048-the-coockie-factory/docs/business-case.md

Cookie Clicker Bot

Metadata

Key	Value
ID	BC-001
CrossReference	SA-001
Language	en
Domain	it

Version History

Date	Status	Author	Reviewer	Change	Commit
2026-10-28	Accepted	Jens Tirsvad Nielsen	AI as stand-in for S01	Initial version (reviewed in RC-001)	96a9a78

---

Executive Summary

Udemy's 100 Days of Code final project of day 48 asks the participant to build a Python bot that plays the browser game Cookie Clicker with Selenium: it clicks the big cookie and buys upgrades by itself, and after five minutes reports the cookies-per-second (CPS) rate it reached. This project delivers that bot as a readable, runnable and tested repository that other course participants (S02) can compare against and GitHub visitors (S03) can browse, with a README and a three-language wiki (English, Danish, Bahasa Malaysia) that show every lecture step with a screenshot and explain what it taught.

Methodological and Standards Foundation

The artifacts follow the SQA and QC framework mounted at framework/ (plan first, review every artifact against its QC checklist). Quality attributes are named with ISO/IEC 25010:2023 characteristics. The code follows the framework's Python conventions and Clean Architecture (business rules free of Selenium), is tested with pytest and documented with Doxygen comments. Graphical user interface (GUI) runs are done headless in a Docker container, never on the host desktop (framework/process/gui-testing.md).

Problem Statement

• The assignment is described in a lecture video only; there is no runnable reference a participant can compare with.
• A bot written as one script of module-level code with threads (the author's earlier solution targeted the old Orteil experiment page and needed an extra threading package) is hard to read, cannot be tested without a browser and does not work against the current Cookie Clicker at ozh.github.io.
• Without screenshots and an explanation per lecture step, a visitor sees code but not what each step achieves or what was learned.

Business Opportunity

A small, well-structured reference solution makes the author's learning visible, lets other participants compare strategies (the lecture invites competition on CPS), and gives GitHub visitors a clean example of a Selenium automation project with tests, documentation and a multilingual wiki.

Objectives

1. O1: A bot plays Cookie Clicker at https://ozh.github.io/cookieclicker/ for five minutes by clicking the big cookie and buying upgrades, then prints the CPS reached.
2. O2: The code uses the assignment's function names, constants live in constants.py, and every source file has Doxygen comments with a Doxyfile provided.
3. O3: Decision logic is covered by pytest tests that need no browser; the only runtime dependency is Selenium.
4. O4: A README and a wiki in English, Danish and Bahasa Malaysia show one screenshot per lecture step and explain what each step taught.
5. O5: The repository has a description and topics on the git host, a Python .gitignore, a pyproject.toml (Python 3.13 or newer) and instructions for creating and using a local .venv.

Scope

In Scope

• The bot for the lecture steps: open the game, choose the language, click the cookie, read the cookie count, buy affordable upgrades, run for five minutes, report CPS.
• Project configuration: pyproject.toml, .gitignore, .venv instructions, Doxyfile, constants.py.
• pytest tests for the logic with a fake game.
• A headless Docker run that produces one screenshot per lecture step.
• README (framework template) and wiki pages in en, da and ms.
• Description and topics on the git host repository.

Out of Scope

• Cheating features of the game (console commands, save editing).
• Browsers other than Chrome, and the old Orteil experiment page.
• A graphical front end or packaging to PyPI.
• Contests or a leaderboard.

Expected Benefits

Tangible Benefits

• A runnable bot, a test suite and generated API documentation.
• Screenshots per lecture step, in the README and in three wiki languages.

Intangible Benefits

• A learning record of Selenium, game-loop strategy and clean structure.
• A portfolio piece for GitHub visitors.

Strategic Alignment

The project supports the author's goal of completing the 100 Days of Code bootcamp with work that is reviewable and shareable, and exercises the SQA and QC framework on a small project.

Success Criteria

#	Criterion	Target	Measure
1	Bot run length	300 seconds	Run log shows start and end times
2	CPS reported	A CPS value is printed at the end of the run	Console output of the headless run
3	Tests	All pytest tests pass, no browser needed	python -m pytest exit code 0
4	Runtime dependencies	Exactly one: selenium	dependencies list in pyproject.toml
5	Lecture step screenshots	One per lecture step, in README and each wiki language	Files under docs/images/ referenced by all pages
6	Wiki languages	Same page set in en, da and ms	check-languages.sh and the file listing
7	Repository metadata	Description and at least five topics set	Git host API response

Risks

Risk	Impact	Mitigation
The game's page structure changes	Bot stops finding elements	Element ids live in constants.py; explicit waits with timeouts; note the game version tested
The game is unreachable from the container	No run, no screenshots	Stop and report; unit tests stay independent of the network
Docker or headless Chrome is unavailable	GUI run cannot be done	Stop and report per the GUI testing rule; never fall back to the host desktop
Selenium is a heavy dependency against S03's wish for none	Conflict between stakeholder concerns	Keep it the single runtime dependency, justified in the architecture decision record ADR-0001
A token leaks into the repository	Secret exposure	.env stays untracked and ignored; tokens are read by scripts only and never printed

Assumptions

• S01 is Product Owner and reviewer; S02 and S03 cannot be interviewed, so their needs are taken from the assignment brief.
• The PO language is English and the domain is IT.
• The game at https://ozh.github.io/cookieclicker/ stays available during the project.
• Docker with a Chrome image is available on the author's machine.
• The stage is a prototype-sized learning project with no budget.

Constraints

• Python 3.13 or newer, venv, pytest, pyproject.toml, constants in constants.py.
• Folder structure src/, tests/, docs/.
• Doxygen comments and a Doxyfile.
• Avoid runtime dependencies unless needed.
• Tokens come from .env, which is for personal use only: it is not imported by the project, not tested and not committed.
• Duration: one week, 2026-10-28 to 2026-11-04. Budget: none.
• One branch and one pull request per milestone.

Cost–Benefit Assessment

Costs	Benefits
About 20 hours of the author's and the AI's time, no money (qualitative assessment, justified: a learning project with no revenue and no budget)	A reviewed reference solution, a learning record and a shareable repository

Stakeholders

ID	Role in this project	Reference
S01	Course participant, Product Owner, developer and reviewer	SA-001
S02	Udemy coursists who compare solutions	SA-001
S03	GitHub viewers browsing for ideas	SA-001

Recommendation

Proceed.

---