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You just have to learn 4 things to know Object-Spatial Programming

Most programming paradigms ask you to learn dozens of concepts, patterns, and best practices. Object-Spatial Programming (OSP) is different. At its core, there are really just four fundamental concepts you need to understand. Master these four things, and you'll have unlocked an entirely new way of thinking about computation—one that's particularly well-suited for modern applications dealing with complex relationships, graph structures, and distributed data.

This article will teach you the complete model of Object-Spatial Programming through these four conceptual buckets. Each builds naturally on the last, and by the end, you'll understand why OSP represents a genuine paradigm shift in how we structure programs.

Dataclasses: Python's Admission That Classes Are Broken (And How Jac Fixes It Properly)

Python's traditional class syntax has a problem: defining any class with fields requires excessive boilerplate. After decades of developers writing the same __init__, __repr__, and __eq__ methods, Python 3.7 introduced dataclasses (PEP 557) as a decorator-based solution. But dataclasses are a retrofit—what if dataclass semantics were built into the language from the start?

How Does Python Get Jac'd with Jaseci?

When explaining complex software architectures, there's this tendency to start with the grand vision and work down to implementation details. But honestly, for developers who actually need to use a tool, the opposite approach makes way more sense. This post if for the Python developer exploring Jac, a programming language and runtime that extends Python rather than trying to replace it. We'll start with what you can actually install and use today, then work our way up to why it exists.