Reproducible and Deployable Data Science with Open-Source Python
Aprenda a criar código de ciência de dados escalável, reproduzível e confiável usando Kedro, Apache Airflow e Great Expectations. Descubra como combinar iteração rápida com manutenibilidade e qualidade de dados consistente.
Making AI Happen at Your Company
Practical insights on implementing AI in established companies, covering strategy, technology adoption, cultural shifts, and overcoming legacy system challenges.
Raise Better Errors with Exception Groups
Explore Python 3.11's Exception Groups for robust error handling. Learn to overcome current limitations and write cleaner code using new features like except* keyword.
Python & Visual Studio Code - Revolutionizing the Way You Do Data Science
Discover how Visual Studio Code, GitHub, Codespaces, and Azure ML enhance Python data science productivity. Learn about VS Code Notebooks, Data Wrangler, collaboration features, and deployment options.
Dance with Shadows - Stubs, Patch and Mock
Aprenda a usar objetos falsos en pruebas de software: stubs, patch y mock. Explore técnicas avanzadas, evite errores comunes y descubra bibliotecas especializadas para desarrollo web.
Choosing the Right Database for Your Next Project - Looking at Options Beyond PostgreSQL and MySQL
Explore diverse database options beyond PostgreSQL and MySQL, covering relational, data warehouse, analytics, and machine learning solutions to find the best fit for your Python project.
How to Embed a Python Interpreter in an iOS App
Learn to embed Python 3.10 in native iOS apps, allowing users to script app behavior. Discover how to integrate Python with Swift, add third-party libraries, and modify app functionality at runtime.
How Much Time Does It Take to Write Tests? A Case Study
Explore the time investment in writing automated tests through a real-world case study, examining the implications and trade-offs in software development practices.
Event-Driven Microservices with Python and Apache Kafka
Explore event-driven microservices using Python and Apache Kafka. Learn to build loosely coupled, extensible distributed systems with an example application and practical considerations.
Data Warehouses Meet Data Lakes
Explore modern data architecture using PySpark, Hudi, Delta.io, and Iceberg to address datalake challenges, supporting real-time processing and enterprise-wide digital transformation.
The Design of Everyday APIs
Explore the art of API design, focusing on key elements like documentation, simplicity, and consistency. Learn to create user-friendly interfaces and optimize the connection between users and libraries.
Protocols - Static Duck Typing for Decoupled Code
Explore static duck typing with Protocols in Python for improved code decoupling and correctness verification. Learn use cases and implementation techniques for more idiomatic and efficient programming.
Making Python Better One Error Message at a Time
Explore Python 3.10's improved error messages and upcoming 3.11 enhancements. Learn about implementation challenges, user benefits, and how to contribute to future improvements.
Using Python to Predict Asset Price Reversals
Learn to predict potential trend reversals in stocks and cryptocurrencies using Python, Pandas, and Plotly. Discover how to identify Fibonacci retracement levels for low-risk trade entries.
CPython Bugs and Risky Features
Explore security risks in CPython, including directory vulnerabilities, code injection possibilities, and socket issues. Learn about potential threats and mitigation strategies for Python developers and administrators.
How to Craft Awesome Machine Learning Demos with Python
Learn to create interactive Machine Learning demos using Python, Gradio, and Streamlit. Discover how to craft engaging interfaces and share your models with both ML experts and novices.
Code Coverage Through Unit Tests Running in Sub-Processes - Threads - Locally and Automated on GitHub
Learn to measure and improve code coverage for tests running in sub-processes/threads, locally and on GitHub. Explore techniques to enhance reliability and automate the process using CI tools.
Protocols in Python - Why You Need Them
Discover the power of Protocols in Python, their advantages over Abstract Base Classes, and how they can enhance your code quality and maintainability.
From Pip to Poetry - Python Ways of Packaging and Publishing
Explore Python package management evolution, from pip to poetry. Learn to create, share, and publish packages efficiently, choosing the best tool for your needs.
Managing the Code Quality of Your Project - Leave the Past Behind - Focus on New Code
Explore the "Clean as you code" approach for managing code quality in legacy projects, focusing on recent changes to improve deliverables incrementally while maintaining productivity.
My Journey Using Docker as a Development Tool
Explore Docker for Python development, from basic images to advanced techniques. Learn to dockerize a FastAPI service, manage dependencies, run tests, and optimize for production environments.