Introduction to Python

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Authors: Samuel Farrens, Santiago Casas
Year: 2019
Email: samuel.farrens@cea.fr, santiago.casas@cea.fr

This tutorial is comprised of a series of Jupyter notebooks with simple demonstrations and exercises.

All code blocks are provided in Python (support for >=3.5) and the number of external packages required to run the examples has be kept to a minimum. All of the code has been clearly presented inside the notebook at least once to avoid the use of any "black boxes" for solving the problems presented.

Requirements

In order to run the tutorial notebooks tutees will need to have the following installed:

• Python (require >=3.5)
• Astropy (recommend >=3.1.2)
• Jupyter (recommend >=1.0.0)
• Matplotlib (recommend >=3.0.3)
• NumPy (recommend >=1.16.2)
• Pandas (recommend >= 0.24.0)
• scikit-learn (recommend >= 0.21.0)
• SciPy (recommend >=1.2.1)
• Seaborn (recommend >= 0.9.0)

Notebooks

Tutorial 1: Beginner Topics

The objective of this tutorial is to provide a first look at Python for beginners. The level is aimed at individuals with little or no experience whatsoever with Python. Experienced users are unlikely to benefit from this tutorial.

1. Table of Contents
2. Native Python
3. Basic Numpy
4. Matplotlib
5. Other Packages
6. Answers to Exercises

Tutorial 2: Intermediate and Advanced Topics

The objective of this tutorial is to provide a more in-depth look at object-oriented and pythonic coding. The level is aimed at individuals with some experience with Python and good knowledge of basic object types. This tutorial will likely benefit all except the most advanced users.

1. Table of Contents
2. Pythonic Thinking
3. Numpy
4. Pandas
5. Scipy and Matplotlib with Cosmology
6. The Anatomy of a Python Class: Part I
7. The Anatomy of a Python Class: Part II
8. Answers to Exercises