages are under src
include_package_data = True, # include everything in source control
# ...but exclude README.txt from all packages
exclude_package_data = { '': ['README.txt'] },
)
The option is a dictionary mapping package names to lists of wildcard patterns, just like the option. And, just as with that option, a key of will apply the given pattern(s) to all packages. However, any files that match these patterns will be excluded from installation, even if they were listed in or were included as a result of using .
In summary, the three options allow you to:
NOTE: Due to the way the distutils build process works, a data file that you include in your project and then stop including may be "orphaned" in your project's build directories, requiring you to run to fully remove them. This may also be important for your users and contributors if they track intermediate revisions of your project using Subversion; be sure to let them know when you make changes that remove files from inclusion so they can run .
Typically, existing programs manipulate a package's attribute in order to find the location of data files. However, this manipulation isn't compatible with PEP 302-based import hooks, including importing from zip files and Python Eggs. It is strongly recommended that, if you are using data files, you should use the Resource Management API of to access them. The module is distributed as part of setuptools, so if you're using setuptools to distribute your package, there is no reason not to use its resource management API. See also Accessing Package Resources for a quick example of converting code that uses to use instead.
The normally install general "data files" to a platform-specific location (e.g. ). This feature intended to be used for things like documentation, example configuration files, and the like. does not install these data files in a separate location, however. They are bundled inside the egg file or directory, alongside the Python modules and packages. The data files can also be accessed using the Resource Management API, by specifying a instead of a package name:
from pkg_resources import Requirement, resource_filename
filename = resource_filename(Requirement.parse("MyProject"),"sample.conf")
The above code will obtain the filename of the "sample.conf" file in the data root of the "MyProject" distribution.
Note, by the way, that this encapsulation of data files means that you can't actually install data files to some arbitrary location on a user's machine; this is a feature, not a bug. You can always include a script in your distribution that extracts and copies your the documentation or data files to a user-specified location, at their discretion. If you put related data files in a single directory, you can use with the directory name to get a filesystem directory that then can be copied with the module. (Even if your package is installed as a zipfile, calling on a directory will return an actual filesystem directory, whose contents will be that entire subtree of your distribution.)
(Of course, if you're writing a new package, you can just as easily place your data files or directories inside one of your packages, rather than using the distutils' approach. However, if you're updating an existing application, it may be simpler not to change the way it currently specifies these data files.)
If you are using tools that expect your resources to be "real" files, or your project includes non-extension native libraries or other files that your C extensions expect to be able to access, you may need to list those files in the argument to , so that the files will be extracted together, whenever a C extension in the project is imported.
This is especially important if your project includes shared libraries other than distutils-built C extensions, and those shared libraries use file extensions other than , , or , which are the extensions that setuptools 0.6a8 and higher automatically detects as shared libraries and adds to the file for you. Any shared libraries whose names do not end with one of those extensions should be listed as , because they need to be present in the filesystem when he C extensions that link to them are used.
The runtime for compressed packages will automatically extract all C extensions and at the same time, whenever any C extension or eager resource is requested via the API. (C extensions are imported using internally.) This ensures that C extensions will see all of the "real" files that they expect to see.
Note also that you can list directory resource names in as well, in which case the directory's contents (including subdirectories) will be extracted whenever any C extension or eager resource is requested.
Please note that if you're not sure whether you need to use this argument, you don't! It's really intended to support projects with lots of non-Python dependencies and as a last resort for crufty projects that can't otherwise handle being compressed. If your package is pure Python, Python plus data files, or Python plus C, you really don't need this. You've got to be using either C or an external program that needs "real" files in your project before there's any possibility of being relevant to your project.
supports creating libraries that "plug in" to extensible applications and frameworks, by letting you register "entry points" in your project that can be imported by the application or framework.
For example, suppose that a blogging tool wants to support plugins that provide translation for various file types to the blog's output format. The framework might define an "entry point group" called , and then allow plugins to register entry points for the file extensions they support.
This would allow people to create distributions that contain one or more parsers for different file types, and then the blogging tool would be able to find the parsers at runtime by looking up an entry point for the file extension (or mime type, or however it wants to).
Note that if the blogging tool includes parsers for certain file formats, it can register these as entry points in its own setup script, which means it doesn't have to special-case its built-in formats. They can just be treated the same as any other plugin's entry points would be.
If you're creating a project that plugs in to an existing application or framework, you'll need to know what entry points or entry point groups are defined by that application or framework. Then, you can register entry points in your setup script. Here are a few examples of ways you might register an file parser entry point in the entry point group, for our hypothetical blogging tool:
setup(
# ...
entry_points = {'blogtool.parsers': '.rst = some_module:SomeClass'}
)
setup(
# ...
entry_points = {'blogtool.parsers': ['.rst = some_module:a_func']}
)
setup(
# ...
entry_points = """
[blogtool.parsers]
.rst = some.nested.module:SomeClass.some_classmethod [reST]
""",
extras_require = dict(reST = "Docutils>=0.3.5")
)
The argument to accepts either a string with -style sections, or a dictionary mapping entry point group names to either strings or lists of strings containing entry point specifiers. An entry point specifier consists of a name and value, separated by an sign. The value consists of a dotted module name, optionally followed by a and a dotted identifier naming an object within the module. It can also include a bracketed list of "extras" that are required for the entry point to be used. When the invoking application or framework requests loading of an entry point, any requirements implied by the associated extras will be passed to , so that an appropriate error message can be displayed if the needed package(s) are missing. (Of course, the invoking app or framework can ignore such errors if it wants to make an entry point optional if a requirement isn't installed.)
Some extensible applications and frameworks may need to define their own kinds of metadata to include in eggs, which they can then access using the metadata APIs. Ordinarily, this is done by having plugin developers include additional files in their directory. However, since it can be tedious to create such files by hand, you may want to create a distutils extension that will create the necessary files from arguments to , in much the same way that does for many of the arguments it adds. See the section below on Creating distutils Extensions for more details, especially the subsection on Adding new EGG-INFO Files.
Under normal circumstances, the assume that you are going to build a distribution of your project, not use it in its "raw" or "unbuilt" form. If you were to use the that way, you would have to rebuild and reinstall your project every time you made a change to it during development.
Another problem that sometimes comes up with the is that you may need to do development on two related projects at the same time. You may need to put both projects' packages in the same directory to run them, but need to keep them separate for revision control purposes. How can you do this?
Setuptools allows you to deploy your projects for use in a common directory or staging area, but without copying any files. Thus, you can edit each project's code in its checkout directory, and only need to run build commands when you change a project's C extensions or similarly compiled files. You can even deploy a project into another project's checkout directory, if that's your preferred way of working (as opposed to using a common independent staging area or the site-packages directory).
To do this, use the command. It works very similarly to or the EasyInstall tool, except that it doesn't actually install anything. Instead, it creates a special file in the deployment directory, that links to your project's source code. And, if your deployment directory is Python's directory, it will also update the file to include your project's source code, thereby making it available on for all programs using that Python installation.
In addition, the command creates wrapper scripts in the target script directory that will run your in-development scripts after ensuring that all your packages are available on .
You can deploy the same project to multiple staging areas, e.g. if you have multiple projects on the same machine that are sharing the same project you're doing development work.
When you're done with a given development task, you can remove the project source from a staging area using , specifying the desired staging area if it's not the default.
There are several options to control the precise behavior of the command; see the section on the develop command below for more details.
Note that you can also apply setuptools commands to non-setuptools projects, using commands like this:
python -c "import setuptools; execfile('setup.py')" develop
That is, you can simply list the normal setup commands and options following the quoted part.
Your users might not have installed on their machines, or even if they do, it might not be the right version. Fixing this is easy; just download ez_setup.py, and put it in the same directory as your script. (Be sure to add it to your revision control system, too.) Then add these two lines to the very top of your setup script, before the script imports anything from setuptools:
import ez_setup ez_setup.use_setuptools()
That's it. The module will automatically download a matching version of from PyPI, if it isn't present on the target system. Whenever you install an updated version of setuptools, you should also update your projects' files, so that a matching version gets installed on the target machine(s).
By the way, setuptools supports the new PyPI "upload" command, so you can use or to upload your source or egg distributions respectively. Your project's current version must be registered with PyPI first, of course; you can use to do that. Or you can do it all in one step, e.g. will register the package, build source and egg distributions, and then upload them both to PyPI, where they'll be easily found by other projects that depend on them.
(By the way, if you need to distribute a specific version of , you can specify the exact version and base download URL as parameters to the function. See the function's docstring for details.)
In general, a setuptools-based project looks just like any distutils-based project -- as long as your users have an internet connection and are installing to , that is. But for some users, these conditions don't apply, and they may become frustrated if this is their first encounter with a setuptools-based project. To keep these users happy, you should review the following topics in your project's installation instructions, if they are relevant to your project and your target audience isn't already familiar with setuptools and .
If your project depends on other projects that may need to be downloaded from PyPI or elsewhere, you should list them in your installation instructions, or tell users how to find out what they are. While most users will not need this information, any users who don't have unrestricted internet access may have to find, download, and install the other projects manually. (Note, however, that they must still install those projects using , or your project will not know they are installed, and your setup script will try to download them again.)
If you want to be especially friendly to users with limited network access, you may wish to build eggs for your project and its dependencies, making them all available for download from your site, or at least create a page with links to all of the needed eggs. In this way, users with limited network access can manually download all the eggs to a single directory, then use the option of to specify the directory to find eggs in. Users who have full network access can just use with the URL of your download page, and will find all the needed eggs using your links directly. This is also useful when your target audience isn't able to compile packages (e.g. most Windows users) and your package or some of its dependencies include C code.
Users and co-developers who are tracking your in-development code using CVS, Subversion, or some other revision control system should probably read this manual's sections regarding such development. Alternately, you may wish to create a quick-reference guide containing the tips from this manual that apply to your particular situation. For example, if you recommend that people use when tracking your in-development code, you should let them know that this needs to be run after every update or commit.
Similarly, if you remove modules or data files from your project, you should remind them to run and delete any obsolete or . (This tip applies to the distutils in general, not just setuptools, but not everybody knows about them; be kind to your users by spelling out your project's best practices rather than leaving them guessing.)
Some users want to manage all Python packages using a single package manager, and sometimes that package manager isn't ! Setuptools currently supports , , and formats for system packaging. If a user has a locally- installed "bdist" packaging tool that internally uses the distutils command, it should be able to work with . Some examples of "bdist" formats that this should work with include the and formats for Windows.
However, packaging tools that build binary distributions by running on the command line or as a subprocess will require modification to work with setuptools. They should use the option to the command, combined with the standard or options. See the install command documentation below for more details. The command is an example of a command that currently requires this kind of patching to work with setuptools.
If you or your users have a problem building a usable system package for your project, please report the problem via the `mailing list`_ so that either the "bdist" tool in question or setuptools can be modified to resolve the issue.
If you're managing several projects that need to use , and you are using Subversion as your revision control system, you can use the "svn:externals" property to share a single copy of between projects, so that it will always be up-to-date whenever you check out or update an individual project, without having to manually update each project to use a new version.
However, because Subversion only supports using directories as externals, you have to turn into in order to do this, then create "externals" definitions that map the directory into each project. Also, if any of your projects use on their setup directory, you will need to exclude the resulting package, to keep it from being included in your distributions, e.g.:
setup( ... packages = find_packages(exclude=['ez_setup']), )
Of course, the package will still be included in your packages' source distributions, as it needs to be.
For your convenience, you may use the following external definition, which will track the latest version of setuptools:
ez_setup svn://svn.eby-sarna.com/svnroot/ez_setup
You can set this by executing this command in your project directory:
svn propedit svn:externals .
And then adding the line shown above to the file that comes up for editing.
For maximum performance, Python packages are best installed as zip files. Not all packages, however, are capable of running in compressed form, because they may expect to be able to access either source code or data files as normal operating system files. So, can install your project as a zipfile or a directory, and its default choice is determined by the project's flag.
You can pass a True or False value for the argument to the function, or you can omit it. If you omit it, the command will analyze your project's contents to see if it can detect any conditions that would prevent it from working in a zipfile. It will output notices to the console about any such conditions that it finds.
Currently, this analysis is extremely conservative: it will consider the project unsafe if it contains any C extensions or datafiles whatsoever. This does not mean that the project can't or won't work as a zipfile! It just means that the authors aren't yet comfortable asserting that the project will work. If the project contains no C or data files, and does no or introspection or source code manipulation, then there is an extremely solid chance the project will work when installed as a zipfile. (And if the project uses for all its data file access, then C extensions and other data files shouldn't be a problem at all. See the Accessing Data Files at Runtime section above for more information.)
However, if can't be sure that your package will work, but you've checked over all the warnings it issued, and you are either satisfied it will work (or if you want to try it for yourself), then you should set to in your call. If it turns out that it doesn't work, you can always change it to , which will force to install your project as a directory rather than as a zipfile.
Of course, the end-user can still override either decision, if they are using EasyInstall to install your package. And, if you want to override for testing purposes, you can just run or in your project directory. to install the package as a zipfile or directory, respectively.
In the future, as we gain more experience with different packages and become more satisfied with the robustness of the runtime, the "zip safety" analysis may become less conservative. However, we strongly recommend that you determine for yourself whether your project functions correctly when installed as a zipfile, correct any problems if you can, and then make an explicit declaration of or for the flag, so that it will not be necessary for or to try to guess whether your project can work as a zipfile.
Sometimes, a large package is more useful if distributed as a collection of smaller eggs. However, Python does not normally allow the contents of a package to be retrieved from more than one location. "Namespace packages" are a solution for this problem. When you declare a package to be a namespace package, it means that the package has no meaningful contents in its , and that it is merely a container for modules and subpackages.
The runtime will then automatically ensure that the contents of namespace packages that are spread over multiple eggs or directories are combined into a single "virtual" package.
The argument to lets you declare your project's namespace packages, so that they will be included in your project's metadata. The argument should list the namespace packages that the egg participates in. For example, the ZopeInterface project might do this:
setup( # ... namespace_packages = ['zope'] )
because it contains a package that lives in the namespace package. Similarly, a project for a standalone would also declare the namespace package. When these projects are installed and used, Python will see them both as part of a "virtual" package, even though they will be installed in different locations.
Namespace packages don't have to be top-level packages. For example, Zope 3's package is a namespace package, and in the future PEAK's package will be too.
Note, by the way, that your project's source tree must include the namespace packages' files (and the of any parent packages), in a normal Python package layout. These files must contain the line:
__import__('pkg_resources').declare_namespace(__name__)
This code ensures that the namespace package machinery is operating and that the current package is registered as a namespace package.
You must NOT include any other code and data in a namespace package's . Even though it may appear to work during development, or when projects are installed as files, it will not work when the projects are installed using "system" packaging tools -- in such cases the files will not be installed, let alone executed.
You must include the line in the of every project that has contents for the namespace package in question, in order to ensure that the namespace will be declared regardless of which project's copy of is loaded first. If the first loaded doesn't declare it, it will never be declared, because no other copies will ever be loaded!)
Setuptools 0.6a automatically calls for you at runtime, but the 0.7a versions will not. This is because the automatic declaration feature has some negative side effects, such as needing to import all namespace packages during the initialization of the runtime, and also the need for to be explicitly imported before any namespace packages work at all. Beginning with the 0.7a releases, you'll be responsible for including your own declaration lines, and the automatic declaration feature will be dropped to get rid of the negative side effects.
During the remainder of the 0.6 development cycle, therefore, setuptools will warn you about missing calls in your files, and you should correct these as soon as possible before setuptools 0.7a1 is released. Namespace packages without declaration lines will not work correctly once a user has upgraded to setuptools 0.7a1, so it's important that you make this change now in order to avoid having your code break in the field. Our apologies for the inconvenience, and thank you for your patience.
When a set of related projects are under development, it may be important to track finer-grained version increments than you would normally use for e.g. "stable" releases. While stable releases might be measured in dotted numbers with alpha/beta/etc. status codes, development versions of a project often need to be tracked by revision or build number or even build date. This is especially true when projects in development need to refer to one another, and therefore may literally need an up-to-the-minute version of something!
To support these scenarios, allows you to "tag" your source and egg distributions by adding one or more of the following to the project's "official" version identifier:
You can add these tags by adding and the desired options to the command line ahead of the or commands that you want to generate a daily build or snapshot for. See the section below on the egg_info command for more details.
(Also, before you release your project, be sure to see the section above on Specifying Your Project's Version for more information about how pre- and post-release tags affect how setuptools and EasyInstall interpret version numbers. This is important in order to make sure that dependency processing tools will know which versions of your project are newer than others.)
Finally, if you are creating builds frequently, and either building them in a downloadable location or are copying them to a distribution server, you should probably also check out the rotate command, which lets you automatically delete all but the N most-recently-modified distributions matching a glob pattern. So, you can use a command line like:
setup.py egg_info -rbDEV bdist_egg rotate -m.egg -k3
to build an egg whose version info includes 'DEV-rNNNN' (where NNNN is the most recent Subversion revision that affected the source tree), and then delete any egg files from the distribution directory except for the three that were built most recently.
If you have to manage automated builds for multiple packages, each with different tagging and rotation policies, you may also want to check out the alias command, which would let each package define an alias like that would perform the necessary tag, build, and rotate commands. Then, a simpler script or cron job could just run in each project directory. (And, you could also define sitewide or per-user default versions of the alias, so that projects that didn't define their own would use the appropriate defaults.)
enhances the distutils' default algorithm for source file selection, so that all files managed by CVS or Subversion in your project tree are included in any source distribution you build. This is a big improvement over having to manually write a file and try to keep it in sync with your project. So, if you are using CVS or Subversion, and your source distributions only need to include files that you're tracking in revision control, don't create a a file for your project. (And, if you already have one, you might consider deleting it the next time you would otherwise have to change it.)
(NOTE: other revision control systems besides CVS and Subversion can be supported using plugins; see the section below on Adding Support for Other Revision Control Systems for information on how to write such plugins.)
If you need to include automatically generated files, or files that are kept in an unsupported revision control system, you'll need to create a file to specify any files that the default file location algorithm doesn't catch. See the distutils documentation for more information on the format of the file.
But, be sure to ignore any part of the distutils documentation that deals with or how it's generated from ; setuptools shields you from these issues and doesn't work the same way in any case. Unlike the distutils, setuptools regenerates the source distribution manifest file every time you build a source distribution, and it builds it inside the project's directory, out of the way of your main project directory. You therefore need not worry about whether it is up-to-date or not.
Indeed, because setuptools' approach to determining the contents of a source distribution is so much simpler, its command omits nearly all of the options that the distutils' more complex process requires. For all practical purposes, you'll probably use only the option, if you use any option at all.
(By the way, if you're using some other revision control system, you might consider creating and publishing a revision control plugin for setuptools.)
If you use the command () to register your package with PyPI, that's most of the battle right there. (See the docs for the register command for more details.)
If you also use the upload command to upload actual distributions of your package, that's even better, because EasyInstall will be able to find and download them directly from your project's PyPI page.
However, there may be reasons why you don't want to upload distributions to PyPI, and just want your existing distributions (or perhaps a Subversion checkout) to be used instead.
So here's what you need to do before running the command. There are three arguments that affect EasyInstall:
A URL is considered a "primary link" if it is a link to a .tar.gz, .tgz, .zip, .egg, .egg.zip, .tar.bz2, or .exe file, or if it has an or fragment identifier attached to it. EasyInstall attempts to determine a project name and optional version number from the text of a primary link without downloading it. When it has found all the primary links, EasyInstall will select the best match based on requested version, platform compatibility, and other criteria.
So, if your or point either directly to a downloadable source distribution, or to HTML page(s) that have direct links to such, then EasyInstall will be able to locate downloads automatically. If you want to make Subversion checkouts available, then you should create links with either or added to the URL. You should replace and with the values they would have in an egg filename. (Be sure to actually generate an egg and then use the initial part of the filename, rather than trying to guess what the escaped form of the project name and version number will be.)
Note that Subversion checkout links are of lower precedence than other kinds of distributions, so EasyInstall will not select a Subversion checkout for downloading unless it has a version included in the suffix, and it's a higher version than EasyInstall has seen in any other links for your project.
As a result, it's a common practice to use mark checkout URLs with a version of "dev" (i.e., ), so that users can do something like this:
easy_install --editable projectname==dev
in order to check out the in-development version of .
If you expect your users to track in-development versions of your project via Subversion, there are a few additional steps you should take to ensure that things work smoothly with EasyInstall. First, you should add the following to your project's file:
[egg_info] tag_build = .dev tag_svn_revision = 1
This will tell to generate package version numbers like , which will be considered to be an older release than . Thus, when you actually release , the entire egg infrastructure (including , and EasyInstall) will know that supersedes any interim snapshots from Subversion, and handle upgrades accordingly.
(Note: the project version number you specify in should always be the next version of your software, not the last released version. Alternately, you can leave out the , and always use the last release as a version number, so that your post-1.0 builds are labelled , indicating a post-1.0 patchlevel. Most projects so far, however, seem to prefer to think of their project as being a future version still under development, rather than a past version being patched. It is of course possible for a single project to have both situations, using post-release numbering on release branches, and pre-release numbering on the trunk. But you don't have to make things this complex if you don't want to.)
Commonly, projects releasing code from Subversion will include a PyPI link to their checkout URL (as described in the previous section) with an suffix. This allows users to request EasyInstall to download in order to get the latest in-development code. Note that if your project depends on such in-progress code, you may wish to specify your (or other requirements) to include , e.g.:
install_requires = ["OtherProject>=0.2a1.dev-r143,==dev"]
The above example says, "I really want at least this particular development revision number, but feel free to follow and use an link if you find one". This avoids the need to have actual source or binary distribution snapshots of in-development code available, just to be able to depend on the latest and greatest a project has to offer.
A final note for Subversion development: if you are using SVN revision tags as described in this section, it's a good idea to run after each Subversion checkin or update, because your project's version number will be changing, and your script wrappers need to be updated accordingly.
Also, if the project's requirements have changed, the command will take care of fetching the updated dependencies, building changed extensions, etc. Be sure to also remind any of your users who check out your project from Subversion that they need to run after every update in order to keep their checkout completely in sync.
When you make an official release, creating source or binary distributions, you will need to override the tag settings from , so that you don't end up registering versions like . This is easy to do if you are developing on the trunk and using tags or branches for your releases - just make the change to after branching or tagging the release, so the trunk will still produce development snapshots.
Alternately, if you are not branching for releases, you can override the default version options on the command line, using something like:
python setup.py egg_info -RDb "" sdist bdist_egg register upload
The first part of this command () will override the configured tag information, before creating source and binary eggs, registering the project with PyPI, and uploading the files. Thus, these commands will use the plain version from your , without adding the Subversion revision number or build designation string.
Of course, if you will be doing this a lot, you may wish to create a personal alias for this operation, e.g.:
python setup.py alias -u release egg_info -RDb ""
You can then use it like this:
python setup.py release sdist bdist_egg register upload
Or of course you can create more elaborate aliases that do all of the above. See the sections below on the egg_info and alias commands for more ideas.
includes transparent support for building Pyrex extensions, as long as you define your extensions using , not . You must also not import anything from Pyrex in your setup script.
If you follow these rules, you can safely list files as the source of your objects in the setup script. will detect at build time whether Pyrex is installed or not. If it is, then will use it. If not, then will silently change the objects to refer to the counterparts of the files, so that the normal distutils C compilation process will occur.
Of course, for this to work, your source distributions must include the C code generated by Pyrex, as well as your original files. This means that you will probably want to include current files in your revision control system, rebuilding them whenever you check changes in for the source files. This will ensure that people tracking your project in CVS or Subversion will be able to build it even if they don't have Pyrex installed, and that your source releases will be similarly usable with or without Pyrex.
Sometimes, you need to use the same commands over and over, but you can't necessarily set them as defaults. For example, if you produce both development snapshot releases and "stable" releases of a project, you may want to put the distributions in different places, or use different tagging options, etc. In these cases, it doesn't make sense to set the options in a distutils configuration file, because the values of the options changed based on what you're trying to do.
Setuptools therefore allows you to define "aliases" - shortcut names for an arbitrary string of commands and options, using , where aliasname is the name of the new alias, and the remainder of the command line supplies its expansion. For example, this command defines a sitewide alias called "daily", that sets various tagging options:
setup.py alias --global-config daily egg_info --tag-svn-revision \ --tag-build=development
Once the alias is defined, it can then be used with other setup commands, e.g.:
setup.py daily bdist_egg # generate a daily-build .egg file setup.py daily sdist # generate a daily-build source distro setup.py daily sdist bdist_egg # generate both
The above commands are interpreted as if the word were replaced with .
Note that setuptools will expand each alias at most once in a given command line. This serves two purposes. First, if you accidentally create an alias loop, it will have no effect; you'll instead get an error message about an unknown command. Second, it allows you to define an alias for a command, that uses that command. For example, this (project-local) alias:
setup.py alias bdist_egg bdist_egg rotate -k1 -m.egg
redefines the command so that it always runs the command afterwards to delete all but the newest egg file. It doesn't loop indefinitely on because the alias is only expanded once when used.
You can remove a defined alias with the (or ) option, e.g.:
setup.py alias --global-config --remove daily
would delete the "daily" alias we defined above.
Aliases can be defined on a project-specific, per-user, or sitewide basis. The default is to define or remove a project-specific alias, but you can use any of the configuration file options (listed under the saveopts command, below) to determine which distutils configuration file an aliases will be added to (or removed from).
Note that if you omit the "expansion" argument to the command, you'll get output showing that alias' current definition (and what configuration file it's defined in). If you omit the alias name as well, you'll get a listing of all current aliases along with their configuration file locations.
This command generates a Python Egg ( file) for the project. Python Eggs are the preferred binary distribution format for EasyInstall, because they are cross-platform (for "pure" packages), directly importable, and contain project metadata including scripts and information about the project's dependencies. They can be simply downloaded and added to directly, or they can be placed in a directory on and then automatically discovered by the egg runtime system.
This command runs the egg_info command (if it hasn't already run) to update the project's metadata () directory. If you have added any extra metadata files to the directory, those files will be included in the new egg file's metadata directory, for use by the egg runtime system or by any applications or frameworks that use that metadata.
You won't usually need to specify any special options for this command; just use and you're done. But there are a few options that may be occasionally useful:
There are also some options you will probably never need, but which are there because they were copied from similar commands used as an example for creating this one. They may be useful for testing and debugging, however, which is why we kept them:
This command allows you to deploy your project's source for use in one or more "staging areas" where it will be available for importing. This deployment is done in such a way that changes to the project source are immediately available in the staging area(s), without needing to run a build or install step after each change.
The command works by creating an file (named for the project) in the given staging area. If the staging area is Python's directory, it also updates an file so that the project is on by default for all programs run using that Python installation.
The command also installs wrapper scripts in the staging area (or a separate directory, as specified) that will ensure the project's dependencies are available on before running the project's source scripts. And, it ensures that any missing project dependencies are available in the staging area, by downloading and installing them if necessary.
Last, but not least, the command invokes the command to ensure any C extensions in the project have been built and are up-to-date, and the command to ensure the project's metadata is updated (so that the runtime and wrappers know what the project's dependencies are). If you make any changes to the project's setup script or C extensions, you should rerun the command against all relevant staging areas to keep the project's scripts, metadata and extensions up-to-date. Most other kinds of changes to your project should not require any build operations or rerunning , but keep in mind that even minor changes to the setup script (e.g. changing an entry point definition) require you to re-run the or commands to keep the distribution updated.
Here are some of the options that the command accepts. Note that they affect the project's dependencies as well as the project itself, so if you have dependencies that need to be installed and you use (for example), the dependencies' scripts will not be installed either! For this reason, you may want to use EasyInstall to install the project's dependencies before using the command, if you need finer control over the installation options for dependencies.
Un-deploy the current project. You may use the or option to designate the staging area. The created file will be removed, if present and it is still pointing to the project directory. The project directory will be removed from if the staging area is Python's directory.
Note that this option currently does not uninstall script wrappers! You must uninstall them yourself, or overwrite them by using EasyInstall to activate a different version of the package. You can also avoid installing script wrappers in the first place, if you use the (aka ) option when you run to deploy the project.
"Multi-version" mode. Specifying this option prevents from adding an entry for the project(s) being deployed, and if an entry for any version of a project already exists, the entry will be removed upon successful deployment. In multi-version mode, no specific version of the package is available for importing, unless you use to put it on , or you are running a wrapper script generated by or EasyInstall. (In which case the wrapper script calls for you.)
Note that if you install to a directory other than , this option is automatically in effect, because files can only be used in (at least in Python 2.3 and 2.4). So, if you use the or option (or they are set via configuration file(s)) your project and its dependencies will be deployed in multi- version mode.
In addition to the above options, the command also accepts all of the same options accepted by . If you've configured any settings in your (or other distutils config files), the command will use them as defaults, unless you override them in a section or on the command line.
This command runs the EasyInstall tool for you. It is exactly equivalent to running the command. All command line arguments following this command are consumed and not processed further by the distutils, so this must be the last command listed on the command line. Please see the EasyInstall documentation for the options reference and usage examples. Normally, there is no reason to use this command via the command line, as you can just use directly. It's only listed here so that you know it's a distutils command, which means that you can:
The setuptools command is basically a shortcut to run the command on the current project. However, for convenience in creating "system packages" of setuptools-based projects, you can also use this option:
This option is automatically in effect when is invoked by another distutils command, so that commands like and will create system packages of eggs. It is also automatically in effect if you specify the option.
Setuptools runs this command as part of operations that use the options. You should not invoke it directly; it is documented here for completeness and so that distutils extensions such as system package builders can make use of it. This command has only one option:
This command assumes that the command has been given valid options via the command line or , as it will invoke the command and use its options to locate the project's source directory.
As you develop new versions of your project, your distribution () directory will gradually fill up with older source and/or binary distribution files. The command lets you automatically clean these up, keeping only the N most-recently modified files matching a given pattern.
Example 1: Delete all .tar.gz files from the distribution directory, except for the 3 most recently modified ones:
setup.py rotate --match=.tar.gz --keep=3
Example 2: Delete all Python 2.3 or Python 2.4 eggs from the distribution directory, except the most recently modified one for each Python version:
setup.py rotate --match=-py2.3*.egg,-py2.4*.egg --keep=1
Finding and editing configuration files can be a pain, especially since you also have to translate the configuration options from command-line form to the proper configuration file format. You can avoid these hassles by using the command. Just add it to the command line to save the options you used. For example, this command builds the project using the C compiler, then saves the --compiler setting as the default for future builds (even those run implicitly by the command):
setup.py build --compiler=mingw32 saveopts
The command saves all options for every commmand specified on the command line to the project's local file, unless you use one of the configuration file options to change where the options are saved. For example, this command does the same as above, but saves the compiler setting to the site-wide (global) distutils configuration:
setup.py build --compiler=mingw32 saveopts -g
Note that it doesn't matter where you place the command on the command line; it will still save all the options specified for all commands. For example, this is another valid way to spell the last example:
setup.py saveopts -g build --compiler=mingw32
Note, however, that all of the commands specified are always run, regardless of where is placed on the command line.
Normally, settings such as options and aliases are saved to the project's local file. But you can override this and save them to the global or per-user configuration files, or to a manually-specified filename.
These options are used by other commands that modify configuration files, such as the alias and setopt commands.
This command is mainly for use by scripts, but it can also be used as a quick and dirty way to change a distutils configuration option without having to remember what file the options are in and then open an editor.
Example 1. Set the default C compiler to (using long option names):
setup.py setopt --command=build --option=compiler --set-value=mingw32
Example 2. Remove any setting for the distutils default package installation directory (short option names):
setup.py setopt -c install -o install_lib -r
Options for the command:
In addition to the above options, you may use any of the configuration file options (listed under the saveopts command, above) to determine which distutils configuration file the option will be added to (or removed from).
When doing test-driven development, or running automated builds that need testing before they are deployed for downloading or use, it's often useful to be able to run a project's unit tests without actually deploying the project anywhere, even using the command. The command runs a project's unit tests without actually deploying it, by temporarily putting the project's source on , after first running and to ensure that any C extensions and project metadata are up-to-date.
To use this command, your project's tests must be wrapped in a test suite by either a function, a class or method, or a module or package containing classes. If the named suite is a module, and the module has an function, it is called and the result (which must be a ) is added to the tests to be run. If the named suite is a package, any submodules and subpackages are recursively added to the overall test suite. (Note: if your project specifies a , the rules for processing the chosen may differ; see the test_loader documentation for more details.)
Note that many test systems including support wrapping their non- tests in objects. So, if you are using a test package that does not support this, we suggest you encourage its developers to implement test suite support, as this is a convenient and standard way to aggregate a collection of tests to be run under a common test harness.
By default, tests will be run in the "verbose" mode of the package's text test runner, but you can get the "quiet" mode (just dots) if you supply the or option, either as a global option to the setup script (e.g. ) or as an option for the command itself (e.g. ). There is one other option available:
Specify the test suite (or module, class, or method) to be run (e.g. ). The default for this option can be set by giving a argument to the function, e.g.:
setup( # ... test_suite = "my_package.tests.test_all" )
If you did not set a in your call, and do not provide a option, an error will occur.
PyPI now supports uploading project files for redistribution; uploaded files are easily found by EasyInstall, even if you don't have download links on your project's home page.
Although Python 2.5 will support uploading all types of distributions to PyPI, setuptools only supports source distributions and eggs. (This is partly because PyPI's upload support is currently broken for various other file types.) To upload files, you must include the command after the or commands on the setup command line. For example:
setup.py bdist_egg upload # create an egg and upload it setup.py sdist upload # create a source distro and upload it setup.py sdist bdist_egg upload # create and upload both
Note that to upload files for a project, the corresponding version must already be registered with PyPI, using the distutils command. It's usually a good idea to include the command at the start of the command line, so that any registration problems can be found and fixed before building and uploading the distributions, e.g.:
setup.py register sdist bdist_egg upload
This will update PyPI's listing for your project's current version.
Note, by the way, that the metadata in your call determines what will be listed in PyPI for your package. Try to fill out as much of it as possible, as it will save you a lot of trouble manually adding and updating your PyPI listings. Just put it in and use the comamnd to keep PyPI up to date.
The command has a few options worth noting:
It can be hard to add new commands or setup arguments to the distutils. But the package makes it a bit easier, by allowing you to distribute a distutils extension as a separate project, and then have projects that need the extension just refer to it in their argument.
With , your distutils extension projects can hook in new commands and arguments just by defining "entry points". These are mappings from command or argument names to a specification of where to import a handler from. (See the section on Dynamic Discovery of Services and Plugins above for some more background on entry points.)
You can add new commands by defining entry points in the group. For example, if you wanted to add a command, you might add something like this to your distutils extension project's setup script:
setup(
# ...
entry_points = {
"distutils.commands": [
"foo = mypackage.some_module:foo",
],
},
)
(Assuming, of course, that the class in is a subclass.)
Once a project containing such entry points has been activated on , (e.g. by running "install" or "develop" with a site-packages installation directory) the command(s) will be available to any -based setup scripts. It is not necessary to use the option or to monkeypatch the package to install your commands; automatically adds a wrapper to the distutils to search for entry points in the active distributions on . In fact, this is how setuptools' own commands are installed: the setuptools project's setup script defines entry points for them!
Sometimes, your commands may need additional arguments to the call. You can enable this by defining entry points in the group. For example, if you wanted a argument called , you might add something like this to your distutils extension project's setup script:
setup(
# ...
entry_points = {
"distutils.commands": [
"foo = mypackage.some_module:foo",
],
"distutils.setup_keywords": [
"bar_baz = mypackage.some_module:validate_bar_baz",
],
},
)
The idea here is that the entry point defines a function that will be called to validate the argument, if it's supplied. The object will have the initial value of the attribute set to , and the validation function will only be called if the call sets it to a non-None value. Here's an example validation function:
def assert_bool(dist, attr, value): """Verify that value is True, False, 0, or 1""" if bool(value) != value: raise DistutilsSetupError( "%r must be a boolean value (got %r)" % (attr,value) )
Your function should accept three arguments: the object, the attribute name, and the attribute value. It should raise a (from the module) if the argument is invalid. Remember, your function will only be called with non-None values, and the default value of arguments defined this way is always None. So, your commands should always be prepared for the possibility that the attribute will be when they access it later.
If more than one active distribution defines an entry point for the same argument, all of them will be called. This allows multiple distutils extensions to define a common argument, as long as they agree on what values of that argument are valid.
Also note that as with commands, it is not necessary to subclass or monkeypatch the distutils class in order to add your arguments; it is sufficient to define the entry points in your extension, as long as any setup script using your extension lists your project in its argument.
Some extensible applications or frameworks may want to allow third parties to develop plugins with application or framework-specific metadata included in the plugins' EGG-INFO directory, for easy access via the metadata API. The easiest way to allow this is to create a distutils extension to be used from the plugin projects' setup scripts (via ) that defines a new setup keyword, and then uses that data to write an EGG-INFO file when the command is run.
The command looks for extension points in an group, and calls them to write the files. Here's a simple example of a distutils extension defining a setup argument , which is a list of lines that will be written to in the EGG-INFO directory of any project that uses the argument:
setup(
# ...
entry_points = {
"distutils.setup_keywords": [
"foo_bar = setuptools.dist:assert_string_list",
],
"egg_info.writers": [
"foo_bar.txt = setuptools.command.egg_info:write_arg",
],
},
)
This simple example makes use of two utility functions defined by setuptools for its own use: a routine to validate that a setup keyword is a sequence of strings, and another one that looks up a setup argument and writes it to a file. Here's what the writer utility looks like:
def write_arg(cmd, basename, filename): argname = os.path.splitext(basename)[0] value = getattr(cmd.distribution, argname, None) if value is not None: value = '\n'.join(value)+'\n' cmd.write_or_delete_file(argname, filename, value)
As you can see, entry points must be a function taking three arguments: a command instance, the basename of the file to write (e.g. ), and the actual full filename that should be written to.
In general, writer functions should honor the command object's setting when writing files, and use the object to do any console output. The easiest way to conform to this requirement is to use the object's , , and methods exclusively for your file operations. See those methods' docstrings for more details.
If you would like to create a plugin for to find files in other source control systems besides CVS and Subversion, you can do so by adding an entry point to the group. The entry point should be a function accepting a single directory name, and should yield all the filenames within that directory (and any subdirectories thereof) that are under revision control.
For example, if you were going to create a plugin for a revision control system called "foobar", you would write a function something like this:
def find_files_for_foobar(dirname): # loop to yield paths that start with `dirname`
And you would register it in a setup script using something like this:
entry_points = {
"setuptools.file_finders": [
"foobar = my_foobar_module:find_files_for_foobar"
]
}
Then, anyone who wants to use your plugin can simply install it, and their local setuptools installation will be able to find the necessary files.
It is not necessary to distribute source control plugins with projects that simply use the other source control system, or to specify the plugins in . When you create a source distribution with the command, setuptools automatically records what files were found in the file. That way, recipients of source distributions don't need to have revision control at all. However, if someone is working on a package by checking out with that system, they will need the same plugin(s) that the original author is using.
A few important points for writing revision control file finders:
If the project containing your distutils/setuptools extension(s) depends on any projects other than setuptools, you must also declare those dependencies as part of your project's keyword, so that they will already be built (and at least temprorarily installed) before your extension project is built.
So, if for example you create a project Foo that includes a new file finder plugin, and Foo depends on Bar, then you must list Bar in both the and arguments to .
If you don't do this, then in certain edge cases you may cause setuptools to try to go into infinite recursion, trying to build your dependencies to resolve your dependencies, while still building your dependencies. (It probably won't happen on your development machine, but it will happen in a full build pulling everything from revision control on a clean machine, and then you or your users will be scratching their heads trying to figure it out!)
Sorry, this section isn't written yet, and neither is a lot of what's below this point, except for the change log. You might want to subscribe to changes in this page to see when new documentation is added or updated.
XXX
Added support for "self-installation" bootstrapping. Packages can now include in their source distribution, and add the following to their , in order to automatically bootstrap installation of setuptools as part of their setup process:
from ez_setup import use_setuptools use_setuptools() from setuptools import setup # etc...
Please use the distutils-sig mailing list for questions and discussion about setuptools, and the setuptools bug tracker ONLY for issues you have confirmed via the list are actual bugs, and which you have reduced to a minimal set of steps to reproduce.
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