Python Developer
A master curriculum from foundational syntax, memory references, and object-oriented design to CPython internals, async architectures, and high-performance AI tooling.
Intelligent Agents & Problem Formulation
Phase 1: Environment Setup & Core Fundamentals
Setting up your development environment and mastering Python variables, control structures, and functional decomposition.
Modern Python Environment & Tooling
Installing Python (3.12+), configuring VS Code with extensions (Pylance, Black, Ruff), isolated virtual environments (venv), and pip package management.
Variables, Data Types & Type Annotations
Dynamic typing, immutable vs mutable types (int, float, str, bool, bytes), type annotations (typing module), and type checking with MyPy.
Control Flow, Loops & Structural Pattern Matching
Boolean logic, if/elif/else statements, for-loops with range/enumerate/zip, while-loops, break/continue/else loop clauses, and modern match/case pattern matching.
Phase 2: Data Structures & Algorithmic Foundations
Core collection types, hash maps, complexity analysis, and the standard collections library.
Core Collections (Lists, Tuples, Dictionaries, Sets)
List amortized array mechanics, tuple immutability and packing/unpacking, dictionary hash maps and collision resolution, and set hashing.
Specialized Collections & Itertools
collections module (deque, defaultdict, Counter, OrderedDict, namedtuple) and itertools (chain, cycle, groupby, combinations, permutations).
Phase 3: Object-Oriented Programming & Metaprogramming
Class architectures, dunder protocols, inheritance hierarchies, dataclasses, and custom decorators.
Object-Oriented Architecture & Dunder Methods
Classes, instances, self, __init__, __repr__, __str__, operator overloading (__eq__, __lt__, __add__), and object lifecycle protocols.
Decorators, Closures & Functional Primitives
First-class functions, closures, LEGB scope resolution, function decorators, class decorators, functools.wraps, and functools.lru_cache.
Dataclasses, Pydantic & Data Validation
Modern declarative data containers with @dataclass, frozen immutability, field factories, and Pydantic v2 validation models.
Phase 4: CPython Internals & Memory Architecture
Understanding how Python executes code under the hood — memory allocation, reference counting, and the GIL.
PyObject Structure & Memory Management
Everything in Python is an object. Examining PyObject, ob_refcnt, ob_type, variable name pointers, and the id() memory address.
Cyclic Garbage Collection & Weak References
Generational garbage collection (Gen 0, 1, 2), detecting circular reference cycles, gc module inspection, and weak references (weakref).
Concurrency: Threading, Multiprocessing & Asyncio
The Global Interpreter Lock (GIL), I/O-bound vs CPU-bound tasks, concurrent.futures, asyncio coroutines, event loops, and free-threaded Python (PEP 703).
Phase 5: High-Performance Python & AI Systems
Connecting Python to modern AI backends, C-extensions, Cython, and high-throughput production serving.
High-Performance Numerical Computing with NumPy C-Arrays
Contiguous memory buffers, striding, memory views, broadcasting internals, and interfacing Python with BLAS/LAPACK libraries.
High-Throughput APIs with FastAPI & vLLM Serving
Asynchronous endpoints with FastAPI, Uvicorn worker clustering, streaming responses (Server-Sent Events), and integrating model backends.
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