Examples

This folder contains design and behavior examples for Python WAGO PLC programs.

What you will find

• arduino-style.py: Minimal Arduino-like API (digitalRead / digitalWrite) in one cyclic function.
• variables.py: Variable-based design with explicit setup mapping in Python. -# variables_external.py: Variable-based task where mapping is expected from external configuration.
• cycle_time_example.py: Scheduler/watchdog behavior and timing model.
• #discussion.md: Pros/cons and the design rationale.

Conceptual differences

1) Arduino-style approach

Reference: arduino-style.py

• #Style: Imperative loop with direct I/O calls on an io object.
• Strengths: Very small and quick to read for users coming from Arduino.
• Trade-offs: Weak semantic naming for process signals, limited type hints/autocomplete, less PLC-like structure.

2) Variables in script

Reference: variables.py

• #Style: Define process variables in setup(), then use named parameters in cyclic tasks.
• Strengths: Clear mapping from hardware channels to descriptive process variables; better readability and maintainability.
• Trade-offs: More boilerplate and larger function signatures as projects grow.

3) Variables with external mapping

Reference: variables_external.py

-# Style: Keep Python logic lean; move I/O and variable mapping to a config file (for example controller.yaml).

• Strengths: Better for larger projects, easier generation/tooling support, portable configuration.
• Trade-offs: Adds indirection and a second source of truth to manage.

Runtime behavior example

Reference: cycle_time_example.py

This example focuses on scheduler semantics:

• cycle time clamping and conversion from ms to seconds
• task priority ordering
• watchdog timeout checks -# sensitivity-based watchdog scaling

Use it to understand real-time constraints before tuning production task timings.

Which example should I start with?

• New to PLC concepts and just want a minimal first run: start with arduino-style.py. -# Building maintainable application logic in Python: use variables.py.
• Building larger or generated projects with stable deployment config: move toward variables_external.py.

Recommendation

For this project, the preferred direction is variable-based design with script-first behavior and optional external configuration, as summarized in discussion.md.