Python Demonstrations For Practice Course

Install Anaconda on Windows by selecting Python 3.6 64-bit, agreeing to the license, choosing just me, setting the destination folder, and ensuring about 2.5 GB of space.

Gain a Python overview as a high-level, object-oriented language with easy syntax, and master immediate, script, and IDE coding using Anaconda and Jupyter.

Explore how to define constants and variables in Python, use uppercase names for constants, demonstrate dynamic typing, reassignment, and multiple assignments, with printing examples.

define a python class for complex numbers with a constructor, self, and two instance variables real and imag, and demonstrate creating objects, displaying, adding a new attribute, and deleting attributes.

Explore Python array implementation with lists and NumPy arrays, covering creation, indexing (including negative indexes), length, appending, removing, modifying, concatenation, slicing, repetition, and multidimensional arrays.

Master Python keywords and identifiers through practical examples of booleans, conditional blocks, loops, functions, classes, and generators, including import, global, nonlocal, and error handling.

Learn how Python tuples differ from lists, highlighting immutability, dictionary key usage, and faster iteration. Explore creation, indexing, slicing, unpacking, and common tuple operations.

Explore Python sets, unordered collections of unique, immutable elements; create sets from lists, perform union, intersection, difference, and symmetric difference, and learn discard vs remove and frozen sets.

Learn to import modules in python, rename imports with aliases like import math as m, use from math import pi, and use from math import * to import all names.

Operate with Python directory and file management by getting and changing the current working directory, listing contents, creating, renaming, and removing files and folders.

Explore Python dictionaries as unordered key-value stores, learn creation, access with keys, get for safe retrieval, handle missing keys, update values, remove items, and use dictionary comprehension for squaring numbers.

Explore how Python strings work, from defining with single, double, triple quotes to indexing, slicing, and immutability, and master string formatting, escaping, and common methods.

Explore implicit and explicit type conversion in Python, showing integer and float operations, string to int conversion, and how mixing int with string raises a TypeError.

Learn Python's number types, including integers, floats, and complex, test and convert them, including binary, hex, and octal forms, plus decimals, fractions, and math and random utilities.

Explore Python namespace and scope, using id() to examine memory addresses and how global and local variables behave in nested functions. See how the global keyword updates values across scopes.

Demonstrate global, local, and nonlocal variables in Python through practical examples of scope and variable updates across functions.

Explore how the Python global keyword updates a global variable, using a nested function to modify X and show 20 becoming 25 in the global scope.

Explore Python iterators and the iterator protocol, including __iter__ and __next__, and learn to build custom iterators and handle stop iteration in this practical demonstration.

Explore Python iterations with for loops, iterating lists and ranges, printing elements, using indentation to define blocks, and nesting for loops with an else clause to signal completion.

Explore inheritance and polymorphism in Python by building base and subclass relationships, using super constructors, and invoking shared methods like can swim and can run across bird examples.

Explore Python's multiple inheritance, using base and super classes and a derived class to inherit methods and functions, with practical examples of print statements.

Explore Python function arguments, including required inputs, default arguments, arbitrary arguments (*args), and keyword arguments, and see how return values and argument order map values.

Explore Python functions, including user defined and library functions, using def, parameters, and indentation, and see function calls for addition, subtraction, multiplication, and division with a menu-driven calculator.

Demonstrate using the break statement to exit an infinite while loop when a randomly generated number matches the counter, highlighting range inclusivity and loop control.

Learn how to use the continue statement in Python to skip odd numbers in a range loop and print only even numbers.

Explore how Python handles errors and exceptions using try, except, and finally, with examples of type errors and division by zero and the role of finally.

Explore how Python try blocks work with except and finally to handle division by zero, type errors, value errors, and undefined variables, with hands-on exception demonstrations.

explore user defined exceptions in python with a voter eligibility example, raising a custom exception for ages under 18, and handling with try-except-finally blocks.

Explore object oriented programming in Python by defining classes and objects, using constructors and self, and applying inheritance and encapsulation to model behaviors like can swim and can run.

Learn how to create and manipulate nested dictionaries in Python, access inner values, add and delete entries, and iterate to print keys like name, age, and sex.

Explore Python operator overloading by building a 2d point class with x and y, implementing __str__, __add__, __sub__, and magnitude-based comparisons.

Study Python statements and comments, including hash-based single line comments and triple-quoted blocks. See how backslash and bracket continuation work, how semicolons separate statements, and how indentation defines blocks.

The pass statement acts as a placeholder in Python, allowing future functionality without producing output, and the final statement prints after the for loop completes.

Discover how python generators simplify iterators by using yield, pausing and resuming execution, and automatically handling stop iteration for efficient, one-at-a-time value delivery.

Learn how Python decorators enable metaprogramming by wrapping a simple function with a decorator, using the @ syntax, and see how behavior changes, including division by zero handling.

Learn to use while loops in Python, including while-else blocks, and to print patterns with blanks and stars through dressing table logic.

The lecture demonstrates how to use if, elif, and else blocks in Python, showing proper indentation, colon usage, and nested conditions for age-based outputs.

Demonstrates building and manipulating a Python two-dimensional matrix with nested lists, including dynamic creation with loops, initialization to zeros, indexing and printing, and shallow versus deep copy behavior.

This tutorial demonstrates how Python regular expressions locate, validate, and format strings, including emails and phone numbers, by searching, matching, and replacing patterns using wildcards, character classes, and escaping.

Learn python list comprehension with practical examples: iterating strings, mapping with lambda, filtering even numbers, and transposing a matrix. Master concise, expressive list operations for practice.

Demonstrate recursion in Python by implementing a factorial function with base case n <= 1 returning 1 and recursive step factorial(n-1). See the example with n = 5.

Explore python input and output, using print to display strings and variables, handle type casting from input to int, and format strings with placeholders, plus importing math to compute powers.

Explore shallow vs deep copy in Python through a practical demonstration using the equal operator and copy module. See how references and new objects affect lists and nested data.

Learn how to define anonymous lambda functions in Python, using map to double list items and filter to extract even numbers.

Assertions are boolean checks that ensure conditions in code; when true, the program continues, when false, it raises an assertion error, demonstrated while guarding average calculation with a nonempty list.

explore python @property to implement a private temperature attribute with a getter and setter, including validation against minus 273 and a fahrenheit conversion.