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• Install Python 3 Osx Command
• Install Python 3 Mac Without Homebrew

System requirements¶

auto-sklearn has the following system requirements:

If you have a CDH cluster, you can install the Anaconda parcel using Cloudera Manager. The Anaconda parcel provides a static installation of Anaconda, based on Python 2.7, that can be used with Python and PySpark jobs on the cluster. Doing it Right¶. Let’s install a real version of Python. Before installing Python, you’ll need to install a C compiler. The fastest way is to install the Xcode Command Line Tools by running xcode-select-install. If your conda installation is for Python 2.7 then conda create will create a 2.7 version. Changing command to conda create -name 3point6 python=3 (adding =3 at the end) makes a python3 version. – Jonah Graham Mar 4 '17 at 22:46.

• Linux operating system (for example Ubuntu) (get Linux here),

• Python (>=3.6) (get Python here).

• C++ compiler (with C++11 supports) (get GCC here) and

• SWIG (version 3.0.* is required; >=4.0.0 is not supported) (get SWIG here).

For an explanation of missing Microsoft Windows and MAC OSX support pleasecheck the Section Windows/OSX compatibility.

Installing auto-sklearn¶

Please install all dependencies manually with:

Then install auto-sklearn:

We recommend installing auto-sklearn into avirtual environmentor anAnaconda environment.

If the pip3 installation command fails, make sure you have the System requirements installed correctly.

Ubuntu installation¶

To provide a C++11 building environment and the lateste SWIG version on Ubuntu,run:

Anaconda installation¶

Anaconda does not ship auto-sklearn, and there are no conda packages forauto-sklearn. Thus, it is easiest to install auto-sklearn as detailed inthe Section Installing auto-sklearn.

A common installation problem under recent Linux distribution is theincompatibility of the compiler version used to compile the Python binaryshipped by AnaConda and the compiler installed by the distribution. This canbe solved by installing the gcc compiler shipped with AnaConda (as well asswig):

Windows/OSX compatibility¶

Windows¶

auto-sklearn relies heavily on the Python module resource. resourceis part of Python’s Unix Specific Servicesand not available on a Windows machine. Therefore, it is not possible to runauto-sklearn on a Windows machine.

Possible solutions (not tested):

• Windows 10 bash shell

• virtual machine

• docker image

Mac OSX¶

We currently do not know if auto-sklearn works on OSX. There are at least twoissues holding us back from actively supporting OSX:

• The resource module cannot enforce a memory limit on a Python process(see SMAC3/issues/115).

• OSX machines on travis-ci take more than 30minutes to spawn. This makes it impossible for us to run unit tests forauto-sklearn and its dependencies SMAC3and ConfigSpace.

In case you’re having issues installing the pyrfr package, check outthis installation suggestion on github.

Possible other solutions (not tested):

• virtual machine

• docker image

Docker Image¶

A Docker image is also provided on dockerhub. To download from dockerhub,use:

You can also verify that the image was downloaded via:

This image can be used to start an interactive session as follows:

To start a Jupyter notebook, you could instead run e.g.:

Alternatively, it is possible to use the development version of auto-sklearn by replacing alloccurences of master by development.

Release Date: April 9, 2012

Note: A newer bugfix release, 2.7.4, is currently available. Its use is recommended over previous versionsof 2.7.

Python 2.7.3 was released on April 9, 2012. 2.7.3 includes fixes for severalreported security issues in 2.7.2: issue 13703 (oCERT-2011-003, hashcollision denial of service), issue 14234 (CVE-2012-0876, hash tablecollisions CPU usage DoS in the expat library), issue 14001 (CVE-2012-0845,SimpleXMLRPCServer denial of service), and issue 13885 (CVE-2011-3389,disabling of the CBC IV attack countermeasure in the _ssl module).

The Python 2.7 series is scheduled to be the last major version in the 2.xseries before 2.x moves into an extended maintenance period. The 2.7 seriescontains many of the features that were first released in Python 3.1.Improvements in this release include:

• An ordered dictionary type
• New unittest features including test skipping, new assert methods, and testdiscovery
• A much faster io module
• Automatic numbering of fields in the str.format() method
• Float repr improvements backported from 3.x
• Tile support for Tkinter
• A backport of the memoryview object from 3.x
• Set literals
• Set and dictionary comprehensions
• Dictionary views
• New syntax for nested with statements
• The sysconfig module

See these resources for further information:

• Change log for this release.
• Report bugs at http://bugs.python.org.
• Help fund Python and its community.

This is a production release. Please report any bugsyou encounter.

Install Python 3 Osx Command

We currently support these formats for download:

• Mac OS X 64-bit/32-bit x86-64/i386 Installer (2.7.3) for Mac OS X 10.6 and 10.7[2](sig).[You may need an updated Tcl/Tk install to run IDLE or use Tkinter,see note 2 for instructions.]
• Mac OS X 32-bit i386/PPC Installer (2.7.3) for Mac OS X 10.3 through 10.6[2](sig).

The source tarballs are signed with Benjamin Peterson's key (fingerprint: 12EF3DC3 8047 DA38 2D18 A5B9 99CD EA9D A413 5B38). The Windows installer was signedby Martin von Löwis' public key, which has a key id of 7D9DC8D2. The Macinstallers were signed with Ned Deily's key, which has a key id of 6F5E1540.The public keys are located on the download page.

MD5 checksums and sizes of the released files:

Install Python 3 Mac Without Homebrew