Anaconda - Revision history

Jrwrigh: Add Python category

2022-09-18T17:14:16Z

Add Python category

Jrwrigh: /* Short list of things included in Anaconda installation */

2021-08-09T23:31:11Z

‎Short list of things included in Anaconda installation

Jrwrigh: /* Short list of things included in Anaconda installation */ : Add spyder

2021-08-09T23:31:00Z

‎Short list of things included in Anaconda installation: : Add spyder

Jrwrigh at 20:59, 20 October 2020

2020-10-20T20:59:32Z

Jrwrigh at 22:51, 25 August 2020

2020-08-25T22:51:48Z

Jrwrigh: Add conda cheatsheet, correct conda documentation link

2020-04-25T15:55:25Z

Add conda cheatsheet, correct conda documentation link

Jrwrigh at 15:45, 25 April 2020

2020-04-25T15:45:38Z

Jrwrigh: Add software category

2020-02-12T16:09:23Z

Add software category

Jrwrigh: Init Anaconda page

2019-12-02T03:16:49Z

Init Anaconda page

New page

This is an overview of accessing Anaconda on the viz nodes. Anaconda is a distribution of Python that includes many commonly used packages for scientific/machine-learning applications.

It also has it's own environment manager, <code>conda</code>, which is a language-agnostic environment manager. It is used to activate access to the Anaconda packages, the Python interpreter associated with the environment, and install packages to the environment from the Anaconda public repositories. Note that installing packages through <code>conda</code> is generally preferable to <code>pip</code> as it can also install non-Python libraries that support pure Python tools (such as LAPack, BLAS, and even PETSc). Management of <code>conda</code> environments (and Python environments in general) won't be covered here (as they shouldn't be overly necessary for our purposes), but you can learn more about them at this [https://www.freecodecamp.org/news/why-you-need-python-environments-and-how-to-manage-them-with-conda-85f155f4353c/ very helpful article].

== Accessing Anaconda ==

The current (20191201) installation of the Anaconda is at <code>/projects/tools/anaconda3</code>. This is where Anaconda's Python interpreter is stored as well as the packages associated with it. To access this, you need to activate the <code>conda</code> environment.

=== Accessing <code>conda</code> ===

First, you need to have access to <code>conda</code> itself. This is done by adding the following to the <code>.bashrc/.zshrc</code> in you home directory:

<nowiki>
# >>> conda initialize >>>
# !! Contents within this block are managed by 'conda init' !!
__conda_setup="$('/projects/tools/anaconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
if [ $? -eq 0 ]; then
eval "$__conda_setup"
else
if [ -f "/projects/tools/anaconda3/etc/profile.d/conda.sh" ]; then
. "/projects/tools/anaconda3/etc/profile.d/conda.sh"
else
export PATH="/projects/tools/anaconda3/bin:$PATH"
fi
fi
unset __conda_setup
# <<< conda initialize <<<
</nowiki>

=== Activating <code>conda</code> Environment ===

By default, adding the above section to your <code>.bashrc/.zshrc</code> will cause <code>conda</code> to activate the "base" environment at whenever a shell is launched.

To not have environment enabled by default (recommended to prevent inadvertent conflicts), run <code>conda config --set auto_activate_base False</code>. This will add a setting to the <code>.condarc</code> file in you home directory.

To activate a <code>conda</code> environment, simply run <code>conda activate [environment name]</code>. If the environment name is not given, it defaults to "base".

To deactivate a <code>conda</code> environment, simply run <code>conda deactivate</code>.

Official documentation on <code>conda</code> can be found [https://docs.conda.io/en/latest/ here].

==Short list of things included in Anaconda installation ==

* [https://ipython.org/ iPython]
** Interactive Python shell
* [https://jupyter.org/ Jupyter]
** Offers unique interactive computing tools, namely Notebooks
** Notebooks can be used for many different programming languages
* [https://numpy.org/ Numpy]
** The fundamental scientific library
** Offers n-dimensional array objects and functions to perform calculations with them
* [https://pandas.pydata.org/ Pandas]
** Essentially numpy arrays with labels
** Allows for easy data manipulation, plotting
** See [http://xarray.pydata.org/en/stable/ xarray] if you're working in structured higher dimensional data
* [https://www.scipy.org/ SciPy]
** Ecosystem of packages (including numpy, matplotlib, sympy, etc.)
** Also a [https://docs.scipy.org/doc/scipy/reference/ standalone package] of miscellaneous scientific computing functions
* [https://matplotlib.org/ Matplotlib]
** Matlab-style plotting package

@@ Line 53: / Line 53: @@
 ==Short list of things included in Anaconda installation ==
-* [https://www.spyder-ide.org/ spyder]
+* [https://www.spyder-ide.org/ Spyder]
 ** A MATLAB-esque IDE for scientific Python
 ** Uses <code>ipython</code> as it's built-in console

← Older revision		Revision as of 20:59, 20 October 2020
Line 45:		Line 45:

	An official cheatsheet for <code>conda</code> commands is [https://docs.conda.io/projects/conda/en/latest/user-guide/cheatsheet.html here].		An official cheatsheet for <code>conda</code> commands is [https://docs.conda.io/projects/conda/en/latest/user-guide/cheatsheet.html here].
		+
		+	== Installing Packages with <code>mamba</code> ==
		+
		+	Using <code>conda</code> to install packages can be quite slow, as it's written in pure Python and resolving package dependencies is [https://stackoverflow.com/a/28102139/7564988 quite hard].
		+	[[Mamba\|<code>mamba</code>]] is a drop-in replacement for <code>conda</code> ''as a package manager''. It's written in C++ and is intercompatible with <code>conda</code>, ''but its a lot faster'' (by orders of magnitude). See [[Mamba]] for more information.

	==Short list of things included in Anaconda installation ==		==Short list of things included in Anaconda installation ==

@@ Line 4: / Line 4: @@
 It also has it's own environment manager, <code>conda</code>, which is a language-agnostic environment manager. It is used to activate access to the Anaconda packages, the Python interpreter associated with the environment, and install packages to the environment from the Anaconda public repositories. Note that installing packages through <code>conda</code> is generally preferable to <code>pip</code> as it can also install non-Python libraries that support pure Python tools (such as LAPACK, BLAS, and even PETSc). Management of <code>conda</code> environments (and Python environments in general) won't be covered here (as they shouldn't be overly necessary for our purposes), but you can learn more about them at this [https://www.freecodecamp.org/news/why-you-need-python-environments-and-how-to-manage-them-with-conda-85f155f4353c/ very helpful article].
 == Accessing Anaconda ==
@@ Line 46: / Line 45: @@
 An official cheatsheet for <code>conda</code> commands is [https://docs.conda.io/projects/conda/en/latest/user-guide/cheatsheet.html here].
 ==Short list of things included in Anaconda installation ==

← Older revision		Revision as of 15:55, 25 April 2020
Line 41:		Line 41:
	To deactivate a <code>conda</code> environment, simply run <code>conda deactivate</code>.		To deactivate a <code>conda</code> environment, simply run <code>conda deactivate</code>.

−	Official documentation on <code>conda</code> can be found [https://docs.conda.io/en/latest/ here].	+	=== Conda Resources ===
		+
		+	Official documentation on <code>conda</code> can be found [https://docs.conda.io/projects/conda/en/latest/ here].
		+
		+	An official cheatsheet for <code>conda</code> commands is [https://docs.conda.io/projects/conda/en/latest/user-guide/cheatsheet.html here].

← Older revision		Revision as of 15:45, 25 April 2020
Line 3:		Line 3:
	This is an overview of accessing Anaconda on the viz nodes. Anaconda is a distribution of Python that includes many commonly used packages for scientific/machine-learning applications.		This is an overview of accessing Anaconda on the viz nodes. Anaconda is a distribution of Python that includes many commonly used packages for scientific/machine-learning applications.

−	It also has it's own environment manager, <code>conda</code>, which is a language-agnostic environment manager. It is used to activate access to the Anaconda packages, the Python interpreter associated with the environment, and install packages to the environment from the Anaconda public repositories. Note that installing packages through <code>conda</code> is generally preferable to <code>pip</code> as it can also install non-Python libraries that support pure Python tools (such as ~~LAPack~~, BLAS, and even PETSc). Management of <code>conda</code> environments (and Python environments in general) won't be covered here (as they shouldn't be overly necessary for our purposes), but you can learn more about them at this [https://www.freecodecamp.org/news/why-you-need-python-environments-and-how-to-manage-them-with-conda-85f155f4353c/ very helpful article].	+	It also has it's own environment manager, <code>conda</code>, which is a language-agnostic environment manager. It is used to activate access to the Anaconda packages, the Python interpreter associated with the environment, and install packages to the environment from the Anaconda public repositories. Note that installing packages through <code>conda</code> is generally preferable to <code>pip</code> as it can also install non-Python libraries that support pure Python tools (such as LAPACK, BLAS, and even PETSc). Management of <code>conda</code> environments (and Python environments in general) won't be covered here (as they shouldn't be overly necessary for our purposes), but you can learn more about them at this [https://www.freecodecamp.org/news/why-you-need-python-environments-and-how-to-manage-them-with-conda-85f155f4353c/ very helpful article].

@@ Line 1: / Line 1: @@
 This is an overview of accessing Anaconda on the viz nodes. Anaconda is a distribution of Python that includes many commonly used packages for scientific/machine-learning applications.
@@ Line 73: / Line 71: @@
 * [https://matplotlib.org/ Matplotlib]
 ** Matlab-style plotting package

← Older revision		Revision as of 16:09, 12 February 2020
Line 1:		Line 1:
		+	[[Category:Software]]
		+
	This is an overview of accessing Anaconda on the viz nodes. Anaconda is a distribution of Python that includes many commonly used packages for scientific/machine-learning applications.		This is an overview of accessing Anaconda on the viz nodes. Anaconda is a distribution of Python that includes many commonly used packages for scientific/machine-learning applications.