Each scripting language has specific words or keywords with specific definitions and usage guidelines. Python is no exception. The fundamental building blocks of any Python program are Python keywords.
The document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans and sets. It explains how to check data types and provides examples. It also discusses Python keywords like True, False, None, and, or, not, in and is. It covers keywords used for iteration like for, while, break and continue. Finally, it discusses exception handling keywords like try, except, finally and raise.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
Engineering CS 5th Sem Python Module-1.pptxhardii0991
The document discusses Python programming concepts like expressions, data types, operators, variables, and functions. It provides instructions for downloading and launching the Mu editor and interactive shell. It explains that expressions in Python evaluate to single values, and covers integer, floating-point, and string data types. It also discusses string concatenation and replication operators, rules for variable names, and uses examples to demonstrate basic programming concepts like if/else statements and functions.
This document provides an introduction to Python programming concepts such as keywords, identifiers, comments, variables, data types, and literals. It defines keywords as reserved words in Python that have special meanings. Identifiers are names given to variables and other objects. Comments are notes for making code more readable. Variables are containers that hold data values. Literals represent fixed values like numbers and strings. The document also discusses Python data types like integers, floats, booleans, lists, tuples, dictionaries and sets.
This document provides an introduction and overview of the Python programming language course CSE 120 handled by G.Gandhi Jaba Kumar. It discusses that Python is an interpreted, object-oriented, and interactive programming language used for web development, software development, mathematics, and system scripting. The document then covers Python syntax including indentation, comments, keywords, variables, data types, operators, and basic programming concepts like conditionals and loops. It provides examples to illustrate Python code and best practices.
Introduction to Python for Data Science and Machine Learning ParrotAI
This document provides an introduction and overview of Python for data science and machine learning. It covers basics of Python including what Python is, its features, why it is useful for data science. It also discusses installing Python, using the IDLE and Jupyter Notebook environments. The document then covers Python basics like variables, data types, operators, decision making and loops. Finally, it discusses collection data types like lists, tuples and dictionaries and functions in Python.
This document discusses variables, data types, expressions, and functions in Python. It defines a variable as a name that represents a stored value in memory. It describes different data types in Python including integers, floats, strings, Booleans, and others. It also discusses expressions, which represent computations that evaluate to a value, and different expression types like arithmetic, relational, logical, and compound expressions. Finally, it introduces functions as blocks of code that perform tasks and can return values.
The document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans and sets. It explains how to check data types and provides examples. It also discusses Python keywords like True, False, None, and, or, not, in and is. It covers keywords used for iteration like for, while, break and continue. Finally, it discusses exception handling keywords like try, except, finally and raise.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
This document discusses Python data types and keywords. It covers standard data types like numbers, strings, lists, tuples, dictionaries, booleans, and sets. It explains that Python automatically determines variable types and the type() function can check types. Keywords are reserved words in Python that have predefined meanings, like True, False, None, and, or, not, in, is for boolean logic and comparison. Other keywords include for, while, break, continue for iteration and try, except, finally, raise, assert for exception handling. The document provides examples and explanations of usage for different Python keywords.
Engineering CS 5th Sem Python Module-1.pptxhardii0991
The document discusses Python programming concepts like expressions, data types, operators, variables, and functions. It provides instructions for downloading and launching the Mu editor and interactive shell. It explains that expressions in Python evaluate to single values, and covers integer, floating-point, and string data types. It also discusses string concatenation and replication operators, rules for variable names, and uses examples to demonstrate basic programming concepts like if/else statements and functions.
This document provides an introduction to Python programming concepts such as keywords, identifiers, comments, variables, data types, and literals. It defines keywords as reserved words in Python that have special meanings. Identifiers are names given to variables and other objects. Comments are notes for making code more readable. Variables are containers that hold data values. Literals represent fixed values like numbers and strings. The document also discusses Python data types like integers, floats, booleans, lists, tuples, dictionaries and sets.
This document provides an introduction and overview of the Python programming language course CSE 120 handled by G.Gandhi Jaba Kumar. It discusses that Python is an interpreted, object-oriented, and interactive programming language used for web development, software development, mathematics, and system scripting. The document then covers Python syntax including indentation, comments, keywords, variables, data types, operators, and basic programming concepts like conditionals and loops. It provides examples to illustrate Python code and best practices.
Introduction to Python for Data Science and Machine Learning ParrotAI
This document provides an introduction and overview of Python for data science and machine learning. It covers basics of Python including what Python is, its features, why it is useful for data science. It also discusses installing Python, using the IDLE and Jupyter Notebook environments. The document then covers Python basics like variables, data types, operators, decision making and loops. Finally, it discusses collection data types like lists, tuples and dictionaries and functions in Python.
This document discusses variables, data types, expressions, and functions in Python. It defines a variable as a name that represents a stored value in memory. It describes different data types in Python including integers, floats, strings, Booleans, and others. It also discusses expressions, which represent computations that evaluate to a value, and different expression types like arithmetic, relational, logical, and compound expressions. Finally, it introduces functions as blocks of code that perform tasks and can return values.
This document introduces a Python workbook for beginners. It covers 7 chapters that teach Python fundamentals like data types, variables, operators, conditional statements, and loops. The chapters also include quizzes to test the reader's understanding. The conclusion encourages the reader to take a paid Python course for more practical learning experiences to advance their skills.
Python is a powerful and widely used general purpose programming language. It has a simple syntax similar to the English language and allows developers to write programs with fewer lines of code compared to other languages. Python supports key data types like numbers, strings, lists, tuples, dictionaries, sets and Boolean values. It also supports common operators for arithmetic, comparison, assignment, logical, identity, membership and bitwise operations. Some key advantages of Python include being interpreted, having dynamic typing and readability due to indentation.
Mastering Python : 100+ Solved and Commented Exercises to Accelerate Your Lea...Lucky Gods
Ready to Unleash Your Python Power?
Tired of coding in the dark? Feeling lost in a sea of syntax errors? Well, ditch the frustration and dive headfirst into Python mastery! This book is your ultimate passport to programming paradise, packed with 100+ solved and commented exercises that'll turn you from coding rookie to confident Python pro in no time!
Imagine:
Cracking the code like a ninja: Demystifying variables, functions, loops, and more!
Conquering challenges with ease: Solving real-world problems with your newfound Python skills!
Leveling up your game: Mastering advanced concepts like data analysis and machine learning!
Sharing your Python prowess: Dazzling everyone with your coding superpowers!
This book is your roadmap to Python success:
Spark your coding curiosity: Ignite your passion for programming with engaging explanations and real-world examples.
Master the fundamentals: Build a solid foundation in Python syntax, data types, and control flow.
Practice makes perfect: Tackle 100+ challenges of varying difficulty, with clear explanations for every step.
Level up your skills: Dive deeper into object-oriented programming, data analysis, and beyond!
So, what are you waiting for? Grab this book, unlock the power of Python, and watch your coding dreams come true!
This document provides an overview and introduction to learning Python. It discusses Python programming concepts like data science, machine learning, data visualizations, and web development. It also outlines benefits of Python like job opportunities, large community, being cross-platform, and free. The document then describes the Anaconda distribution tool for scientific computing projects. It introduces the Spyder IDE and its features like source code area, IPython console, and variable/file explorers. Basic Python syntax is covered such as printing, strings, variables, and conditionals. Finally, it discusses lists, loops, and common list methods.
Python (Data Analysis) cleaning and visualizeIruolagbePius
This document provides an overview of Python programming language. It discusses Python features, uses, variables, data types, operators, decision making statements, and loops. Specifically, it covers:
- Python features like being easy to learn and read, having an interactive mode, and being portable.
- Python variables, naming rules, and basic data types like numbers, strings, booleans.
- Operators for arithmetic, comparison, assignment, and logic.
- Conditional statements like if, elif, else for decision making.
- Looping structures like while and for loops, with examples of using break, continue, else, range().
- How to write comments, take user input, and
Python dictionaries allow storing data as key-value pairs. Keys must be unique and can only contain one component, while values can be of any type including integers, lists, and tuples. Dictionaries are created using curly brackets or the dict() function. Values can be accessed and modified using their keys, and elements deleted with the del keyword. Dictionary methods like cmp(), len(), and items() allow comparing dictionaries, getting the length, and accessing items as tuples. Errors occur due to syntax or logical issues, and exceptions should be handled using try/except blocks to catch errors and continue execution.
This document provides information about various Python data types including text, numeric, sequence, mapping, set, boolean, and binary types. It discusses how variables can store different data types in Python. It also covers numeric types like integers, floats, and complexes. Strings are described as arrays of characters that can be indexed and sliced. Boolean values and operators like or, and, and not are explained. The document contrasts mutable and immutable objects in Python.
This document provides an overview of Python basics training. It covers installing Python, running Python code through various methods like the command line, IDLE, and Jupyter notebooks. It also discusses Python syntax, variables, data types, operators, conditional statements, and loops. Key Python data types include integers, floats, strings, lists, and dictionaries. The document is intended as an introduction to Python for beginners.
The document discusses PHP concepts including:
- PHP is a server-side scripting language used for web development and can be used as an alternative to Microsoft ASP.
- XAMPP is an open-source cross-platform web server bundle that can be used to test PHP scripts locally.
- PHP has different data types including strings, integers, floats, booleans, and arrays.
- PHP includes various operators, conditional statements like if/else, and loops like while and foreach to control program flow.
- Functions allow code reusability and modularity in PHP programs. Built-in and user-defined functions are discussed.
- Arrays are a special variable type that can hold multiple values,
The document discusses comparison, logical, and bitwise operators in Python. It begins by defining comparison operators like >, <, ==, which return True or False based on relations between operands. Logical operators like and, or, not allow combining conditions and return True/False. Bitwise operators like &, |, ^ manipulate single bits and perform operations like conjunction, disjunction, exclusive or on a bit level. The document provides truth tables and examples to explain the usage and precedence of these different operator types in Python.
The document discusses dictionaries in Python. It explains that dictionaries are a mapping type that store key-value pairs, with keys being immutable types and values being any type. It provides examples of creating, accessing, updating, removing entries from, and accessing properties of dictionaries. It also covers functions, control flow statements like if/else and while loops, and list comprehensions.
python programming language Python is a high-level, interpreted, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. INTRODUCTION
HISTORY
USES OF PYTHON
FEATURES OF PYTHON
PYTHON PROJECT FOR BEGINNERS
PYTHON PROGRAM
KEY CHANGES IN PYTHON
BASIC SYNTAX
VARIABLE
NUMBERS
STANDARD TYPE HIERARCHY
STRING
CONDITIONALS
FOR LOOP
FUNCTION
KEYWORDS
WHY PYTHON ?
DIFFERENTIATE
EXAMPLES
This document is an introductory tutorial on PHP web development. It begins by explaining what PHP is and its role in server-side programming. It then covers PHP basics like variables, arrays, functions, loops and conditional statements. Examples are provided for each concept to demonstrate how it works in PHP code. The document concludes by providing a full program example that combines these elements to check names in an array against a condition using a loop and function.
Functions allow programmers to organize and reuse code. They take in parameters and return values. Parameters act as variables that represent the information passed into a function. Arguments are the actual values passed into the function call. Functions can have default parameter values. Functions can return values using the return statement. Python passes arguments by reference, so changes made to parameters inside functions will persist outside the function as well. Functions can also take in arbitrary or keyword arguments. Recursion is when a function calls itself within its own definition. It breaks problems down into sub-problems until a base case is reached. The main types of recursion are direct, indirect, and tail recursion. Recursion can make code more elegant but uses more memory than iteration.
This document provides an introduction to Python programming through a series of lectures. It begins with defining Python, what it can be used for, and why it is a popular language. It then covers Python syntax compared to other languages, getting started with Python including installation and running a simple program. The document continues with topics like Python variables, data types, strings, numbers, operators, and lists. It provides examples and explanations of core Python concepts to help newcomers learn the essentials of the language.
PHP was created by Rasmus Lerdorf in 1994 to track visitors on his personal website. It later became a popular open source scripting language embedded in HTML documents. PHP code is interpreted on the server and outputs HTML and client-side code to the browser. It supports both procedural and object-oriented programming and has a large standard library of functions.
The document discusses comments, identifiers, and keywords in Python. It provides examples of single-line and docstring comments in Python. It describes the rules for valid Python identifiers, including that they can start with letters or underscores and contain letters, numbers, and underscores. The document lists some Python keywords and notes that keywords cannot be used as identifiers since they have special meanings in the language.
First in the series of slides for python programming, covering topics like programming language, python programming constructs, loops and control statements.
Python is a general-purpose, high-level programming language that can be used for web development, software development, data analysis, and more. It was created in the 1980s by Guido van Rossum. The document discusses why Python is useful, including that it is interpreted, dynamically typed, strongly typed, requires less code than other languages, and works on many platforms. Basic Python syntax and data types are also covered.
This document introduces a Python workbook for beginners. It covers 7 chapters that teach Python fundamentals like data types, variables, operators, conditional statements, and loops. The chapters also include quizzes to test the reader's understanding. The conclusion encourages the reader to take a paid Python course for more practical learning experiences to advance their skills.
Python is a powerful and widely used general purpose programming language. It has a simple syntax similar to the English language and allows developers to write programs with fewer lines of code compared to other languages. Python supports key data types like numbers, strings, lists, tuples, dictionaries, sets and Boolean values. It also supports common operators for arithmetic, comparison, assignment, logical, identity, membership and bitwise operations. Some key advantages of Python include being interpreted, having dynamic typing and readability due to indentation.
Mastering Python : 100+ Solved and Commented Exercises to Accelerate Your Lea...Lucky Gods
Ready to Unleash Your Python Power?
Tired of coding in the dark? Feeling lost in a sea of syntax errors? Well, ditch the frustration and dive headfirst into Python mastery! This book is your ultimate passport to programming paradise, packed with 100+ solved and commented exercises that'll turn you from coding rookie to confident Python pro in no time!
Imagine:
Cracking the code like a ninja: Demystifying variables, functions, loops, and more!
Conquering challenges with ease: Solving real-world problems with your newfound Python skills!
Leveling up your game: Mastering advanced concepts like data analysis and machine learning!
Sharing your Python prowess: Dazzling everyone with your coding superpowers!
This book is your roadmap to Python success:
Spark your coding curiosity: Ignite your passion for programming with engaging explanations and real-world examples.
Master the fundamentals: Build a solid foundation in Python syntax, data types, and control flow.
Practice makes perfect: Tackle 100+ challenges of varying difficulty, with clear explanations for every step.
Level up your skills: Dive deeper into object-oriented programming, data analysis, and beyond!
So, what are you waiting for? Grab this book, unlock the power of Python, and watch your coding dreams come true!
This document provides an overview and introduction to learning Python. It discusses Python programming concepts like data science, machine learning, data visualizations, and web development. It also outlines benefits of Python like job opportunities, large community, being cross-platform, and free. The document then describes the Anaconda distribution tool for scientific computing projects. It introduces the Spyder IDE and its features like source code area, IPython console, and variable/file explorers. Basic Python syntax is covered such as printing, strings, variables, and conditionals. Finally, it discusses lists, loops, and common list methods.
Python (Data Analysis) cleaning and visualizeIruolagbePius
This document provides an overview of Python programming language. It discusses Python features, uses, variables, data types, operators, decision making statements, and loops. Specifically, it covers:
- Python features like being easy to learn and read, having an interactive mode, and being portable.
- Python variables, naming rules, and basic data types like numbers, strings, booleans.
- Operators for arithmetic, comparison, assignment, and logic.
- Conditional statements like if, elif, else for decision making.
- Looping structures like while and for loops, with examples of using break, continue, else, range().
- How to write comments, take user input, and
Python dictionaries allow storing data as key-value pairs. Keys must be unique and can only contain one component, while values can be of any type including integers, lists, and tuples. Dictionaries are created using curly brackets or the dict() function. Values can be accessed and modified using their keys, and elements deleted with the del keyword. Dictionary methods like cmp(), len(), and items() allow comparing dictionaries, getting the length, and accessing items as tuples. Errors occur due to syntax or logical issues, and exceptions should be handled using try/except blocks to catch errors and continue execution.
This document provides information about various Python data types including text, numeric, sequence, mapping, set, boolean, and binary types. It discusses how variables can store different data types in Python. It also covers numeric types like integers, floats, and complexes. Strings are described as arrays of characters that can be indexed and sliced. Boolean values and operators like or, and, and not are explained. The document contrasts mutable and immutable objects in Python.
This document provides an overview of Python basics training. It covers installing Python, running Python code through various methods like the command line, IDLE, and Jupyter notebooks. It also discusses Python syntax, variables, data types, operators, conditional statements, and loops. Key Python data types include integers, floats, strings, lists, and dictionaries. The document is intended as an introduction to Python for beginners.
The document discusses PHP concepts including:
- PHP is a server-side scripting language used for web development and can be used as an alternative to Microsoft ASP.
- XAMPP is an open-source cross-platform web server bundle that can be used to test PHP scripts locally.
- PHP has different data types including strings, integers, floats, booleans, and arrays.
- PHP includes various operators, conditional statements like if/else, and loops like while and foreach to control program flow.
- Functions allow code reusability and modularity in PHP programs. Built-in and user-defined functions are discussed.
- Arrays are a special variable type that can hold multiple values,
The document discusses comparison, logical, and bitwise operators in Python. It begins by defining comparison operators like >, <, ==, which return True or False based on relations between operands. Logical operators like and, or, not allow combining conditions and return True/False. Bitwise operators like &, |, ^ manipulate single bits and perform operations like conjunction, disjunction, exclusive or on a bit level. The document provides truth tables and examples to explain the usage and precedence of these different operator types in Python.
The document discusses dictionaries in Python. It explains that dictionaries are a mapping type that store key-value pairs, with keys being immutable types and values being any type. It provides examples of creating, accessing, updating, removing entries from, and accessing properties of dictionaries. It also covers functions, control flow statements like if/else and while loops, and list comprehensions.
python programming language Python is a high-level, interpreted, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. INTRODUCTION
HISTORY
USES OF PYTHON
FEATURES OF PYTHON
PYTHON PROJECT FOR BEGINNERS
PYTHON PROGRAM
KEY CHANGES IN PYTHON
BASIC SYNTAX
VARIABLE
NUMBERS
STANDARD TYPE HIERARCHY
STRING
CONDITIONALS
FOR LOOP
FUNCTION
KEYWORDS
WHY PYTHON ?
DIFFERENTIATE
EXAMPLES
This document is an introductory tutorial on PHP web development. It begins by explaining what PHP is and its role in server-side programming. It then covers PHP basics like variables, arrays, functions, loops and conditional statements. Examples are provided for each concept to demonstrate how it works in PHP code. The document concludes by providing a full program example that combines these elements to check names in an array against a condition using a loop and function.
Functions allow programmers to organize and reuse code. They take in parameters and return values. Parameters act as variables that represent the information passed into a function. Arguments are the actual values passed into the function call. Functions can have default parameter values. Functions can return values using the return statement. Python passes arguments by reference, so changes made to parameters inside functions will persist outside the function as well. Functions can also take in arbitrary or keyword arguments. Recursion is when a function calls itself within its own definition. It breaks problems down into sub-problems until a base case is reached. The main types of recursion are direct, indirect, and tail recursion. Recursion can make code more elegant but uses more memory than iteration.
This document provides an introduction to Python programming through a series of lectures. It begins with defining Python, what it can be used for, and why it is a popular language. It then covers Python syntax compared to other languages, getting started with Python including installation and running a simple program. The document continues with topics like Python variables, data types, strings, numbers, operators, and lists. It provides examples and explanations of core Python concepts to help newcomers learn the essentials of the language.
PHP was created by Rasmus Lerdorf in 1994 to track visitors on his personal website. It later became a popular open source scripting language embedded in HTML documents. PHP code is interpreted on the server and outputs HTML and client-side code to the browser. It supports both procedural and object-oriented programming and has a large standard library of functions.
The document discusses comments, identifiers, and keywords in Python. It provides examples of single-line and docstring comments in Python. It describes the rules for valid Python identifiers, including that they can start with letters or underscores and contain letters, numbers, and underscores. The document lists some Python keywords and notes that keywords cannot be used as identifiers since they have special meanings in the language.
First in the series of slides for python programming, covering topics like programming language, python programming constructs, loops and control statements.
Python is a general-purpose, high-level programming language that can be used for web development, software development, data analysis, and more. It was created in the 1980s by Guido van Rossum. The document discusses why Python is useful, including that it is interpreted, dynamically typed, strongly typed, requires less code than other languages, and works on many platforms. Basic Python syntax and data types are also covered.
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
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.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
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.)
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
1. Each scripting language has specific words or keywords with specific definitions and usage
guidelines. Python is no exception. The fundamental building blocks of any Python program
are Python keywords.
In this tutorial, you will get a basic overview of all Python keywords and a detailed
discussion of some important keywords that are often used.
Introduction to Python Keywords
Python keywords are unique reserved words with specific meanings and functions that we
can apply only to those functions. You will never need to import keywords into your program
because they are always there.
Python's built-in methods and classes are not the same as keywords. Built-in methods and
classes are still present; however, their use is not limited to keywords
Assigning a specific meaning to Python keywords means that we cannot use them for other
purposes in our code. You will get a SyntaxError if you try to do the same. If you try to
assign something to a built-in method or type, you won't get a SyntaxError; However, it's still
not the smartest idea.
The latest version of Python, namely Python 3.8, contains thirty-five keywords. Here we have
shown a complete list of Python keywords for the reader's reference.
Wrong, expect another import pass
Not a single pause except a restart
Real class is finally back
and continue testing Lambda
as the definition of nonlocal while
the state of the world doesn't use it
elif asynchronous if or exit
The above keywords may change in different versions of Python. Some additions may be
added and others may be removed. By writing the following statement in the coding window,
you can get a set of keywords in the version you are working on at any time.
Coded
# Python program to demonstrate is keyword()
# Import keyword library with lists
import keyword
# display the full list using "kwlist()".
print("Keyword set in this version:")
print (keyword. twist)
Exit:
2. Keyword defined in this version:
['False', 'None', 'True', 'and', 'as', 'assert', 'asynchronous', 'wait', 'abort', 'class', 'continue', 'def', '
del', 'elif', 'else', 'except', 'finally', 'for', 'from', 'global', 'if', 'import', 'in', 'is', 'lambda',
"nonlocal", "not", "or", "pass", "retry", "return", "try", "during", "with", "exit"]
By calling help() you can get a list of currently suggested keywords:
Coded:
help("keywords")
How to identify Python keywords
The Python keyword collection has evolved as new versions have been released. The wait
and async keywords, for example, were only introduced with Python 3.7. Additionally, in
Python 2.7, print and exec are keywords; However, in Python 3+ they have been converted to
built-in methods and are no longer part of the keyword set. In the following paragraphs, we
will introduce several methods to determine whether or not a particular word is a keyword in
Python.
Write code in an IDE with syntax highlighting
There are many excellent Python IDEs available. They all highlight keywords to distinguish
them from other terms in the code. This feature will help you immediately identify Python
keywords while coding so that you don't use them incorrectly.
3. Checking keywords using a script in the REPL
There are several ways to discover acceptable Python keywords, as well as more information
about them in Python REPL.
Find syntax error
Finally, if you get a SyntaxError when you try to allocate memory, call a method with it, or
do anything else with it, and it's not allowed, it's probably a word -key. It's a little harder to
see, but it still allows Python to tell you if you're using a keyword incorrectly.
Python Keywords and Their Uses:
The following sections categorize Python keywords into titles based on how often they are
used. For example, the first category includes all keywords used as values, while the next
group includes keywords used as operators. These classifications will help you understand
how keywords are used and help you organize Python's vast collection of keywords.
Some of the terms mentioned in the following segment may not be familiar to you. They are
explained here and you should understand what they mean before continuing:
The Boolean estimate of a variable is called veracity. Value truth indicates whether the value
of a variable is true or false.
In the Boolean paradigm, truth refers to any variable whose value is true. Pass the element as
input to bool() to check if it is true. If True is returned, the item's value is true. Examples of
real values are strings and lists that are not empty, non-zero numbers, and many other objects.
False refers to any element of a Boolean expression that evaluates to false. Pass an element as
input to bool() to check if it is false. If False is returned, the element value is false. Examples
of false values are " ", 0, { }, and [ ].
Keyword values: True, False, None.
This example uses three Python keywords as values. These are singular values that can be
reused endlessly and which correspond to the same entity each time. These meanings are
likely to be encountered and used frequently.
Keywords true and false:
These keywords are typed in lowercase letters in common computer languages (true and
false); however, in Python, they are capitalized every time. In a Python script, the True
Python keyword represents a true logical state. False is a keyword equivalent to True, except
that it has a negative Boolean status of false.
True and False are keywords that can be assigned to variables or parameters and compared
directly.
Coded
4. print(4==4)
print(6>9)
print (True or False)
print(99)
print (True and False)
Exit:
TRUE
LIE
TRUE
TRUE
LIE
LIE
Since the first, third, and fourth statements are true, the interpreter assigns the value “True” to
these statements and “False” to the other statements. True and False in Python are equal to 1
and 0. We can use an illustration to support this statement:
Coded
print(True==3)
print(False==0)
print (True + True + True)
Exit:
LIE
TRUE
3
Keyword “No”
None is a Python keyword meaning "nothing". None are referred to in various computer
languages as null, null, or undefined.
If a function does not have a return clause, it will produce None as its default output:
Coded
print (No == 0)
print(No == """)
print (No == False)
A = no
B=n
print(A==B)
Exit:
5. LIE
LIE
LIE
TRUE
If no_return_function returns nothing, it will simply return None. None are provided by
functions that do not match the expression returned in the program flow. Consider the
following scenario:
Coded
protection no_return_function():
number1 = 10
number2 = 20
addition = number1 + number2
number = no_return_function()
print (number)
None
This program has a with_return function that performs several operations and contains a
return expression. Therefore, if we print a number, we get None, which is the default when
there is no return statement. Here is an example showing this:
Coded
def with_return(num):
if num% 4 == 0:
return False
number = with_return(67)
print (number)
Exit:
None
Keyword operators: and or not, in, is
Several Python keywords are used as operators to perform mathematical operations. In many
other computer languages, these operators are represented by symbols such as &, | AND!
These are all keyword operations in Python:
Mathematical operations Operations in other languages Python keyword
E, ⊥ && e
6. OR, ⊦ || OR
NO, ¬! NO
CONTAINS, ∈ inches
IDENTITY === yes
The authors created Python programming with clarity in mind. As a result, many operators in
other computer languages that use symbols in Python are English words called keywords.
Keyword and:
The Python keyword determines whether the left and right operands are true or false. The
result will be true if both components are true. If one of them is false, the result will also be
false:
The truth table for e
X Y X and Y
True True True
False True False
True False False
Lie, lie, lie
AND
It should be noted that operator results are not always true or false. This is due to the
particular behavior of e. Instead of processing the input to produce the corresponding
Boolean values, it simply returns whether it is false or true. The output of the a and
expression can be used with an if conditional clause or passed to bool() to produce an obvious
True or False answer.
Keyword or
The or keyword in Python is used to check if at least one of the inputs is true. If the first
argument is true, the operation returns it; otherwise, the second argument is returned:
OR
Like the and keyword, the or keyword does not modify its entries to corresponding Boolean
values. Instead, results are determined by whether they are true or false.
The truth table for o
X Y X or Y
True True True
True False True
False True True
Lie, lie, lie
Keyword “no”
The not keyword in Python is used to get the opposite Boolean value of a variable:
7. The not keyword is used to modify the logical interpretation or produce conditions or other
logical equations. No, unlike, and, and or, specifies a specific logical state, True or False, and
therefore returns the opposite value.
The truth table for no
X is not
Right wrong
False truth
Coded
Lies and truth
Lies or truth
not true
Exit:
LIE
TRUE
LIE
Keyword
The keyword in Python is a robust constraint check, also known as the membership operator.
If you give it an element to search for and a container or series to search for, it will return
True or False, depending on whether the specified element was in that container:
V:
Testing for a specific character in a string is a good example of using the keyword in:
Coded:
container = "Javapoint"
print("p" in container)
print("P" in container)
Exit:
TRUE
LIE
Lists, dictionaries, tuples, strings, or any data type that uses the __contains__() method, or we
can iterate over them, will work with the in keyword.
Keyword
8. In Python, it is used to verify the identity of objects. The == operator is used to determine the
identity of two arguments. It also determines whether the two arguments refer to a single
object.
When the objects are the same, returns True; otherwise, False is returned.
Coded
print(The truth is the truth)
print (False equals True)
print (No - not No)
print((9 + 5) = (7 * 2))
Exit:
TRUE
LIE
LIE
TRUE
9. True, False, and None are the same thing in Python because there is only one version.
Coded:
print([]==[])
print([] is [])
print({}=={})
print({} is {})
Exit:
TRUE
LIE
TRUE
LIE
An empty dictionary or list is similar to another empty dictionary. However, they are not
identical objects because they are stored in memory independently. Indeed, the list and the
dictionary are modifiable.
Coded:
print(''=='')
print(''is''')
Exit:
TRUE
TRUE
Strings and tuples, unlike lists and dictionaries, are immutable. Therefore, even two identical
strings or tuples are identical. Both belong to a single memory region.
Non-local Keyword:
Using non-local keywords is very similar to using global keywords. The nonlocal keyword is
intended to indicate that a variable in a function is inside the function, that is, a nested
function is simply not local to it, implying that it is in the external function. We need to
define a nonlocal parameter using Nonlocal if we ever need to change its value in a nested
function. Otherwise, the nested function creates a local variable using this header. The
following example will help us clarify this.
Coded:
protect the_outer_function():
variable = 10
protect the_inner_function():
10. non-local variable
variable = 14
print("Value inside internal function:", var)
the_internal_function()
print("Value inside external function:", var)
the_external_function()
Exit:
The value inside the internal function: 14
The value inside the external function: 14
In this case, the_inner_function() is placed inside the_outer_function.
The outer_function has a variable called var. As you may have noticed, Var is not a global
variable. Therefore, if we want to modify it in the_inner_function(), we need to declare it
using non-local.
As a result, the variable was updated in the nested function the_inner_function, as evidenced
by the results. Here's what happens if you don't use the nonlocal keyword:
Coded:
protect the_outer_function():
variable = 10
protect the_inner_function():
variable = 14
print("Value inside internal function:", var)
the_internal_function()
print("Value inside external function:", var)
the_external_function()
Exit:
The value inside the internal function: 14
The value inside the external function: 10
Iteration Keywords: for, while, Break, continue.
The iterative process and loops are important fundamentals of programming. There are
several keywords for creating and using loops in Python. They will be used and seen in
almost every Python program. Knowing how to use them correctly can help you become a
better Python developer.
11. Keyword:
The for loop is by far the most popular loop in Python. It is created by combining two Python
keywords. They are for and for, as explained above.
While Keyword:
The while loop in Python uses the term while and works similarly to while loops in other
computer languages. The block after the while clause will be repeated repeatedly until the
condition following the while keyword is false.
Keyword Skipping:
If you want to quickly break out of a loop, use the Break keyword. We can use this keyword
in for and while loops.
Keyword “Continue”
You can use Python's continue keyword if you want to move to the next iteration of the loop.
The continue keyword, as in many other computer languages, allows you to stop the
execution of the current iteration of a loop and move on to the next one.
12. Coded:
# Program to show keyword usage for, while, break, continue
for me in the range (15):
print(i + 4, end = """)
# break the loop when i = 9
if I == 9:
to break
Press()
# cycle from 1 to 15
i = 0 # initial condition
while I am < 15 years old:
# When i is 9, the loop will move to the next iteration using continue. It will not print
if I == 9:
i+= 3
keep on going
Moreover:
# when i is not equal to 9, add 2 and print the value
print(i + 2, end = """)
I += 1
Exit:
4 5 6 7 8 9 10 11 12 13
2 3 4 5 6 7 8 9 10 14 15 16
Exception handling keywords: try, except, raise, finally, and assert
Try: This keyword is intended for exception handling and is used in conjunction with the
"exception" keyword to handle problems in a program. If an error occurs, the program inside
the "try" block is checked, but the code in that block is not executed.
Except: As noted above, this works in conjunction with exception handling.
finally: Regardless of the result of the "test" section, the "finally" field will be implemented
every time.
raise - The raise keyword can be used to specifically raise an exception.
Statement: This method is used for troubleshooting. Often used to verify code correctness.
Nothing happens if the expression is interpreted as true; however, if it is false, an
"AssertionError" message is generated. You can also print the result with an error followed
by a comma.
Coded:
13. # initialization of numbers
variable1 = 4
variable2 = 0
# The exception was thrown in the try section.
Attempt:
d = var1 // var2 # This will cause a divide by zero exception.
print(s)
# This section will handle the exception thrown in the try block
except ZeroDivisionError:
print("Cannot divide by zero")
Finally:
# Whether an exception occurred or not, this block will be executed every time
print("It's finally inside the block")
# using the assert keyword we will check if var2 is equal to 0
print("The value of var1/var2 is:")
Assert var2 != 0, "Error dividing by 0"
print (var1 / var2)
Exit:
You can't divide by zero
It's finally inside the block
var1/var2 value:
-------------------------------------------------- -------------------------
AssertionError Traceback (most recent call is last)
Enter in [44], in ()
15 # Using the Assert keyword we will check if var2 is equal to 0
16 print("Value var1/var2:")
---> 17 Assert var2 != 0, “Division by 0 error”
18 seals (var1/var2)
AssertionError: division by 0 error
Keyword “pass”
In Python, a null clause is called a pass. It serves as a substitute for something else. When it
starts, nothing happens.
Let's say we have a feature that hasn't been coded yet, but we want to build it long-term. If we
write it in the middle of the code,
Coded:
def pass_function(arguments):
Exit:
pass_protection function (arguments):
14. IndentationError:
Indented block expected after function definition on line 1.
as shown, an IndentationError will be raised. Instead, we use the pass command to create an
empty container.
Coded:
def pass_function(arguments):
to go up
We can also use the pass keyword to create an empty class.
Coded:
class passed_class:
to go up
returns the keyword
The return expression is used to exit the function and generate a result.
The None keyword is returned by default unless a value is specifically returned. The
following example demonstrates this.
Coded:
protection func_with_return():
variable = 13
return var
def func_with_no_return():
variable = 10
print(function_with_return())
print(function_with_no_return())
Exit:
13
None
Keyword of
The del keyword is used to remove any reference to an object. In Python, each entity is an
object. We can use the del command to remove a reference to a variable.
Coded:
15. var1 = var2 = 5
of var1
print(var2)
print (var1)
Exit:
5
-------------------------------------------------- -------------------------
NameError Traceback (most recent call is last)
Enter in [42], in ()
2 of variable 1
3 seals (var2)
----> 4 prints (var1)
NameError: Name "var1" is not defined
We see that the reference to the variable var1 has been deleted. Result: it is no longer
recognized. However, var2 still exists.
You can also delete entries from a collection such as a list or a dictionary using del:
Coded
list_ = ['A', 'B', 'C']
delete list_[2]
print(list_)
Exit:
['A B']