Python Fast-Track: Learn Code, Crack Interviews

Master core Python fundamentals and common interview questions, from namespace and the global interpreter lock to encapsulation, abstraction, and object oriented programming, including lists, tuples, and immutability.

Contrast list and tuple by mutability, container type, and performance: lists are mutable and versatile with insertion and slicing, while tuples are immutable, faster to retrieve, and memory efficient.

Explore how a decorator takes a function, wraps it with a wrapper, and returns the original function without altering its source, enabling structured api and backend use.

Discover Python list and dictionary comprehensions, compare their output types and syntax, and learn to build a list of odd numbers and a dictionary of squares from 1 to 10.

Explore how memory is managed in Python, including the private heap, Python memory manager, and built-in garbage collector that frees unreferenced objects. Learn how the GC module toggles automatic collection.

Compare Python generators and iterators, focusing on how generators use yield to produce values. Show iterators with iter and next, and note that every generator is an iterator.

Explore the init keyword in Python, comparing init function and init method as constructors that initialize class variables with self. Examine how the init.py file marks modules and guides imports.

Understand the difference between modules and packages in Python: a module is a file with functions and globals, while a package is a directory of modules with an init file.

Compare range and x range in Python: range returns a list with memory use and slower speed, while x range returns a generator and is faster, deprecated in Python 3.

Discover how generators create iterators that yield squared values from 1 to n using range and yield, and how to advance the generator with next to retrieve each value.

Learn built-in data types in Python and distinguish mutable from immutable objects, such as lists, sets, and dictionaries versus booleans, numbers, strings, tuples, and frozen sets.

Learn how the Python ternary operator enables an inline if-else expression, with a simple example of a discount by age, and compare it to a traditional if-else approach.

Python inheritance lets a derived class inherit properties and methods from a base class. A and B show inherited display and added show, with hierarchical and multiple inheritance.

Learn the differences between local and global variables in Python, including declaration inside vs outside functions, scope, lifetime, data sharing, and how initialization and modification behave across calls.

Master Python loop control with break, continue, and pass. Break terminates loops; continue skips the current iteration; pass acts as a null statement ignored by the interpreter.

Explain how the self keyword references the current instance in Python and accesses class variables like name and age. Demonstrate using a person class and a simple init constructor.

Explore how pickling uses the Python pickle module to serialize objects with dump and deserialize with load, and how unpickling restores objects for model saving.

Explore Python type conversion, including int, float, oct, hex, unicode point of a character, eval, and str conversions, plus default object representations for custom classes.

Explore how args let Python functions accept a varied number of arguments. Understand kwargs as a dictionary of keyword arguments and their uses.

Learn how Python opens files with the open function and read content, and use the with statement, a context manager, to auto close files and handle exceptions.

Learn how to read and write files in Python with the open function, covering r, w, a, plus variants, text and binary modes, and exclusive creation.

Explore how the Python path, an environment variable, adds directories to Python's search path so you can import modules not yet installed, including local development projects, at runtime.

Learn how Python handles exceptions using try, except, else, and finally to manage errors, execute cleanup, and ensure code runs smoothly.

Compare Python 2 and Python 3, covering print with brackets, range vs xrange, and division behavior. See how Unicode strings, simpler syntax, and library compatibility drive shift to Python 3.

Explore how pip, the Python package manager, installs, uninstalls, upgrades, and lists packages from PyPI via the command line, supports specific versions, shows package details, and uses requirements.txt.

Learn how to use f strings and the dot format method, and the legacy percentage formats in Python, with variables placed in curly braces.

Explore how abstraction hides data at the design level while encapsulation hides code and data from external access, with Java interfaces, abstract classes, and Python public and private modifiers.

Explore how Python handles multiple inheritance and the diamond problem using the method resolution order, showing how the first inherited class's show method is chosen, unlike Java.

The Python .py source compiles to .pyc bytecode before execution, speeding programs; .pyc files are not human readable and are regenerated only when the .py file changes.

You can concatenate two tuples in Python by using the plus operator to create a new tuple, leaving the original tuples unchanged. You can also concatenate via unpacking.

Explore how underscores work in Python, with single underscores signaling internal use and double underscores triggering name mangling to protect private members, while special methods enable operator overloading.