Best way to simplify repetitive calculations in GitHub Actions workflows? #194424
Replies: 2 comments
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For simple calculations in GitHub Actions, I’d usually avoid calling external tools or services. That adds extra dependency, latency, and possible failure points. Best practice is:
Example: - name: Calculate percentage
run: |
score=45
total=60
percentage=$(( score * 100 / total ))
echo "percentage=$percentage" >> $GITHUB_ENVThen later: - name: Use percentage
run: echo "Percentage is $percentage%"I wouldn’t recommend using an online calculator inside the workflow itself. It is fine for manually testing the logic before implementation, but production workflows should keep the calculation inside the repo so it is reproducible, reviewable, and not dependent on an external website. So the cleanest approach is: expressions for simple workflow decisions, small scripts for calculations, and reusable scripts/composite actions when the logic grows. |
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🏷️ Discussion Type
Bug
💬 Feature/Topic Area
ARC (Actions Runner Controller)
Discussion Details
I’ve been working with GitHub Actions recently to automate some workflows, and overall it’s been really useful for handling repetitive tasks like builds, validations, and small data processing steps. As we know, GitHub Actions is mainly used to automate workflows like CI/CD pipelines and reduce manual effort in development processes.
However, I ran into a small challenge.
In one of my workflows, I need to repeatedly calculate values (like percentages or simple scoring logic) as part of a process. While this can be done using scripts inside the workflow (bash, Python, etc.), it sometimes feels like overkill for very simple calculations.
What’s the best practice for handling simple calculations inside GitHub Actions?
Do you prefer writing small scripts, or calling external tools/services?
Is there a cleaner or more lightweight approach for this?
For example, in a different context (not directly inside CI/CD), I’ve used a simple online grade calculator quickly test and validate calculation logic before implementing it into scripts. It helped reduce errors when translating logic into code.
Curious to know how others handle this in real workflows ,especially when trying to keep things simple and maintainable.
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