Welcome to the World of Python!
This is a crash course in Python, with Jupyter Notebook as the User Interface (IDE), prepared by Sourav Sen Gupta.
Python is a fun language to learn, and really easy to pick up even if you are new to programming. In fact, quite often, Python is easier to pick up if you do not have any programming experience whatsoever. Python is a high level language, targeted at students and professionals from diverse backgrounds. It offers an amazing array of Useful Libraries too.
Python has two flavors -- Python 2 and Python 3. This set of examples are in Python 3, written and executed in the beautifully simple IDE Jupyter Notebook. Note that Jupyter sets up a localhost:8888 server to render the notebook in your computer's browser. It can render anything thereafter -- should be fun! Once you are familiar with the Jupyter Notebook environment, and the basic Python syntax in Module 0, feel free to explore the rest of the Python Modules.
Module 0 : Python in Jupyter
Module 1 : Data Types in Python
Module 2 : Data Structures in Python
Module 3 : Conditions and Loops in Python
Module 4 : Functions and Modules in Python
Module 5 : Computing with Python
To get the most out of this crash course, you'll need to download and use the Jupyter Notebooks for individual Modules posted in this repository (or git clone the repository). Before that, prepare your computer by installing the following.
Platform : Anaconda for Python 3.7 (https://www.anaconda.com/)
Core Engine : Python 3.7 (it will get installed with Anaconda)
User Interface (IDE) : Jupyter Notebook (comes with Anaconda)
In case installing Anaconda for Python 3.7 is too heavy for you, and you know how to manage conda environments and packages, you may also download and install the MiniConda (https://docs.conda.io/en/latest/miniconda.html) package for Python 3.7. It's lightweight, but you will have to install all required packages individually, on your own.
This set of introductory material for Python is heavily inspired from two wonderful lecture series in Python, as follows.
- Python4Maths by Andreas Ernst : https://gitlab.erc.monash.edu.au/andrease/Python4Maths
- Python Lectures by Rajath Kumar : https://github.com/rajathkmp/Python-Lectures
Highly recommended : Python 3 Cheat Sheet by Laurent Pointal. This 2-pager is a life-saver -- print and frame it!
License Declaration : Following the lead from the inspirations for this material, and the spirit of Python education and development, all modules of this work are licensed under the Creative Commons Attribution 3.0 Unported License.