Add solution and explanation for problem 3577: Count the Number of Computer Unlocking Permutations #114
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…mputer Unlocking Permutations
Reviewer's GuideImplements the accepted solution for problem 3577 by tightening the validity condition on complexities and adding a detailed English explanation document describing the O(n) factorial-based counting logic. Class diagram for Solution.countPermutations implementationclassDiagram
class Solution {
+countPermutations(complexity: list[int]) int
}
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WalkthroughAdded a new problem (3577) with explanation and Python solution, updating the type annotation from Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes
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Pre-merge checks and finishing touches❌ Failed checks (1 warning)
✅ Passed checks (2 passed)
✨ Finishing touches
🧪 Generate unit tests (beta)
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Actionable comments posted: 2
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Plan: Pro
📒 Files selected for processing (3)
data/book-sets.json(2 hunks)explanations/3577/en.md(1 hunks)solutions/3577/01.py(1 hunks)
🧰 Additional context used
🧬 Code graph analysis (1)
solutions/3577/01.py (1)
visualizations/3623/01.jsx (1)
MOD(39-39)
🪛 LanguageTool
explanations/3577/en.md
[style] ~57-~57: Using many exclamation marks might seem excessive (in this case: 7 exclamation marks for a text that’s 2668 characters long)
Context: ...resbyi` (since we're computing (n-1)!, and i ranges from 1 to n-1). **2.5 Re...
(EN_EXCESSIVE_EXCLAMATION)
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- GitHub Check: Sourcery review
🔇 Additional comments (3)
data/book-sets.json (1)
64-66: LGTM! Problem 3577 correctly added to the problem sets.The problem ID is properly placed in numerical sequence within the "All" problems list.
solutions/3577/01.py (1)
6-14: LGTM! Algorithm correctly implements the permutation counting logic.The solution efficiently validates that all computers can be unlocked (complexity[i] > complexity[0] for all i > 0) and computes (n-1)! modulo 10^9+7 when valid. The incremental factorial calculation with modulo arithmetic is correct and prevents integer overflow.
explanations/3577/en.md (1)
1-61: Excellent explanation with clear strategy and walkthrough.The documentation provides a comprehensive breakdown of the problem-solving approach, including:
- Complexity analysis
- Comparison of brute force vs. optimized strategy
- Step-by-step trace with a helpful table
- Clear reasoning for why (n-1)! is the answer
This will be very helpful for understanding the solution.
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| The goal is to count valid permutations where computers can be unlocked in order. Computer 0 is already unlocked. Each computer i > 0 can only be unlocked using a previously unlocked computer j where j < i and complexity[j] < complexity[i]. Since computer 0 is the root, all other computers must be unlockable using computer 0, which means they must all have complexity greater than computer 0. | ||
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| ![Visualization showing computer 0 as root with arrows to other computers that must have higher complexity] |
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Missing visualization image.
The markdown references an image that doesn't exist in the repository:
![Visualization showing computer 0 as root with arrows to other computers that must have higher complexity]
Either provide the image file or remove this line if the visualization isn't available yet.
Do you want me to generate sample code or suggestions for creating this visualization diagram?
🤖 Prompt for AI Agents
In explanations/3577/en.md around line 16 the markdown references a non-existent
image: the line "![Visualization showing computer 0 as root with arrows to other
computers that must have higher complexity]". Fix by either (A) adding the
missing image file to the repo at a relative path and updating the markdown to
point to that path (ensure the filename and extension match exactly and commit
the image), or (B) remove the image reference line if the visualization is not
available yet; if you add an image, keep a clear descriptive filename (e.g.,
explanations/3577/visualization.png) and commit it with the markdown change so
the link resolves.
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| class Solution: | ||
| def countPermutations(self, complexity: List[int]) -> int: | ||
| def countPermutations(self, complexity: list[int]) -> int: |
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🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
# Check Python version requirements in the repository
# Look for Python version specifications
echo "=== Checking pyproject.toml ==="
fd -t f '^pyproject.toml$' -x cat {}
echo -e "\n=== Checking setup.py ==="
fd -t f '^setup.py$' -x cat {}
echo -e "\n=== Checking .python-version ==="
fd -t f '^\.python-version$' -x cat {}
echo -e "\n=== Checking other Python files for type hint style ==="
rg -t py "from typing import List" -C 2Repository: romankurnovskii/leetcode-apps
Length of output: 11914
Use List[int] from typing module for consistency with codebase.
The type hint list[int] (PEP 585) requires Python 3.9+. The entire codebase consistently uses from typing import List with List[int] syntax. Update this method to follow the established pattern:
from typing import List
def countPermutations(self, complexity: List[int]) -> int:🤖 Prompt for AI Agents
In solutions/3577/01.py around line 2, the method signature uses the PEP 585
form `list[int]`; change it to use the codebase-consistent typing import by
adding `from typing import List` (if not already present) and update the
signature to `def countPermutations(self, complexity: List[int]) -> int:` so the
parameter type uses `List[int]`.
romankurnovskii
deleted the
problems-3577-3769-3753-3743-3739-3734-3733-3729-2728-3668-3637-3633-3606-3591-3582-3536
branch
2 participants
Problem 3577: Count the Number of Computer Unlocking Permutations
Status: ✅ Accepted (833/833 test cases passed)
Approach:
Note: Solutions for problems 3769, 3753, 3743, 3739, 3734, 3733, 3729, 2728, 3668, 3637, 3633, 3606, 3591, 3582, 3536 are written but need submission testing (LeetCode session expired). Will create separate PRs once solutions are accepted.
Summary by Sourcery
Add a validated counting solution and written explanation for problem 3577: Count the Number of Computer Unlocking Permutations.
New Features:
Enhancements:
Summary by CodeRabbit
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