How datascientest/pipeline-calculatrice-jenkins works
1. Repository purpose
- This is a very small Python project centered on a command-line calculator for integers.
- The repo is also used as a teaching example for a Jenkins pipeline tutorial, so the codebase is intentionally simple and testable.
2. Core domain layer: sources/calc.py
- calc.py contains the calculator’s business logic: addition, subtraction, multiplication, and division.
- This is the main reusable subsystem and likely the most stable boundary in the repo.
- Because the README says it operates on integers, the functions probably implement basic arithmetic rather than UI or persistence concerns.
3. Application entry point: sources/prog.py
- prog.py is the executable program that launches the calculator.
- Its role is orchestration: it likely reads user input, calls functions from calc.py, and displays results.
- This file is the boundary between the pure computation layer and runtime interaction.
4. Testing layer: sources/test_calc.py
- test_calc.py is the unit test suite for the calculator functions.
- It validates the behavior of calc.py independently from the launcher in prog.py.
- This separation means the calculation logic can be tested without involving any interactive program flow.
5. Data flow
- The primary flow is: user interaction in prog.py → arithmetic function in calc.py → result returned to prog.py → output shown to the user.
- The test flow is separate: test_calc.py → imports and exercises calc.py directly.
- There is no indication of external storage, network calls, or shared state.
6. Subsystem boundaries
- calc.py should be treated as a pure logic boundary.
- prog.py is the UI/entry boundary.
- test_calc.py is the verification boundary that protects the logic layer from regressions.
7. Runtime and language
- The repository is a Python project with a very small footprint.
- No framework is involved; the architecture is lightweight and script-based.
- The project appears designed to run locally and be validated by automated tests.
8. CI/CD intent
- The README explicitly frames the repo as input for a Jenkins pipeline tutorial.
- Jenkins is therefore an external automation concern, not part of the app itself.
- In an architecture diagram, Jenkins would sit outside the codebase and run the test suite as part of pipeline validation.
9. What is notably absent
- There is no database, API server, message broker, or frontend in this repo.
- There are no visible infrastructure components beyond the intended Jenkins tutorial context.
- The architecture is intentionally minimal: computation, program entry, and tests.
10. How to diagram it
- Show prog.py as the user-facing launcher.
- Show calc.py as the central computation module.
- Show test_calc.py as a separate test consumer of calc.py.
- Optionally show Jenkins outside the repo as a pipeline system that runs the tests and validates the project.
Main entry points: prog.py Launcher · calc.py Calculator · test_calc.py Unit tests
Components 5
Source code
Core calculator modules and tests.
- Calculator · Integer arithmetic functions for add, subtract, multiply, and divide.
sources/calc.py - Launcher · Executable entry point that coordinates user interaction and calculator calls.
sources/prog.py - Unit tests · Tests that exercise the calculator logic directly.
sources/test_calc.py
External systems
Automation and runtime context outside the repository.
- Jenkins · External automation that runs the repository tests and validates the tutorial pipeline.
- User · Local person interacting with the calculator program.
Connections 6
- User → Launcher: uses · A user runs the calculator program and provides input.
- Launcher → Calculator: calls · The launcher delegates arithmetic work to the calculation module.
- Calculator → Launcher: returns · Computed results flow back to the launcher for display.
- Unit tests → Calculator: verifies · Unit tests import and exercise the calculator functions directly.
- Jenkins → Unit tests: runs · The pipeline executes the test suite as part of validation.
- Jenkins → Launcher: checks · The pipeline can also validate that the program project remains buildable and runnable.