Create dfs #7
Create dfs #7
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WalkthroughA new Python module introduces a Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Graph
User->>Graph: create Graph()
User->>Graph: addEdge(u, v) (multiple times)
User->>Graph: DFS(start_vertex)
Graph->>Graph: DFSUtil(start_vertex, visited)
loop For each reachable vertex
Graph->>Graph: Mark as visited, print vertex
Graph->>Graph: Recurse on adjacent unvisited vertices
end
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Summary of Changes
Hello @visz11, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request adds a foundational implementation of Depth First Search (DFS) in Python. It provides a reusable Graph class that can represent directed graphs using an adjacency list, along with the necessary methods to build and traverse such graphs using the DFS algorithm. The inclusion of a driver's code block makes it immediately runnable and demonstrates its intended usage.
Highlights
- New File:
dfs.py: This pull request introduces a new file,dfs.py, which contains a Python implementation of Depth First Search (DFS) for graph traversal. - Graph Class Implementation: A
Graphclass is defined, utilizing adefaultdictfor an adjacency list representation. It includes methods for initializing the graph (__init__), adding directed edges (addEdge), and performing the DFS traversal (DFS). - Recursive DFS Traversal: The
DFSmethod uses a recursive helper function,DFSUtil, to traverse the graph. It employs asetto keep track of visited nodes, preventing infinite loops in cyclic graphs and ensuring each node is processed once. - Example Usage: A
if __name__ == "__main__":block is included to demonstrate how to instantiate theGraphclass, add edges to form a sample graph, and execute the DFS traversal starting from a specified vertex (vertex 2 in the example).
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Actionable comments posted: 0
🧹 Nitpick comments (1)
dfs.py (1)
46-59: Add a newline after DFS output for better formatting.The sample usage correctly demonstrates the DFS functionality. Consider adding a newline after the DFS traversal for cleaner output formatting.
# Function call g.DFS(2) + print() # Add newline for better formatting
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dfs.py(1 hunks)
🔇 Additional comments (5)
dfs.py (5)
1-5: LGTM!The import statement and class definition are well-structured. Using
defaultdict(list)is an excellent choice for representing the adjacency list of a directed graph.
7-11: LGTM!The constructor properly initializes the graph using
defaultdict(list), which automatically handles new vertices without requiring explicit initialization.
14-16: LGTM!The
addEdgemethod correctly implements adding a directed edge by appending the destination vertex to the source vertex's adjacency list.
19-31: LGTM!The recursive DFS implementation is correct. It properly marks vertices as visited, prints them, and recursively visits all unvisited neighbors. The algorithm follows the standard depth-first search pattern.
34-43: LGTM!The main
DFSmethod properly initializes the visited set and delegates to the recursive helper. This separation of concerns makes the code clean and easy to understand.
🤖 Refacto.AI: PR Summary & Reviewer Guide🎯 1. The Goal (Why was this PR raised?)This PR implements a Depth-First Search (DFS) algorithm by adding a new Python file containing a Graph class with DFS traversal functionality. The goal appears to be adding a standard graph traversal algorithm implementation to the codebase. 🗺️ 2. The Changes (What was implemented?)
🤔 3. Key Areas for Human ReviewArea of Concern: Graph Data Structure Implementation
Area of Concern: DFS Algorithm Correctness
Area of Concern: Driver Code Test Case
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Code Review
The code introduces a Python script for Depth-First Search (DFS) on a directed graph. There are opportunities for improvement regarding Python conventions (PEP 8 & PEP 257), reusability, and correctness. The review suggests changing method names to snake_case, using docstrings for documentation, refactoring the implementation to use a generator, and renaming the DFS method to dfs_from_vertex to reflect its behavior.
| def DFS(self, v): | ||
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| # Create a set to store visited vertices | ||
| visited = set() | ||
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| # Call the recursive helper function | ||
| # to print DFS traversal | ||
| self.DFSUtil(v, visited) |
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This DFS implementation has two main issues:
- Correctness/Clarity: It only traverses the graph from a specific starting vertex
v. If the graph has multiple disconnected components, it will only visit the component containingv. The method nameDFSis misleading as it implies a full graph traversal. Renaming it todfs_from_vertexmakes its behavior explicit and the API clearer. - API Design: To work with the suggested generator-based
_dfs_util, this method should return the generator to the caller.
def dfs_from_vertex(self, v):
"""Performs DFS traversal starting from a given vertex.
Returns:
A generator that yields nodes in DFS order.
"""
# Create a set to store visited vertices for this traversal
visited = set()
# Return the generator from the helper function
return self._dfs_util(v, visited)| # This class represents a directed graph using | ||
| # adjacency list representation | ||
| class Graph: |
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According to Python's style guide PEP 257, it's standard practice to use docstrings ("""...""") for documenting classes, functions, and modules. This is more idiomatic than using a comment block above the class definition and allows tools to automatically generate documentation and users to get help via the help() function.
"""Represents a directed graph using an adjacency list."""| def addEdge(self, u, v): | ||
| self.graph[u].append(v) |
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Per Python's style guide PEP 8, method names should be in snake_case. Additionally, PEP 257 recommends using docstrings for documenting functions instead of comments above them.
def add_edge(self, u, v):
"""Adds an edge from vertex u to v."""| def DFSUtil(self, v, visited): | ||
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| # Mark the current node as visited | ||
| # and print it | ||
| visited.add(v) | ||
| print(v, end=' ') | ||
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| # Recur for all the vertices | ||
| # adjacent to this vertex | ||
| for neighbour in self.graph[v]: | ||
| if neighbour not in visited: | ||
| self.DFSUtil(neighbour, visited) |
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This method can be significantly improved in terms of reusability and Python conventions:
- Reusability: Printing directly to the console couples the traversal logic with a specific action. A more flexible design is to make this a generator that
yields each node. The caller can then decide what to do with the nodes (e.g., print them, collect them into a list). - Naming (PEP 8): Helper methods intended for internal use should be prefixed with an underscore (e.g.,
_dfs_util) and usesnake_case. - Documentation (PEP 257): The comment should be converted to a docstring.
def _dfs_util(self, v, visited):
"""A recursive generator for DFS traversal from a given vertex."""
visited.add(v)
yield v
# Recur for all the vertices adjacent to this vertex
for neighbour in self.graph[v]:
if neighbour not in visited:
yield from self._dfs_util(neighbour, visited)| if __name__ == "__main__": | ||
| g = Graph() | ||
| g.addEdge(0, 1) | ||
| g.addEdge(0, 2) | ||
| g.addEdge(1, 2) | ||
| g.addEdge(2, 0) | ||
| g.addEdge(2, 3) | ||
| g.addEdge(3, 3) | ||
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| print("Following is Depth First Traversal (starting from vertex 2)") | ||
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| # Function call | ||
| g.DFS(2) |
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This driver code needs to be updated to reflect the suggested changes to method names (add_edge, dfs_from_vertex) and to correctly handle the generator returned by the new DFS implementation.
if __name__ == "__main__":
g = Graph()
g.add_edge(0, 1)
g.add_edge(0, 2)
g.add_edge(1, 2)
g.add_edge(2, 0)
g.add_edge(2, 3)
g.add_edge(3, 3)
print("Following is Depth First Traversal (starting from vertex 2)")
# The dfs_from_vertex method returns a generator.
# We can unpack it with * to print all items.
traversal_generator = g.dfs_from_vertex(2)
print(*traversal_generator)
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PR already reviewed at the latest commit: c48efe2. |
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