This tutorial will go through how to set up python on a Mac ( Windows users can go here). There are many schools of thought on the ‘best’ development environments, IDE’s, etc to work with. The goal of this article is to help you get up and running on a Mac writing Python using the Sublime Text IDE.

  • The next consideration is the specs of the Mac. Coding an app isn’t going to be as big a power drain on your Mac as playing a graphic intensive game (unless you happen to be developing a graphic.
  • One of the best and simplest coding tools ever available to Mac users. Sublime Text is a notepad-like application that lets you write your code, highlight certain parts using its various syntax detecting algorithms and so on. The app has a number of features including Goto Anything, Multiple Selections, Command Palette, etc.
  • ‎A quick, open source Python interpreter for the iOS platform. Create and test Python on the go. Whether you're just learning, practicing or creating a tiny snippet for your new project, the Python IDE can help you with all of that. Debug Quickly test and run your code in the synthetic Python conso.
  • Espresso is an advanced web editor built for Mac users to build delightful, speedy, and innovative websites as it combines virtually all the tools they will need into a single working environment such as CSSEdit tools, Server sync, a Navigator, Live Preview with Browser Xray, Dynamo auto-building, and an exceptionally beautiful UI compliant with the macOS aesthetic.
  • The part of the standard library implemented in pure Python. Mac Mac-specific code (e.g., using IDLE as an OS X application). Misc Things that do not belong elsewhere. Typically this is varying kinds of developer-specific documentation. Modules The part of the standard library (plus some other code) that is implemented in C.
Author

Bob Savage <bobsavage@mac.com>

Python on a Macintosh running Mac OS X is in principle very similar to Python onany other Unix platform, but there are a number of additional features such asthe IDE and the Package Manager that are worth pointing out.

The Mac-specific modules are documented in Mac OS X specific services.

Python on Mac OS 9 or earlier can be quite different from Python on Unix orWindows, but is beyond the scope of this manual, as that platform is no longersupported, starting with Python 2.4. See http://www.cwi.nl/~jack/macpython forinstallers for the latest 2.3 release for Mac OS 9 and related documentation.

4.1. Getting and Installing MacPython¶

Mac OS X 10.8 comes with Python 2.7 pre-installed by Apple. If you wish, youare invited to install the most recent version of Python from the Python website(https://www.python.org). A current “universal binary” build of Python, whichruns natively on the Mac’s new Intel and legacy PPC CPU’s, is available there.

What you get after installing is a number of things:

  • A MacPython2.7 folder in your Applications folder. In hereyou find IDLE, the development environment that is a standard part of officialPython distributions; PythonLauncher, which handles double-clicking Pythonscripts from the Finder; and the “Build Applet” tool, which allows you topackage Python scripts as standalone applications on your system.

  • A framework /Library/Frameworks/Python.framework, which includes thePython executable and libraries. The installer adds this location to your shellpath. To uninstall MacPython, you can simply remove these three things. Asymlink to the Python executable is placed in /usr/local/bin/.

The Apple-provided build of Python is installed in/System/Library/Frameworks/Python.framework and /usr/bin/python,respectively. You should never modify or delete these, as they areApple-controlled and are used by Apple- or third-party software. Remember thatif you choose to install a newer Python version from python.org, you will havetwo different but functional Python installations on your computer, so it willbe important that your paths and usages are consistent with what you want to do.

IDLE includes a help menu that allows you to access Python documentation. If youare completely new to Python you should start reading the tutorial introductionin that document.

If you are familiar with Python on other Unix platforms you should read thesection on running Python scripts from the Unix shell.

4.1.1. How to run a Python script¶

Your best way to get started with Python on Mac OS X is through the IDLEintegrated development environment, see section The IDE and use the Help menuwhen the IDE is running.

If you want to run Python scripts from the Terminal window command line or fromthe Finder you first need an editor to create your script. Mac OS X comes with anumber of standard Unix command line editors, vim andemacs among them. If you want a more Mac-like editor,BBEdit or TextWrangler from Bare Bones Software (seehttp://www.barebones.com/products/bbedit/index.html) are good choices, as isTextMate (see https://macromates.com/). Other editors includeGvim (http://macvim.org) and Aquamacs(http://aquamacs.org/).

To run your script from the Terminal window you must make sure that/usr/local/bin is in your shell search path.

To run your script from the Finder you have two options:

  • Drag it to PythonLauncher

  • Select PythonLauncher as the default application to open yourscript (or any .py script) through the finder Info window and double-click it.PythonLauncher has various preferences to control how your script islaunched. Option-dragging allows you to change these for one invocation, or useits Preferences menu to change things globally.

4.1.2. Running scripts with a GUI¶

With older versions of Python, there is one Mac OS X quirk that you need to beaware of: programs that talk to the Aqua window manager (in other words,anything that has a GUI) need to be run in a special way. Use pythonwinstead of python to start such scripts.

With Python 2.7, you can use either python or pythonw.

4.1.3. Configuration¶

Python on OS X honors all standard Unix environment variables such asPYTHONPATH, but setting these variables for programs started from theFinder is non-standard as the Finder does not read your .profile or.cshrc at startup. You need to create a file~/.MacOSX/environment.plist. See Apple’s Technical Document QA1067 fordetails.

For more information on installation Python packages in MacPython, see sectionInstalling Additional Python Packages.

4.2. The IDE¶

MacPython ships with the standard IDLE development environment. A goodintroduction to using IDLE can be found athttps://hkn.eecs.berkeley.edu/~dyoo/python/idle_intro/index.html.

4.3. Installing Additional Python Packages¶

There are several methods to install additional Python packages:

  • Packages can be installed via the standard Python distutils mode (pythonsetup.pyinstall).

  • Many packages can also be installed via the setuptools extensionor pipMac os wiki app. wrapper, see https://pip.pypa.io/.

4.4. GUI Programming on the Mac¶

There are several options for building GUI applications on the Mac with Python.

PyObjC is a Python binding to Apple’s Objective-C/Cocoa framework, which isthe foundation of most modern Mac development. Information on PyObjC isavailable from https://pythonhosted.org/pyobjc/.

The standard Python GUI toolkit is Tkinter, based on the cross-platformTk toolkit (https://www.tcl.tk). An Aqua-native version of Tk is bundled with OSX by Apple, and the latest version can be downloaded and installed fromhttps://www.activestate.com; it can also be built from source.

wxPython is another popular cross-platform GUI toolkit that runs natively onMac OS X. Packages and documentation are available from http://www.wxpython.org.

PyQt is another popular cross-platform GUI toolkit that runs natively on MacOS X. More information can be found athttps://riverbankcomputing.com/software/pyqt/intro.

4.5. Distributing Python Applications on the Mac¶

The “Build Applet” tool that is placed in the MacPython 2.7 folder is fine forpackaging small Python scripts on your own machine to run as a standard Macapplication. This tool, however, is not robust enough to distribute Pythonapplications to other users.

The standard tool for deploying standalone Python applications on the Mac ispy2app. More information on installing and using py2app can be foundat http://undefined.org/python/#py2app.

4.6. Other Resources¶

The MacPython mailing list is an excellent support resource for Python users anddevelopers on the Mac:

Another useful resource is the MacPython wiki:

These instructions cover how to get a working copy of the source code and acompiled version of the CPython interpreter (CPython is the version of Pythonavailable from https://www.python.org/). It also gives an overview of thedirectory structure of the CPython source code.

Alternatively, if you have Docker installed youmight want to use our official images. Thesecontain the latest releases of several Python versions, along with git head,and are provided for development and testing purposes only.

See also

The Quick Reference gives brief summary of the process frominstalling git to submitting a pull request.

1.1. Install git

CPython is developed using git for version control. The gitcommand line program is named git; this is also used to refer to gititself. git is easily available for all common operating systems.

  • Install

    As the CPython repo is hosted on GitHub, please refer to either theGitHub setup instructionsor the git project instructions for step-by-stepinstallation directions. You may also want to consider a graphical clientsuch as TortoiseGit orGitHub Desktop.

  • Configure

    Configure your name and email and createan SSH keyas this will allow you to interact with GitHub without typing a usernameand password each time you execute a command, such as gitpull,gitpush, or gitfetch. On Windows, you should alsoenable autocrlf.

1.2. Get the source code¶

The CPython repo is hosted on GitHub. To get a copy of the source code you shouldfork the Python repository on GitHub, create a localclone of your personal fork, and configure the remotes.

You will only need to execute these steps once:

  1. Go to https://github.com/python/cpython.

  2. Press Fork on the top right.

  3. When asked where to fork the repository, choose to fork it to your username.

  4. Your fork will be created at https://github.com/<username>/cpython.

  5. Clone your GitHub fork (replace <username> with your username):

    (You can use both SSH-based or HTTPS-based URLs.)

  6. Mac app store today. Configure an upstream remote:

  7. Verify that your setup is correct:

If you did everything correctly, you should now have a copy of the codein the cpython directory and two remotes that refer to your own GitHub fork(origin) and the official CPython repository (upstream).

If you want a working copy of an already-released version of Python,i.e., a version in maintenance mode, you can checkouta release branch. For instance, to checkout a working copy of Python 3.8,do gitcheckout3.8.

You will need to re-compile CPython when you do such an update.

Do note that CPython will notice that it is being run from a working copy.This means that if you edit CPython’s source code in your working copy,changes to Python code will be picked up by the interpreter for immediateuse and testing. (If you change C code, you will need to recompile theaffected files as described below.)

Patches for the documentation can be made from the same repository; seeDocumenting Python.

1.3. Compile and build¶

CPython provides several compilation flags which help with debugging variousthings. While all of the known flags can be found in theMisc/SpecialBuilds.txt file, the most critical one is the Py_DEBUG flagwhich creates what is known as a “pydebug” build. This flag turns on variousextra sanity checks which help catch common issues. The use of the flag is socommon that turning on the flag is a basic compile option.

You should always develop under a pydebug build of CPython (the only instance ofwhen you shouldn’t is if you are taking performance measurements). Even whenworking only on pure Python code the pydebug build provides several usefulchecks that one should not skip.

1.3.1. UNIX¶

The core CPython interpreter only needs a C compiler to be built,however, some of the extension modules will need development headersfor additional libraries (such as the zlib library for compression).Depending on what you intend to work on, you might need to install theseadditional requirements so that the compiled interpreter supports thedesired features.

If you want to install these optional dependencies, consult theInstall dependencies section below.

If you don’t need to install them, the basic steps for building Pythonfor development is to configure it and then compile it.

Configuration is typically:

More flags are available to configure, but this is the minimum you shoulddo to get a pydebug build of CPython.

Note

You might need to run makeclean before or after re-running configurein a particular build directory.

Once configure is done, you can then compile CPython with:

This will build CPython with only warnings and errors being printed tostderr and utilize up to 2 CPU cores. If you are using a multi-core machinewith more than 2 cores (or a single-core machine), you can adjust the numberpassed into the -j flag to match the number of cores you have (or if yourversion of Make supports it, you can use -j without a number and Makewill not limit the number of steps that can run simultaneously.).

At the end of the build you should see a success message, possibly followedby a list of extension modules that haven’t been built because theirdependencies were missing:

If the build failed and you are using a C89 or C99-compliant compiler,please open a bug report.

If you decide to Install dependencies, you will need to re-run bothconfigure and make.

Once CPython is done building you will then have a working buildthat can be run in-place; ./python on most machines (and what is used inall examples), ./python.exe wherever a case-insensitive filesystem is used(e.g. on OS X by default), in order to avoid conflicts with the Pythondirectory. There is normally no need to install your built copyof Python! The interpreter will realize where it is being run fromand thus use the files found in the working copy. If you are worriedyou might accidentally install your working copy build, you can add--prefix=/tmp/python to the configuration step. When running from yourworking directory, it is best to avoid using the --enable-shared flagto configure; unless you are very careful, you may accidentally runwith code from an older, installed shared Python library rather than fromthe interpreter you just built.

1.3.1.1. Clang¶

If you are using clang to build CPython, some flags you might want to set toquiet some standard warnings which are specifically superfluous to CPython are-Wno-unused-value-Wno-empty-body-Qunused-arguments. You can set yourCFLAGS environment variable to these flags when running configure.

If you are using clang with ccache, turn off the noisyparentheses-equality warnings with the -Wno-parentheses-equality flag.These warnings are caused by clang not having enough information to detectthat extraneous parentheses in expanded macros are valid, because thepreprocessing is done separately by ccache.

If you are using LLVM 2.8, also use the -no-integrated-as flag in order tobuild the ctypes module (without the flag the rest of CPython willstill build properly).

1.3.2. Windows¶

For a quick guide to building you can read this documentation from VictorStinner.

Python 3.6 and later can use Microsoft Visual Studio 2017. You can downloadand use any of the free or paid versions of Visual Studio 2017.

When installing Visual Studio 2017, select the Python development workloadand the optional Python native development tools component to obtain all ofthe necessary build tools. If you do not already have git installed, you canfind git for Windows on the Individual components tab of the installer.

Note

If you want to build MSI installers, be aware that the build toolchainfor them has a dependency on the Microsoft .NET Framework Version 3.5 (whichmay not be configured on recent versions of Windows, such as Windows 10). Ifyou are building on a recent Windows version, use the Control Panel (Programs Programs and Features Turn Windows Features on or off) and ensure that theentry “.NET Framework 3.5 (includes .NET 2.0 and 3.0)” is enabled.

Your first build should use the command line to ensure any external dependenciesare downloaded:

After this build succeeds, you can open the PCBuildpcbuild.sln solution inVisual Studio to continue development.

See the readme for more details on what other software is necessary and howto build.

Note

Python 2.7 uses Microsoft Visual Studio 2008, which is most easilyobtained through an MSDN subscription. To use the build files in thePCbuild directory you will also need Visual Studio 2010, see the 2.7readme for more details. If you have VS 2008 but not 2010 you can use thebuild files in the PC/VS9.0 directory, see the VS9 readme for details.

Note

If you are using the Windows Subsystem for Linux (WSL), clone therepository from a native Windows terminal program like cmd.exe command promptor PowerShell as well as use a build of git targeted for Windows, e.g., theofficial one from https://git-scm.com. Otherwise, Visual Studio willnot be able to find all the project’s files and will fail the build.

1.4. Install dependencies¶

This section explains how to install additional extensions (e.g. zlib)on Linux and macOs/OS X. On Windows,extensions are already included and built automatically.

1.4.1. Linux¶

For UNIX based systems, we try to use system libraries whenever available.This means optional components will only build if the relevant system headersare available. The best way to obtain the appropriate headers will vary bydistribution, but the appropriate commands for some popular distributionsare below.

On Fedora, Red Hat Enterprise Linux and other yum based systems:

On Fedora and other DNF based systems:

On Debian, Ubuntu, and other apt based systems, try to get thedependencies for the Python you’re working on by using the apt command.

First, make sure you have enabled the source packages in the sources list.You can do this by adding the location of the source packages, includingURL, distribution name and component name, to /etc/apt/sources.list.Take Ubuntu Bionic for example:

For other distributions, like Debian, change the URL and names to correspondwith the specific distribution.

Then you should update the packages index:

Now you can install the build dependencies via apt:

If that package is not available for your system, try reducing the minorversion until you find a package that is available.

1.4.2. macOS and OS X¶

For macOS systems (versions 10.12+) and OS X 10.9 and later,the Developer Tools can be downloaded and installed automatically;you do not need to download the complete Xcode application.

If necessary, run the following:

This will also ensure that the system header files are installed into/usr/include.

On Mac OS X systems (versions 10.0 - 10.7) and OS X 10.8, use the Ccompiler and other development utilities provided by Apple’s Xcode DeveloperTools. The Developer Tools are not shipped with Mac OS X.

For these older releases (versions 10.0 - 10.8), you will need to download either thecorrect version of the Command Line Tools, if available, or install them from thefull Xcode app or package for that OS X release. Older versions may beavailable either as a no-cost download through Apple’s App Store or fromthe Apple Developer web site.

Also note that OS X does not include several libraries used by the Pythonstandard library, including libzma, so expect to see some extension modulebuild failures unless you install local copies of them. As of OS X 10.11,Apple no longer provides header files for the deprecated system version ofOpenSSL which means that you will not be able to build the _ssl extension.One solution is to install these libraries from a third-party packagemanager, like Homebrew or MacPorts, and then add the appropriate pathsfor the header and library files to your configure command. For example,

with Homebrew:

and configure Python versions >= 3.7:

or configure Python versions < 3.7:

and make:

or MacPorts:

and configure:

and make:

There will sometimes be optional modules added for a new release whichwon’t yet be identified in the OS level build dependencies. In those cases,just ask for assistance on the core-mentorship list. If working on bugfixes for Python 2.7, use python in place of python3 in the abovecommands.

Explaining how to build optional dependencies on a UNIX based system withoutroot access is beyond the scope of this guide.

Note

While you need a C compiler to build CPython, you don’t need anyknowledge of the C language to contribute! Vast areas of CPython arewritten completely in Python: as of this writing, CPython contains slightlymore Python code than C.

1.5. Regenerate configure

If a change is made to Python which relies on some POSIX system-specificfunctionality (such as using a new system call), it is necessary to update theconfigure script to test for availability of the functionality.

Python’s configure script is generated from configure.ac using Autoconf.Instead of editing configure, edit configure.ac and then runautoreconf to regenerate configure and a number of other files (such aspyconfig.h).

When submitting a patch with changes made to configure.ac, you should alsoinclude the generated files.

Note that running autoreconf is not the same as running autoconf. Forexample, autoconf by itself will not regenerate pyconfig.h.in.autoreconf runs autoconf and a number of other tools repeatedly as isappropriate.

Python’s configure.ac script typically requires a specific version ofAutoconf. At the moment, this reads: AC_PREREQ(2.69).

If the system copy of Autoconf does not match this version, you will need toinstall your own copy of Autoconf.

Python Coding Software

1.6. Troubleshoot the build¶

Python Coding App Machine Learning

This section lists some of the common problems that may arise during thecompilation of Python, with proposed solutions.

1.6.1. Avoid recreating auto-generated files¶

Under some circumstances you may encounter Python errors in scripts likeParser/asdl_c.py or Python/makeopcodetargets.py while running make.Python auto-generates some of its own code, and a full build from scratch needsto run the auto-generation scripts. However, this makes the Python build requirean already installed Python interpreter; this can also cause version mismatcheswhen trying to build an old (2.x) Python with a new (3.x) Python installed, orvice versa.

To overcome this problem, auto-generated files are also checked into theGit repository. So if you don’t touch the auto-generation scripts, there’sno real need to auto-generate anything.

1.7. Editors and Tools¶

Python is used widely enough that practically all code editors have some formof support for writing Python code. Various coding tools also include Pythonsupport.

For editors and tools which the core developers have felt some special commentis needed for coding in Python, see Additional Resources.

1.8. Directory structure¶

There are several top-level directories in the CPython source tree. Knowing whateach one is meant to hold will help you find where a certain piece offunctionality is implemented. Do realize, though, there are always exceptions toevery rule.

Doc
The official documentation. This is what https://docs.python.org/ uses.See also Building the documentation.
Grammar
Contains the EBNF grammar file forPython.
Include
Contains all interpreter-wide header files.
Lib
The part of the standard library implemented in pure Python.
Mac
Mac-specific code (e.g., using IDLE as an OS X application).
Misc
Things that do not belong elsewhere. Typically this is varying kinds ofdeveloper-specific documentation.
Modules
The part of the standard library (plus some other code) that is implementedin C.
Objects
Code for all built-in types.
PC
Windows-specific code.
PCbuild
Build files for the version of MSVC currently used for the Windowsinstallers provided on python.org.
Parser
Code related to the parser. The definition of the AST nodes is also kepthere.
Programs
Source code for C executables, including the main function for theCPython interpreter (in versions prior to Python 3.5, these files arein the Modules directory).
Python
The code that makes up the core CPython runtime. This includes thecompiler, eval loop and various built-in modules.
Tools
Various tools that are (or have been) used to maintain Python.
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