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Python was designed to be a readable powerful programming language. It is an interpreted language written in C. The Python project was initiated and named by Guido Von Rossum in the early 1990 who was fond of the BBC show “Monty Python’s Flying Circus”.
Python aims for quick development times and quick execution times. As Python is an interpreted language, it is necessarily slower than compiled languages. But Python is associated to libraries especially scientific libraries (Numpy, SciPy, Pandas, etc.) which integrates compiled functions and makes computation really fast.
Python easily intercommunicates with a large number of languages.
It has efficient high-level data structures and a simple but effective approach to object-oriented programming.
Python may be used as a server-side language and may output HTM (such as PHP)
It is an open source and multi-platforms language.
The interpreter and the extensive standard libraries are available at https://www.python.org/ : you can download the latest version or specific releases of Python.
Depending on different aspects you may download the 2.x or 3.x version of Python.
For more information, you should refer to wiki.python.org web site:
Refer to https://docs.python.org/3/whatsnew/3.0.html to see what is new in Python 3.x
Integrated Development Environment:
Python distribution: it exists many distributions for installing Python. Distributions come with inbuilt packages (libraries) and Integrated Development Environment (IDE). They set the computing environment for us.
To learn Python, you can either choose to:
download the Python release of your choice from the python official website [https://www.python.org/downloads/] (https://www.python.org/downloads/). It comes with an Integrated Development Environment built with the Tkinter GUI toolkit: IDLE.
install a distribution of your choice as Anaconda for example.
For this tutorial it could be convenient to install the Python distribution Anaconda from https://www.continuum.io/downloads.Anaconda is one of the leading open data science platform. On a linux system, refer to https://docs.continuum.io/anaconda/install/linux.html.
It is an easy-to-install package which includes everything you need to build data science application:
Note that if you are running out of time or disk space for the entire anaconda distribution, you can install Miniconda which contains only conda and Python from [https://conda.io/miniconda.html] (https://conda.io/miniconda.html). Then you will need to install the individual packages (libraries) you want through the
Note that with
conda, you can create, export, list, remove, and update environments that have different versions of Python and/or packages installed in them.
For more information about distributions and IDE refer to the following section.
Depending on the purpose of your applications, many distributions exist. TODO to develop
Python distributions come with in-built IDE but you can chose a specific IDE of your choice aside to the default installed IDE. TODO develop