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VincentArak and others added 3 commits

December 15, 2025 16:13


 add dinic.py in networking_flow folder

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 add doctest

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networking_flow/dinic.py Outdated

class Dinic:

def __init__(self, n: int):

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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide descriptive name for the parameter: n

self.graph = [[] for _ in range(n)]

self.level = []

def add_edge(self, u: int, v: int, capacity: int) -> None:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function add_edge

Please provide descriptive name for the parameter: u

Please provide descriptive name for the parameter: v

# Backward edge: [u, 0, index_of_forward_edge]

self.graph[v].append([u, 0, len(self.graph[u]) - 1])

def bfs(self, source: int, sink: int) -> bool:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function bfs

networking_flow/dinic.py Outdated

return self.level[sink] >= 0

def dfs(self, u: int, sink: int, flow: int, ptr: list) -> int:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function dfs

Please provide descriptive name for the parameter: u

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VincentArak added 3 commits

December 15, 2025 17:54


 add ISAP (Improved Shortest Augmenting Path) Algorithm for Maximum Flow.

45ea549


 Revert "add doctest"

8c968b0

This reverts commit e85f71a.


 Revert "add ISAP (Improved Shortest Augmenting Path) Algorithm for Ma...

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...ximum Flow."
This reverts commit 45ea549.
revert ISAP

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networking_flow/dinic.py Outdated

class Dinic:

def __init__(self, n: int):

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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide descriptive name for the parameter: n

self.graph = [[] for _ in range(n)]

self.level = []

def add_edge(self, u: int, v: int, capacity: int) -> None:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function add_edge

Please provide descriptive name for the parameter: u

Please provide descriptive name for the parameter: v

# Backward edge: [u, 0, index_of_forward_edge]

self.graph[v].append([u, 0, len(self.graph[u]) - 1])

def bfs(self, source: int, sink: int) -> bool:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function bfs

networking_flow/dinic.py Outdated

return self.level[sink] >= 0

def dfs(self, u: int, sink: int, flow: int, ptr: list) -> int:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function dfs

Please provide descriptive name for the parameter: u

# RETREAT step: If no flow can be pushed, this node is dead for this phase.

return 0

def max_flow(self, source: int, sink: int) -> int:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function max_flow


 add doctest

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Repository:

Contributing guidelines

Project Euler solution guidelines

Python:

Formatted string literals (f-strings)

Type hints

doctest

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pytest

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networking_flow/dinic.py Outdated

class Dinic:

def __init__(self, n: int):

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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:

Please provide descriptive name for the parameter: n

self.graph = [[] for _ in range(n)]

self.level = []

def add_edge(self, u: int, v: int, capacity: int) -> None:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function add_edge

Please provide descriptive name for the parameter: u

Please provide descriptive name for the parameter: v

# Backward edge: [u, 0, index_of_forward_edge]

self.graph[v].append([u, 0, len(self.graph[u]) - 1])

def bfs(self, source: int, sink: int) -> bool:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function bfs

networking_flow/dinic.py Outdated

return self.level[sink] >= 0

def dfs(self, u: int, sink: int, flow: int, ptr: list) -> int:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function dfs

Please provide descriptive name for the parameter: u

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@algorithms-keeper algorithms-keeper bot added tests are failing and removed tests are failing labels

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Great implementation of Dinic's Algorithm for Maximum Flow! The algorithm is correctly implemented and the comments explain the approach well.

Feedback:

The algorithm correctly uses BFS to build level graphs and DFS to find blocking flows
Time complexity O(V^2 * E) is optimal for dense graphs
Code structure is clean and follows the project conventions

Minor suggestions:

Consider adding more detailed docstrings with parameter descriptions
Add type hints for better code clarity
Include complexity analysis in the docstring

Overall, this is a solid contribution that adds value to the algorithms collection.

VincentArak and others added 2 commits

December 15, 2025 19:14


 Address reviewer feedback: update docstrings and type hints

eb72b1e

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VincentArak commented Dec 15, 2025

Great implementation of Dinic's Algorithm for Maximum Flow! The algorithm is correctly implemented and the comments explain the approach well.

Feedback:

The algorithm correctly uses BFS to build level graphs and DFS to find blocking flows

Time complexity O(V^2 * E) is optimal for dense graphs

Code structure is clean and follows the project conventions

Minor suggestions:

Consider adding more detailed docstrings with parameter descriptions

Add type hints for better code clarity

Include complexity analysis in the docstring

Overall, this is a solid contribution that adds value to the algorithms collection.

Thanks again for the review!

I've just pushed the updates based on your feedback:

Added detailed Args and Returns sections to docstrings.
Updated type hints to be more specific (e.g., list[int]).
Added time complexity analysis to the max_flow docstring.

Please let me know if there's anything else needed! 🚀

@VincentArak VincentArak requested a review from shivaganesht

December 15, 2025 11:18

@algorithms-keeper algorithms-keeper bot added tests are failing and removed tests are failing labels

mindaugl

mindaugl approved these changes


 pass the mypy test

a3d9507

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 pass the mypy test, and fix the little bug

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Repository:

Contributing guidelines

Project Euler solution guidelines

Python:

Formatted string literals (f-strings)

Type hints

doctest

unittest

pytest

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Implements Dinic's Algorithm for finding the Maximum Flow in a flow network.

"""

def __init__(self, n: int) -> None:

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Please provide descriptive name for the parameter: n

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@VincentArak VincentArak Dec 16, 2025

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In the context of graph algorithms, n is the standard convention for representing the number of vertices, similar to how i is used in loops. It is widely understood in this domain and changing it might actually reduce readability for those familiar with the algorithm.

self.graph: list[list[list[int]]] = [[] for _ in range(n)]

self.level: list[int] = []

def add_edge(self, u: int, v: int, capacity: int) -> None:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function add_edge

Please provide descriptive name for the parameter: u

Please provide descriptive name for the parameter: v

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@VincentArak VincentArak Dec 16, 2025

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Regarding parameters u and v: These are universally recognized standard notations for the start and end nodes of an edge in graph theory.

Regarding the doctest: This is a helper method. Its functionality is implicitly and fully verified by the comprehensive doctests in the max_flow method, which relies on add_edge to construct the graph correctly.

# Backward edge: [u, 0, index_of_forward_edge]

self.graph[v].append([u, 0, len(self.graph[u]) - 1])

def bfs(self, source: int, sink: int) -> bool:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function bfs

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@VincentArak VincentArak Dec 16, 2025

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This bfs function is an internal component of the Dinic algorithm. I have included comprehensive doctests in the main max_flow function. If those tests pass, it proves that the internal components (like bfs) are functioning correctly.

return self.level[sink] >= 0

def dfs(self, u: int, sink: int, flow: int, ptr: list[int]) -> int:

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As there is no test file in this pull request nor any test function or class in the file networking_flow/dinic.py, please provide doctest for the function dfs

Please provide descriptive name for the parameter: u

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@VincentArak VincentArak Dec 16, 2025

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Similar to bfs, this dfs function is an internal helper verified integrally by the max_flow doctests. u is the standard notation for the current node being visited in graph traversal algorithms.

@algorithms-keeper algorithms-keeper bot removed the tests are failing label