Python Flask - Create APIs using Python

Explore Python's role in data engineering and AI, from installation and virtual environments to IDEs like PyCharm or VS code, and essential libraries for data science.

Explore Python fundamentals in PyCharm and CLI, from interpreting vs compiling, objects and data types to type conversion and memory, with hands-on setup and package management.

Explore how Python can run as an interpreted language in IDEs or the command line, and how pre-compiling with py_compile produces bytecode (.pyc) for faster execution.

Explore how Python treats every entity as an object, using classes as templates and objects that exist in memory, and learn core data types like list, tuple, dictionary, and set.

Learn how to work with strings in python by creating and assigning string variables, converting with str(), and applying operations such as split, strip, capitalize, lower/upper, numeric checks, and concatenation.

Explore numeric data types in Python, including integers, floats, and decimal values, with operations like round, divmod, power, hex conversion, and is_integer checks, plus practical hands-on initialization.

Explore lists as mixed-type containers in Python, including initialization with list(), zero-based indexing, and common operations like append, insert, pop, extend, remove, reverse, sort, and clear.

Learn about tuples, immutable data types similar to lists, where elements cannot be changed; access by index, count, search values, and modify inner lists in a practical example.

Master Python data types by studying sets and dictionaries, their operations like add, union, intersection, pop, keys and values, updates, and type conversion between lists, sets, and primitives.

Explore memory allocation in Python, where variables store addresses, not values, and use id and hex to reveal locations; grasp objects, basic operators, and assignment versus comparison operators.

Set up a Python interpreter and a virtual environment in PyCharm, creating a project folder. Install libraries such as Pi Spark and Apache Airflow from the IDE or terminal.

Learn the print function to output variables and strings, use format to compose messages, and employ the input function to capture user data and convert types with int.

Explore conditional logic in Python using if, elif, and else, handling thresholds like 5000, 3000, and 1111.11 with actions such as calling, texting, or gifting, including indentation and operators.

Learn how to use for loops to iterate over lists, tuples, dictionaries, sets, and ranges, and how to break when needed. Understand while loops and prevent infinite loops with conditions.

Explore Python functions and their role as methods in classes, including defining with def, calling, returning values, and how to use them to create reusable code and APIs with Flask.

Explore function scope and the LGB rule (local, global, built in) in Python, and learn how the global keyword can break the rule to apply changes globally.

Learn how the return keyword transfers a value from a function to the caller, using single and multiple returns, and capturing results in variables or tuples.

Pass dynamic values to Python functions using arguments and avoid hard-coded data. Understand how memory addresses and references enable calculations and returns.

explain passing and modifying arguments for integers, strings, lists, sets, dictionaries, and tuples, and how the LGB rule governs local versus global changes inside functions.

demonstrates python's positional and keyword arguments, showing that positional calls rely on order while keyword calls map values by parameter names, avoiding order errors.

Master positional and keyword arguments in Python, learn to use *args and **kwargs to accept variable inputs, and handle mixed argument scenarios for flexible function definitions.

Explore object oriented programming in Python, defining classes and creating objects with methods, constructors, and self to manage instance state, memory, and identity.

Learn how self identifies an instance, distinguish instance from class variables, and use __init__ as a constructor to initialize object state with lgb rules for class variables.

Create two Python classes for a customer onboarding app and a salary hike calculator, printing names and ages, generating random ids and emails, and computing hikes from years of experience.

Implement a Python class called hike generator to compute salary hikes from current salary and years of experience, calculated from the date of joining, using a lookup table of percentages.

Inheritance lets a child class reuse the parent class's methods and variables while adding its own, showing parent and child classes, and how multiple inheritance works.

Explains memory management in Python by walking through function and class memory, stack frames, object creation, application heap, and Python's garbage collection.

Explore modules and packages in Python, learn import techniques with dot notation and aliases, understand namespaces, package init files, and best practices for organizing code.

Write modular Flask APIs to manage a bank's customers, accounts, and loans, including adding customers, accounts, and loan records, and retrieving details by customer or account identifiers.

Python compiles each module to bytecode in the __pycache__ folder on import, so later imports reuse precompiled .pyc files unless the source timestamp is newer.

Use the dunder __name__ to run code only when the program starts directly, and understand how imports, namespaces, and from import affect module versus current program scope.

Master graceful error handling in Python with try-except-else and raise statements, using built-in exceptions to manage edge cases and prevent production crashes.

Master file handling and basic debugging in Python for data engineering, and explore multithreading concepts while manipulating csv and json files.

Master the CSV module to read and write CSV files using csv.reader and csv.writer, including delimiter and code character; then learn the JSON module for serialization with dumps and loads.

Explore how Python uses multithreading to run code in parallel by creating threads with the threading module, starting them, and joining to wait for completion.

Develop multi-threading in Python by running five threads to read files in parallel, and aggregate sums by payment method at the end.

Master debugging and profiling in Python using breakpoints, print statements, and PyCharm or VS Code, and use cProfile and memory_profiler to measure time and memory.