#Python517 pages

Pages tagged Python across 50 sections.

AI Agents Best Practices Chunking & Ingestion Evaluation & Guardrails LangChain LangGraph & Agent Loops LlamaIndex Model Context Protocol (MCP)RAG Basics Retrieval & Re-ranking The RAG Pipeline and Agent Loop Mental Model Tool Use & Function Calling Vector Databases

API y Seguridad

API & Security Best Practices API Design Basics cryptography Essentials Dependency & Supply-Chain Security GraphQL in Python Input Validation & Injection OAuth2 & JWT Password & Credential Handling Rate Limiting & Abuse Prevention Secrets Management The Python API Trust Boundary

Arquitectura y Diseño

Architecture Best Practices Clean / Hexagonal Architecture Codebase Audit Checklist Configuration & Settings Dependency Injection & Wiring Domain Modeling Migrating a Legacy Python 2/Django/Flask App Project Architecture Decision Checklist Refactoring Decisions src Layout & Package Structure The Architecture Mental Model for Python Services

Python Asíncrono

Async Best Practices Async Context Managers & Iterators Async Databases Async HTTP with httpx/aiohttp Asyncio Basics Debugging Async Code Structured Concurrency Sync/Async Bridging Tasks & Gather The Event Loop Mental Model

BDD y Gherkin

BDD Best Practices BDD Decision Checklist behave / pytest-bdd Setup Gherkin Syntax Gherkin to CI Pipeline Gherkin to Code Step Definitions The BDD Living Documentation Model

Casos de Estudio

Before/After: Refactoring a Legacy Django Monolith Before/After: Sync to Async Migration How to Read a Case Study Lessons-Learned Catalog Reference: A Data Platform / ETL System Reference: A FastAPI SaaS Backend Reference: A Production ML Pipeline Scalability Benchmarks

ML Clásico

Datasets & Splits Feature Engineering Gradient Boosting Hyperparameter Tuning Imbalanced Data Machine Learning Basics Machine Learning Best Practices Model Evaluation Pipelines Supervised Learning The Classical ML Mental Model Unsupervised Learning

Herramientas CLI

argparse CLI Basics CLI Best Practices Click Config & Environment Interactive Prompts Packaging & Distributing CLIs Rich Output The CLI Contract: What Makes a Command-Line Tool a Good Citizen Typer

SDKs de Nube

boto3 Basics Cloud SDK Best Practices Credential & Session Patterns DynamoDB google-cloud & azure-sdk Lambda Retry, Pagination & Throttling S3 Secrets Manager & SSM SQS & SNS The boto3 Architecture Mental Model

Concurrencia

Choosing a Concurrency Model Concurrency Basics Concurrency Best Practices concurrent.futures multiprocessing Queues & Producer/Consumer Shared State and Isolation Boundaries Subinterpreters The GIL & Free-Threaded Python threading

Contenedores y Despliegue

AWS Lambda & Serverless CI/CD Pipelines Configuration & Secrets in Prod Deployment Basics Deployment Best Practices Dockerizing Python Gunicorn & Uvicorn Kubernetes for Python Apps The Deployment Artifact Model: Build Once, Configure at Runtime Zero-Downtime Deploys

Análisis de Datos

Cleaning & Transforming Data Data Analysis Basics Data Analysis Best Practices GroupBy & Aggregation Joins & Merges NumPy Arrays NumPy Indexing & Reshaping pandas Series & DataFrames Performance & Memory Polars The NumPy and pandas Mental Model Time Series

Ingeniería de Datos

Airflow Data Engineering Basics Data Engineering Best Practices Data Validation & Quality dbt with Python File Formats Prefect & Dagster PySpark Streaming (Kafka / Faust)The Batch, Streaming, and Orchestration Mental Model Workflow Reliability

Estructuras de Datos

arrays, bytes & memoryview Choosing the Right Data Structure Collections Best Practices collections Module Data Structures Basics Dictionaries heapq & Priority Queues Immutability & Hashability Lists & Tuples Sets & Frozensets The Container Model Behind Python's Data Structures

Visualización

Altair Dashboards (Streamlit / Dash / Gradio)Grammar of Graphics vs. Imperative Plotting matplotlib Plotly Plotting Large Data seaborn Visualization Basics Visualization Best Practices

Bases de Datos

Async Database Access Connection Management Databases Basics Databases Best Practices Migrations with Alembic NoSQL & Caching Query Patterns & N+1 SQLAlchemy Core SQLAlchemy ORM 2.0 SQLModel The Python Database Layering Model

Depuración

asyncio Deadlocks & Blocking-the-Loop Circular Import Scenarios Data Pipeline Defects Debugging Refactor Snippets Debugging Tools Dependency & Environment Conflicts Encoding & Unicode Bugs Floating-Point & Numeric Bugs Memory Leak Scenarios Mutable Default Argument Bugs The Debugging Mental Model for Python Services

Aprendizaje Profundo

Autograd Building Models with nn.Module Datasets & DataLoaders Deep Learning Best Practices Distributed Training GPUs & Mixed Precision PyTorch Basics PyTorch Lightning Saving, Loading & Export The Deep Learning Mental Model Training Loops Transfer Learning & Fine-Tuning

Django

Async Views & Channels Authentication & Permissions Caching & Performance Django Basics Django Best Practices Django REST Framework Migrations Models & the ORM Scaling & Deployment Templates & Forms The Admin The Django MTV Request Cycle & ORM Laziness

Entrega Empresarial

A/B Testing & Experimentation Delivery Best Practices DORA Metrics Environments & Config Promotion Feature Flags & Progressive Delivery Release Management Rollback Strategies What Enterprise Delivery Actually Optimizes For

Entornos

Dependency Resolution & Lockfiles Editable Installs & Local Packages Environments & Packaging Basics Environments Best Practices Managing Python Versions Poetry & PDM Private Indexes & Mirrors pyproject.toml Explained The Python Environment & Resolution Model uv - The Fast Toolchain

Errores y Registro

Custom Exception Hierarchies Errors & Logging Best Practices Errors vs Logging: The Two-Channel Mental Model Exception Groups & except*Exceptions Basics Raising & Chaining Retries & Backoff Structured & Contextual Logging The logging Module Warnings & Deprecations

Librerías Esenciales

beautifulsoup4 & lxml celery Essential Libraries Best Practices httpx & requests openpyxl / python-docx / reportlab pendulum / arrow Pillow pydantic-settings Rich & Textual SQLModel / SQLAlchemy tenacity The Python Dependency Model

FastAPI

Async Routes & Databases Authentication & Authorization Background Tasks & Workers Dependency Injection Deploying FastAPI FastAPI Basics FastAPI Best Practices Middleware & Error Handling Request & Response Models Testing FastAPI The FastAPI Request Lifecycle Model WebSockets & Streaming

Flask

Application Factories & Blueprints Building REST APIs Deploying Flask Extensions Flask Basics Flask Best Practices Flask vs FastAPI vs Django Request Lifecycle & Context Templating with Jinja2 Testing Flask The Flask WSGI & Context Model

Git y GitHub

Branching & Merging Essential Git Commands Git Best Practices Git Configuration Git for Data/Notebooks Git Worktrees GitHub CLI Merge Conflict Resolution Checklist The Git Object Model

Gobernanza

Career Growth: Senior to Lead to Staff/Principal Coding Standards & Style Guides Contribution Guidelines Dependency & Supply-Chain Governance Deprecation & Upgrade Policy Documentation Conventions Engineering Governance at Scale Governance Best Practices Spikes, PoCs & Adopting New Tools

Automatización de Infraestructura

Ansible Configuration Management Infrastructure Automation Basics Infrastructure Automation Best Practices Provisioning Cloud Resources Pulumi (Python IaC)Terraform with Python Testing Infrastructure Code The Declarative Infrastructure Mental Model

Iteradores y Generadores

Class & Method Decorators Closures & Scope Capture Closures, Protocols & Lazy Evaluation Context Managers functools Generators & yield Iterators & Decorators Best Practices Iterators & the Iterator Protocol itertools Writing Decorators yield from & Sub-generators

Linting y Formateo

Black / Ruff Format Editor Integration Essential Lint Rules isort & Import Organization Linting & Formatting Best Practices Linting in CI/CD mypy & pyright in CI pre-commit Hooks Ruff Setup The Static Analysis Pipeline Model

CLI de Linux

Linux CLI Best Practices Linux CLI Fluency for Python Engineers Pipes & Text Processing Process & Resource Management Python-in-the-Shell Search & Regex Shell Productivity SSH & Remote Work Sysadmin Essentials

LLMs y GenAI

Anthropic Claude SDK Embeddings & Similarity Hugging Face transformers LLMs Basics LLMs Best Practices Local & Open Models OpenAI & Other SDKs Prompt Engineering Streaming & Async LLM Calls Structured Output The LLM Interface Model Tokens, Cost & Rate Limits

MLOps

Batch & Streaming Inference Data & Model Versioning (DVC)Dedicated Serving (BentoML / Triton / TorchServe)Experiment Tracking GPU Infrastructure & Cost MLOps Basics MLOps Best Practices Model Registries & Versioning Monitoring and Drift Serving with FastAPI The Notebook-to-Production Lifecycle

Observabilidad

Distributed Tracing Error Tracking Health & Readiness Metrics Observability Basics Observability Best Practices Performance Monitoring (APM)Structured Logging The Observability Correlation Model

POO

Abstract Base Classes Class vs Instance vs Static Methods dataclasses Dunder / Magic Methods Enums Inheritance & MRO Metaclasses & `__init_subclass__`Object-Oriented Python Best Practices OOP Basics Properties & Descriptors Protocols & Structural Typing The Python Object Model

Empaquetado y Publicación

Build Backends Distributing Applications Entry Points & Console Scripts Native Extensions & Wheels Packaging Basics Packaging Best Practices Publishing to PyPI The Python Packaging Model: From Source Tree to Installed Package Versioning & Changelogs

Rendimiento

Async & Concurrency for Throughput Caching & Memoization cProfile & Profilers Cython & mypyc How Python Spends Time and Memory Memory Profiling Performance Audit Checklist Performance Basics Performance Best Practices PyPy & Alternative Runtimes timeit & Microbenchmarks Vectorization with NumPy

Producto y Stakeholders

Estimation & Risk Making the Process Work (Scrum/Kanban/SAFe)Prioritizing Platform & Tech Debt Product Collaboration Best Practices Requirements to Technical Specs Roadmap Contributions Stakeholder Communication The Product-Engineering Partnership

Pydantic

Dataclasses vs Pydantic vs attrs Field Types & Constraints Nested & Recursive Models Performance & pydantic-core Pydantic Basics Serialization Settings Management The Pydantic Boundary Model Validation Best Practices Validators

pytest

Assertions & Test Structure Coverage & Reporting Fixtures Mocking & Patching Parametrization Property-Based Testing pytest Setup Testing Async Code Testing Best Practices Testing Web APIs The Anatomy of a pytest Suite tox / nox

Fundamentos

Comprehensions & Generator Expressions Control Flow Files & I/O Functions, Args & Scope Modules, Imports & Packages Numbers, Booleans & Arithmetic Python Basics Python Fundamentals Best Practices Strings & f-strings The Python Execution Model Variables, Types & Dynamic Typing Virtual Environments Quickstart

Reglas de Python

30 Async Rules 30 Data/ML Code Rules 30 Security Rules for Python 40 API Design Rules (FastAPI/Django/Flask)50 Python Rules Every Specialist Should Follow How to Use a Python Rules List PEP 8 & Style Reference Problem / Solution Reference Python Architecture Decisions

Patrones Pythonic

Common Anti-Patterns Context Managers as a Pattern Dependency Injection in Python Duck Typing and the Data Model EAFP vs LBYL Factory & Builder Patterns Null Object & Sentinels Observer & Pub/Sub Pythonic Patterns Basics Pythonic Patterns Best Practices The Strategy & Dispatch Patterns

Habilidades de Agente

Data Pipeline Skill FastAPI Expert Skill Infra Automation Skill LLM App / RAG Skill Packaging & Publishing Skill pytest / Testing Skill Python Best-Practices Skill PyTorch / Deep Learning Skill The Agent Skill Model for Python Teams Type-Hinting Skill

Biblioteca Estándar

argparse & configparser collections, itertools & functools Recap dataclasses, enum & contextlib datetime, zoneinfo & time hashlib, secrets & uuid json & Serialization pathlib & os re - Regular Expressions Standard Library Best Practices Standard Library Overview subprocess The Standard Library Mental Model

Scripting de Sistema

File & Directory Automation Parsing Logs & Text Robust Scripts Scheduling & Cron Scripting Basics SSH & Remote Execution subprocess & Shell Interop System Scripting Best Practices The Process Contract: How Automation Scripts Talk to Their Environment Working with APIs & Webhooks

Equipo y Onboarding

Code Review Guidelines Codebase Orientation Conventions & Style Guide Environment Setup Checklist Onboarding Devs Checklist Team Best Practices The Python Team Capability Model

Liderazgo Técnico

Architecture Decision Records (ADRs)Code Review Culture Delegation & Spreading Context Handling Technical Disagreements Leadership Best Practices Mentoring & Leveling Running Design Reviews Technical Decision-Making The Tech Lead Mental Model

Respuesta a Incidentes

Blameless Post-Mortems & RCA Common Production Failure Modes Incident Response Playbooks On-Call Health Production Debugging Production Incident Response as a Discipline Rollback & Recovery Runbooks Turning Incidents into Guardrails

Type Hints

Built-in & Collection Generics Generics & TypeVar Gradual Typing Strategy Literal, Final & Annotated mypy & pyright Setup Optional, Union & the `|` Operator Overloads & Callable Types Protocols & Structural Typing The Type Checking Mental Model Type Hints Basics Type Hints Best Practices TypedDict & NamedTuple

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