Merge 5afefe1 into bceb7e1

doc/source/getting_started/Installation.rst

@@ -0,0 +1,92 @@
+##################
+Installation guide
+##################
+
+This section provides detailed information about installing ArviZ. Most ArviZ
+functionality is available with the basic requirements, but ArviZ also has optional
+dependencies to further enhance the library. This guide will cover both basic and fully-fledged ArviZ installs and several installation methods.
+
+
+******
+Stable
+****** 
+
+ArviZ can be installed either using pip or conda-forge.
+
+Using pip
+=========
+
+.. code:: bash
+
+    pip install arviz
+
+Use the below pip command to install ArviZ with all of it's :ref:`Optional-dependencies`.
+
+.. code:: bash
+
+    pip install arviz[all]
+    
+Using conda-forge
+=================
+
+.. code:: bash
+
+    conda install -c conda-forge arviz
+
+.. _dev-version:
+
+***********
+Development
+*********** 
+
+If you want to install the latest development version of ArviZ, then you
+may use
+
+.. code:: bash
+
+    pip install git+https://github.com/arviz-devs/arviz
+
+
+************
+Dependencies
+************
+
+Required dependencies
+=====================
+
+The required dependencies for installing ArviZ are:
+
+.. literalinclude:: ../../../requirements.txt
+
+.. _Optional-dependencies:
+
+Optional dependencies
+=====================
+
+The list of optional dependencies to further enhance ArviZ are.
+
+.. literalinclude:: ../../../requirements-optional.txt
+
+
+- Numba
+
+  Necessary to speed up the code computation. The installation details can be found
+  `here <https://numba.pydata.org/numba-doc/latest/user/installing.html>`_. Further details on enhanced functionality provided in ArviZ by Numba can be 
+  `found here <https://arviz-devs.github.io/arviz/user_guide/Numba.html>`_.
+
+- Bokeh
+
+  Necessary for creating advanced interactive visualisations. The Bokeh installation guide can be found `over here <http://docs.bokeh.org/en/dev/docs/first_steps/installation.html>`_.
+
+- UltraJSON
+
+  If available, ArviZ makes use of faster ujson when :func:`arviz.from_json` is
+  invoked. UltraJSON can be either installed via `pip <https://pypi.org/project/ujson/>`_ or `conda <https://anaconda.org/anaconda/ujson>`_.
+
+- Dask
+
+  Necessary to scale the packages and the surrounding ecosystem. The installation details can be found `at this link <https://docs.dask.org/en/latest/install.html>`_.
+
+
+
+

doc/source/getting_started/index.md

@@ -3,6 +3,7 @@
 # Getting Started
 
 ```{toctree}
+Installation
 Introduction
 XarrayforArviZ
 CreatingInferenceData

doc/source/index.rst

@@ -43,11 +43,7 @@ Alternatively you can use conda-forge
 
     conda install -c conda-forge arviz
 
-For the latest (unstable) version
-
-.. code:: bash
-
-    pip install git+https://github.com/arviz-devs/arviz
+To install the latest development version of ArviZ, please check the :ref:`Installation guide <dev-version>` for details.
 
 **Contributions** and **issue reports** are very welcome at `the github repository <https://github.com/arviz-devs/arviz>`_. We have a `contributing guide <https://github.com/arviz-devs/arviz/blob/main/CONTRIBUTING.md>`_ to help you through the process. If you have any doubts, please do not hesitate to contact us on `gitter <https://gitter.im/arviz-devs/community>`_.