feat: add minTime solutions in Python, C++, and Go for LC problem #3604

[Speccy-Rom]

Summary by Sourcery

Introduce new solutions for "Minimum Time to Reach Destination in Directed Graph" (LeetCode 3604) in Python, C++, and Go, and update documentation to reflect these additions

New Features:

• Add Python implementation of the minTime function using a priority queue for LC problem 3604
• Add C++ implementation of the minTime function with a min-heap for LC problem 3604
• Add Go implementation of the minTime function with a priority queue for LC problem 3604

Documentation:

• Update README and README_EN to include the new Python, C++, and Go solutions

[sourcery-ai]

Reviewer's Guide

This PR introduces new implementations of the minTime function for LC problem doocs#3604 in Python, C++, and Go, each leveraging a priority-queue-based Dijkstra variant that respects edge time windows to compute the minimum travel time or return -1 if unreachable.

Class diagram for Go solution: minTime and supporting types

classDiagram
    class Item {
        int value
        int priority
        int index
    }
    class PriorityQueue {
        +Len() int
        +Less(i, j int) bool
        +Swap(i, j int)
        +Push(x any)
        +Pop() any
    }
    class minTime {
        +minTime(n int, edges [][]int) int
    }
    minTime ..> PriorityQueue : uses
    PriorityQueue o-- Item : holds

Loading

Class diagram for C++ solution: Solution class

classDiagram
    class Solution {
        - vector<vector<vector<int>>> adj
        - vector<int> sol
        - priority_queue<pair<int,int>, vector<pair<int,int>>, greater<>> pq
        - void pushNeighbours(int node, int curr)
        + int minTime(int n, vector<vector<int>>& edges)
    }

Loading

Class diagram for Python solution: Solution class

classDiagram
    class Solution {
        +minTime(n: int, edges: List[List[int]]) -> int
    }

Loading

File-Level Changes

Change	Details	Files
Implement Python version of minTime with time-constrained Dijkstra	Initialize minReachTime array and adjacency lists from edge inputs Use a min-heap to process nodes by current reach time Calculate wait time against edge start/end and update reach times accordingly	solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/README.md solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/README_EN.md solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/Solution.py
Implement C++ version of minTime with helper function and priority queue	Build nested vector adjacency list and sol vector initialized to INT_MAX Define pushNeighbours helper to evaluate and push valid edges Use a min-oriented priority_queue for earliest-time extraction Add atexit hooks to output runtime and memory placeholders	solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/README.md solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/README_EN.md solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/Solution.cpp
Implement Go version of minTime with custom heap.Interface types	Construct graph as slice of [3]int for each edge (v, start, end) Maintain dist slice with -1 as unreachable sentinel and initialize start node Define Item and PriorityQueue types implementing heap.Interface Perform Dijkstra-like loop with wait time calculation and priority queue updates	solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/README.md solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/README_EN.md solution/3600-3699/3604.Minimum Time to Reach Destination in Directed Graph/Solution.go

---

Tips and commands

Interacting with Sourcery

• Trigger a new review: Comment @sourcery-ai review on the pull request.
• Continue discussions: Reply directly to Sourcery's review comments.
• Generate a GitHub issue from a review comment: Ask Sourcery to create an
  issue from a review comment by replying to it. You can also reply to a
  review comment with @sourcery-ai issue to create an issue from it.
• Generate a pull request title: Write @sourcery-ai anywhere in the pull
  request title to generate a title at any time. You can also comment
  @sourcery-ai title on the pull request to (re-)generate the title at any time.
• Generate a pull request summary: Write @sourcery-ai summary anywhere in
  the pull request body to generate a PR summary at any time exactly where you
  want it. You can also comment @sourcery-ai summary on the pull request to
  (re-)generate the summary at any time.
• Generate reviewer's guide: Comment @sourcery-ai guide on the pull
  request to (re-)generate the reviewer's guide at any time.
• Resolve all Sourcery comments: Comment @sourcery-ai resolve on the
  pull request to resolve all Sourcery comments. Useful if you've already
  addressed all the comments and don't want to see them anymore.
• Dismiss all Sourcery reviews: Comment @sourcery-ai dismiss on the pull
  request to dismiss all existing Sourcery reviews. Especially useful if you
  want to start fresh with a new review - don't forget to comment
  @sourcery-ai review to trigger a new review!

Customizing Your Experience

Access your dashboard to:

• Enable or disable review features such as the Sourcery-generated pull request
  summary, the reviewer's guide, and others.
• Change the review language.
• Add, remove or edit custom review instructions.
• Adjust other review settings.

Getting Help

• Contact our support team for questions or feedback.
• Visit our documentation for detailed guides and information.
• Keep in touch with the Sourcery team by following us on X/Twitter, LinkedIn or GitHub.

[sourcery-ai]

Hey @Speccy-Rom - I've reviewed your changes - here's some feedback:

• Add the required imports (List, inf from math, and heapq) to the Python snippet so it’s runnable as-is.
• The C++ solver’s atexit hook writing to display_runtime.txt/display_memory.txt seems unrelated to the algorithm and could be removed or documented separately.
• You currently have two Go implementations (in the README and Solution.go); consider consolidating into a single source to reduce duplication.

Prompt for AI Agents

Please address the comments from this code review:
## Overall Comments
- Add the required imports (List, inf from math, and heapq) to the Python snippet so it’s runnable as-is.
- The C++ solver’s atexit hook writing to display_runtime.txt/display_memory.txt seems unrelated to the algorithm and could be removed or documented separately.
- You currently have two Go implementations (in the README and Solution.go); consider consolidating into a single source to reduce duplication.

---

Sourcery is free for open source - if you like our reviews please consider sharing them ✨

• X
• Mastodon
• LinkedIn
• Facebook

_{Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.}