Python, AWS & clean architecture. Nearly 20 years building software, courses and content for the Spanish-speaking community.
I work on several machines, and some of them aren't mine. At the end of the week I need to know what I did on each one, and the answer was spread across dozens of repositories. didwhat is a command that gets it in one step, with nothing to install but a binary.
I wanted to ship a new version of my library, and my first ideas were adding Pyrefly or raising the Python version. Neither changed anything for the people who use it. What did: accepting a reference typed in lower case without breaking the 1.0 promise, and proving it is safe without the GIL instead of assuming it.
To grow my address library I reviewed more than 800 open data sources across 31 states. Most declared no license, in several the publisher's license did not match the aggregator's, and only nine states passed. This is how you actually verify a license.
A real-world case of integrating language models into a text processing pipeline. Learn how to combine multiple providers to enrich your text data asynchronously and efficiently, using AWS Step Functions and Lambda.
This talk analyzes how to apply Clean Architecture principles in FastAPI projects to improve maintainability, scalability, and code quality. It covers separation of concerns, business logic organization, best practices for integrating with external services and databases, and strategies for testing and refactoring, leveraging FastAPI's native capabilities for data validation and dependency injection.
