YAGL is Yet Another Graph Library™ for storing and manipulating mathematical graphs. It can be used in a wide range of applications, from package managers that need to find the correct dependencies to network analysis.
⚠ Some components haven't thoroughly been tested yet. You are invited to try out this library and report any bugs in the issue tracker.
- Fully typed graph algorithms with support for adding your own
- Algorithms in this library can be paused to only provide part of the result
- Generic graph interface allowing you to define your own graph on which the algorithms will work
- Support for asynchronous iteration protocol, allowing data to be fetched as the algorithm continues.
Sorting a dependency graph
The following is an example of a simple graph with vertices numbered from 1 to 4.
If we want to know which node goes before the next, we can use this library to perform a toplogical sort, like so:
;console.logordered.next.value; // outputs 2// the rest of the items will not get calculated
If you want to force calculating all elements upfront you can make use of the spread operator:
console.log // [2, 1, 3, 4];
Using the asynchronus API
The following example demonstrates how to use the asynchronous version of the library to count how many people in a database are connected to one another either directly or indirectly:
|Path||Edge check||Add edge||Remove edge||Incoming||Outgoing|
To import a graph implementation, first specify if it should be directed and then if it should be labeled. Finally, use the name of the implementation converted in lowercase and underscores, like so:
|Name||Undirected||Directed||Labeled||Directed and labeled|
The algorithms are written using ES6 generators, which means that they incrementally perform calculations on-demand. This can be extremely useful if you e.g. only need the first strongly connected component in a graph, or only want to calculate the next task if the previous task has finished.
Performs a depth-first graph traversal starting at the given node. The nodes are traversed in pre-order, meaning that first the node itself is returned, and then its children are visited. Returns an Iterable that generates the next node that has been visited.
Performs a depth-first graph traversal starting at the given node. The nodes are traversed in post-order, meaning that first the children are visited, and then the node itself is returned. Returns an Iterable that generates the next node that has been visited.
Performs a breadth-first graph traversal starting at the given node. Returns an Iterable that generates the next node that has been visited.
Finds all nodes in the graph that do not have an ancestor. Takes
Returns an Iterable that generates the next root in unspecified order.
Finds all strongly connected components in a graph by going through all
nodes and edges. Takes
O(|E| + |V|) time. Returns an Iterable that
generates lists of nodes that are strongly connected to one another.
Quickly detect whether a given graph has cycles. In the worst case, this method
O(|E| + |V|) time, but it might return faster if there is a cycle.
Performs a topological sort on the graph. Also takes
O(|E| + |V|) time. Throws an error if the graph contains one or more cycles. Returns
an Iterable that generates the next dependency in reverse order.
Copyright 2019 Sam Vervaeck
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