Oscar
HomeServicesDocumentation
  • Overview
  • Quickstart
  • Getting Started
  • System Hardware
  • Account Information
  • Short "How to" Videos
  • Quick Reference
    • Common Acronyms and Terms
    • Managing Modules
    • Common Linux Commands
  • Getting Help
    • ❓FAQ
  • Citing CCV
  • CCV Account Information
  • Student Accounts
  • Offboarding
  • Connecting to Oscar
    • SSH (Terminal)
      • SSH Key Login (Passwordless SSH)
        • Mac/Linux/Windows(PowerShell)
        • Windows(PuTTY)
      • SSH Configuration File
      • X-Forwarding
      • SSH Agent Forwarding
        • Mac/Linux
        • Windows (PuTTY)
      • Arbiter2
    • Open OnDemand
      • Using File Explorer on OOD
      • Web-based Terminal App
      • Interactive Apps on OOD
      • Using Python or Conda environments in the Jupyter App
      • Using RStudio
      • Desktop App (VNC)
    • SMB (Local Mount)
    • Remote IDE (VS Code)
      • From Non-compliant Networks (2-FA)
      • Setup virtual environment and debugger
  • Managing files
    • Oscar's Filesystem
    • Transferring Files to and from Oscar
    • Transferring Files between Oscar and Campus File Storage (Replicated and Non-Replicated)
    • Resolving quota issues
      • Understanding Disk Quotas
    • Inspecting Disk Usage (Ncdu)
    • Restoring Deleted Files
    • Best Practices for I/O
    • Version Control
  • Submitting jobs
    • Running Jobs
    • Slurm Partitions
    • Interactive Jobs
    • Batch Jobs
    • Managing Jobs
    • Job Arrays
    • MPI Jobs
    • Condo/Priority Jobs
    • Dependent Jobs
    • Associations & Quality of Service (QOS)
  • GPU Computing
    • GPUs on Oscar
      • Grace Hopper GH200 GPUs
      • H100 NVL Tensor Core GPUs
      • Ampere Architecture GPUs
    • Submitting GPU Jobs
    • Intro to CUDA
    • Compiling CUDA
    • Installing Frameworks (PyTorch, TensorFlow, Jax)
      • Installing JAX
      • Installing TensorFlow
    • Mixing MPI and CUDA
  • Large Memory Computing
    • Large Memory Nodes on Oscar
  • Software
    • Software on Oscar
    • Using Modules
    • Migration of MPI Apps to Slurm 22.05.7
    • Python on Oscar
    • Python in batch jobs
    • Installing Python Packages
    • Installing R Packages
    • Using CCMake
    • Intro to Parallel Programming
    • Anaconda
    • Conda and Mamba
    • DMTCP
    • Screen
    • VASP
    • Gaussian
    • IDL
    • MPI4PY
  • Jupyter Notebooks/Labs
    • Jupyter Notebooks on Oscar
    • Jupyter Labs on Oscar
    • Tunneling into Jupyter with Windows
  • Debugging
    • Arm Forge
      • Configuring Remote Launch
      • Setting Job Submission Settings
  • MATLAB
    • Matlab GUI
    • Matlab Batch Jobs
    • Improving Performance and Memory Management
    • Parallel Matlab
  • Visualization 🕶
    • ParaView Remote Rendering
  • Singularity Containers
    • Intro to Apptainer
    • Building Images
    • Running Images
    • Accessing Oscar Filesystem
      • Example Container (TensorFlow)
    • Singularity Tips and Tricks
  • Installing Software Packages Locally
    • Installing your own version of Quantum Espresso
    • Installing your own version of Qmcpack
  • dbGaP
    • dbGaP Architecture
    • dbGaP Data Transfers
    • dbGaP Job Submission
  • RHEL9 Migration
    • RHEL-9 Migration
    • LMOD - New Module System
    • Module Changes
    • Testing Jupyter Notebooks on RHEL9 mini-cluster
  • Large Language Models
    • Ollama
Powered by GitBook
On this page

Was this helpful?

Export as PDF
  1. Software

Python on Oscar

PreviousMigration of MPI Apps to Slurm 22.05.7NextPython in batch jobs

Last updated 1 year ago

Was this helpful?

Several versions of Python are available on Oscar as modules. However, we recommend using the system Python available at /usr/bin/python . You do not need to load any module to use this version of Python.

$ which python
/usr/bin/python
$ python --version
Python 3.9.16

pip is also installed as a system package, but other common Python packages (e.g., SciPy, NumPy) are not installed on the system. This affords individual users complete control over the packages they are using, thereby avoiding issues that can arise when code written in Python requires specific versions of Python packages.

We do not provide Python version 2 modules since it has reached its end of life. You may install Python 2 locally in your home directory, but CCV will not provide any Python2 modules.

Users can install any Python package they require by following the instructions given on the page.

Intel provides optimized packages for numerical and scientific work that you can install through or .

Python 2 has entered End-of-Life (EOL) status and will receive no further official support as of January 2020. As a consequence, you may see the following message when using pip with Python 2.

DEPRECATION: Python 2.7 will reach the end of its life on January 1st, 2020. Please upgrade your Python as Python 2.7 won't be maintained after that date. A future version of pip will drop support for Python 2.7.

Going forward, the using Python 3 for development.

Installing Python Packages
pip
anaconda
Python Software Foundation recommends