Download Python 3.7 For Mac

There are different ways to install scikit-learn:

Just click on downloads in the menu, and then click on the Python 3.7.0 button, or a later version if it has changed since this post. This will start the download to your downloads area called python-3.7.0-macosx10.9.pkg where the version number 3.7.0 may be more advanced. Find the file in finder and open it to start the process. There are now newer bugfix releases of Python 3.7 that supersede 3.7.0 and Python 3.8 is now the latest feature release of Python 3. Get the latest releases of 3.7.x and 3.8.x here. We plan to continue to provide bugfix releases for 3.7.x until mid 2020 and security fixes until mid 2023. Among the major new features in Python 3.7 are. The easiest way to combine Qt Designer and Python is via the PyQt binding. To install PyQt, simply enter the following on the command line: python3 -m venv venv source venv/bin/activate # or 'call venvScriptsactivate.bat' on Windows python3 -m pip install PyQt5 (This assumes you have Python 3. Oct 09, 2020 Prerequisites for installing Python3 on Mac Install Xcode. Xcode is Apple's Integrated Development Environment (IDE). You might already have Xcode on your Mac.

  • Install the latest official release. Thisis the best approach for most users. It will provide a stable versionand pre-built packages are available for most platforms.

  • Install the version of scikit-learn provided by youroperating system or Python distribution.This is a quick option for those who have operating systems or Pythondistributions that distribute scikit-learn.It might not provide the latest release version.

  • Building the package from source. This is best for users who want thelatest-and-greatest features and aren’t afraid of runningbrand-new code. This is also needed for users who wish to contribute to theproject.

Installing the latest release¶

Operating System
Install the 64bit version of Python 3, for instance from Python 3 using homebrew (brew install python) or by manually installing the package from python3 and python3-pip using the package manager of the Linux Distribution.Install conda (no administrator permission required).

Then run:

In order to check your installation you can use

Note that in order to avoid potential conflicts with other packages it isstrongly recommended to use a virtual environment, e.g. python3 virtualenv(see python3 virtualenv documentation) or conda environments.

Using an isolated environment makes possible to install a specific version ofscikit-learn and its dependencies independently of any previously installedPython packages.In particular under Linux is it discouraged to install pip packages alongsidethe packages managed by the package manager of the distribution(apt, dnf, pacman…).

Note that you should always remember to activate the environment of your choiceprior to running any Python command whenever you start a new terminal session.

If you have not installed NumPy or SciPy yet, you can also install these usingconda or pip. When using pip, please ensure that binary wheels are used,and NumPy and SciPy are not recompiled from source, which can happen when usingparticular configurations of operating system and hardware (such as Linux ona Raspberry Pi).

If you must install scikit-learn and its dependencies with pip, you can installit as scikit-learn[alldeps].

Scikit-learn plotting capabilities (i.e., functions start with “plot_”and classes end with “Display”) require Matplotlib (>= 2.1.1). For running theexamples Matplotlib >= 2.1.1 is required. A few examples requirescikit-image >= 0.13, a few examples require pandas >= 0.18.0, some examplesrequire seaborn >= 0.9.0.


Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4.Scikit-learn 0.21 supported Python 3.5-3.7.Scikit-learn 0.22 supported Python 3.5-3.8.Scikit-learn now requires Python 3.6 or newer.


For installing on PyPy, PyPy3-v5.10+, Numpy 1.14.0+, and scipy 1.1.0+are required.

Third party distributions of scikit-learn¶

Some third-party distributions provide versions ofscikit-learn integrated with their package-management systems.

These can make installation and upgrading much easier for users sincethe integration includes the ability to automatically installdependencies (numpy, scipy) that scikit-learn requires.

The following is an incomplete list of OS and python distributionsthat provide their own version of scikit-learn.

Arch Linux¶

Arch Linux’s package is provided through the official repositories aspython-scikit-learn for Python.It can be installed by typing the following command:


The Debian/Ubuntu package is splitted in three different packages calledpython3-sklearn (python modules), python3-sklearn-lib (low-levelimplementations and bindings), python3-sklearn-doc (documentation).Only the Python 3 version is available in the Debian Buster (the more recentDebian distribution).Packages can be installed using apt-get:


The Fedora package is called python3-scikit-learn for the python 3 version,the only one available in Fedora30.It can be installed using dnf:

Python 3.7.6 Download 64 Bit Windows 10


scikit-learn is available via pkgsrc-wip:

MacPorts for Mac OSX¶

The MacPorts package is named py<XY>-scikits-learn,where XY denotes the Python version.It can be installed by typing the followingcommand:

Canopy and Anaconda for all supported platforms¶

Canopy and Anaconda both ship a recentversion of scikit-learn, in addition to a large set of scientific pythonlibrary for Windows, Mac OSX and Linux.

Anaconda offers scikit-learn as part of its free distribution.

Intel conda channel¶

Intel maintains a dedicated conda channel that ships scikit-learn:

IDLE And Tkinter With Tcl/Tk On MacOS

This version of scikit-learn comes with alternative solvers for some commonestimators. Those solvers come from the DAAL C++ library and are optimized formulti-core Intel CPUs.


Note that those solvers are not enabled by default, please refer to thedaal4py documentationfor more details.

Compatibility with the standard scikit-learn solvers is checked by running thefull scikit-learn test suite via automated continuous integration as reportedon

WinPython for Windows¶

The WinPython project distributesscikit-learn as an additional plugin.


Error caused by file path length limit on Windows¶

It can happen that pip fails to install packages when reaching the default pathsize limit of Windows if Python is installed in a nested location such as theAppData folder structure under the user home directory, for instance:

In this case it is possible to lift that limit in the Windows registry byusing the regedit tool:

Python 3.7 Download For Mac

  1. Type “regedit” in the Windows start menu to launch regedit.

  2. Go to theComputerHKEY_LOCAL_MACHINESYSTEMCurrentControlSetControlFileSystemkey.

  3. Edit the value of the LongPathsEnabled property of that key and setit to 1.

  4. Reinstall scikit-learn (ignoring the previous broken installation):

Active Python Releases

For more information visit the Python Developer's Guide.

Looking for a specific release?

Python releases by version number:

  1. Python 2.7.8July 2, 2014 DownloadRelease Notes
  2. Python 2.7.7June 1, 2014 DownloadRelease Notes
  3. Python 3.4.1May 19, 2014 DownloadRelease Notes
  4. Python 3.4.0March 17, 2014 DownloadRelease Notes
  5. Python 3.3.5March 9, 2014 DownloadRelease Notes
  6. Python 3.3.4Feb. 9, 2014 DownloadRelease Notes
  7. Python 3.3.3Nov. 17, 2013 DownloadRelease Notes
  8. Python 2.7.6Nov. 10, 2013 DownloadRelease Notes
  9. Python 2.6.9Oct. 29, 2013 DownloadRelease Notes
  10. Python 3.3.2May 15, 2013 DownloadRelease Notes
  11. Python 3.2.5May 15, 2013 DownloadRelease Notes
  12. Python 2.7.5May 12, 2013 DownloadRelease Notes
  13. Python 3.3.1April 6, 2013 DownloadRelease Notes
  14. Python 3.2.4April 6, 2013 DownloadRelease Notes
  15. Python 2.7.4April 6, 2013 DownloadRelease Notes
  16. Python 3.3.0Sept. 29, 2012 DownloadRelease Notes
  17. Python 3.2.3April 10, 2012 DownloadRelease Notes
  18. Python 2.6.8April 10, 2012 DownloadRelease Notes
  19. Python 3.1.5April 9, 2012 DownloadRelease Notes
  20. Python 2.7.3April 9, 2012 DownloadRelease Notes
  21. Python 3.2.2Sept. 3, 2011 DownloadRelease Notes
  22. Python 3.2.1July 9, 2011 DownloadRelease Notes
  23. Python 2.7.2June 11, 2011 DownloadRelease Notes
  24. Python 3.1.4June 11, 2011 DownloadRelease Notes
  25. Python 2.6.7June 3, 2011 DownloadRelease Notes
  26. Python 2.5.6May 26, 2011 DownloadRelease Notes
  27. Python 3.2.0Feb. 20, 2011 DownloadRelease Notes
  28. Python 2.7.1Nov. 27, 2010 DownloadRelease Notes
  29. Python 3.1.3Nov. 27, 2010 DownloadRelease Notes
  30. Python 2.6.6Aug. 24, 2010 DownloadRelease Notes
  31. Python 2.7.0July 3, 2010 DownloadRelease Notes
  32. Python 3.1.2March 20, 2010 DownloadRelease Notes
  33. Python 2.6.5March 18, 2010 DownloadRelease Notes
  34. Python 2.5.5Jan. 31, 2010 DownloadRelease Notes
  35. Python 2.6.4Oct. 26, 2009 DownloadRelease Notes
  36. Python 2.6.3Oct. 2, 2009 DownloadRelease Notes
  37. Python 3.1.1Aug. 17, 2009 DownloadRelease Notes
  38. Python 3.1.0June 26, 2009 DownloadRelease Notes
  39. Python 2.6.2April 14, 2009 DownloadRelease Notes
  40. Python 3.0.1Feb. 13, 2009 DownloadRelease Notes
  41. Python 2.5.4Dec. 23, 2008 DownloadRelease Notes
  42. Python 2.4.6Dec. 19, 2008 DownloadRelease Notes
  43. Python 2.5.3Dec. 19, 2008 DownloadRelease Notes
  44. Python 2.6.1Dec. 4, 2008 DownloadRelease Notes
  45. Python 3.0.0Dec. 3, 2008 DownloadRelease Notes
  46. Python 2.6.0Oct. 2, 2008 DownloadRelease Notes
  47. Python 2.3.7March 11, 2008 DownloadRelease Notes
  48. Python 2.4.5March 11, 2008 DownloadRelease Notes
  49. Python 2.5.2Feb. 21, 2008 DownloadRelease Notes
  50. Python 2.5.1April 19, 2007 DownloadRelease Notes
  51. Python 2.3.6Nov. 1, 2006 DownloadRelease Notes
  52. Python 2.4.4Oct. 18, 2006 DownloadRelease Notes
  53. Python 2.5.0Sept. 19, 2006 DownloadRelease Notes
  54. Python 2.4.3April 15, 2006 DownloadRelease Notes
  55. Python 2.4.2Sept. 27, 2005 DownloadRelease Notes
  56. Python 2.4.1March 30, 2005 DownloadRelease Notes
  57. Python 2.3.5Feb. 8, 2005 DownloadRelease Notes
  58. Python 2.4.0Nov. 30, 2004 DownloadRelease Notes
  59. Python 2.3.4May 27, 2004 DownloadRelease Notes
  60. Python 2.3.3Dec. 19, 2003 DownloadRelease Notes
  61. Python 2.3.2Oct. 3, 2003 DownloadRelease Notes
  62. Python 2.3.1Sept. 23, 2003 DownloadRelease Notes
  63. Python 2.3.0July 29, 2003 DownloadRelease Notes
  64. Python 2.2.3May 30, 2003 DownloadRelease Notes
  65. Python 2.2.2Oct. 14, 2002 DownloadRelease Notes
  66. Python 2.2.1April 10, 2002 DownloadRelease Notes
  67. Python 2.1.3April 9, 2002 DownloadRelease Notes
  68. Python 2.2.0Dec. 21, 2001 DownloadRelease Notes
  69. Python 2.0.1June 22, 2001 DownloadRelease Notes

Python Release Python 3.7.0

View older releases


All Python releases are Open Source. Historically, most, but not all, Python releases have also been GPL-compatible. The Licenses page details GPL-compatibility and Terms and Conditions.


For most Unix systems, you must download and compile the source code. The same source code archive can also be used to build the Windows and Mac versions, and is the starting point for ports to all other platforms.

Download the latest Python 3 and Python 2 source.

Alternative Implementations

This site hosts the 'traditional' implementation of Python (nicknamed CPython). A number of alternative implementations are available as well.


Python was created in the early 1990s by Guido van Rossum at Stichting Mathematisch Centrum in the Netherlands as a successor of a language called ABC. Guido remains Python’s principal author, although it includes many contributions from others.

Looking for the release schedule? Check the Google Calendar.