Introduction to Python – Saidemy
What is Python?
Python is a powerful language with excellent tools for data crunching and preparation, as well as for complex scientific data analysis and modeling. Python is a popular programming language created in 1991 by Guido van Rossum. It is primarily used for:
Development of web applications (server-side).
Development of software,
Scripting for the operating system.
Due to the fact that Python is an interpreted language, it is very popular among other languages.
On machines with Python installed, it is usually located at /usr/local/bin/python3.9;
Adding /usr/local/bin to your Unix shell's search path makes it possible to run Python 3.x by typing the command: python3.
The python3.9 command will be available where you have installed Python on Windows machines. If you have the py.exe launcher installed, you can also use the py command.
In addition to argument passing, the interpreter is also used for interactive operations.
In just a few easy steps, we can install Python on our Windows server or local machine.
You will need to download the Python .exe installer and run it on your system in order to complete the installation procedure. The version you need varies depending on what you want to accomplish with Python. You should download both Python 2 and Python 3 at the same time.
Navigate to the Downloads for Windows section of the official Python website and download the Python executable installer.
Download either the Windows x86-64 executable installer or the Windows x86 executable installer from the Python website.
Execute the executable installer.
If you select Disable path length limit, Python will bypass the 260-character MAX_PATH limit.
Make sure Python is installed on your system.
Python Installation For Windows
To install Python on Windows, we need to follow the same installation process as we discussed above. After that, we need to verify that Python is properly installed on the system.
Find the Python installation directory on the system. In our case, it is
The latest version of Python is installed at C:/Users/Username/AppData/Local/Programs/Python/Python37.
The python.exe file should be double-clicked.
Similar results should be obtained
We must now verify whether Pip is installed. Pip is a powerful package manager for Python software packages. If you installed an older version of Python, it may not have come with Pip preinstalled.
To verify whether Pip was installed:
Type "cmd" in the Start menu.
The Command Prompt application should be selected.
If Pip was successfully installed, you should see the following output:
Python Installation For Linux:
First, install the development packages required to build Python.
On Debian we need to do the following:
$ sudo apt update
$ sudo apt install build-essential zlib1g-dev \
libncurses5-dev libgdbm-dev libnss3-dev \
libssl-dev libreadline-dev libffi-dev curl
On Fedora we need to do the following.
$ sudo dnfgroupinstall development
Download the latest stable version of Python. Visit the official Python website and download the latest version of Python. After the download is complete, you will have a .tar.xz archive file (a “tarball”) containing the source code of Python.
Extract the tarball
Configure the script. Once the Python tarball has been extracted, navigate to the configure script and execute it in your Linux terminal with:$ cd Python-3.*
Start the build process using the command $ sudo make altinstall
Verify the installation with the help of the command python –version
Python Installation For Mac
Python 2.7 comes with Mac OS X out of the box. If you want to use Python 2, you do not need to install or configure anything else. But if you are working with Python 3, you need to do the following.
The Homebrew version of Python 2 is already installed, and the Homebrew version of Python 3 is as well.
$ Python will launch the Homebrew-installed Python 3 interpreter.
$ python2 Command will launch the Homebrew-installed Python 2 interpreter (if any).
$ python3Command will launch the Homebrew-installed Python 3 interpreter.
If the Homebrew version of Python 2 is available, point to Python 2. If the Homebrew version of Python 3 is installed, pip will point to Python 3.
The rest of the guide will assume that Python references Python 3.
$ python –version
Python 3.7.1 # Success!
A code editor is a tool that is used to write and edit code.
They are usually convenient and helpful for learning.
The IDE (Integrated Development Environment) understands your code much better than a text editor.
It usually provides features such as build automation, code linting, testing, and debugging. This can significantly speed up your work.
The downside is that IDEs can be complicated to use.
Below are some of the most popular IDEs.
Online Compiler from Programs.
Sublime Text 3
Visual Studio Code
Featuring many latest features, PyCharm is an IDE for professional developers.
It is developed and created by JetBrains, which is a company well-known for creating high-quality software development tools.
There are two versions of PyCharm available on the internet:
Community - It is a free open-source version, lightweight, and suitable for Python and scientific development. It is also recommended for beginners.
Professional - It is a paid version mostly used by corporate developers. It comes with a full-featured IDE with support for Web development as well.
PyCharm provides all the essential features of a good IDE.
It should provide: code completion, code inspections, error highlighting and fixes, debugging, a version control system, and code refactoring.
All these features come out of the box.
PyCharm is considered the leading IDE for Python development.
Jupyter offers one way of accessing your notebook from the IDE.
But it is not the only way. Like Spyder, other IDEs have a long history of offering an interactive mode for scripts with double-percent cell markers.
Hydrogen is a plugin for the Atom editor that lets you run these scripts interactively.
Here the search among notebooks is super easy, so it's very widely used, and they're just text files.
Drafting a brand-new notebook is so comfortable here.
It provides you with the benefit of the advanced capabilities of the IDE: syntax checks, completion, reformats, and documentation tips.
Jupytext solves the issue of version control.
Why learn Python?
Python has already proved its worth in the data science industry and is widely accepted by most of the industry. Because of this, it has taken the lead as a toolkit for scientific data analysis and modeling.
These open libraries provide different ways of obtaining the same output.
As technology nowadays gets more and more competitive, data scientists and engineers are continually striving for ways to
Process information, extract insights, and model, by processing massive datasets.
Python is the only platform where we can explore the various, so you must be familiar with the various Python libraries that support your data science tasks. You will also benefit from the benefits they provide. They will make your output more robust and faster.
In addition, with the above Python code, we can perform the following, which is highly recommended.
Python can be used on a server to create web applications.
Python can be used alongside software to create workflows.
Python can connect to database systems. It can also read and modify files.
Python can be used to handle big data and perform complex mathematics.
Python can be used for rapid prototyping, or for production-ready software development.
Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
Python has a simple syntax like the English language.
Python has a syntax that allows developers to write programs with fewer lines than some other programming languages.
Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick.
Python can be treated in a procedural way, an object-oriented way, or a functional way.
In Python, as we have already established, Python is the only Python platform on which we can explore various possibilities. Therefore, you should be well-versed in the various Python libraries that support your data science tasks and the benefits they offer. This will make your output more robust and faster. It has many applications, of which I will list a few below.
Scientific and Numeric Applications Development.
Artificial Intelligence and Machine Learning-based application development.
Software development is application development.
Enterprise-level/business-based application development.
Education programs and training courses.
Scope @ Saidemy:
In Saidemy's Python application development program, you will receive extensive hands-on training in front-end, middleware, and back-end technologies.
It prepares you for phase-end and capstone projects based on real business scenarios.
Here you learn concepts from leading industry experts with content structured to ensure industrial relevance.
An end-to-end application with exciting features
Earn an industry-recognized certificate of completion.