can-py-state-machine 0.1.0

A lightweight Python implementation of a generic, event-driven state machine inspired by can-state-machine.

Can State Machine (CSM)

Can State Machinew is an architectural and programming approach focused on replacing traditional sequential logic with explicit state machine modeling — making complex behavior easier to understand, test, and evolve.

It's called Can State Machine not only as a nod to state-driven architecture, but also as a personal imprint: this philosophy originates from Can — and yes, state can flow.

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🌱 Why Can State Machine?

In modern software systems, control flow is often hidden deep inside long function chains, async callbacks, and implicit branching logic. This makes code harder to maintain, test, and reason about over time.

Can State Machine (CSM) embraces a different idea:

✨ Treat all control logic as a flow of explicit states — where every transition is visible, named, and controlled.

This mindset is especially powerful in domains like:

• Complex UI/UX flows
• Business rule engines
• Long-running backend processes
• Reactive systems
• Async orchestration (e.g. workflows, jobs, handlers)

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🧠 What is State Machine Modeling?

State machine modeling describes a system in terms of:

• A set of states
• A set of events or conditions
• A defined set of transitions between states
• (Optionally) side effects or actions triggered by transitions

This structure gives you predictability and declarative control — instead of spaghetti-like control flow logic.

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✅ Benefits of CSF

Benefit	Why it matters
Maintainability	Every transition is named, controlled, and visual — no mystery logic buried in conditionals.
Transparency	The logic is modeled declaratively — what happens is described, not encoded.
Predictability	You always know what state you're in, and what can happen next.
Testability	States and transitions can be tested in isolation, without simulating entire flows.