Introduction to programming in Julia
====================================


Julia is a scientific programming language that is free and open
source - see the `official website <https://julialang.org/>`_ for downloads, documentation,
learning resources etc. Bridging high-level interpreted and low-level
compiled languages, it offers high performance (comparable to C and
Fortran) without sacrificing simplicity and programming productivity
(like in Python or R).

Julia has a rich ecosystem of libraries aimed
towards scientific computing and a powerful in-built package manager
to install and manage their dependencies. Julia is also gaining ground
in both data science and high-performance computing (HPC), thanks to a rich 
package ecosystem around data analysis and visualisation, machine learning, 
deep learning, threading and distributed-memory parallelisation, 
as well as GPU computing.

This lesson covers the basics of Julia: its syntax,
multiple-dispatch paradigm, package development and best practices. 
It spans the necessary foundational skills required to follow the two other 
ENCCS lessons on Julia:

- `Julia for High Performance Scientific Computing <https://enccs.github.io/julia-for-hpc/>`__
- `Julia for High Performance Data Analysis <https://enccs.github.io/julia-for-hpda/>`__


.. prereq::

   - Experience in one or more programming languages.
   - Basic familiarity with a command line (terminal) interface.

.. toctree::
   :hidden:
   :maxdepth: 1
   :caption: Prerequisites

   setup

.. toctree::
   :hidden:
   :maxdepth: 1
   :caption: The lesson

   motivation
   syntax-intro
   overview
   development
   scientific-computing

.. toctree::
   :maxdepth: 1
   :caption: Reference

   quick-reference
   guide



.. _learner-personas:



Who is the lesson for?
----------------------

This lesson is appropriate for researchers, engineers and analysts from academia, 
industry or the public sector who want to adopt a new programming language into their 
repertoire. It also represents the prerequisite knowledge to follow other ENCCS lessons 
on Julia - `Julia for High Performance Scientific Computing <https://enccs.github.io/julia-for-hpc/>`__
and `Julia for High Performance Data Analysis <https://enccs.github.io/julia-for-hpda/>`__.



About the lesson
----------------

This lesson is developed by `ENCCS <https://enccs.se/>`__ - the Swedish node of the EuroCC network.
It is open source and can be reused and remixed in derivative work; see detailed 
license information below.



See also
--------

Many excellent learning resources exist for the Julia language.
For an overview, visit https://julialang.org/learning/.



Credits
-------

The lesson file structure and browsing layout is inspired by and derived from
`work <https://github.com/coderefinery/sphinx-lesson>`_ by `CodeRefinery
<https://coderefinery.org/>`_ licensed under the `MIT license
<http://opensource.org/licenses/mit-license.html>`_.
We have copied and adapted most of their license text.



Instructional Material
^^^^^^^^^^^^^^^^^^^^^^

This instructional material is made available under the
`Creative Commons Attribution license (CC-BY-4.0) <https://creativecommons.org/licenses/by/4.0/>`_.
The following is a human-readable summary of (and not a substitute for) the
`full legal text of the CC-BY-4.0 license <https://creativecommons.org/licenses/by/4.0/legalcode>`_.
You are free to:

- **share** - copy and redistribute the material in any medium or format
- **adapt** - remix, transform, and build upon the material for any purpose,
  even commercially.

The licensor cannot revoke these freedoms as long as you follow these license terms:

- **Attribution** - You must give appropriate credit (mentioning that your work
  is derived from work that is Copyright (c) ENCCS and individual contributors and, where practical, linking
  to `<https://enccs.github.io/sphinx-lesson-template>`_), provide a `link to the license
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With the understanding that:

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Software
^^^^^^^^

Except where otherwise noted, the example programs and other software provided
with this repository are made available under the `OSI <http://opensource.org/>`_-approved
`MIT license <https://opensource.org/licenses/mit-license.html>`_.