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__TOC__
 
__TOC__
 +
 
=== Application Details ===
 
=== Application Details ===
 
* Description: Python is a high-level interpreted programming language for general-purpose programming, supported by a large number of libraries for many tasks
 
* Description: Python is a high-level interpreted programming language for general-purpose programming, supported by a large number of libraries for many tasks
 
* Versions: Python 2.7.11 and 3.5.1
 
* Versions: Python 2.7.11 and 3.5.1
* Module names: python/2.7.11 python/3.5.1  
+
* Module names: python/anaconda/4.0/2.7, python/anaconda/4.0/3.5, python/anaconda/4.1.1/2.7 and python/anaconda/4.3.31/3.6-VE
 +
* Additional module: python/anaconda/4.6/miniconda/3.7 and python/anaconda/202111/3.9 (used for virtual environments)
 
* License: Free to use - [https://en.wikipedia.org/wiki/Python_Software_Foundation_License Python Software Foundation License]
 
* License: Free to use - [https://en.wikipedia.org/wiki/Python_Software_Foundation_License Python Software Foundation License]
  
 +
== Introduction ==
 +
 +
* Python is provided by the [[applications/Anaconda|Anaconda package]] too.
 +
* Anaconda is the leading open data science platform powered by Python.
 +
 +
== Virtual Environments ==
 +
 +
A Python virtual environment allows users to create a custom environment(s) in which they can have the packages, and versions of those packages that are required without having elevated user privileges.
  
== Usage Examples ==
+
We recommend the Virtualenv installation when you use a specialised package that would not be used by the wider HPC community. Virtualenv is a virtual Python environment isolated from other Python development, incapable of interfering with or being affected by other Python programs on the same HPC. During the Virtualenv installation process, you will install can install not only the additional package but all the dependencies that go with it. (This is actually pretty easy.)  All in all, Virtualenv provides a safe and reliable mechanism for installing and running additional packages.
  
Python is provided by the [[applications/Anaconda|Anaconda package]] too
+
There are many benefits to using a virtual environment on a system. Here is a short non-exhaustive list of a few of the key benefits:
  
=== Interactive ===
+
* Control over packages and package versions.
 +
* An arbitrary number of virtual environments can be created for different tasks.
 +
* Reproducible - A user can replicate a python environment on any system, so as to be able to run or re-run a particular task or job under the same conditions.
 +
 
 +
 
 +
===Creation of Virtual Environment Using Anaconda on Viper===
 +
 
 +
* See [[Applications/Miniconda]] page for creating your own virtual environment. This is the preferred method for specialised python modules required such as biopython or TensorFlow for example.
 +
 
 +
 
 +
==Usage Examples==
 +
 
 +
=== Interactive Session ===
  
 
Interactive with command line:
 
Interactive with command line:
Line 25: Line 47:
 
</pre>
 
</pre>
  
Interactive with command line with IPython:
+
ipython with the command line  
 +
 
 
<pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 
<pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 
[username@c170 ~]$ ipython
 
[username@c170 ~]$ ipython
Line 41: Line 64:
  
 
=== Batch Submission ===
 
=== Batch Submission ===
 +
 
<pre style="background-color: #C8C8C8; color: black; font-family: monospace, sans-serif;">
 
<pre style="background-color: #C8C8C8; color: black; font-family: monospace, sans-serif;">
 
#!/bin/bash
 
#!/bin/bash
Line 50: Line 74:
 
#SBATCH -p compute                  # Slurm partition, where you want the job to be queued  
 
#SBATCH -p compute                  # Slurm partition, where you want the job to be queued  
  
 
 
module purge
 
module purge
module add python/3.5.1
+
module add python/anaconda/4.0/3.5
 
   
 
   
 
python PythonTest.py
 
python PythonTest.py
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<pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 
<pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 
[username@login01 ~]$ sbatch Pythontest.job
 
[username@login01 ~]$ sbatch Pythontest.job
Submitted batch job 289522
+
Submitted batch job 2895122
 
</pre>
 
</pre>
  
=== Virtual Environments ===
+
===Popular Python Packages===
A Python Virtual Environment allows users to create a custom environment/s in which they can have the packages, and versions of said packages that they require without having to have elevated user privileges on the system.
+
 
 +
* TensorFlow
 +
* Scikit-Learn
 +
* Numpy
 +
* PyTorch
 +
* SciPy
 +
* Matplotlib
 +
* Pandas
 +
 
 +
===Python Virtual Environment===
  
There are many benefits to using a virtual environment on a system. Here is a short non-exhaustive list of a few of the key benefits:
+
This part refers to non-conda virtual environments.
  
* Control over packages and package versions
+
The creation of a virtual environment is done by executing the command venv:
* An arbitrary number of virtual environments can be created for different tasks
 
* Reproducibility - A user can replicate a python environment on any system, so as to be able to run or re-run a particular task or job under the same conditions
 
  
'''Creation of Virtual Environment Using Python 2.7.11 or 3.5.1 on Viper'''
+
<pre>
 +
python -m venv machinelearn
 +
</pre>
  
To create a virtual environment you would issue the following command:
+
Running this command creates the target directory (creating any parent directories that don’t exist already) and places a pyvenv.cfg file in it with a home key pointing to the Python installation from which the command was run (a common name for the target directory is .venv).
  
'''IMPORTANT NOTE: By default the virtual environment does not use the system python packages. However because of the way viper is configured it will see system packages because of the PYTHONPATH environment variable. So it is advised if you would like a clean environment (meaning no system packages being included) to set this variable to empty as follows: ''export PYTHONPATH=''
+
To activate
  
<pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
+
<pre>
[user@c001 ~ ]$ virtualenv foo
+
source machinelearn/bin/activate
</pre>
 
This creates a directory containing your virtual environment named '''foo''' . To activate this virtual environment you would issue the following command:
 
<pre style="background-color: #000000; color: white; border: 2px solid black; font-family: monospace, sans-serif;">
 
[user@c001 ~ ]$ source foo/bin/activate
 
 
</pre>
 
</pre>
  
== Further Information ==
+
==Next Steps==
* [https://www.hpc.hull.ac.uk/forum/viewforum.php?f=15 UoH Python forum]
+
 
* [[Programming/Python|Wiki: Python Programming]]
+
* [[Applications/Miniconda|Miniconda Python virtual environments]]
* [[Main Page#General_Support|Wiki: General Support]]
+
* [[Applications/Anaconda|Anaconda Python]]  
* [[Main Page|Wiki: Home]]
+
* [[Programming/Python|Python Programming]]
  
{|
+
{{Modulepagenav}}
|style="width:5%; border-width: 0" | [[File:icon_home.png]]
 
|style="width:95%; border-width: 0" |
 
* [[Main_Page|Home]]
 
* [[Applications|Application support]]
 
* [[General|General]]
 
* [[Training|Training]]
 
* [[Programming|Programming support]]
 
|-
 
|}
 

Latest revision as of 12:30, 17 February 2023

Application Details

  • Description: Python is a high-level interpreted programming language for general-purpose programming, supported by a large number of libraries for many tasks
  • Versions: Python 2.7.11 and 3.5.1
  • Module names: python/anaconda/4.0/2.7, python/anaconda/4.0/3.5, python/anaconda/4.1.1/2.7 and python/anaconda/4.3.31/3.6-VE
  • Additional module: python/anaconda/4.6/miniconda/3.7 and python/anaconda/202111/3.9 (used for virtual environments)
  • License: Free to use - Python Software Foundation License

Introduction

  • Python is provided by the Anaconda package too.
  • Anaconda is the leading open data science platform powered by Python.

Virtual Environments

A Python virtual environment allows users to create a custom environment(s) in which they can have the packages, and versions of those packages that are required without having elevated user privileges.

We recommend the Virtualenv installation when you use a specialised package that would not be used by the wider HPC community. Virtualenv is a virtual Python environment isolated from other Python development, incapable of interfering with or being affected by other Python programs on the same HPC. During the Virtualenv installation process, you will install can install not only the additional package but all the dependencies that go with it. (This is actually pretty easy.) All in all, Virtualenv provides a safe and reliable mechanism for installing and running additional packages.

There are many benefits to using a virtual environment on a system. Here is a short non-exhaustive list of a few of the key benefits:

  • Control over packages and package versions.
  • An arbitrary number of virtual environments can be created for different tasks.
  • Reproducible - A user can replicate a python environment on any system, so as to be able to run or re-run a particular task or job under the same conditions.


Creation of Virtual Environment Using Anaconda on Viper

  • See Applications/Miniconda page for creating your own virtual environment. This is the preferred method for specialised python modules required such as biopython or TensorFlow for example.


Usage Examples

Interactive Session

Interactive with command line:

[username@c170 ~]$ module add python/anaconda/4.0/2.7
[username@c170 ~]$ python
Python 2.7.5 (default, Nov 20 2015, 02:00:19)
[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>>

ipython with the command line

[username@c170 ~]$ ipython
Python 2.7.13 |Anaconda custom (64-bit)| (default, Dec 20 2016, 23:09:15)
Type "copyright", "credits" or "license" for more information.

IPython 5.1.0 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]:

Batch Submission

#!/bin/bash
#SBATCH -J PythonTest                # Job name, you can change it to whatever you want
#SBATCH -N 1                                  # Number of nodes 
#SBATCH --ntasks-per-node 1    # Number of cores per node
#SBATCH -o %N.%j.out                # Standard output will be written here
#SBATCH -e %N.%j.err                 # Standard error will be written here
#SBATCH -p compute                  # Slurm partition, where you want the job to be queued 

module purge
module add python/anaconda/4.0/3.5
 
python PythonTest.py

This is then submitted as follows:

[username@login01 ~]$ sbatch Pythontest.job
Submitted batch job 2895122

Popular Python Packages

  • TensorFlow
  • Scikit-Learn
  • Numpy
  • PyTorch
  • SciPy
  • Matplotlib
  • Pandas

Python Virtual Environment

This part refers to non-conda virtual environments.

The creation of a virtual environment is done by executing the command venv:

python -m venv machinelearn

Running this command creates the target directory (creating any parent directories that don’t exist already) and places a pyvenv.cfg file in it with a home key pointing to the Python installation from which the command was run (a common name for the target directory is .venv).

To activate

source machinelearn/bin/activate

Next Steps





Modules | Main Page | Further Topics