Check Box To Add: Private sessions from my elite mentoring group, with top software engineers and data pros - 6 hours in total. How to think about mocks, and the bottom line of what mocks are good for; When to use generator functions/methods vs. regular functions/methods; When we do NOT want to use dataclasses, and the trade-offs of using @dataclass vs. not using it; A key for writing technical articles that you want to have mass appeal and go viral; Pyodbc vs. SQLAlchemy vs. SQLModel; Runtime validation (with Pydantic) vs. static code analysis (with mypy); How Pydantic models and dataclasses are similar and different from each other; A discussion about using DRF (Django REST Framework) with Pydantic; Aaron's current thoughts on generative coding AI, and how we want to use it as technology professionals; Why we want to keep our test methods isolated and independent, and how to do that; When to use setUp() and tearDown() in your unit tests; Coaching a student on how to choose his next career objective; Running Python modules as programs. Why and when to do this, and when NOT to do it; The essence of what virtual environments do, and their common use cases; Tips on creating a job posting to hire Python developers; Using Python for system automation tasks, and when NOT to choose it over Bash, etc.; Low vs. high level OS operations in Python; Using the subprocess module; The optimal learning strategy for complex skills like Python mastery; Aaron's strategy for finding modern replacements of legacy libraries; Why function objects are useful; What makes a function easily testable; Static methods in Python vs. in other languages; The right way to use Stack Overflow (and how to avoid mis-using it); A small distributed Pythonic app to get around a corporate firewall; How to learn a new programming language that's different from what you are familiar with; Book recommendations for Pythonistas (not just about Python); and more. Not available except as an add-on today.
