=====================
Anaconda Distribution
=====================

Anaconda Distribution Open Data Science Core 
============================================

Anaconda is an easy-to-install free package manager, environment manager, Python 
distribution, and collection of over 720 open source packages offering free 
community support. Get the :download:`Anaconda cheat sheet <Anaconda_CheatSheet.pdf>` 
and then download `Anaconda <https://www.continuum.io/downloads>`_. 

Don't want the huge collection of packages? Then get 
`Miniconda <http://conda.pydata.org/miniconda.html>`_ and get started with this guide.

.. toctree::
    :maxdepth: 1
    :hidden:
    
    install
    hashes/index
    pkg-docs
    r-language-pkg-docs
    glossary
    changelog
    navigator
    ide_integration
    jupyter-notebook-extensions
    r_language
    images
    excel
    oldpkglists
    eula
    faq
    troubleshooting

Conda, Anaconda and Miniconda
=============================

`Conda <http://conda.pydata.org/docs/index.html>`_ is an open source package 
management system and environment management system for installing multiple 
versions of software packages and their dependencies and switching easily 
between them. It works on Linux, OS X and Windows, and was created for Python 
programs but can package and distribute any software.

`Anaconda <https://www.continuum.io/downloads>`_ is a distribution of Python 
containing Python, the conda package and environment manager, and many software 
packages for data analytics, data science, and scientific computing.

`Miniconda <http://conda.pydata.org/miniconda.html>`_ is a mini version of 
Anaconda that includes just conda, its dependencies, and Python.

Any Anaconda package can be installed, removed, or updated with a single conda 
command after installing either Anaconda or Miniconda.

Data scientists and other users usually want all of Anaconda installed on their 
workstations so they can use any of the packages in Anaconda at any time. 
However, in some environments such as compute nodes in a supercomputer, or on a 
continuous integration system, users know before installing the system exactly 
which few packages the system will need. In these environments, installing just 
Miniconda and those packages saves time and disk space. Some experienced users 
also prefer to install Miniconda on their workstations and install each 
Anaconda package when it is first used, rather than installing all of Anaconda.

Product specifications
======================

* License: Anaconda is free to use and (re)distribute under the terms of the :doc:`eula`
* Windows Vista\* or newer, OS X 10.7+, or Linux (Ubuntu, RedHat and others; CentOS 5+)
* 32-bit or 64-bit
* Minimum 3 GB disk space to download and install.

\*Windows XP is supported on Anaconda versions 2.2 and earlier. See  :doc:`oldpkglists`.

Packages available in Anaconda
==============================

* Over 150 packages are :doc:`automatically installed with Anaconda <pkg-docs>`.
* Over 250 additional open source packages can be individually installed from the Anaconda repository at the command line, by using the  "conda install" command.
* Thousands of other packages are available from Anaconda.org.
* Others can be downloaded using the "pip install" command that is included and installed with Anaconda.
* You can also make your own custom packages using the "conda build" command, and upload them to Anaconda.org, PyPi or other repositories.

Managing packages in Anaconda
=============================

Packages in Anaconda are managed using the "conda" command. Take our `30-minute conda test drive <http://conda.pydata.org/docs/test-drive.html>`_, 
download a `conda cheat sheet <http://conda.pydata.org/docs/_downloads/conda-cheatsheet.pdf>`_ 
and see our "`Using conda <http://conda.pydata.org/docs/using>`_" section for fun things to do with Anaconda.

High performance
================

Anaconda provides high performance computing with :doc:`Anaconda Accelerate </accelerate/index>` and several other components:

.. toctree::
   :maxdepth: 1

   IOPro </iopro/index>
   MKL Optimizations </mkl-optimizations/index>
   NumbaPro </numbapro/index>
   license-installation

What's new in Anaconda 4.2?
===========================

Anaconda 4.2 was released on September 27, 2016 and includes the following:

* Updated Qt from major version 4 to 5
* Updated IPython from 4.2 to 5.1
* Updated Matplotlib from 1.5.1 to 1.5.3
* Updated OpenSSL from 1.0.2h to 1.0.2j
* Added anaconda-clean, a new tool for cleaning up Anaconda related configuration files and directories
* Over 55 packages updated
* About 20 new packages were added
* Windows installer improvements

For full details please see the :doc:`changelog <changelog>`.

Product archive
===============

Prior versions of Anaconda are available in the `archive <https://repo.continuum.io/archive/>`_.
See the list of packages included in each prior version in the :doc:`oldpkglists`.

The following Continuum products have been replaced and are no longer available to new users. 
Documentation for these products is made available for existing users only:

* :doc:`Anaconda Launcher </anaconda-launcher/index>` (replaced by :doc:`Anaconda Navigator </anaconda/navigator>`)
* :doc:`Anaconda for Cluster Management  </anaconda-cluster/index>` (replaced by :doc:`Anaconda Scale </anaconda-scale/index>`)

.. _anaconda-support:

Support
=======

For free community support, join the `Anaconda Mailing List <https://groups.google.com/a/continuum.io/forum/?fromgroups#!forum/anaconda>`_.

Please report bugs on the `Anaconda GitHub issue tracker <https://github.com/ContinuumIO/anaconda-issues/issues>`_.

Packages: Refer to the :doc:`Anaconda included packages list <pkg-docs>`.

Continuum Analytics also offers `support <http://continuum.io/support>`_ & `training <https://www.continuum.io/training>`_.
