Python Training at EthansPune is certification-oriented course focused on 100% Practical and Project based learning experience. Our online Python certification ..
Python is a high-level programming language that emphasizes code readability. It has a clear syntax and large standard library. Python can be used for system programming, GUIs, internet scripting, database programming, and more. Some key strengths of Python include being object-oriented, free, portable, powerful, easy to use and learn. Popular uses of Python include web development, scientific computing, and financial applications. The document provides an overview of Python fundamentals like data types, control flow statements, functions, classes, and modules.
This document provides an introduction to Python programming. It discusses the history and origins of Python, its key features and applications. Some of the main points covered include:
- Python was created in the late 1980s by Guido van Rossum and takes influence from other languages like ABC, Modula-3, C, C++ and Unix shell scripts.
- Python is an interpreted, object-oriented scripting language that is designed to be highly readable. It has applications in systems programming, GUIs, web development, data analysis, scientific computing and more.
- The document outlines Python's technical strengths like being free, portable, powerful, easy to use and learn. It also covers basics like variables,
Python is an interpreted, high-level, general-purpose programming language.
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decision-making.
This document is a report on Python for a class. It includes sections on the history of Python, why it is a good choice for learning programming, its core characteristics like being interpreted and object-oriented, common data structures like lists and dictionaries, the NumPy package for scientific computing, and a conclusion about the benefits of using Python as a teaching language.
This document is a report on Python for a class. It includes sections on the history of Python, why it is a good choice for learning programming, its core characteristics like being interpreted and object-oriented, common data structures like lists and dictionaries, the NumPy package for scientific computing, and a conclusion about the benefits of using Python as a teaching language.
Python was conceived in the late 1980s and its implementation was started in 1989. Python 2.0 was released in 2000 with major new features like garbage collection and unicode support. Python 3.0 was released in 2008 as a backwards-incompatible version after long testing. Python is a general-purpose, high-level programming language designed for code readability. It supports multiple programming paradigms like object-oriented, imperative, and functional programming. Python has a large standard library and interpreters available for many operating systems.
This presentation is a part of the COP2271C college level course taught at the Florida Polytechnic University located in Lakeland Florida. The purpose of this course is to introduce Freshmen students to both the process of software development and to the Python language.
The course is one semester in length and meets for 2 hours twice a week. The Instructor is Dr. Jim Anderson.
A video of Dr. Anderson using these slides is available on YouTube at: https://www.youtube.com/watch?feature=player_embedded&v=_LxfIQuFALY
Python is a high-level programming language that emphasizes code readability. It has a clear syntax and large standard library. Python can be used for system programming, GUIs, internet scripting, database programming, and more. Some key strengths of Python include being object-oriented, free, portable, powerful, easy to use and learn. Popular uses of Python include web development, scientific computing, and financial applications. The document provides an overview of Python fundamentals like data types, control flow statements, functions, classes, and modules.
This document provides an introduction to Python programming. It discusses the history and origins of Python, its key features and applications. Some of the main points covered include:
- Python was created in the late 1980s by Guido van Rossum and takes influence from other languages like ABC, Modula-3, C, C++ and Unix shell scripts.
- Python is an interpreted, object-oriented scripting language that is designed to be highly readable. It has applications in systems programming, GUIs, web development, data analysis, scientific computing and more.
- The document outlines Python's technical strengths like being free, portable, powerful, easy to use and learn. It also covers basics like variables,
Python is an interpreted, high-level, general-purpose programming language.
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data.
Data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decision-making.
This document is a report on Python for a class. It includes sections on the history of Python, why it is a good choice for learning programming, its core characteristics like being interpreted and object-oriented, common data structures like lists and dictionaries, the NumPy package for scientific computing, and a conclusion about the benefits of using Python as a teaching language.
This document is a report on Python for a class. It includes sections on the history of Python, why it is a good choice for learning programming, its core characteristics like being interpreted and object-oriented, common data structures like lists and dictionaries, the NumPy package for scientific computing, and a conclusion about the benefits of using Python as a teaching language.
Python was conceived in the late 1980s and its implementation was started in 1989. Python 2.0 was released in 2000 with major new features like garbage collection and unicode support. Python 3.0 was released in 2008 as a backwards-incompatible version after long testing. Python is a general-purpose, high-level programming language designed for code readability. It supports multiple programming paradigms like object-oriented, imperative, and functional programming. Python has a large standard library and interpreters available for many operating systems.
This presentation is a part of the COP2271C college level course taught at the Florida Polytechnic University located in Lakeland Florida. The purpose of this course is to introduce Freshmen students to both the process of software development and to the Python language.
The course is one semester in length and meets for 2 hours twice a week. The Instructor is Dr. Jim Anderson.
A video of Dr. Anderson using these slides is available on YouTube at: https://www.youtube.com/watch?feature=player_embedded&v=_LxfIQuFALY
Python is a popular, high-level programming language used for web development, software development, data science, and more. It can be used to build both simple scripting programs as well as large-scale applications. Key characteristics of Python include being dynamically typed, having automatic memory management, and using indentation to define code blocks rather than curly braces. Python supports procedural, object-oriented, and functional programming styles and has a large standard library.
Python is a popular, high-level programming language used for web development, software development, data science, and more. It can be used to build both simple scripting programs as well as large-scale applications. Key characteristics of Python include being dynamically typed, having automatic memory management, and using indentation to define code blocks rather than curly braces. Python supports procedural, object-oriented, and functional programming styles and has a large standard library.
This document provides an overview of the Python programming language. It discusses that Python is an interpreted, high-level, general-purpose programming language created by Guido van Rossum in 1991. It is commonly used for web development, software development, data science, and more. The document then covers Python syntax, basic programming concepts like variables and data types, and how to set up a Python environment and write simple Python programs.
This document discusses Python programming language and its libraries. It provides an introduction to Python, describes popular Python IDEs like Spyder and Jupyter Notebook, and discusses commonly used Python libraries such as TensorFlow, Scikit-Learn, NumPy, Keras and PyTorch. It also covers basic Python commands, functions, modules and built-in data structures.
Python is a programming language that uses objects, modules, threads, exceptions and automatic memory management. It is simple, portable, extensible, and has built-in data structures. Python is also open source. It provides a framework with system class libraries, runtime environment, and compiler/interpreter to create applications like computer programs, mobile apps, and web apps. The framework offers standard libraries, codecs, and templates to build many objects.
This document outlines the syllabus for a Python programming course. It covers 4 chapters: an introduction to Python, control statements, lists, functions, tuples and dictionaries, sets, modules, files, and exception handling. The introduction discusses Python's history and features. It also covers basic Python concepts like data types, variables, operators, and input/output. Subsequent chapters go into more depth on control flow, data structures, functions, modules and files, exceptions, and assignments include basics, strings, functions, files and dates. The course aims to teach students core Python programming concepts and skills.
Python is a popular programming language created by Guido van Rossum in 1991. It is used for web development, software development, mathematics, and system scripting. Python code can be written and executed quickly as it runs on an interpreter system. It has a simple, English-like syntax and works across many platforms. The latest major version is Python 3, though Python 2 remains popular.
The document provides an overview of using Python for bioinformatics, discussing what Python is, why it is useful for bioinformatics, how to set up Python in integrated development environments like Eclipse with PyDev, how to share code using Git and GitHub, and includes examples of Hello World and bioinformatics programs in Python. It introduces Python and argues it is well-suited for bioinformatics due to its extensive standard libraries, ease of use, and wide adoption in science. The document demonstrates how to install Python, set up an IDE, create and run simple Python programs, and use version control with Git and GitHub to collaborate on projects.
The document is a presentation on Python given at the USENIX LISA conference in 2007. It introduces Python by discussing its history, influences, uses, and focus on systems programming. It provides an overview of getting started with Python, including where to get it, running Python in interactive mode or from files, and creating Python programs. It also includes a sample mortgage calculation program written in Python as an example.
Dr. Tanvi FOCP Unit-2 Session-1 PPT (Revised).pdfRahulSingh190790
This document outlines the agenda and objectives for a series of sessions on introducing Python programming. The sessions will cover Python features, environment setup, syntax, data types, operators, strings, and regular expressions. The goals are for students to understand why Python is useful, install Python correctly, configure their environment, and gain familiarity with Python's core concepts and fundamentals. Real-world uses of Python include web development, data science, machine learning, automation, and cross-platform software development.
Introduction to Analytics with Azure Notebooks and PythonJen Stirrup
Introduction to Analytics with Azure Notebooks and Python for Data Science and Business Intelligence. This is one part of a full day workshop on moving from BI to Analytics
This document provides an overview of key Python concepts:
1. Modules allow organizing Python code into files and namespaces. The file name is the module name with a .py extension.
2. Python code is compiled into bytecode cache files (.pyc) for improved performance. These files are platform independent.
3. Advanced optimizations can be applied to bytecode with command line flags, but may affect program functionality in rare cases.
4. Standard modules provide useful functions like dir() to inspect modules and packages for organizing code. Input/output, strings, files and exceptions are also covered.
Python is a versatile and widely-used high-level programming language known for its simplicity, readability, and extensive library support. Created by Guido van Rossum and first released in 1991, Python has since gained immense popularity across various domains, including web development, data science, scientific computing, artificial intelligence, and more. In this comprehensive description, we'll delve into Python's history, features, applications, and its vibrant community, highlighting why it continues to be a preferred choice for developers worldwide.
Table of Contents
Introduction to Python
Python's History and Evolution
Python's Key Features
3.1. Readability and Simplicity
3.2. High-level Language
3.3. Interpreted and Dynamic
3.4. Cross-platform Compatibility
3.5. Rich Standard Library
3.6. Community Support
Python's Application Domains
4.1. Web Development
4.2. Data Science and Machine Learning
4.3. Scientific Computing
4.4. Automation and Scripting
4.5. Game Development
4.6. Desktop Applications
Python Development Environments
5.1. IDLE
5.2. PyCharm
5.3. Jupyter Notebook
5.4. Visual Studio Code
Getting Started with Python
6.1. Installing Python
6.2. Your First Python Program
Python Syntax and Basic Concepts
7.1. Variables and Data Types
7.2. Conditional Statements
7.3. Loops
7.4. Functions
7.5. Exception Handling
Working with Python Libraries
8.1. NumPy
8.2. Pandas
8.3. Matplotlib
8.4. Scikit-Learn
Python and Web Development
9.1. Frameworks (Django, Flask)
9.2. Front-end Integration (HTML/CSS)
9.3. Database Interaction (SQL, NoSQL)
Python in Data Science
10.1. Data Analysis with Pandas
10.2. Data Visualization with Matplotlib and Seaborn
10.3. Machine Learning with Scikit-Learn
10.4. Deep Learning with TensorFlow and PyTorch
Scientific Computing with Python
11.1. Scientific Libraries (SciPy, SymPy)
11.2. Plotting and Visualization (Matplotlib)
Automation and Scripting
12.1. Automating Tasks
12.2. Scripting for System Administration
Game Development with Python
13.1. Pygame
13.2. Unity and Unreal Engine Integration
Desktop Applications with Python
14.1. Tkinter
14.2. PyQt
Python's Ecosystem and Package Management
Python Best Practices
16.1. Code Readability (PEP 8)
16.2. Documentation and Comments
16.3. Testing (Unit Testing, pytest)
16.4. Version Control (Git)
Python's Future and Trends
Conclusion
1. Introduction to Python
Python is a general-purpose, high-level programming language that was designed with a focus on code readability and simplicity. It uses an elegant and straightforward syntax that makes it easy for developers to express their ideas effectively, reducing the cost of program maintenance. Python's philosophy emphasizes the importance of code clarity and readability, which is encapsulated in the Zen of Python (PEP 20).
The language has gained immense popularity due to its versatility and a rich ecosystem of libraries and frameworks. Python is renowned for its vibrant community and extensive documentation, making it in p
Introduction to python history and platformsKirti Verma
This document provides an introduction to Python and discusses popular tools used in data science, the evolution of Python, advantages of using Python, coding environments including Integrated Development Environments (IDEs) like PyCharm, Jupyter Notebook, and Spyder. It describes features of these IDEs and how they can be used for coding, debugging, and data analysis in Python.
Python is an easy to learn programming language that is widely used for a variety of tasks. It has a simple syntax that allows developers to focus on solving problems rather than dealing with complex language features. Python code can be written quickly and read easily by others. It also has a large ecosystem of libraries and frameworks that support application development, data science, machine learning, and more. While not the fastest language, Python makes up for it with versatility and the ability to connect different systems through its "glue" programming capabilities.
Python is a general purpose, dynamic, high-level and interpreted programming language. It is used widely in data science, machine learning, web development, automation and more. Python was created in the 1990s by Guido van Rossum to be an interpreted language that bridged the gap between C and shell scripting. It has many advantages like being readable, cross-platform, having a large standard library and being open source.
Certainly! Here's a detailed 3000-word description of Python:
# Python: A Comprehensive Overview
Python is a high-level, versatile, and dynamically-typed programming language known for its simplicity and readability. Created by Guido van Rossum in the late 1980s, Python has since become one of the most popular programming languages worldwide. In this comprehensive overview, we will delve into the key aspects of Python, from its history and design philosophy to its syntax, libraries, and real-world applications.
## **History and Evolution of Python**
Python's history dates back to December 1989 when Guido van Rossum, a Dutch programmer, began working on it as a side project during his Christmas holidays. His aim was to create a language that emphasized code readability and allowed developers to express their ideas in fewer lines of code compared to other languages like C++ or Perl.
The first official Python release, Python 0.9.0, was released in February 1991. Python's name was inspired by Guido's love for the British comedy group Monty Python. Despite its humorous origins, Python quickly gained popularity in the software development community.
Python's major versions include Python 1.0 (1994), Python 2.0 (2000), Python 3.0 (2008), and the subsequent 3.x releases. The transition from Python 2 to Python 3 was a significant milestone in Python's history, as it involved breaking compatibility with Python 2 to introduce improvements and address some language inconsistencies. Python 2 reached its end of life on January 1, 2020, and Python 3 is now the standard and recommended version for new projects.
## **Design Philosophy: The Zen of Python**
Python's success can be attributed, in part, to its clear and guiding design principles, often referred to as "The Zen of Python" or "PEP 20" (Python Enhancement Proposal 20). These principles encapsulate the language's philosophy and provide a framework for writing clean, readable, and maintainable code. Some notable principles from "The Zen of Python" include:
- **Readability Counts:** Code should be easy to read and understand. Python's syntax enforces this with its use of indentation for block structure.
- **Simple is Better Than Complex:** Python encourages simplicity in both code design and implementation. It favors straightforward solutions over convoluted ones.
- **Explicit is Better Than Implicit:** Code should be explicit and not rely on hidden or magical behavior. This principle promotes code clarity and predictability.
- **There Should Be One-- and Preferably Only One --Obvious Way to Do It:** Python aims to provide a single, clear way to perform a specific task to reduce confusion and make code more consistent.
- **Errors Should Never Pass Silently:** Python encourages robust error handling and reporting to help developers identify and fix issues promptly.
## **Python Syntax and Language Features**
Python's syntax is known for its simplicity and readability. Here are some key languag
This document provides an overview of the Python programming language. It discusses Python's history, key features such as being easy to use, scalable, high-level, object-oriented, interpreted, and having a rich core library. It also covers Python's uses in areas like web development, databases, GUI programming, and more. The document is intended to introduce readers to Python and provide context for a book on making use of the language.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Python is a popular, high-level programming language used for web development, software development, data science, and more. It can be used to build both simple scripting programs as well as large-scale applications. Key characteristics of Python include being dynamically typed, having automatic memory management, and using indentation to define code blocks rather than curly braces. Python supports procedural, object-oriented, and functional programming styles and has a large standard library.
Python is a popular, high-level programming language used for web development, software development, data science, and more. It can be used to build both simple scripting programs as well as large-scale applications. Key characteristics of Python include being dynamically typed, having automatic memory management, and using indentation to define code blocks rather than curly braces. Python supports procedural, object-oriented, and functional programming styles and has a large standard library.
This document provides an overview of the Python programming language. It discusses that Python is an interpreted, high-level, general-purpose programming language created by Guido van Rossum in 1991. It is commonly used for web development, software development, data science, and more. The document then covers Python syntax, basic programming concepts like variables and data types, and how to set up a Python environment and write simple Python programs.
This document discusses Python programming language and its libraries. It provides an introduction to Python, describes popular Python IDEs like Spyder and Jupyter Notebook, and discusses commonly used Python libraries such as TensorFlow, Scikit-Learn, NumPy, Keras and PyTorch. It also covers basic Python commands, functions, modules and built-in data structures.
Python is a programming language that uses objects, modules, threads, exceptions and automatic memory management. It is simple, portable, extensible, and has built-in data structures. Python is also open source. It provides a framework with system class libraries, runtime environment, and compiler/interpreter to create applications like computer programs, mobile apps, and web apps. The framework offers standard libraries, codecs, and templates to build many objects.
This document outlines the syllabus for a Python programming course. It covers 4 chapters: an introduction to Python, control statements, lists, functions, tuples and dictionaries, sets, modules, files, and exception handling. The introduction discusses Python's history and features. It also covers basic Python concepts like data types, variables, operators, and input/output. Subsequent chapters go into more depth on control flow, data structures, functions, modules and files, exceptions, and assignments include basics, strings, functions, files and dates. The course aims to teach students core Python programming concepts and skills.
Python is a popular programming language created by Guido van Rossum in 1991. It is used for web development, software development, mathematics, and system scripting. Python code can be written and executed quickly as it runs on an interpreter system. It has a simple, English-like syntax and works across many platforms. The latest major version is Python 3, though Python 2 remains popular.
The document provides an overview of using Python for bioinformatics, discussing what Python is, why it is useful for bioinformatics, how to set up Python in integrated development environments like Eclipse with PyDev, how to share code using Git and GitHub, and includes examples of Hello World and bioinformatics programs in Python. It introduces Python and argues it is well-suited for bioinformatics due to its extensive standard libraries, ease of use, and wide adoption in science. The document demonstrates how to install Python, set up an IDE, create and run simple Python programs, and use version control with Git and GitHub to collaborate on projects.
The document is a presentation on Python given at the USENIX LISA conference in 2007. It introduces Python by discussing its history, influences, uses, and focus on systems programming. It provides an overview of getting started with Python, including where to get it, running Python in interactive mode or from files, and creating Python programs. It also includes a sample mortgage calculation program written in Python as an example.
Dr. Tanvi FOCP Unit-2 Session-1 PPT (Revised).pdfRahulSingh190790
This document outlines the agenda and objectives for a series of sessions on introducing Python programming. The sessions will cover Python features, environment setup, syntax, data types, operators, strings, and regular expressions. The goals are for students to understand why Python is useful, install Python correctly, configure their environment, and gain familiarity with Python's core concepts and fundamentals. Real-world uses of Python include web development, data science, machine learning, automation, and cross-platform software development.
Introduction to Analytics with Azure Notebooks and PythonJen Stirrup
Introduction to Analytics with Azure Notebooks and Python for Data Science and Business Intelligence. This is one part of a full day workshop on moving from BI to Analytics
This document provides an overview of key Python concepts:
1. Modules allow organizing Python code into files and namespaces. The file name is the module name with a .py extension.
2. Python code is compiled into bytecode cache files (.pyc) for improved performance. These files are platform independent.
3. Advanced optimizations can be applied to bytecode with command line flags, but may affect program functionality in rare cases.
4. Standard modules provide useful functions like dir() to inspect modules and packages for organizing code. Input/output, strings, files and exceptions are also covered.
Python is a versatile and widely-used high-level programming language known for its simplicity, readability, and extensive library support. Created by Guido van Rossum and first released in 1991, Python has since gained immense popularity across various domains, including web development, data science, scientific computing, artificial intelligence, and more. In this comprehensive description, we'll delve into Python's history, features, applications, and its vibrant community, highlighting why it continues to be a preferred choice for developers worldwide.
Table of Contents
Introduction to Python
Python's History and Evolution
Python's Key Features
3.1. Readability and Simplicity
3.2. High-level Language
3.3. Interpreted and Dynamic
3.4. Cross-platform Compatibility
3.5. Rich Standard Library
3.6. Community Support
Python's Application Domains
4.1. Web Development
4.2. Data Science and Machine Learning
4.3. Scientific Computing
4.4. Automation and Scripting
4.5. Game Development
4.6. Desktop Applications
Python Development Environments
5.1. IDLE
5.2. PyCharm
5.3. Jupyter Notebook
5.4. Visual Studio Code
Getting Started with Python
6.1. Installing Python
6.2. Your First Python Program
Python Syntax and Basic Concepts
7.1. Variables and Data Types
7.2. Conditional Statements
7.3. Loops
7.4. Functions
7.5. Exception Handling
Working with Python Libraries
8.1. NumPy
8.2. Pandas
8.3. Matplotlib
8.4. Scikit-Learn
Python and Web Development
9.1. Frameworks (Django, Flask)
9.2. Front-end Integration (HTML/CSS)
9.3. Database Interaction (SQL, NoSQL)
Python in Data Science
10.1. Data Analysis with Pandas
10.2. Data Visualization with Matplotlib and Seaborn
10.3. Machine Learning with Scikit-Learn
10.4. Deep Learning with TensorFlow and PyTorch
Scientific Computing with Python
11.1. Scientific Libraries (SciPy, SymPy)
11.2. Plotting and Visualization (Matplotlib)
Automation and Scripting
12.1. Automating Tasks
12.2. Scripting for System Administration
Game Development with Python
13.1. Pygame
13.2. Unity and Unreal Engine Integration
Desktop Applications with Python
14.1. Tkinter
14.2. PyQt
Python's Ecosystem and Package Management
Python Best Practices
16.1. Code Readability (PEP 8)
16.2. Documentation and Comments
16.3. Testing (Unit Testing, pytest)
16.4. Version Control (Git)
Python's Future and Trends
Conclusion
1. Introduction to Python
Python is a general-purpose, high-level programming language that was designed with a focus on code readability and simplicity. It uses an elegant and straightforward syntax that makes it easy for developers to express their ideas effectively, reducing the cost of program maintenance. Python's philosophy emphasizes the importance of code clarity and readability, which is encapsulated in the Zen of Python (PEP 20).
The language has gained immense popularity due to its versatility and a rich ecosystem of libraries and frameworks. Python is renowned for its vibrant community and extensive documentation, making it in p
Introduction to python history and platformsKirti Verma
This document provides an introduction to Python and discusses popular tools used in data science, the evolution of Python, advantages of using Python, coding environments including Integrated Development Environments (IDEs) like PyCharm, Jupyter Notebook, and Spyder. It describes features of these IDEs and how they can be used for coding, debugging, and data analysis in Python.
Python is an easy to learn programming language that is widely used for a variety of tasks. It has a simple syntax that allows developers to focus on solving problems rather than dealing with complex language features. Python code can be written quickly and read easily by others. It also has a large ecosystem of libraries and frameworks that support application development, data science, machine learning, and more. While not the fastest language, Python makes up for it with versatility and the ability to connect different systems through its "glue" programming capabilities.
Python is a general purpose, dynamic, high-level and interpreted programming language. It is used widely in data science, machine learning, web development, automation and more. Python was created in the 1990s by Guido van Rossum to be an interpreted language that bridged the gap between C and shell scripting. It has many advantages like being readable, cross-platform, having a large standard library and being open source.
Certainly! Here's a detailed 3000-word description of Python:
# Python: A Comprehensive Overview
Python is a high-level, versatile, and dynamically-typed programming language known for its simplicity and readability. Created by Guido van Rossum in the late 1980s, Python has since become one of the most popular programming languages worldwide. In this comprehensive overview, we will delve into the key aspects of Python, from its history and design philosophy to its syntax, libraries, and real-world applications.
## **History and Evolution of Python**
Python's history dates back to December 1989 when Guido van Rossum, a Dutch programmer, began working on it as a side project during his Christmas holidays. His aim was to create a language that emphasized code readability and allowed developers to express their ideas in fewer lines of code compared to other languages like C++ or Perl.
The first official Python release, Python 0.9.0, was released in February 1991. Python's name was inspired by Guido's love for the British comedy group Monty Python. Despite its humorous origins, Python quickly gained popularity in the software development community.
Python's major versions include Python 1.0 (1994), Python 2.0 (2000), Python 3.0 (2008), and the subsequent 3.x releases. The transition from Python 2 to Python 3 was a significant milestone in Python's history, as it involved breaking compatibility with Python 2 to introduce improvements and address some language inconsistencies. Python 2 reached its end of life on January 1, 2020, and Python 3 is now the standard and recommended version for new projects.
## **Design Philosophy: The Zen of Python**
Python's success can be attributed, in part, to its clear and guiding design principles, often referred to as "The Zen of Python" or "PEP 20" (Python Enhancement Proposal 20). These principles encapsulate the language's philosophy and provide a framework for writing clean, readable, and maintainable code. Some notable principles from "The Zen of Python" include:
- **Readability Counts:** Code should be easy to read and understand. Python's syntax enforces this with its use of indentation for block structure.
- **Simple is Better Than Complex:** Python encourages simplicity in both code design and implementation. It favors straightforward solutions over convoluted ones.
- **Explicit is Better Than Implicit:** Code should be explicit and not rely on hidden or magical behavior. This principle promotes code clarity and predictability.
- **There Should Be One-- and Preferably Only One --Obvious Way to Do It:** Python aims to provide a single, clear way to perform a specific task to reduce confusion and make code more consistent.
- **Errors Should Never Pass Silently:** Python encourages robust error handling and reporting to help developers identify and fix issues promptly.
## **Python Syntax and Language Features**
Python's syntax is known for its simplicity and readability. Here are some key languag
This document provides an overview of the Python programming language. It discusses Python's history, key features such as being easy to use, scalable, high-level, object-oriented, interpreted, and having a rich core library. It also covers Python's uses in areas like web development, databases, GUI programming, and more. The document is intended to introduce readers to Python and provide context for a book on making use of the language.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
The chapter Lifelines of National Economy in Class 10 Geography focuses on the various modes of transportation and communication that play a vital role in the economic development of a country. These lifelines are crucial for the movement of goods, services, and people, thereby connecting different regions and promoting economic activities.
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
2. OVERVIEW OF PYTHON
•Python is a general-purpose, object-
oriented programming language with
high-level programming capabilities. It
has become famous because of its
apparent and easily understandable
syntax, portability, and easy to learn.
3. INSTALLING
• Python is pre-installed on most Unix systems, including Linux and
MAC OS X
• The pre-installed version may not be the most recent one (2.6.2 and
3.1.1 as of Sept 09)
• Download from http://python.org/download/
• Python comes with a large library of standard modules
• There are several options for an IDE
• IDLE – works well with Windows
• Emacs with python-mode or your favorite text editor
• Eclipse with Pydev (http://pydev.sourceforge.net/)
4. ASSIGHNMENT
• Binding a variable in Python means setting a name to hold a reference to some object
• Assignment creates references, not copies
• Names in Python do not have an intrinsic type, objects have types
• Python determines the type of the reference automatically based on what data is assigned
to it
• You create a name the first time it appears on the left side of an assignment expression:
x = 3
• A reference is deleted via garbage collection after any names bound to it have passed out
of scope
• Python uses reference semantics (more later)
5. NAMING CONVENTIONS
The Python community has these recommend-ed naming conventions
•joined_lower for functions, methods and, attributes
•joined_lower or ALL_CAPS for constants
•StudlyCaps for classes
•camelCase only to conform to pre-existing conventions
•Attributes: interface, _internal, __private
6. COMMENTS
• Start comments with #, rest of line is ignored
• Can include a “documentation string” as the first line of a new
function or class you define
• Development environments, debugger, and other tools use it: it’s
good style to include one
def fact(n):
“““fact(n) assumes n is a positive integer and
returns facorial of n.”””
assert(n>0)
return 1 if n==1 else n*fact(n-1)
7. WHAT IS PYTHON USED FOR?
• Python is commonly used for developing websites and software, task automation,
data analysis, and data visualization. Since it’s relatively easy to learn, Python has
been adopted by many non-programmers such as accountants and scientists, for a
variety of everyday tasks, like organizing finances.
• “Writing programs is a very creative and rewarding activity,” says University of
Michigan and Coursera instructor Charles R Severance in his book Python for
Everybody. “You can write programs for many reasons, ranging from making your
living to solving a difficult data analysis problem to having fun to helping someone
else solve a problem.”