Python And Flask Demonstrations Practice Course

Install Anaconda on Windows. Select Python 3.6 64-bit, agree to the license, choose just me, set the destination folder, complete installation, and explore running Python programs in next videos.

Explore Python overview as a high-level, object-oriented language with easy syntax, and learn immediate mode, script mode, and development environments like Jupiter Lab.

Explore defining constants and variables in Python, using uppercase names for constants, dynamic typing, and reassignment. Learn multiple assignments and printing to observe types and values.

Define a complex number class with a constructor, real and imaginary parts, and a display method to print them; illustrate creating objects and deleting attributes.

Explore Python arrays and lists, including indexing, negative indexing, and length, then learn to append, remove, and modify elements, and perform concatenation and slicing.

Explore Python keywords and identifiers with hands-on demonstrations. Learn booleans and none, control flow (if, elif, else; for, while), and topics like functions (def, lambda, yield), classes, and error handling.

Explore how Python tuples are immutable and differ from lists, and learn to create, index, slice, and use tuples as dictionary keys.

Explore Python sets as unordered, mutable containers of unique elements, learn to add, remove, and update items, and perform union, intersection, difference, and symmetric difference, plus frozenset concepts.

Learn Python module import techniques, including aliasing with import as. See how to use from math import pi and star imports to print pi.

Learn Python directory and file management by working with current working directory, changing directories, listing contents, and creating, renaming, or removing folders and files.

Explore how Python dictionaries store key-value pairs, create and update them, handle missing keys with get vs direct access, and perform deletion, iteration, and comprehension.

Define strings in Python with single, double, and triple quotes, including multiline strings. Explore indexing, slicing, immutability, concatenation, formatting, escapes, and methods like find, replace, lower, and upper.

Explore implicit and explicit type conversion in Python, including int to float arithmetic, string to int casting, and the TypeError raised when adding an integer and a string.

Master Python numbers by exploring integers, floats, and complex types, testing with is instance checks, and using binary, hexadecimal, and octal representations along with decimal, fractions, math, and random modules.

Explains python namespace and scope by demonstrating id to view object memory addresses and showing how the global keyword interacts with nested outer and inner functions across scopes.

Explore Python global, local, and nonlocal variables through practical examples that show scope, the global keyword, and how nonlocal updates inner and outer bindings.

Demonstrates how the Python global keyword modifies a global variable, showing that updating X inside a nested function affects the global X (25 outside, 20 inside).

Explore how Python iterators operate as objects that yield data one at a time, implementing __iter__ and __next__, guiding loops, generators, and iterators, including a powers-of-two example and stop iteration.

Explore Python iterations using for loops, including iterating lists with indentation, using range with step increments, and applying nested for loops and else blocks to control execution and print results.

Explore Python inheritance and polymorphism in object oriented programming through base and subclass examples, constructor calls, and methods like can fly and can swim with penguin and parrot.

Explore Python's multiple inheritance by building a derived class that inherits from three base classes, showcasing inherited and own methods and their print outputs.

Explore how Python functions handle input parameters, including default values, keyword arguments, and variable argument lists with *args, and how returning or printing results works.

Explore Python functions by defining with def, passing parameters, and using indentation; distinguish user defined versus library or built-in functions, and practice return values, prints, and division by zero check.

Demonstrates break to exit an infinite while loop when a random guess matches the current number, generating 1 to 19 (20 exclusive) and printing guesses until a match.

Learn to use the continue statement in a for loop (range(1, 20)) to skip odd numbers and print only even values.

Explore Python errors and exceptions using try, except, and finally blocks, handle value conversion errors, division by zero, and raising or catching type errors.

Explore Python error handling with a try block and multiple except blocks, covering division by zero, data type errors, and undefined variables, and finally blocks.

Learn how to implement user defined exceptions in Python with a voter’s eligibility example, raising when age is under 18 and handling try, except, else, and finally blocks.

Explore Python object oriented programming by defining classes and objects, using constructors and instance variables, and demonstrating inheritance, encapsulation, and public versus private members with methods.

Explore Python nested dictionary implementation by defining and accessing nested key-value pairs, adding and deleting entries, and iterating with for loops to print results.

Explore operator overloading in python by implementing a two-dimensional point class with x and y, defining __str__, __add__, __sub__, and __lt__ to support printing, addition, subtraction, and magnitude comparisons.

Explore Python statements and comments, including single-line hash comments, triple-quoted blocks, and implicit and explicit continuations, with indentation defining blocks and semicolon-separated statements.

Explain how the Python pass statement serves as a placeholder to add future functionality within a for construct, producing no output and leaving room for later code.

Discover how Python generators create iterators by producing values one at a time, automatically handling stop iteration and internal state with practical examples.

Explore Python decorators and metaprogramming by defining a decorator that wraps a simple function, prints decoration messages, and handles division by zero in a demo.

This lecture demonstrates using while loops in Python, including while-else structures, to print patterns with blanks and stars and to build a dressing-table style pattern, with practice problems.

Master the use of if, elif, and else in Python, with proper indentation and colon-driven blocks; explore nested conditionals, input handling, and simple age-based and numeric classifications.

Learn to implement a two-dimensional matrix in Python using nested lists, create dynamic matrices, and perform indexing, printing, and element updates while exploring memory reference behavior and shallow copies.

Learn to search, match, and replace with Python regular expressions, using wildcards, character classes, and backslash handling; apply to emails, phone numbers, and data formatting.

Master Python list comprehension through practical examples: convert a string with a for loop and a lambda, filter even numbers, and transpose a matrix.

Learn recursion in Python by implementing a factorial function named fact, using a base case n <= 1 and recursive calls down to 1, demonstrated with n = 5.

Learn to use the print function and input prompts, handle string to number typecasting for arithmetic, and explore string formatting and math.pow usage.

Demonstrate shallow versus deep copy in Python with a practical example using the copy module. Learn how the equal operator creates shared references, while deep copy recursively copies nested objects.

Learn how Python lambda functions act as anonymous definitions, and see how map and filter double inputs and select even numbers from lists.

Learn how Python assertions validate conditions with boolean expressions and raise an assertion error when false. See how non-empty input is required to compute averages, with optional error messages.

Explore Python's property decorator to manage a Celsius temperature with a getter and setter, including validation against minus 273 and demonstrating how property simplifies attribute access.