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Kelleher"},"license":"MIT","homepage":"https://github.com/datavis-tech/graph-data-structure#readme","keywords":["graph","data","structures","algorithms"],"repository":{"type":"git","url":"git+https://github.com/datavis-tech/graph-data-structure.git"},"description":"A graph data structure with topological sort.","contributors":[{"name":"Jonathan MASSUCHETTI","email":"jonathan.massuchetti@dappit.fr","url":"https://github.com/JesusTheHun"}],"maintainers":[{"name":"curran","email":"curran.kelleher@gmail.com"}],"readme":"# graph-data-structure\n\nA [graph data structure](<https://en.wikipedia.org/wiki/Graph_(abstract_data_type)>) with [topological sort](https://en.wikipedia.org/wiki/Topological_sorting).\n\nThis library provides a minimalist implementation of a directed graph data structure. Nodes are represented by unique strings or any other object. Internally, an [adjacency list](https://en.wikipedia.org/wiki/Adjacency_list) is used to represent nodes and edges.\n\nThe primary use case for this library is in implementing [dataflow programming](https://en.wikipedia.org/wiki/Dataflow_programming) or [reactive programming](https://en.wikipedia.org/wiki/Reactive_programming). The key algorithm necessary for these is topological sorting, to get an ordering of nodes such that for each edge (**u** -> **v**), **u** comes before **v** in the sorted order. The topological sorting algorithm exposed here has modifications useful for computing the order in which functions in a data flow graph should be executed, namely specifying source nodes for propagation and specifying to exclude the source nodes themselves from the result.\n\n**Table of Contents**\n\n- [Installing](#installing)\n- [Examples](#examples)\n  - [ABC](#abc)\n  - [Getting Dressed](#getting-dressed)\n- [API Reference](#api-reference)\n\n## Installing\n\nThis library is distributed only via [NPM](npmjs.com). Install by running\n\n`npm install graph-data-structure`\n\nRequire it in your code like this.\n\n```javascript\nimport {\n  Graph,\n  serializeGraph,\n  deserializeGraph,\n  topologicalSort,\n  shortestPath,\n} from 'graph-data-structure';\n```\n\n## Examples\n\n### ABC\n\nStart by creating a new **[Graph](#graph)** object.\n\n```javascript\nvar graph = new Graph();\n```\n\nAdd some nodes and edges with **[addNode](#add-node)** and **[addEdge](#add-edge)**.\n\n```javascript\ngraph.addNode('a');\ngraph.addNode('b');\ngraph.addEdge('a', 'b');\n```\n\nNodes are added implicitly when edges are added.\n\n```javascript\ngraph.addEdge('b', 'c');\n```\n\nNow we have the following graph. <img src=\"https://cloud.githubusercontent.com/assets/68416/15385597/44a10522-1dc0-11e6-9054-2150f851db46.png\">\n\n[Topological sorting](https://en.wikipedia.org/wiki/Topological_sorting) can be done by invoking the standalone function **[topologicalSort](#topological-sort)** like this.\n\n```javascript\ntopologicalSort(graph); // Returns [\"a\", \"b\", \"c\"]\n```\n\n### Getting Dressed\n\nHere's an example of topological sort with getting dressed (from Cormen et al. \"Introduction to Algorithms\" page 550).\n\n<p align=\"center\">\n  <img src=\"https://cloud.githubusercontent.com/assets/68416/15385742/36f76410-1dc1-11e6-9fac-a8e41379c795.png\">\n</p>\n\n```javascript\nconst graph = new Graph();\ngraph\n  .addEdge('socks', 'shoes')\n  .addEdge('shirt', 'belt')\n  .addEdge('shirt', 'tie')\n  .addEdge('tie', 'jacket')\n  .addEdge('belt', 'jacket')\n  .addEdge('pants', 'shoes')\n  .addEdge('underpants', 'pants')\n  .addEdge('pants', 'belt');\n\n// prints [ \"underpants\", \"pants\", \"shirt\", \"tie\", \"belt\", \"jacket\", \"socks\", \"shoes\" ]\nconsole.log(topologicalSort(graph));\n```\n\nFor more detailed example code that shows more methods, have a look at the [tests](https://github.com/datavis-tech/graph-data-structure/blob/master/test.js).\n\n## API Reference\n\n- [Creating a Graph](#creating-a-graph)\n- [Adding and Removing Nodes](#adding-and-removing-nodes)\n- [Adding and Removing Edges](#adding-and-removing-edges)\n- [Querying the Graph](#querying-the-graph)\n- [Serialization](#serialization)\n- [Graph Algorithms](#graph-algorithms)\n\n### Creating a Graph\n\n<a name=\"graph\" href=\"#graph\">#</a> <b>Graph</b>([<i>serialized</i>])\n\nConstructs an instance of the graph data structure.\n\nThe optional argument _serialized_ is a serialized graph that may have been generated by **[serializeGraph](#serializeGraph)**. If _serialized_ is present, it is deserialized by invoking **[deserializeGraph(mySerializedObject)](#deserializeGraph)**.\n\n### Adding and Removing Nodes\n\n<a name=\"add-node\" href=\"#add-node\">#</a> <i>graph</i>.<b>addNode</b>(<i>node</i>)\n\nAdds a node to the graph. Returns _graph_ to support method chaining. If the given _node_ was already added to the graph, this function does nothing.\n\n<a name=\"remove-node\" href=\"#remove-node\">#</a> <i>graph</i>.<b>removeNode</b>(<i>node</i>)\n\nRemoves the specified node. Returns _graph_ to support method chaining. The argument _node_ is a string or object identifier for the node to remove. This function also removes all edges connected to the specified node, both incoming and outgoing.\n\n**Note:** You have to remove them using the exact same reference as when they were created. One can use getNode() to retrieve such reference.\n\n### Adding and Removing Edges\n\n<a name=\"add-edge\" href=\"#add-edge\">#</a> <i>graph</i>.<b>addEdge</b>(<i>u</i>, <i>v</i>[,<i>weight</i>])\n\nAdds an edge from node _u_ to node _v_. Returns _graph_ to support method chaining. The arguments _u_ and _v_ are node references (either objects or strings). This function also adds _u_ and _v_ as nodes if they were not already added.\n\nThe last argument _weight_ (optional) specifies the weight of this edge.\n\n<a name=\"remove-edge\" href=\"#remove-edge\">#</a> <i>graph</i>.<b>removeEdge</b>(<i>u</i>, <i>v</i>)\n\nRemoves the edge from node _u_ to node _v_. Returns _graph_ to support method chaining. The arguments _u_ and _v_ are node references. This function does not remove the nodes _u_ and _v_. Does nothing if the edge does not exist.\n\n<a name=\"has-edge\" href=\"#has-edge\">#</a> <i>graph</i>.<b>hasEdge</b>(<i>u</i>, <i>v</i>)\n\nReturns `true` if there exists an edge from node _u_ to node _v_. Returns `false` otherwise.\n\n### Working with Edge Weights\n\n<a name=\"set-edge-weight\" href=\"#set-edge-weight\">#</a> <i>graph</i>.<b>setEdgeWeight</b>(<i>u</i>, <i>v</i>, <i>weight</i>)\n\nSets the _weight_ (a number) of the edge from node _u_ to node _v_.\n\n<a name=\"get-edge-weight\" href=\"#get-edge-weight\">#</a> <i>graph</i>.<b>getEdgeWeight</b>(<i>u</i>, <i>v</i>)\n\nGets the _weight_ of the edge from node _u_ to node _v_. If no weight was previously set on this edge, then the value 1 is returned.\n\n### Querying the Graph\n\n<a name=\"adjacent\" href=\"#adjacent\">#</a> <i>graph</i>.<b>adjacent</b>(<i>node</i>)\n\nGets the adjacent node list for the specified node. The argument _node_ is a node reference (object or string). Returns a `Set` of adjacent node references or `undefined` if the node is not found.\n\n### Serialization\n\n<a name=\"serializeGraph\" href=\"#serializeGraph\">#</a> <b>serializeGraph</b>(<i>graph</i>)\n\nSerializes the graph. Returns an object with the following properties.\n\n- `nodes` An array of objects, each representing a node reference.\n- `links` An array of objects representing edges, each with the following properties.\n  - `source` The node reference of the source node (**u**).\n  - `target` The node reference of the target node (**v**).\n  - `weight` The weight of the edge between the source and target nodes.\n\nHere's example code for serializing a graph.\n\n```javascript\nvar graph = new Graph();\ngraph.addEdge('a', 'b');\ngraph.addEdge('b', 'c');\nvar serialized = serializeGraph(graph);\n```\n\n<a name=\"deserializeGraph\" href=\"#deserializeGraph\">#</a> <b>deserializeGraph</b>(<i>serialized</i>)\n\nDeserializes the given serialized graph. Returns a new _graph_. The argument _serialized_ is a graph representation with the structure described in **[serializeGraph](#serializeGraph)**.\n\n### Graph Algorithms\n\n<a name=\"topological-sort\" href=\"#topological-sort\">#</a> <b>topologicalSort</b>(<i>graph</i>)\n\nPerforms [Topological Sort](\n\nhttps://en.wikipedia.org/wiki/Topological_sorting). Returns an array of node identifier strings. The returned array includes nodes in topologically sorted order. This means that for each visited edge (**u** -> **v**), **u** comes before **v** in the topologically sorted order.\n\nNote: this function raises a `CycleError` when the input is not a DAG.\n\n<a name=\"shortest-path\" href=\"#shortest-path\">#</a> <b>shortestPath</b>(<i>graph</i>, <i>sourceNode</i>, <i>destinationNode</i>)\n\nPerforms [Dijkstra's Algorithm](https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm). Returns an object with two properties: `nodes`, an array of node references representing the path, and `weight`, the total weight of the path.\n\n```javascript\nvar result = shortestPath(graph, 'a', 'c');\nconsole.log(result.nodes); // Prints the array of nodes in the shortest path\nconsole.log(result.weight); // Prints the total weight of the path\n```\n\n<a name=\"shortest-path\" href=\"#shortest-path\">#</a> <b>shortestPath</b>(<i>graph</i>, <i>sourceNode</i>, <i>destinationNode</i>, <i>nextWeightFn</i>)\n\nCalculates the weight based on the custom function.\n\n```javascript\nimport type { NextWeightFnParams } from '../../types.js';\nfunction multiplyWeightFunction(wp: NextWeightFnParams): number {\n    if (wp.currentPathWeight === undefined) {\n        return wp.edgeWeight;\n    }\n    return wp.edgeWeight * wp.currentPathWeight;\n}\nvar result = shortestPath(graph, 'a', 'c', multiplyWeightFunction);\nconsole.log(result.nodes); // Prints the array of nodes in the shortest path\nconsole.log(result.weight); // Prints the total weight of the path\n```\n\n<p align=\"center\">\n  <a href=\"https://datavis.tech/\">\n    <img src=\"https://cloud.githubusercontent.com/assets/68416/15298394/a7a0a66a-1bbc-11e6-9636-367bed9165fc.png\">\n  </a>\n</p>\n```\n","readmeFilename":"README.md","users":{"heuert":true,"dgolovin":true,"mihaimetal":true,"saturnfive":true}}