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Manchester | 25-SDC-Nov | Rahwa Haile | Sprint 5 |implement laptop allocation #292

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Manchester | 25-SDC-Nov | Rahwa Haile | Sprint 5 |implement laptop allocation #292

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@RahwaZeslusHaile RahwaZeslusHaile commented Dec 8, 2025 •
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Manchester | 25-SDC-Nov | Rahwa Haile | Sprint 5 |implement laptop allocation

Learners, PR Template

Self checklist

  • I have titled my PR with Region | Cohort | FirstName LastName | Sprint | Assignment Title
  • My changes meet the requirements of the task
  • I have tested my changes
  • My changes follow the style guide

Changelist

Implement laptop allocation algorithm and detailed output

  • Added allocate_laptops function to assign laptops to people minimizing total sadness
  • Used brute-force permutations approach for small datasets
  • Updated Person dataclass to use tuple for preferred_operating_system (hashable)
  • Printed each person's allocated laptop with individual sadness score

Questions

This solution is good for small data, but it doesn't scale because permutations grow factorially. The SciPy/Hungarian way to solve the problem is polynomial time and stays fast even with more laptops/people. Which approach do you prefer for this version?
Please review my work — thank you!

@RahwaZeslusHaile RahwaZeslusHaile added the Needs Review Trainee to add when requesting review. PRs without this label will not be reviewed. label Dec 8, 2025
@OracPrime OracPrime added the Review in progress This review is currently being reviewed. This label will be replaced by "Reviewed" soon. label Jan 11, 2026
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OracPrime reviewed Jan 11, 2026
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You need an algorithm that scales. This one doesn't

sprint-5/laptop-allocation.py Outdated
best_assignment = None
lowest_sadness = float("inf")

for perm in permutations(laptops):
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I think you need to revisit this algorithm. If you have 20 laptops, how many iterations is this loop?

sprint-5/laptop-allocation.py Outdated
Laptop(4, "Apple", "MacBook Air", 13, OperatingSystem.MACOS),
Laptop(5, "Apple", "MacBook Pro", 16, OperatingSystem.MACOS),
Laptop(6, "Dell", "Latitude", 15, OperatingSystem.ARCH),
Laptop(7, "HP", "EliteBook", 13, OperatingSystem.MACOS),
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HP running MacOS? Cute :)

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@RahwaZeslusHaile RahwaZeslusHaile Jan 16, 2026

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I let HP join the macOS club for this dataset 😄 I’ll switch it to a more realistic OS

.gitignore Outdated
@@ -1 +1,2 @@
node_modules
.venv
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While it's correct to gitignore .venv, if you've had to create a venv you should probably commit a requirements.txt that describes it.

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@RahwaZeslusHaile RahwaZeslusHaile Jan 16, 2026

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Thank you @OracPrime . Agreed — I’ll generate and commit a requirements.txt so the environment can be reproduced

@OracPrime OracPrime added Reviewed Volunteer to add when completing a review with trainee action still to take. and removed Needs Review Trainee to add when requesting review. PRs without this label will not be reviewed. Review in progress This review is currently being reviewed. This label will be replaced by "Reviewed" soon. labels Jan 11, 2026
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RahwaZeslusHaile commented Jan 16, 2026

Yes, you are right @OracPrime — I considered scalability, but assumed the input would remain limited to 8 for this sprint. For larger sets, I will replace the brute-force permutation approach with an optimal algorithm such as the Hungarian algorithm.Thank you

@RahwaZeslusHaile
Refactor laptop allocation: optimize algorithm for scalability, fix H…
2b38492 
…P/MacOS data, add requirements.txt, and implement full unit tests
@RahwaZeslusHaile RahwaZeslusHaile added the Needs Review Trainee to add when requesting review. PRs without this label will not be reviewed. label Jan 16, 2026
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