Python And Flask Framework Complete Course For Beginners

Discover Python overview, its high level, object oriented design, and easy syntax; explore immediate, script, and IDE coding modes with tools like the Python prompt, Anaconda, and Jupyter.

Learn how to install Anakonda on Windows, choose Python 3.6 64-bit, accept the license, select the destination folder, and complete the setup.

Learn how Python variables act as named memory locations with automatic initialization, without upfront declarations. Understand constants defined in capital letters, dynamic typing, and single-line multi-variable assignments.

Explore Python object-oriented concepts through a complex number class, showing class and object creation, instantiation, constructors, attributes, and methods with real and imaginary parts.

Learn how Python lists act as arrays, using methods like append, extend, insert, remove, pop, clear, index, count, sort, reverse, and copy; master indexing, slicing, concatenation, repetition, and multidimensional lists.

Explore Python file methods such as open, close, detach, fileno, seek, tell, read, readline, readlines, truncate, and writable or readable checks, with parameter-driven behavior.

Learn Python keywords and identifiers, including reserved words and naming rules. Explore booleans, control flow, functions (def, lambda, yield), classes, imports, nonlocal and global, file handling with the with keyword.

Explore Python tuples, their immutable nature, and heterogeneous data capabilities, compare them to lists, and learn indexing, slicing, concatenation, and key tuple operations like all, any, len, max, and min.

Explore Python sets: unordered, unique elements; perform union, intersection, difference, and symmetric difference; use methods like add, remove, discard, update, and explore frozen sets.

Explore how Python models and modules organize code, how packages form directories, and how importing with aliasing enables reusability of functions.

Learn to manage Python directories and files with the os module by getting the current directory, changing directories, listing contents, and creating, renaming, and removing items.

Explore how Python dictionaries store key-value pairs, retrieve values by key, and apply common methods like clear, copy, fromkeys, and get. See dictionary creation, updating, deletion, and comprehension in practice.

Learn how Python strings are sequences of characters stored as binary via ASCII and Unicode encoding, and explore defining, indexing, concatenation, formatting, escaping, and common operations.

Learn how Python handles data type conversion, including implicit and explicit type conversion, by examining int, float, and string interactions and the resulting type errors.

Explore Python number types—integers, floats, and complex numbers—using type checks and conversions, with binary, octal, and hexadecimal representations (0b, 0o, 0x prefixes) and precision handling via decimal and fractions.

Discover how Python namespaces isolate names into local and global scopes, how functions create local namespaces, and how id and global show memory addresses and access across nested scopes.

Explore how Python global, local, and nonlocal variables behave across function scopes, including nested functions, and see practical demonstrations of updating and accessing variables with global and nonlocal keywords.

Discover how the Python global keyword reads and writes variables inside and outside a function. See a practical demo where X updates from 20 to 25.

Explore how Python iterators work by implementing __iter__ and __next__ to create iterable objects and handle stop iteration. Apply concepts with practical examples like powers of two and custom iterators.

Explore Python for loops to iterate over sequences using range, including start, stop, and step, with else blocks and break control for practical traversal.

Learn how Python inheritance creates derived classes from base classes, explores single, multiple, hierarchical, multilevel, and hybrid inheritance, and demonstrates constructor calls and methods like can swim and can run.

Explore how Python implements multiple inheritance by deriving a class from several base classes, with practical demonstrations of base classes, a derived class, and integrated methods.

Explore how to define Python functions with default, keyword, and arbitrary arguments, pass optional inputs, return values, and include examples like finding max and summing arguments.

Learn how to write Python functions with def, parameters, and docstrings. Apply modular, reusable code through built-in and user-defined functions with examples like add, subtract, multiply, divide, and zero-division checks.

Master the break statement in Python to terminate loops and control flow after a loop. Explore syntax, effects on inner loops, and a practical demonstration with a random number loop.

Understand how the Python continue statement skips the rest of the loop for the current iteration and proceeds to the next one, with a range example printing only even numbers.

Learn Python errors and exceptions, including syntax and semantic errors, and use try, except, and finally to handle conditions like import error, index error, and division by zero.

Learn how Python handles exceptions with try, except, and finally blocks, built-in exceptions, and see how division by zero and value errors trigger messages and controlled program flow.

Defines a custom exception voter's eligibility by subclassing exception, uses a constructor calling super, raises when age is under 18, with try-except-else-finally blocks and non-numeric handling.

Explore how Python uses object oriented programming to model problems with classes, objects, attributes, and methods, and how inheritance, encapsulation, and polymorphism enable reusable, dry code.

Explore Python nested dictionaries, define and access inner dictionaries, add and delete entries, and iterate to print nested key values such as name, age, and gender.

Showcases Python operator overloading by implementing a two-dimensional point class with __add__ and __str__, highlighting how operators adapt to input types and compare X squared plus Y squared magnitudes.

Explore how Python uses statements and indentation to define blocks, supports line continuation, and employs # comments, triple-quoted multiline comments, and documentation strings.

Explore how the Python pass statement acts as a null operation and placeholder, distinguishing it from comments, with a practical demonstration in code.

Explore Python generators that simplify iterators by automatically handling stop iteration and internal state, with generator functions that produce one value at a time using next and __next__.

Explore Python decorators and metaprogramming by implementing and applying decorator functions that modify existing code, including the decorator syntax with @ and practical examples like simple functions and division.

Learn how Python’s while loop executes a block while a condition is true. Apply it when iterations are unknown, and explore break and while-else patterns.

Learn how to use if, elif, and else in Python with proper indentation and nested conditions. See practical examples of age-based classification and positive or negative numbers.

Explore Python matrix implementation using two-dimensional lists, create dynamic matrices with loops, initialize with zeros, and practice indexing, printing, and understanding shallow copy effects.

Explore Python regular expressions to locate, verify formats, and replace strings, using patterns, wildcards, character classes, and escaping for email and phone validation.

Learn Python list comprehension for beginners through practical examples like building lists from strings, using lambda, filtering even numbers, and transposing a matrix.

Explore recursion in Python by showing direct and indirect self-calls and a recursive factorial function with base cases, stack unwinding, and memory-time trade-offs.

Learn how to handle input and output in Python using input and print, and organize code by importing models and modules such as math for power operations.

Learn python file read and write operations: store data in non-volatile storage by opening, reading or writing in text or binary modes, then closing to free resources.

Learn Python looping techniques, from top-condition and middle-condition loops to bottom-condition and do-while style simulations, including infinite loops with while True and break control.

This lecture explains shallow copy versus deep copy in Python, using the copy module to show how assignment and copy.copy share references while copy.deepcopy creates independent nested copies.

Explore anonymous functions in python by using the lambda keyword, with examples that double numbers and filter even values. Learn how map and filter apply lambda to list items.

Explore how assertions use boolean expressions to validate conditions in Python, raising an assertion error when false and aiding debugging.

Learn how Python's @property implements a temperature attribute with a getter and setter, enforcing a minimum of -273 and enabling seamless access to Celsius and Fahrenheit conversion.

Explore Python closures: a function object that remembers values in enclosing scopes. Learn how nested functions access nonlocal variables and how to return closures with a multiplier example.