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Zeng zrwusa@gmail.com"},"license":"MIT","homepage":"https://data-structure-typed-docs.vercel.app","keywords":["Directed Graph","directed graph","directedgraph","directed-graph","directed","Directed","digraph","javascript","java script","JavaScript","js","typescript","type script","TypeScript","ts","vertex","Vertex","node","Node","edge","Edge","graph theory","Graph Theory","graph structure","weighted","Weighted","unweighted","Unweighted","graph","adjacency","Adjacency","connectivity","path","cycle","acyclic","traversal","depth","Depth","breadth","Breadth","first","search","depth first search","dfs","DFS","breadth first search","breadth-first search","bfs","BFS","graph algorithms","graph representation","connectivity matrix","adjacency list","adjacency matrix","matrix","network","node degree","sparse graph","dense graph","directed cycle","directed acyclic graph","DAG","topologic","topological","sorting","strongly connected components","weighted digraph","directed weighted 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size](https://img.shields.io/bundlephobia/minzip/directed-graph-typed)\n![npm bundle size](https://img.shields.io/bundlephobia/min/directed-graph-typed)\n![npm](https://img.shields.io/npm/v/directed-graph-typed)\n\n# What\n\n## Brief\n\nThis is a standalone Directed Graph data structure from the data-structure-typed collection. If you wish to access more\ndata structures or advanced features, you can transition to directly installing the\ncomplete [data-structure-typed](https://www.npmjs.com/package/data-structure-typed) package\n\n# How\n\n## install\n\n### npm\n\n```bash\nnpm i directed-graph-typed --save\n```\n\n### yarn\n\n```bash\nyarn add directed-graph-typed\n```\n\n### snippet\n\n[//]: # (No deletion!!! Start of Example Replace Section)\n\n### basic DirectedGraph vertex and edge creation\n```typescript\n // Create a simple directed graph\n    const graph = new DirectedGraph<string>();\n\n    // Add vertices\n    graph.addVertex('A');\n    graph.addVertex('B');\n    graph.addVertex('C');\n\n    // Verify vertices exist\n    console.log(graph.hasVertex('A')); // true;\n    console.log(graph.hasVertex('B')); // true;\n    console.log(graph.hasVertex('C')); // true;\n    console.log(graph.hasVertex('D')); // false;\n\n    // Check vertex count\n    console.log(graph.size); // 3;\n```\n\n### DirectedGraph edge operations\n```typescript\n const graph = new DirectedGraph<string>();\n\n    // Add vertices\n    graph.addVertex('A');\n    graph.addVertex('B');\n    graph.addVertex('C');\n\n    // Add directed edges\n    graph.addEdge('A', 'B', 1);\n    graph.addEdge('B', 'C', 2);\n    graph.addEdge('A', 'C', 3);\n\n    // Verify edges exist\n    console.log(graph.hasEdge('A', 'B')); // true;\n    console.log(graph.hasEdge('B', 'C')); // true;\n    console.log(graph.hasEdge('C', 'B')); // false; // Graph is directed\n\n    // Get neighbors of A\n    const neighborsA = graph.getNeighbors('A');\n    console.log(neighborsA[0].key); // 'B';\n    console.log(neighborsA[1].key); // 'C';\n```\n\n### DirectedGraph dijkstra shortest path for network routing\n```typescript\n // Build a weighted directed graph representing network nodes and costs\n    const network = new DirectedGraph<string>();\n\n    // Add network nodes\n    network.addVertex('Router-A');\n    network.addVertex('Router-B');\n    network.addVertex('Router-C');\n    network.addVertex('Router-D');\n    network.addVertex('Router-E');\n\n    // Add weighted edges (network latency costs)\n    network.addEdge('Router-A', 'Router-B', 5);\n    network.addEdge('Router-A', 'Router-C', 10);\n    network.addEdge('Router-B', 'Router-D', 3);\n    network.addEdge('Router-C', 'Router-D', 2);\n    network.addEdge('Router-D', 'Router-E', 4);\n    network.addEdge('Router-B', 'Router-E', 12);\n\n    // Find shortest path from Router-A to Router-E\n    const { minDist, minPath } = network.dijkstra('Router-A', 'Router-E', true, true) || {\n      minDist: undefined,\n      minPath: undefined\n    };\n\n    // Verify shortest path is found\n    console.log(minDist); // defined;\n    console.log(minPath); // defined;\n\n    // Shortest path should be A -> B -> D -> E with cost 5+3+4=12\n    // Or A -> C -> D -> E with cost 10+2+4=16\n    // So the minimum is 12\n    console.log(minDist); // <= 16;\n\n    // Verify path is valid (includes start and end)\n    console.log(minPath?.[0].key); // 'Router-A';\n    console.log(minPath?.[minPath.length - 1].key); // 'Router-E';\n```\n\n[//]: # (No deletion!!! End of Example Replace Section)\n\n\n## API docs & Examples\n\n[API Docs](https://data-structure-typed-docs.vercel.app)\n\n[Live Examples](https://vivid-algorithm.vercel.app)\n\n<a href=\"https://github.com/zrwusa/vivid-algorithm\" target=\"_blank\">Examples Repository</a>\n\n## Data Structures\n\n<table>\n<thead>\n<tr>\n<th>Data Structure</th>\n<th>Unit Test</th>\n<th>Performance Test</th>\n<th>API Docs</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n<td>Directed Graph</td>\n<td><img src=\"https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg\" alt=\"\"></td>\n<td><img src=\"https://raw.githubusercontent.com/zrwusa/assets/master/images/data-structure-typed/assets/tick.svg\" alt=\"\"></td>\n<td><a href=\"https://data-structure-typed-docs.vercel.app/classes/DirectedGraph.html\"><span>DirectedGraph</span></a></td>\n</tr>\n</tbody>\n</table>\n\n## Standard library data structure comparison\n\n<table>\n  <thead>\n  <tr>\n    <th>Data Structure Typed</th>\n    <th>C++ STL</th>\n    <th>java.util</th>\n    <th>Python collections</th>\n  </tr>\n  </thead>\n  <tbody>\n  <tr>\n    <td>DirectedGraph&lt;V, E&gt;</td>\n    <td>-</td>\n    <td>-</td>\n    <td>-</td>\n  </tr>\n  </tbody>\n</table>\n\n## Benchmark\n\n[//]: # (No deletion!!! Start of Replace Section)\n<div class=\"json-to-html-collapse clearfix 0\">\n      <div class='collapsible level0' ><span class='json-to-html-label'>directed-graph</span></div>\n      <div class=\"content\"><table style=\"display: table; width:100%; table-layout: fixed;\"><tr><th>test name</th><th>time taken (ms)</th><th>executions per sec</th><th>sample deviation</th></tr><tr><td>1,000 addVertex</td><td>0.10</td><td>9534.93</td><td>8.72e-7</td></tr><tr><td>1,000 addEdge</td><td>6.30</td><td>158.67</td><td>0.00</td></tr><tr><td>1,000 getVertex</td><td>0.05</td><td>2.16e+4</td><td>3.03e-7</td></tr><tr><td>1,000 getEdge</td><td>22.31</td><td>44.82</td><td>0.00</td></tr><tr><td>tarjan</td><td>210.90</td><td>4.74</td><td>0.01</td></tr><tr><td>tarjan all</td><td>214.72</td><td>4.66</td><td>0.01</td></tr><tr><td>topologicalSort</td><td>172.52</td><td>5.80</td><td>0.00</td></tr></table></div>\n    </div>\n\n[//]: # (No deletion!!! End of Replace Section)\n\n## Built-in classic algorithms\n\n<table>\n  <thead>\n  <tr>\n    <th>Algorithm</th>\n    <th>Function Description</th>\n    <th>Iteration Type</th>\n  </tr>\n  </thead>\n  <tbody>\n  <tr>\n    <td>Graph DFS</td>\n    <td>Traverse a graph in a depth-first manner, starting from a given node, exploring along one path as deeply as\n      possible, and backtracking to explore other paths. Used for finding connected components, paths, etc.\n    </td>\n    <td>Recursion + Iteration</td>\n  </tr>\n  <tr>\n    <td>Graph BFS</td>\n    <td>Traverse a graph in a breadth-first manner, starting from a given node, first visiting nodes directly connected\n      to the starting node, and then expanding level by level. Used for finding shortest paths, etc.\n    </td>\n    <td>Recursion + Iteration</td>\n  </tr>\n  <tr>\n    <td>Graph Tarjan's Algorithm</td>\n    <td>Find strongly connected components in a graph, typically implemented using depth-first search.</td>\n    <td>Recursion</td>\n  </tr>\n  <tr>\n    <td>Graph Bellman-Ford Algorithm</td>\n    <td>Finding the shortest paths from a single source, can handle negative weight edges</td>\n    <td>Iteration</td>\n  </tr>\n  <tr>\n    <td>Graph Dijkstra's Algorithm</td>\n    <td>Finding the shortest paths from a single source, cannot handle negative weight edges</td>\n    <td>Iteration</td>\n  </tr>\n  <tr>\n    <td>Graph Floyd-Warshall Algorithm</td>\n    <td>Finding the shortest paths between all pairs of nodes</td>\n    <td>Iteration</td>\n  </tr>\n  <tr>\n    <td>Graph getCycles</td>\n    <td>Find all cycles in a graph or detect the presence of cycles.</td>\n    <td>Recursion</td>\n  </tr>\n  <tr>\n    <td>Graph getCutVertexes</td>\n    <td>Find cut vertices in a graph, which are nodes that, when removed, increase the number of connected components in\n      the graph.\n    </td>\n    <td>Recursion</td>\n  </tr>\n  <tr>\n    <td>Graph getSCCs</td>\n    <td>Find strongly connected components in a graph, which are subgraphs where any two nodes can reach each other.\n    </td>\n    <td>Recursion</td>\n  </tr>\n  <tr>\n    <td>Graph getBridges</td>\n    <td>Find bridges in a graph, which are edges that, when removed, increase the number of connected components in the\n      graph.\n    </td>\n    <td>Recursion</td>\n  </tr>\n  <tr>\n    <td>Graph topologicalSort</td>\n    <td>Perform topological sorting on a directed acyclic graph (DAG) to find a linear order of nodes such that all\n      directed edges go from earlier nodes to later nodes.\n    </td>\n    <td>Recursion</td>\n  </tr>\n  </tbody>\n</table>\n\n## Software Engineering Design Standards\n<table>\n    <tr>\n        <th>Principle</th>\n        <th>Description</th>\n    </tr>\n    <tr>\n        <td>Practicality</td>\n        <td>Follows ES6 and ESNext standards, offering unified and considerate optional parameters, and simplifies method names.</td>\n    </tr>\n    <tr>\n        <td>Extensibility</td>\n        <td>Adheres to OOP (Object-Oriented Programming) principles, allowing inheritance for all data structures.</td>\n    </tr>\n    <tr>\n        <td>Modularization</td>\n        <td>Includes data structure modularization and independent NPM packages.</td>\n    </tr>\n    <tr>\n        <td>Efficiency</td>\n        <td>All methods provide time and space complexity, comparable to native JS performance.</td>\n    </tr>\n    <tr>\n        <td>Maintainability</td>\n        <td>Follows open-source community development standards, complete documentation, continuous integration, and adheres to TDD (Test-Driven Development) patterns.</td>\n    </tr>\n    <tr>\n        <td>Testability</td>\n        <td>Automated and customized unit testing, performance testing, and integration testing.</td>\n    </tr>\n    <tr>\n        <td>Portability</td>\n        <td>Plans for porting to Java, Python, and C++, currently achieved to 80%.</td>\n    </tr>\n    <tr>\n        <td>Reusability</td>\n        <td>Fully decoupled, minimized side effects, and adheres to OOP.</td>\n    </tr>\n    <tr>\n        <td>Security</td>\n        <td>Carefully designed security for member variables and methods. Read-write separation. Data structure software does not need to consider other security aspects.</td>\n    </tr>\n    <tr>\n        <td>Scalability</td>\n        <td>Data structure software does not involve load issues.</td>\n    </tr>\n</table>\n\n\n\n","readmeFilename":"README.md"}