Contents

Aim

  1. Introduce the python ecosystem

    • How do I run a .py script?

    • Where do I enter python commands?

    • What is Python 2 and Python 3?

    • wait!, there is something called Anaconda?

    • JupyterLab, Jupyter Notebooks and reproducible research

  2. Why should I use python?

    • Is python as easy as Ferret?

    • Is python as fast as Fortran?

    • Does python have many toolboxes like in MATLAB?

    • Can python read and write netCDF files?

    • Can python plot geographic maps and coastlines?

    • Can it handle larger than memory files (say >2 GB)?

  3. Possibilities with python

    • Exploratory Data Analysis

    • Interactive plotting

    • Parallel processing

    • Cloud computing

Python ecosystem

Running a .py script

  • Activate your environment, and run the script by

     python your_script.py

Three ways to spawn a python interpreter

  • old fashioned python console

  • rich and colorful ipython console

  • JupyterLab

Starting the console

  • In terminal, type python

  • In terminal, type ipython

  • In terminal, type jupyter lab

IPython

  • Old python interface is boring and less interactive

  • IPython supports tab completion, syntax highlighting, documentation lookup

  • cell magics like %run, %debug, %edit and %bookmark makes interactive coding easier

Note

More info can be found here

JupyterLab and Jupyter Notebook

  • JupyterLab is an interface where you can

    • create notebooks

    • manage files and folders

    • display images

    • start terminal

    • display csv files and much more

  • Notebooks holds your code, plots and discussion in a single space

  • Notebook sharing promotes reproducible research

  • Notebooks are future of scientific communication, (Nature article)

  • Jupyter is not limited to Python. You can run codes in

    • Julia

    • Bash

    • R

    • Pyferret and much more

Tip

Additional benefits of JupyterLab/Notebook

  • Start jupyter in a remote computer say HPC and connect in your local browser

     # in remote machine type:
 jupyter lab --no-browser --ip="$HOSTNAME" --port=8888
 # in local machine type:
 ssh -N -L 8888:localhost:8888 username@remoteIP

  • Open browser and type address as localhost:8888 and press Enter

  • No more waiting for the slow X-window forwarding to pop-up

  • Easily access and view remote files

Anaconda, miniconda and conda env

  • Anaconda and miniconda differs only in the number of pre-packed packages

  • Anaconda comes with many common-use packages (> 500 MB)

  • While miniconda is a lite version (<60 MB)

  • Both installs conda, which is the package manager

  • Conda helps you isolate environments, allowing you to update/install certain packages without affecting
    other working environment.

Attention

  • Stay away from Python 2

    • Avoid Python 2. It is now in legacy mode

    • Packages are dropping support for Python 2

    • Most scientific packages have moved to Python 3

    • Found an old code in Python 2? Use conda to create a Python 2 environment

Python for data analysis in Oceanography Jupyter Notebook