Introduction to Python
Certified Python and Data Science Training – DataFlair
Agenda
What is Python? History of Python Features of Python Components of Python Frameworks for Python Flavors of Python Why Python?
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What is Python? An interpreted, high-level programming languagefor general-purpose programming ― ― ― ― ― ― ―
Each statement translated into subroutines Platform-independent Dynamic typing Easier debugging Automatic memory management Adding or changing functions at runtime No need to recompile again to test a small section
― Slower ― Checking for errors- dynamic Certified Python and Data Science Training – DataFlair
What is Python? An interpreted, high-level programming languagefor general-purpose programming ― ― ― ― ―
Strong abstraction Closer to the end-user May use elements of natural language May be simpler May automate areas like memory management
Certified Python and Data Science Training – DataFlair
Certified Python and Data Science Training – DataFlair
History of Python 1980 1980- Conception 1989- Implementation 1989 20002000 Python 2.0 Release 20082008 Python 3.0 Release 20172017Python 2.7 to Go Transcompiler 20202020End-of-life: Python 2.7 Guido Van Rossum Certified Python and Data Science Training – DataFlair
History of Python
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Features of Python
Large Library
Easy Extensible
Dynamically typed
Interpreted
and Embeddable
Free and
GUI
Programming
Open-Source
Portable
Objectoriented
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Components of Python Functions
Packages
Classes
Modules
Certified Python and Data Science Training – DataFlair
Components of Python
Functions Collection of statements May return a value
Certified Python and Data Science Training – DataFlair
Components of Python
Packages
Classes
Modules
Certified Python and Data Science Training – DataFlair
Components of Python
Abstract data type Holds no values
Classes
Certified Python and Data Science Training – DataFlair
Components of Python
Packages
Modules
Certified Python and Data Science Training – DataFlair
Components of Python
Collection of related classes and functions
Certified Python and Data Science Training – DataFlair
Modules
Components of Python
Packages
Collection of related modules
Certified Python and Data Science Training – DataFlair
Frameworks for Python
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Frameworks for Python
― ― ― ―
Free and open-source Database-driven websites DRY Principle (Don’t Repeat Yourself) Instagram, Mozilla, Disqus
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Frameworks for Python
― ― ― ―
Web framework Microframework No database abstraction layer/ form validation Extensions
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Frameworks for Python ― ― ― ―
Microframework Web development Fast and light-weight Simple
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Frameworks for Python
― ― ― ―
Open-source Web framework High-performing and scalable Written in Python
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Frameworks for Python
― ― ― ―
Web-framework Not a mega-framework Not a micro-framework Optimal liberty for project
Certified Python and Data Science Training – DataFlair
Frameworks for Python ― ― ― ― ―
Open-source Web-framework Rapid development MVC architecture Written in Python
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Frameworks for Python ― ― ― ―
Open-source Web-framework Extensive use of third-party tools Deprecated framework
Certified Python and Data Science Training – DataFlair
Flavors of Python
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Flavors of Python
― Most-widely used implementation of Python ― Written in C ― An interpreter
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Flavors of Python
― Implemented in C# ― Extensibility layer to application frameworks written in a .NET language
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Flavors of Python ― Written in Java ― Can import Java classes ― Compiles to Java bytecode
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Flavors of Python ― ― ― ―
MicroPython Designed to run on a microcontroller Uses a MicroPython board This runs MicroPython on bare metal
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Flavors of Python
― Implemented in Python ― Fast ― Easy to experiment with
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Flavors of Python ― Browser Python ― Runs in the browser
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Flavors of Python ― Bridge between Python and Ruby interpreters ― Marshals data between Python and Ruby virtual machines
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Why Python?
Computer Vision
Scientific Computing
Build a website
Robotics
Develop a game Scripting
Artificial
Intelligence
Web Scraping
Machine Learning
Data Analysis
Automate a web browser
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