<h1 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Lab Details</h1><ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">In this lab we will learn about keywords and Identifiers in Python on JupyterLab Notebook.</li><li dir="ltr">Duration:&nbsp;60 minutes.</li></ol><h1 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Introduction</h1><h2 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">What are Keywords in Python?</h2>Keywords in Python are reserved words that have special meanings and purposes within the language. These words cannot be used as identifiers (variable names, function names, etc.) because they are already predefined by Python for specific tasks. Python has a small set of keywords that are fundamental to the language's syntax and functionality. Here is a list of Python keywords:<ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">False: Represents the Boolean value False.</li><li dir="ltr">None: Represents a null or undefined value.</li><li dir="ltr">True: Represents the Boolean value True.</li><li dir="ltr">and: Used for logical conjunction (e.g.,&nbsp;x and y).</li><li dir="ltr">as: Used for creating an alias while importing modules (e.g.,&nbsp;import module_name as alias).</li><li dir="ltr">assert: Used for debugging purposes to check if a condition is True (e.g.,&nbsp;assert condition).</li><li dir="ltr">async: Declares a function as asynchronous (used with&nbsp;await&nbsp;in asynchronous programming).</li><li dir="ltr">await: Used to pause execution until the awaited coroutine is complete (used with&nbsp;async&nbsp;in asynchronous programming).</li><li dir="ltr">break: Exits the current loop (e.g.,&nbsp;while&nbsp;or&nbsp;for).</li><li dir="ltr">class: Defines a class.</li><li dir="ltr">continue: Skips the rest of the current iteration of a loop and proceeds to the next one.</li><li dir="ltr">def: Defines a function.</li><li dir="ltr">del: Deletes an object or an element from a collection.</li><li dir="ltr">elif: Used in conditional statements as a short form of "else if" (e.g.,&nbsp;if...elif...else).</li><li dir="ltr">else: Specifies a block of code to be executed when a conditional expression is False.</li><li dir="ltr">except: Catches exceptions during exception handling.</li><li dir="ltr">finally: Defines a block of code that will be executed regardless of whether an exception is raised or not.</li><li dir="ltr">for: Initiates a for loop.</li><li dir="ltr">from: Used for importing specific attributes or functions from a module (e.g.,&nbsp;from module_name import attribute).</li><li dir="ltr">global: Declares a global variable inside a function.</li><li dir="ltr">if: Begins a conditional statement.</li><li dir="ltr">import: Imports modules or packages.</li><li dir="ltr">in: Checks for membership in a sequence (e.g.,&nbsp;element in sequence).</li><li dir="ltr">is: Checks if two objects are the same.</li><li dir="ltr">lambda: Defines an anonymous (inline) function.</li><li dir="ltr">nonlocal: Declares a variable in an enclosing (but non-global) scope.</li><li dir="ltr">not: Used for logical negation (e.g.,&nbsp;not condition).</li><li dir="ltr">or: Used for logical disjunction (e.g.,&nbsp;x or y).</li><li dir="ltr">pass: Represents a null operation; does nothing.</li><li dir="ltr">raise: Raises an exception.</li><li dir="ltr">return: Returns a value from a function.</li><li dir="ltr">try: Starts exception handling.</li><li dir="ltr">while: Initiates a while loop.</li><li dir="ltr">with: Simplifies resource management (e.g., file handling) using the "context manager" protocol.</li><li dir="ltr">yield: Used in generator functions to yield a value.</li></ol><h2 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">What are Identifiers in Python?</h2>Identifiers in Python are user-defined names used to identify variables, functions, classes, modules, or other objects in the code. Python has certain rules and conventions for naming identifiers:<ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">An identifier must start with a letter (a-z, A-Z) or an underscore (_).</li><li dir="ltr">The subsequent characters can be letters, numbers (0-9), or underscores.</li><li dir="ltr">Python is case-sensitive, so&nbsp;myVar&nbsp;and&nbsp;myvar&nbsp;are treated as different identifiers.</li><li dir="ltr">Identifiers should not be a Python keyword.</li></ol><h2 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Naming Conventions for Identifiers:</h2>Python developers typically follow naming conventions to make their code more readable and maintainable:<ul style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">Variable names: Use lowercase letters with words separated by underscores (e.g.,&nbsp;my_variable,&nbsp;count_of_items).</li><li dir="ltr">Function names: Use lowercase letters with words separated by underscores (e.g.,&nbsp;calculate_mean,&nbsp;process_data).</li><li dir="ltr">Class names: Use CamelCase (also known as CapWords) with the first letter of each word capitalized (e.g.,&nbsp;MyClass,&nbsp;PersonInfo).</li><li dir="ltr">Module names: Use lowercase letters with words separated by underscores (e.g.,&nbsp;my_module,&nbsp;data_processing).</li><li dir="ltr">Constants: Use uppercase letters with words separated by underscores (e.g.,&nbsp;PI,&nbsp;MAX_VALUE).</li></ul>Remember that following consistent naming conventions and choosing descriptive identifiers enhances code readability and collaboration with others.<h1 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Task Details</h1><ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">Sign in to JupyterLab Notebook</li><li dir="ltr">Explore Keywords in Python</li><li dir="ltr">Explore Identifiers in Python</li><li dir="ltr">Download the Notebook</li></ol>

<h1 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Lab Details</h1><ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">In this lab we will learn about Comments, Indentation and Statements in Python on JupyterLab Notebook.</li><li dir="ltr">Duration:&nbsp;60 minutes.</li></ol><h1 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Introduction</h1><h2 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">What are Comments in Python?</h2>In Python, comments are annotations within the code that are ignored by the interpreter during execution. They are used to add explanatory notes or remarks to make the code more understandable for developers. Comments are not executed, so they don't affect the program's functionality. There are two main types of comments: single-line comments and multi-line comments.<ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">Single-line comments: These comments are used for brief explanations on a single line of code. You create a single-line comment using the hash symbol #. Anything following the # on that line is considered a comment.</li><li dir="ltr">Multi-line comments: In Python, there is no specific syntax for multi-line comments like in some other programming languages. However, you can use triple double-quotes """ or triple single-quotes ''' to create a multi-line string, which is often used as a workaround for multi-line comments.</li></ol><h2 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">What is Indentation in Python?</h2>Indentation in Python refers to the spacing at the beginning of a line of code. Unlike many other programming languages that use braces {} or keywords like begin and end to define blocks of code, Python uses indentation to indicate the grouping of statements within a block.Indentation is a fundamental part of Python syntax and plays a crucial role in defining the structure of the code. It is used to represent the scope and hierarchy of statements within control structures, functions, classes, and other code blocks.<h2 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">What are Statements in Python?</h2>In Python, a statement is a single line of code that performs a specific action. Statements are the building blocks of a Python program, and each statement typically represents a complete instruction for the computer to execute. Here are some common types of statements in Python:<ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">Assignment Statements</li><li dir="ltr">Print Statements</li><li dir="ltr">Conditional Statements</li><li dir="ltr">Loop Statements</li><li dir="ltr">Functional Call Statements</li></ol><h1 dir="ltr" style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Task Details</h1><ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">Sign in to JupyterLab Notebook</li><li dir="ltr">Explore Comments in Python</li><li dir="ltr">Explore Indentation in Python</li><li dir="ltr">Explore Statements in Python</li><li dir="ltr">Download the Notebook</li></ol><h1 style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);">Launching Lab Environment</h1><ol style="color: rgb(51, 51, 51); background-color: rgb(249, 249, 249);"><li dir="ltr">To launch the lab environment, click on the&nbsp;Start Lab&nbsp;button.</li><li dir="ltr">Please wait until the cloud environment is provisioned.</li><li dir="ltr">Once the lab is started, you will be provided with a&nbsp;username&nbsp;and&nbsp;password.&nbsp;</li></ol><div style="color: rgb(51, 51, 51); background: rgb(238, 238, 238); border: 1px solid rgb(204, 204, 204); padding: 5px 10px;">Note&nbsp;: You can only start one lab at a time.</div>

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