24 docs tagged with "projects"

Build an interactive CLI playground to deeply understand binary representation, bitwise operators, masking, shifting, truth tables, and two’s complement in Python.

Build a robust command-line unit converter that teaches parsing, structured data modeling, validation, floating-point precision handling, and defensive input engineering.

Two production-style concurrency engineering projects - a concurrent web scraper and an async API system.

Three production-style database engineering projects - a CRUD app with proper data layer, a transaction-safe service, and a full ORM-backed API.

Three hands-on functional programming engineering projects for the Python Intermediate module. Build real systems using decorators, generators, closures, composition, and pure functions.

Build a production-grade interactive calculator CLI that teaches input handling, parsing, type conversion, operator semantics, truthiness, and safe evaluation without using eval.

Overview of the two hands-on engineering projects for the Testing and Quality module - a full pytest suite for a banking system and a complete CI quality pipeline setup.

Two production-focused projects for Module 06 - a fully tested Task Management REST API with FastAPI and SQLAlchemy, and a local deployment stack with Docker, Nginx, PostgreSQL, and Alembic migrations.

Four hands-on OOP engineering projects for the Python Intermediate module. Build real systems using classes, inheritance, ABCs, dunders, and composition.

Apply Python’s runtime semantics, object model, dynamic typing, operator behavior, and memory concepts through engineering-grade projects.

Build a banking system using Python OOP. Covers inheritance, @property validation, @classmethod factory methods, __repr__, overdraft protection, and transaction history.

Build a Python bytecode analysis tool using the ast module, dis.get_instructions(), and CPython's value stack model. Parse source to AST, disassemble to bytecode, simulate stack evolution, and compare two implementations side by side.

Build a production-quality Python decorator library with retry, rate limiting, timeout, argument validation, and structured call logging. Covers closures, functools.wraps, inspect.signature, and decorator composition.

Build a production-quality pytest test suite for the BankAccount and SavingsAccount system - fixtures, parametrized edge cases, mocked external dependencies, integration tests, Hypothesis property-based tests, and 90% branch coverage enforcement.

Build a production-quality Task Management REST API with FastAPI, Pydantic v2, SQLAlchemy, pytest TestClient, RFC 7807 error responses, request ID middleware, and Docker - full CRUD, pagination, filtering, and OpenAPI docs.

Configure a complete Python quality pipeline from scratch - pre-commit hooks, pyproject.toml tool configuration, GitLab CI four-stage pipeline, tox/nox multi-version testing, Makefile targets, coverage gate, and JUnit test report artifacts.

Build a lazy data processing pipeline in Python that handles datasets larger than RAM. Covers generators, generator chaining, lazy evaluation, immutable pipeline objects, and streaming architecture.

Build a library management system using Python OOP. Covers __repr__, __eq__, __hash__, Abstract Base Classes, checkout systems with date tracking, overdue detection, and fine calculation.

Configure a production-like local deployment stack for the Task Management API - multi-stage Dockerfile, Docker Compose with Nginx and PostgreSQL, Alembic migrations, Pydantic BaseSettings, health checks, graceful shutdown, and a Makefile for operations.

Build a production-quality Python profiler using sys.setprofile(), tracemalloc, and call tree construction. Supports context manager and decorator usage, formatted report tables, run comparison, and JSON export for CI integration.

Build a working chess engine in Python using ABCs, dunders, dataclasses, and composition. Covers Piece ABC, concrete piece classes, Board with __getitem__/__setitem__, Move dataclass, check detection, and algebraic notation.

Build a functional-style data transformation system in Python using function composition, pipe, partial, singledispatch, and the Result monad pattern. All functions are pure; error handling avoids exceptions.

Two hands-on Python internals engineering projects for the Python Intermediate module. Build real tools using CPython's bytecode APIs, the dis module, AST inspection, tracemalloc, and sys.setprofile.

Build an interactive CLI tool that inspects Python objects at runtime and reveals their type, identity, mutability, truthiness, and internal behavior.