=================
Managing packages
=================

.. contents::
   :local:
   :depth: 1

.. note::
   There are many options available for the commands described
   on this page. For details, see :doc:`../../commands`.


Searching for packages
======================

Use the terminal or an Anaconda Prompt for the following steps.

To see if a specific package, such as SciPy, is available for
installation:

.. code-block:: bash

   conda search scipy

To see if a specific package, such as SciPy, is available for
installation from Anaconda.org:

.. code-block:: bash

   conda search --override-channels --channel defaults scipy

To see if a specific package, such as iminuit, exists in a
specific channel, such as http://conda.anaconda.org/mutirri,
and is available for installation:

.. code-block:: bash

   conda search --override-channels --channel http://conda.anaconda.org/mutirri iminuit


Installing packages
===================

Use the terminal or an Anaconda Prompt for the following steps.

To install a specific package such as SciPy into an existing
environment "myenv":

.. code-block:: bash

   conda install --name myenv scipy

If you do not specify the environment name, which in this
example is done by ``--name myenv``, the package installs
into the current environment:

.. code-block:: bash

   conda install scipy

To install a specific version of a package such as SciPy:

.. code-block:: bash

   conda install scipy=0.15.0

.. _`installing multiple packages`:

To install multiple packages at once, such as SciPy and cURL:

.. code-block:: bash

   conda install scipy curl

.. note::
   It is best to install all packages at once, so that all of
   the dependencies are installed at the same time.

To install multiple packages at once and specify the version of
the package:

.. code-block:: bash

   conda install scipy=0.15.0 curl=7.26.0

To install a package for a specific Python version:

.. code-block:: bash

   conda install scipy=0.15.0 curl=7.26.0 -n py34_env

If you want to use a specific Python version, it is best to use
an environment with that version. For more information,
see :doc:`../troubleshooting`.

Installing similar packages
===========================
Installing packages that have similar filenames and serve similar
purposes may return unexpected results. The package last installed
will likely determine the outcome, which may be undesirable.
If the two packages have different names, or if you're building
variants of packages and need to line up other software in the stack,
we recommend using :ref:`mutex-metapackages`.

Installing packages from Anaconda.org
=====================================

Packages that are not available using ``conda install`` can be
obtained from Anaconda.org, a package management service for
both public and private package repositories. Anaconda.org
is an Anaconda product, just like Anaconda and Miniconda.

To install a package from Anaconda.org:

#. In a browser, go to http://anaconda.org.

#. To find the package named bottleneck, type ``bottleneck``
   in the top-left box named Search Packages.

#. Find the package that you want and click it to go to the
   detail page.

   The detail page displays the name of the channel. In this
   example it is the "pandas" channel.

#. Now that you know the channel name, use the ``conda install``
   command to install the package. In your terminal window or
   an Anaconda Prompt, run:

   .. code::

      conda install -c pandas bottleneck

   This command tells conda to install the bottleneck package
   from the pandas channel on Anaconda.org.

#. To check that the package is installed, in your terminal window
   or an Anaconda Prompt, run:

   .. code::

      conda list

   A list of packages appears, including bottleneck.

.. note::
   For information on installing packages from multiple
   channels, see :doc:`manage-channels`.


Installing non-conda packages
=============================

If a package is not available from conda or Anaconda.org, you may be able to
find and install the package via conda-forge or with another package manager
like pip.

Pip packages do not have all the features of conda packages and we recommend
first trying to install any package with conda. If the package is unavailable
through conda, try finding and installing it with
`conda-forge <https://conda-forge.org/search.html>`_.

If you still cannot install the package, you can try
installing it with pip. The differences between pip and
conda packages cause certain unavoidable limits in compatibility but conda
works hard to be as compatible with pip as possible.

.. note::
   Both pip and conda are included in Anaconda and Miniconda, so you do not
   need to install them separately.

   Conda environments replace virtualenv, so there is no need to activate a
   virtualenv before using pip.

It is possible to have pip installed outside a conda environment or inside a
conda environment.

To gain the benefits of conda integration, be sure to install pip inside the
currently active conda environment and then install packages with that
instance of pip. The command ``conda list`` shows packages installed this way,
with a label showing that they were installed with pip.

You can install pip in the current conda environment with the command
``conda install pip``, as discussed in :ref:`pip-in-env`.

If there are instances of pip installed both inside and outside the current
conda environment, the instance of pip installed inside the current conda
environment is used.

To install a non-conda package:

#. Activate the environment where you want to put the program:

   * On Windows, in your Anaconda Prompt, run ``activate myenv``.
   * On macOS and Linux, in your terminal window, run ``conda activate myenv``.

#. To use pip to install a program such as See, in your terminal window or an Anaconda Prompt,
   run::

     pip install see

#. To verify the package was installed, in your terminal window or an Anaconda Prompt,
   run:

   .. code::

      conda list

   If the package is not shown, install pip as described in :ref:`pip-in-env`
   and try these commands again.


Installing commercial packages
==============================

Installing a commercial package such as IOPro is the same as
installing any other package. In your terminal window or an Anaconda Prompt,
run:

.. code-block:: bash

   conda install --name myenv iopro

This command installs a free trial of one of Anaconda's
commercial packages called `IOPro
<https://docs.continuum.io/iopro/>`_, which can speed up your
Python processing. Except for academic use, this free trial
expires after 30 days.


Viewing a list of installed packages
====================================

Use the terminal or an Anaconda Prompt for the following steps.

To list all of the packages in the active environment:

.. code::

   conda list

To list all of the packages in a deactivated environment:

.. code::

   conda list -n myenv

Listing package dependencies
============================

To find what packages are depending on a specific package in
your environment, there is not one specific conda command.
It requires a series of steps:

#. List the dependencies that a specific package requires to run:
   ``conda search package_name --info``

#. Find your installation’s package cache directory:
   ``conda info``

#. Find package dependencies. By default, Anaconda/Miniconda stores packages in ~/anaconda/pkgs/ (or ~/opt/pkgs/ on macOS Catalina).
   Each package has an index.json file which lists the package’s dependencies.
   This file resides in ~anaconda/pkgs/package_name/info/index.json.

#. Now you can find what packages depend on a specific package. Use grep to search all index.json files
   as follows: ``grep package_name ~/anaconda/pkgs/*/info/index.json``

The result will be the full package path and version of anything containing the <package_name>.

Example:
``grep numpy ~/anaconda3/pkgs/*/info/index.json``

Output from the above command::

  /Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpy 1.11.3 py36_0
  /Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpydoc 0.6.0 py36_0
  /Users/testuser/anaconda3/pkgs/anaconda-4.3.0-np111py36_0/info/index.json: numpy 1.11.3 py36_0

Note this also returned “numpydoc” as it contains the string “numpy”. To get a more specific result
set you can add \< and \>.

Updating packages
=================

Use ``conda update`` command to check to see if a new update is
available. If conda tells you an update is available, you can
then choose whether or not to install it.

Use the terminal or an Anaconda Prompt for the following steps.

* To update a specific package:

  .. code::

    conda update biopython

* To update Python:

  .. code::

    conda update python

* To update conda itself:

  .. code::

    conda update conda

.. note::
   Conda updates to the highest version in its series, so
   Python 2.7 updates to the highest available in the 2.x series and
   3.6 updates to the highest available in the 3.x series.

To update the Anaconda metapackage:

.. code-block:: bash

   conda update conda
   conda update anaconda

Regardless of what package you are updating, conda compares
versions and then reports what is available to install. If no
updates are available, conda reports "All requested packages are
already installed."

If a newer version of your package is available and you wish to
update it, type ``y`` to update:

.. code::

   Proceed ([y]/n)? y


.. _pinning-packages:

Preventing packages from updating (pinning)
===========================================

Pinning a package specification in an environment prevents
packages listed in the ``pinned`` file from being updated.

In the environment's ``conda-meta`` directory, add a file
named ``pinned`` that includes a list of the packages that you
do not want updated.

EXAMPLE: The file below forces NumPy to stay on the 1.7 series,
which is any version that starts with 1.7. This also forces SciPy to
stay at exactly version 0.14.2::

  numpy 1.7.*
  scipy ==0.14.2

With this ``pinned`` file, ``conda update numpy`` keeps NumPy at
1.7.1, and ``conda install scipy=0.15.0`` causes an error.

Use the ``--no-pin`` flag to override the update restriction on
a package. In the terminal or an Anaconda Prompt, run:

.. code-block:: bash

   conda update numpy --no-pin

Because the ``pinned`` specs are included with each conda
install, subsequent ``conda update`` commands without
``--no-pin`` will revert NumPy back to the 1.7 series.


Adding default packages to new environments automatically
=========================================================

To automatically add default packages to each new environment that you create:

#. Open Anaconda Prompt or terminal and run:
   ``conda config --add create_default_packages PACKAGENAME1 PACKAGENAME2``

#. Now, you can create new environments and the default packages will be installed in all of them.

You can also :ref:`edit the .condarc file <config-add-default-pkgs>` with a list of packages to create
by default.

You can override this option at the command prompt with the ``--no-default-packages`` flag.

Removing packages
=================

Use the terminal or an Anaconda Prompt for the following steps.

* To remove a package such as SciPy in an environment such as
  myenv:

  .. code-block:: bash

    conda remove -n myenv scipy

* To remove a package such as SciPy in the current environment:

  .. code-block:: bash

    conda remove scipy

* To remove multiple packages at once, such as SciPy and cURL:

  .. code-block:: bash

    conda remove scipy curl

* To confirm that a package has been removed:

  .. code::

    conda list
