Backend Python Developer Ecosystem

Data Structures & Algorithms with Python Guide

A complete guide to data structures and algorithms implemented in Python: arrays, stacks, queues, linked lists, trees, hash tables, sorting, searching, and Big O Notation. More than 25 algorithms documented with their complexity, implemented from scratch. It's the path's differentiator: 95% of backend courses don't cover this, and it's exactly what gets asked in technical interviews.

48 lecciones

Python for Backend Development Guide

This guide teaches you the Python skills every backend developer needs: advanced OOP, type hints with mypy, async/await, decorators, context managers, generators, professional error handling, logging and basic testing. 5 progressive modules with hands-on projects applied to backend work.

40 lecciones

Git & GitHub Guide

Master version control with Git and collaborative development with GitHub, from your first commit to production CI/CD pipelines. This guide walks you step by step through everything you need to work professionally with Git: local workflow, branches, conflict resolution, Pull Requests, team workflows, automation with hooks and GitHub Actions, and error recovery. Built for developers of any language who want to stop fearing Git and start using it with confidence on real teams.

104 lecciones

REST APIs & HTTP Fundamentals Guide

This guide teaches you the HTTP protocol and the REST principles behind every web API. Before you build APIs with FastAPI, you need to understand what a request is, what a response is, how status codes work, and how to design APIs that scale.

32 lecciones

FastAPI Fundamentals Guide

This guide teaches you FastAPI from installation all the way to building a complete CRUD API. You'll learn path operations, parameter handling, validation with Pydantic, professional error handling and CORS configuration. It's the core of the Backend Python Developer path.

52 lecciones

FastAPI Advanced Features Guide

This guide takes your FastAPI knowledge to the next level: dependency injection for DRY, testable code, APIRouter for modular apps, WebSockets for real-time communication, background tasks, file uploads and custom middleware.

30 lecciones

PostgreSQL & SQLAlchemy Guide

Learn PostgreSQL from installation to optimized queries, model your data with the SQLAlchemy ORM, manage your schema with Alembic, and integrate everything asynchronously with FastAPI. This guide replaces in-memory data with real, professional persistence, exactly as it is used in production. Built for developers who have already built APIs with FastAPI and need to take the next step: a well-designed relational database that scales.

48 lecciones

Authentication & Authorization Guide

This guide teaches you how to implement complete authentication and authorization: password hashing, JWT tokens, OAuth2 flows, RBAC with roles and permissions, security headers, and FastAPI's native Security integration.

48 lecciones

Redis & Caching Strategies Guide

Master Redis as a professional caching layer for your FastAPI APIs. You will learn the 5 data types with real judgment (not just strings), the 3 fundamental caching patterns (cache-aside, write-through, write-behind), rate limiting with sliding windows and sorted sets, session storage that complements JWT, Pub/Sub for asynchronous events, and async integration with FastAPI using `redis.asyncio` (the official client — not the deprecated `aioredis` library). It is an intermediate guide that closes the backend infrastructure block of the Backend Python Developer path before Testing.

25 lecciones

Testing Backend Applications Guide

Learn backend testing end to end: pytest fundamentals, fixtures, mocking with unittest.mock and pytest-mock, integration testing with test databases and factories, E2E testing with the FastAPI TestClient, coverage with pytest-cov, the TDD workflow, and CI with GitHub Actions. Build a production-grade test suite with 80%+ coverage.

48 lecciones

Database Performance & Query Tuning Guide

Master PostgreSQL performance tuning for FastAPI: deep EXPLAIN ANALYZE reading, advanced indexing (composite, covering, partial, expression, GIN), eliminating the N+1 problem in SQLAlchemy, query profiling with `pg_stat_statements` and `auto_explain`, PgBouncer pooling, autovacuum tuning, and refactoring scaling anti-patterns.

64 lecciones

SQL Patterns for Production APIs Guide

Master the SQL patterns every production multi-tenant API needs: cursor pagination (17x faster than OFFSET on deep pages), correct soft deletes, audit logs, Row-Level Security multi-tenancy, zero-downtime migrations, optimistic locking, schema versioning, and bulk operations with COPY — fully integrated with FastAPI and SQLAlchemy 2.0 async.

64 lecciones

Advanced PostgreSQL for Backend Guide

Master PostgreSQL's advanced features for production backend apps: deep JSONB with operators and GIN indexes, full-text search in Spanish as an Elasticsearch replacement, native partitioning for massive tables, materialized views for in-DB analytics, advisory locks as a Redis replacement, savepoints for nested transactions, useful extensions (`pg_trgm`, `citext`, `uuid-ossp`, `hstore`), and recursive CTEs for hierarchies and graphs.

64 lecciones

CI/CD for Python Backend Guide

Master CI/CD applied to Python backends with FastAPI: GitHub Actions workflows, testing automation with Pytest + coverage, linting with Ruff/Black/mypy, pre-commit hooks, deployment automation to Railway/Render/Fly.io, environment management (dev/staging/prod), secrets handling, database migrations with Alembic in CI, and rollback strategies with blue-green and canary deployments. Build a production-ready pipeline that automates everything from commit to production.

40 lecciones

Docker Essentials Guide

Master Docker for AI applications: build optimized images, containerize FastAPI + LLM apps, orchestrate multi-service stacks with Docker Compose (API + ChromaDB + Redis), and apply production best practices including multi-stage builds, secrets management, and health checks. Your gateway to production deployment.

64 lecciones

Monitoring & Observability Guide

Master the observability of AI systems in production with OpenTelemetry, the industry standard for 2026. Learn to instrument LLM applications with traces for prompts, embeddings, and tool calls, build dashboards for latency and cost, design alerting strategies, implement AI-specific monitoring (prompt quality, token usage, model drift), and debug production issues like hallucinations and cost spikes. Integrates with LangSmith and monitoring backends.

64 lecciones