I was looking for a tree or graph data structure in C# but I guess there isn't one provided. An Extensive Examination of Data Structures Using C# 2.0 explains a bit about why. Is there a convenient library which is commonly used to provide this functionality? Perhaps through a strategy pattern to solve the issues presented in the article.
I feel a bit silly implementing my own tree, just as I would implementing my own ArrayList.
I just want a generic tree which can be unbalanced. Think of a directory tree. C5 looks nifty, but their tree structures seem to be implemented as balanced red-black trees better suited to search than representing a hierarchy of nodes.
This question is related to
c#
data-structures
The generally excellent C5 Generic Collection Library has several different tree-based data structures, including sets, bags and dictionaries. Source code is available if you want to study their implementation details. (I have used C5 collections in production code with good results, although I haven't used any of the tree structures specifically.)
Here's a Tree
public class Tree<T> : List<Tree<T>>
{
public T Data { get; private set; }
public Tree(T data)
{
this.Data = data;
}
}
Here's my own:
class Program
{
static void Main(string[] args)
{
var tree = new Tree<string>()
.Begin("Fastfood")
.Begin("Pizza")
.Add("Margherita")
.Add("Marinara")
.End()
.Begin("Burger")
.Add("Cheese burger")
.Add("Chili burger")
.Add("Rice burger")
.End()
.End();
tree.Nodes.ForEach(p => PrintNode(p, 0));
Console.ReadKey();
}
static void PrintNode<T>(TreeNode<T> node, int level)
{
Console.WriteLine("{0}{1}", new string(' ', level * 3), node.Value);
level++;
node.Children.ForEach(p => PrintNode(p, level));
}
}
public class Tree<T>
{
private Stack<TreeNode<T>> m_Stack = new Stack<TreeNode<T>>();
public List<TreeNode<T>> Nodes { get; } = new List<TreeNode<T>>();
public Tree<T> Begin(T val)
{
if (m_Stack.Count == 0)
{
var node = new TreeNode<T>(val, null);
Nodes.Add(node);
m_Stack.Push(node);
}
else
{
var node = m_Stack.Peek().Add(val);
m_Stack.Push(node);
}
return this;
}
public Tree<T> Add(T val)
{
m_Stack.Peek().Add(val);
return this;
}
public Tree<T> End()
{
m_Stack.Pop();
return this;
}
}
public class TreeNode<T>
{
public T Value { get; }
public TreeNode<T> Parent { get; }
public List<TreeNode<T>> Children { get; }
public TreeNode(T val, TreeNode<T> parent)
{
Value = val;
Parent = parent;
Children = new List<TreeNode<T>>();
}
public TreeNode<T> Add(T val)
{
var node = new TreeNode<T>(val, this);
Children.Add(node);
return node;
}
}
Output:
Fastfood
Pizza
Margherita
Marinara
Burger
Cheese burger
Chili burger
Rice burger
I have a little extension to the solutions.
Using a recursive generic declaration and a deriving subclass you can better concentrate on your actual target.
Notice, it's different from a non generic implementation, you don`t need to cast 'node' in 'NodeWorker'.
Here's my example:
public class GenericTree<T> where T : GenericTree<T> // recursive constraint
{
// no specific data declaration
protected List<T> children;
public GenericTree()
{
this.children = new List<T>();
}
public virtual void AddChild(T newChild)
{
this.children.Add(newChild);
}
public void Traverse(Action<int, T> visitor)
{
this.traverse(0, visitor);
}
protected virtual void traverse(int depth, Action<int, T> visitor)
{
visitor(depth, (T)this);
foreach (T child in this.children)
child.traverse(depth + 1, visitor);
}
}
public class GenericTreeNext : GenericTree<GenericTreeNext> // concrete derivation
{
public string Name {get; set;} // user-data example
public GenericTreeNext(string name)
{
this.Name = name;
}
}
static void Main(string[] args)
{
GenericTreeNext tree = new GenericTreeNext("Main-Harry");
tree.AddChild(new GenericTreeNext("Main-Sub-Willy"));
GenericTreeNext inter = new GenericTreeNext("Main-Inter-Willy");
inter.AddChild(new GenericTreeNext("Inter-Sub-Tom"));
inter.AddChild(new GenericTreeNext("Inter-Sub-Magda"));
tree.AddChild(inter);
tree.AddChild(new GenericTreeNext("Main-Sub-Chantal"));
tree.Traverse(NodeWorker);
}
static void NodeWorker(int depth, GenericTreeNext node)
{ // a little one-line string-concatenation (n-times)
Console.WriteLine("{0}{1}: {2}", String.Join(" ", new string[depth + 1]), depth, node.Name);
}
I create a Node class that could be helpfull for other people. The class has properties like:
There is also the possibility to convert a flat list of items with an Id and a ParentId to a tree. The nodes holds a reference to both the children and the parent, so that makes iterating nodes quite fast.
See http://quickgraph.codeplex.com/
QuickGraph provides generic directed/undirected graph datastructures and algorithms for .Net 2.0 and up. QuickGraph comes with algorithms such as depth first seach, breath first search, A* search, shortest path, k-shortest path, maximum flow, minimum spanning tree, least common ancestors, etc... QuickGraph supports MSAGL, GLEE, and Graphviz to render the graphs, serialization to GraphML, etc...
I've completed the code that @Berezh has shared.
public class TreeNode<T> : IEnumerable<TreeNode<T>>
{
public T Data { get; set; }
public TreeNode<T> Parent { get; set; }
public ICollection<TreeNode<T>> Children { get; set; }
public TreeNode(T data)
{
this.Data = data;
this.Children = new LinkedList<TreeNode<T>>();
}
public TreeNode<T> AddChild(T child)
{
TreeNode<T> childNode = new TreeNode<T>(child) { Parent = this };
this.Children.Add(childNode);
return childNode;
}
public IEnumerator<TreeNode<T>> GetEnumerator()
{
throw new NotImplementedException();
}
IEnumerator IEnumerable.GetEnumerator()
{
return (IEnumerator)GetEnumerator();
}
}
public class TreeNodeEnum<T> : IEnumerator<TreeNode<T>>
{
int position = -1;
public List<TreeNode<T>> Nodes { get; set; }
public TreeNode<T> Current
{
get
{
try
{
return Nodes[position];
}
catch (IndexOutOfRangeException)
{
throw new InvalidOperationException();
}
}
}
object IEnumerator.Current
{
get
{
return Current;
}
}
public TreeNodeEnum(List<TreeNode<T>> nodes)
{
Nodes = nodes;
}
public void Dispose()
{
}
public bool MoveNext()
{
position++;
return (position < Nodes.Count);
}
public void Reset()
{
position = -1;
}
}
If you would like to write your own, you can start with this six-part document detailing effective usage of C# 2.0 data structures and how to go about analyzing your implementation of data structures in C#. Each article has examples and an installer with samples you can follow along with.
“An Extensive Examination of Data Structures Using C# 2.0” by Scott Mitchell
Here is my implementation of BST
class BST
{
public class Node
{
public Node Left { get; set; }
public object Data { get; set; }
public Node Right { get; set; }
public Node()
{
Data = null;
}
public Node(int Data)
{
this.Data = (object)Data;
}
public void Insert(int Data)
{
if (this.Data == null)
{
this.Data = (object)Data;
return;
}
if (Data > (int)this.Data)
{
if (this.Right == null)
{
this.Right = new Node(Data);
}
else
{
this.Right.Insert(Data);
}
}
if (Data <= (int)this.Data)
{
if (this.Left == null)
{
this.Left = new Node(Data);
}
else
{
this.Left.Insert(Data);
}
}
}
public void TraverseInOrder()
{
if(this.Left != null)
this.Left.TraverseInOrder();
Console.Write("{0} ", this.Data);
if (this.Right != null)
this.Right.TraverseInOrder();
}
}
public Node Root { get; set; }
public BST()
{
Root = new Node();
}
}
The generally excellent C5 Generic Collection Library has several different tree-based data structures, including sets, bags and dictionaries. Source code is available if you want to study their implementation details. (I have used C5 collections in production code with good results, although I haven't used any of the tree structures specifically.)
delegate void TreeVisitor<T>(T nodeData);
class NTree<T>
{
private T data;
private LinkedList<NTree<T>> children;
public NTree(T data)
{
this.data = data;
children = new LinkedList<NTree<T>>();
}
public void AddChild(T data)
{
children.AddFirst(new NTree<T>(data));
}
public NTree<T> GetChild(int i)
{
foreach (NTree<T> n in children)
if (--i == 0)
return n;
return null;
}
public void Traverse(NTree<T> node, TreeVisitor<T> visitor)
{
visitor(node.data);
foreach (NTree<T> kid in node.children)
Traverse(kid, visitor);
}
}
Simple recursive implementation... < 40 lines of code... You just need to keep a reference to the root of the tree outside of the class, or wrap it in another class, maybe rename to TreeNode??
The generally excellent C5 Generic Collection Library has several different tree-based data structures, including sets, bags and dictionaries. Source code is available if you want to study their implementation details. (I have used C5 collections in production code with good results, although I haven't used any of the tree structures specifically.)
Yet another tree structure:
public class TreeNode<T> : IEnumerable<TreeNode<T>>
{
public T Data { get; set; }
public TreeNode<T> Parent { get; set; }
public ICollection<TreeNode<T>> Children { get; set; }
public TreeNode(T data)
{
this.Data = data;
this.Children = new LinkedList<TreeNode<T>>();
}
public TreeNode<T> AddChild(T child)
{
TreeNode<T> childNode = new TreeNode<T>(child) { Parent = this };
this.Children.Add(childNode);
return childNode;
}
... // for iterator details see below link
}
Sample usage:
TreeNode<string> root = new TreeNode<string>("root");
{
TreeNode<string> node0 = root.AddChild("node0");
TreeNode<string> node1 = root.AddChild("node1");
TreeNode<string> node2 = root.AddChild("node2");
{
TreeNode<string> node20 = node2.AddChild(null);
TreeNode<string> node21 = node2.AddChild("node21");
{
TreeNode<string> node210 = node21.AddChild("node210");
TreeNode<string> node211 = node21.AddChild("node211");
}
}
TreeNode<string> node3 = root.AddChild("node3");
{
TreeNode<string> node30 = node3.AddChild("node30");
}
}
BONUS
See fully-fledged tree with:
I have a little extension to the solutions.
Using a recursive generic declaration and a deriving subclass you can better concentrate on your actual target.
Notice, it's different from a non generic implementation, you don`t need to cast 'node' in 'NodeWorker'.
Here's my example:
public class GenericTree<T> where T : GenericTree<T> // recursive constraint
{
// no specific data declaration
protected List<T> children;
public GenericTree()
{
this.children = new List<T>();
}
public virtual void AddChild(T newChild)
{
this.children.Add(newChild);
}
public void Traverse(Action<int, T> visitor)
{
this.traverse(0, visitor);
}
protected virtual void traverse(int depth, Action<int, T> visitor)
{
visitor(depth, (T)this);
foreach (T child in this.children)
child.traverse(depth + 1, visitor);
}
}
public class GenericTreeNext : GenericTree<GenericTreeNext> // concrete derivation
{
public string Name {get; set;} // user-data example
public GenericTreeNext(string name)
{
this.Name = name;
}
}
static void Main(string[] args)
{
GenericTreeNext tree = new GenericTreeNext("Main-Harry");
tree.AddChild(new GenericTreeNext("Main-Sub-Willy"));
GenericTreeNext inter = new GenericTreeNext("Main-Inter-Willy");
inter.AddChild(new GenericTreeNext("Inter-Sub-Tom"));
inter.AddChild(new GenericTreeNext("Inter-Sub-Magda"));
tree.AddChild(inter);
tree.AddChild(new GenericTreeNext("Main-Sub-Chantal"));
tree.Traverse(NodeWorker);
}
static void NodeWorker(int depth, GenericTreeNext node)
{ // a little one-line string-concatenation (n-times)
Console.WriteLine("{0}{1}: {2}", String.Join(" ", new string[depth + 1]), depth, node.Name);
}
Here's mine, which is very similar to Aaron Gage's, just a little more conventional, in my opinion. For my purposes, I haven't ran into any performance issues with List<T>. It would be easy enough to switch to a LinkedList if needed.
namespace Overby.Collections
{
public class TreeNode<T>
{
private readonly T _value;
private readonly List<TreeNode<T>> _children = new List<TreeNode<T>>();
public TreeNode(T value)
{
_value = value;
}
public TreeNode<T> this[int i]
{
get { return _children[i]; }
}
public TreeNode<T> Parent { get; private set; }
public T Value { get { return _value; } }
public ReadOnlyCollection<TreeNode<T>> Children
{
get { return _children.AsReadOnly(); }
}
public TreeNode<T> AddChild(T value)
{
var node = new TreeNode<T>(value) {Parent = this};
_children.Add(node);
return node;
}
public TreeNode<T>[] AddChildren(params T[] values)
{
return values.Select(AddChild).ToArray();
}
public bool RemoveChild(TreeNode<T> node)
{
return _children.Remove(node);
}
public void Traverse(Action<T> action)
{
action(Value);
foreach (var child in _children)
child.Traverse(action);
}
public IEnumerable<T> Flatten()
{
return new[] {Value}.Concat(_children.SelectMany(x => x.Flatten()));
}
}
}
I've completed the code that @Berezh has shared.
public class TreeNode<T> : IEnumerable<TreeNode<T>>
{
public T Data { get; set; }
public TreeNode<T> Parent { get; set; }
public ICollection<TreeNode<T>> Children { get; set; }
public TreeNode(T data)
{
this.Data = data;
this.Children = new LinkedList<TreeNode<T>>();
}
public TreeNode<T> AddChild(T child)
{
TreeNode<T> childNode = new TreeNode<T>(child) { Parent = this };
this.Children.Add(childNode);
return childNode;
}
public IEnumerator<TreeNode<T>> GetEnumerator()
{
throw new NotImplementedException();
}
IEnumerator IEnumerable.GetEnumerator()
{
return (IEnumerator)GetEnumerator();
}
}
public class TreeNodeEnum<T> : IEnumerator<TreeNode<T>>
{
int position = -1;
public List<TreeNode<T>> Nodes { get; set; }
public TreeNode<T> Current
{
get
{
try
{
return Nodes[position];
}
catch (IndexOutOfRangeException)
{
throw new InvalidOperationException();
}
}
}
object IEnumerator.Current
{
get
{
return Current;
}
}
public TreeNodeEnum(List<TreeNode<T>> nodes)
{
Nodes = nodes;
}
public void Dispose()
{
}
public bool MoveNext()
{
position++;
return (position < Nodes.Count);
}
public void Reset()
{
position = -1;
}
}
See http://quickgraph.codeplex.com/
QuickGraph provides generic directed/undirected graph datastructures and algorithms for .Net 2.0 and up. QuickGraph comes with algorithms such as depth first seach, breath first search, A* search, shortest path, k-shortest path, maximum flow, minimum spanning tree, least common ancestors, etc... QuickGraph supports MSAGL, GLEE, and Graphviz to render the graphs, serialization to GraphML, etc...
If you would like to write your own, you can start with this six-part document detailing effective usage of C# 2.0 data structures and how to go about analyzing your implementation of data structures in C#. Each article has examples and an installer with samples you can follow along with.
“An Extensive Examination of Data Structures Using C# 2.0” by Scott Mitchell
Here's my own:
class Program
{
static void Main(string[] args)
{
var tree = new Tree<string>()
.Begin("Fastfood")
.Begin("Pizza")
.Add("Margherita")
.Add("Marinara")
.End()
.Begin("Burger")
.Add("Cheese burger")
.Add("Chili burger")
.Add("Rice burger")
.End()
.End();
tree.Nodes.ForEach(p => PrintNode(p, 0));
Console.ReadKey();
}
static void PrintNode<T>(TreeNode<T> node, int level)
{
Console.WriteLine("{0}{1}", new string(' ', level * 3), node.Value);
level++;
node.Children.ForEach(p => PrintNode(p, level));
}
}
public class Tree<T>
{
private Stack<TreeNode<T>> m_Stack = new Stack<TreeNode<T>>();
public List<TreeNode<T>> Nodes { get; } = new List<TreeNode<T>>();
public Tree<T> Begin(T val)
{
if (m_Stack.Count == 0)
{
var node = new TreeNode<T>(val, null);
Nodes.Add(node);
m_Stack.Push(node);
}
else
{
var node = m_Stack.Peek().Add(val);
m_Stack.Push(node);
}
return this;
}
public Tree<T> Add(T val)
{
m_Stack.Peek().Add(val);
return this;
}
public Tree<T> End()
{
m_Stack.Pop();
return this;
}
}
public class TreeNode<T>
{
public T Value { get; }
public TreeNode<T> Parent { get; }
public List<TreeNode<T>> Children { get; }
public TreeNode(T val, TreeNode<T> parent)
{
Value = val;
Parent = parent;
Children = new List<TreeNode<T>>();
}
public TreeNode<T> Add(T val)
{
var node = new TreeNode<T>(val, this);
Children.Add(node);
return node;
}
}
Output:
Fastfood
Pizza
Margherita
Marinara
Burger
Cheese burger
Chili burger
Rice burger
In case you need a rooted tree data structure implementation that uses less memory, you can write your Node class as follows (C++ implementation):
class Node {
Node* parent;
int item; // depending on your needs
Node* firstChild; //pointer to left most child of node
Node* nextSibling; //pointer to the sibling to the right
}
I am surprised nobody mentioned the possibility to use XML with Linq :
https://docs.microsoft.com/fr-fr/dotnet/standard/linq/create-xml-trees
XML is the most mature and flexible solution when it comes to using trees and Linq provides you with all the tools that you need. The configuration of your tree also gets much cleaner and user-friendly as you can simply use an XML file for the initialization.
If you need to work with objects, you can use XML serialization :
https://docs.microsoft.com/fr-fr/dotnet/standard/serialization/introducing-xml-serialization
If you would like to write your own, you can start with this six-part document detailing effective usage of C# 2.0 data structures and how to go about analyzing your implementation of data structures in C#. Each article has examples and an installer with samples you can follow along with.
“An Extensive Examination of Data Structures Using C# 2.0” by Scott Mitchell
delegate void TreeVisitor<T>(T nodeData);
class NTree<T>
{
private T data;
private LinkedList<NTree<T>> children;
public NTree(T data)
{
this.data = data;
children = new LinkedList<NTree<T>>();
}
public void AddChild(T data)
{
children.AddFirst(new NTree<T>(data));
}
public NTree<T> GetChild(int i)
{
foreach (NTree<T> n in children)
if (--i == 0)
return n;
return null;
}
public void Traverse(NTree<T> node, TreeVisitor<T> visitor)
{
visitor(node.data);
foreach (NTree<T> kid in node.children)
Traverse(kid, visitor);
}
}
Simple recursive implementation... < 40 lines of code... You just need to keep a reference to the root of the tree outside of the class, or wrap it in another class, maybe rename to TreeNode??
Try this simple sample.
public class TreeNode<TValue>
{
#region Properties
public TValue Value { get; set; }
public List<TreeNode<TValue>> Children { get; private set; }
public bool HasChild { get { return Children.Any(); } }
#endregion
#region Constructor
public TreeNode()
{
this.Children = new List<TreeNode<TValue>>();
}
public TreeNode(TValue value)
: this()
{
this.Value = value;
}
#endregion
#region Methods
public void AddChild(TreeNode<TValue> treeNode)
{
Children.Add(treeNode);
}
public void AddChild(TValue value)
{
var treeNode = new TreeNode<TValue>(value);
AddChild(treeNode);
}
#endregion
}
Tree With Generic Data
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Linq;
using System.Threading;
using System.Threading.Tasks;
public class Tree<T>
{
public T Data { get; set; }
public LinkedList<Tree<T>> Children { get; set; } = new LinkedList<Tree<T>>();
public Task Traverse(Func<T, Task> actionOnNode, int maxDegreeOfParallelism = 1) => Traverse(actionOnNode, new SemaphoreSlim(maxDegreeOfParallelism, maxDegreeOfParallelism));
private async Task Traverse(Func<T, Task> actionOnNode, SemaphoreSlim semaphore)
{
await actionOnNode(Data);
SafeRelease(semaphore);
IEnumerable<Task> tasks = Children.Select(async input =>
{
await semaphore.WaitAsync().ConfigureAwait(false);
try
{
await input.Traverse(actionOnNode, semaphore).ConfigureAwait(false);
}
finally
{
SafeRelease(semaphore);
}
});
await Task.WhenAll(tasks);
}
private void SafeRelease(SemaphoreSlim semaphore)
{
try
{
semaphore.Release();
}
catch (Exception ex)
{
if (ex.Message.ToLower() != "Adding the specified count to the semaphore would cause it to exceed its maximum count.".ToLower())
{
throw;
}
}
}
public async Task<IEnumerable<T>> ToList()
{
ConcurrentBag<T> lst = new ConcurrentBag<T>();
await Traverse(async (data) => lst.Add(data));
return lst;
}
public async Task<int> Count() => (await ToList()).Count();
}
Unit Tests
using System.Threading.Tasks;
using Xunit;
public class Tree_Tests
{
[Fact]
public async Task Tree_ToList_Count()
{
Tree<int> head = new Tree<int>();
Assert.NotEmpty(await head.ToList());
Assert.True(await head.Count() == 1);
// child
var child = new Tree<int>();
head.Children.AddFirst(child);
Assert.True(await head.Count() == 2);
Assert.NotEmpty(await head.ToList());
// grandson
child.Children.AddFirst(new Tree<int>());
child.Children.AddFirst(new Tree<int>());
Assert.True(await head.Count() == 4);
Assert.NotEmpty(await head.ToList());
}
[Fact]
public async Task Tree_Traverse()
{
Tree<int> head = new Tree<int>() { Data = 1 };
// child
var child = new Tree<int>() { Data = 2 };
head.Children.AddFirst(child);
// grandson
child.Children.AddFirst(new Tree<int>() { Data = 3 });
child.Children.AddLast(new Tree<int>() { Data = 4 });
int counter = 0;
await head.Traverse(async (data) => counter += data);
Assert.True(counter == 10);
counter = 0;
await child.Traverse(async (data) => counter += data);
Assert.True(counter == 9);
counter = 0;
await child.Children.First!.Value.Traverse(async (data) => counter += data);
Assert.True(counter == 3);
counter = 0;
await child.Children.Last!.Value.Traverse(async (data) => counter += data);
Assert.True(counter == 4);
}
}
Here's a Tree
public class Tree<T> : List<Tree<T>>
{
public T Data { get; private set; }
public Tree(T data)
{
this.Data = data;
}
}
Most trees are formed by the data you are processing.
Say you have a
personclass that includes details of someone’sparents, would you rather have the tree structure as part of your “domain class”, or use a separate tree class that contained links to your person objects? Think about a simple operation like getting all thegrandchildrenof aperson, should this code be in thepersonclass, or should the user of thepersonclass have to know about a separate tree class?
Another example is a parse tree in a compiler…
What both of these examples show is that the concept of a tree is part of the domain of the data and using a separate general purpose tree at least doubles the number of objects that are created as well as making the API harder to program again.
What we want is a way to reuse the standard tree operations, without having to re-implement them for all trees, while at the same time, not having to use a standard tree class. Boost has tried to solve this type of problem for C++, but I yet to see any effect for .NET get adapted.
Yet another tree structure:
public class TreeNode<T> : IEnumerable<TreeNode<T>>
{
public T Data { get; set; }
public TreeNode<T> Parent { get; set; }
public ICollection<TreeNode<T>> Children { get; set; }
public TreeNode(T data)
{
this.Data = data;
this.Children = new LinkedList<TreeNode<T>>();
}
public TreeNode<T> AddChild(T child)
{
TreeNode<T> childNode = new TreeNode<T>(child) { Parent = this };
this.Children.Add(childNode);
return childNode;
}
... // for iterator details see below link
}
Sample usage:
TreeNode<string> root = new TreeNode<string>("root");
{
TreeNode<string> node0 = root.AddChild("node0");
TreeNode<string> node1 = root.AddChild("node1");
TreeNode<string> node2 = root.AddChild("node2");
{
TreeNode<string> node20 = node2.AddChild(null);
TreeNode<string> node21 = node2.AddChild("node21");
{
TreeNode<string> node210 = node21.AddChild("node210");
TreeNode<string> node211 = node21.AddChild("node211");
}
}
TreeNode<string> node3 = root.AddChild("node3");
{
TreeNode<string> node30 = node3.AddChild("node30");
}
}
BONUS
See fully-fledged tree with:
Tree With Generic Data
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Linq;
using System.Threading;
using System.Threading.Tasks;
public class Tree<T>
{
public T Data { get; set; }
public LinkedList<Tree<T>> Children { get; set; } = new LinkedList<Tree<T>>();
public Task Traverse(Func<T, Task> actionOnNode, int maxDegreeOfParallelism = 1) => Traverse(actionOnNode, new SemaphoreSlim(maxDegreeOfParallelism, maxDegreeOfParallelism));
private async Task Traverse(Func<T, Task> actionOnNode, SemaphoreSlim semaphore)
{
await actionOnNode(Data);
SafeRelease(semaphore);
IEnumerable<Task> tasks = Children.Select(async input =>
{
await semaphore.WaitAsync().ConfigureAwait(false);
try
{
await input.Traverse(actionOnNode, semaphore).ConfigureAwait(false);
}
finally
{
SafeRelease(semaphore);
}
});
await Task.WhenAll(tasks);
}
private void SafeRelease(SemaphoreSlim semaphore)
{
try
{
semaphore.Release();
}
catch (Exception ex)
{
if (ex.Message.ToLower() != "Adding the specified count to the semaphore would cause it to exceed its maximum count.".ToLower())
{
throw;
}
}
}
public async Task<IEnumerable<T>> ToList()
{
ConcurrentBag<T> lst = new ConcurrentBag<T>();
await Traverse(async (data) => lst.Add(data));
return lst;
}
public async Task<int> Count() => (await ToList()).Count();
}
Unit Tests
using System.Threading.Tasks;
using Xunit;
public class Tree_Tests
{
[Fact]
public async Task Tree_ToList_Count()
{
Tree<int> head = new Tree<int>();
Assert.NotEmpty(await head.ToList());
Assert.True(await head.Count() == 1);
// child
var child = new Tree<int>();
head.Children.AddFirst(child);
Assert.True(await head.Count() == 2);
Assert.NotEmpty(await head.ToList());
// grandson
child.Children.AddFirst(new Tree<int>());
child.Children.AddFirst(new Tree<int>());
Assert.True(await head.Count() == 4);
Assert.NotEmpty(await head.ToList());
}
[Fact]
public async Task Tree_Traverse()
{
Tree<int> head = new Tree<int>() { Data = 1 };
// child
var child = new Tree<int>() { Data = 2 };
head.Children.AddFirst(child);
// grandson
child.Children.AddFirst(new Tree<int>() { Data = 3 });
child.Children.AddLast(new Tree<int>() { Data = 4 });
int counter = 0;
await head.Traverse(async (data) => counter += data);
Assert.True(counter == 10);
counter = 0;
await child.Traverse(async (data) => counter += data);
Assert.True(counter == 9);
counter = 0;
await child.Children.First!.Value.Traverse(async (data) => counter += data);
Assert.True(counter == 3);
counter = 0;
await child.Children.Last!.Value.Traverse(async (data) => counter += data);
Assert.True(counter == 4);
}
}
In case you need a rooted tree data structure implementation that uses less memory, you can write your Node class as follows (C++ implementation):
class Node {
Node* parent;
int item; // depending on your needs
Node* firstChild; //pointer to left most child of node
Node* nextSibling; //pointer to the sibling to the right
}
Here is my implementation of BST
class BST
{
public class Node
{
public Node Left { get; set; }
public object Data { get; set; }
public Node Right { get; set; }
public Node()
{
Data = null;
}
public Node(int Data)
{
this.Data = (object)Data;
}
public void Insert(int Data)
{
if (this.Data == null)
{
this.Data = (object)Data;
return;
}
if (Data > (int)this.Data)
{
if (this.Right == null)
{
this.Right = new Node(Data);
}
else
{
this.Right.Insert(Data);
}
}
if (Data <= (int)this.Data)
{
if (this.Left == null)
{
this.Left = new Node(Data);
}
else
{
this.Left.Insert(Data);
}
}
}
public void TraverseInOrder()
{
if(this.Left != null)
this.Left.TraverseInOrder();
Console.Write("{0} ", this.Data);
if (this.Right != null)
this.Right.TraverseInOrder();
}
}
public Node Root { get; set; }
public BST()
{
Root = new Node();
}
}
Most trees are formed by the data you are processing.
Say you have a
personclass that includes details of someone’sparents, would you rather have the tree structure as part of your “domain class”, or use a separate tree class that contained links to your person objects? Think about a simple operation like getting all thegrandchildrenof aperson, should this code be in thepersonclass, or should the user of thepersonclass have to know about a separate tree class?
Another example is a parse tree in a compiler…
What both of these examples show is that the concept of a tree is part of the domain of the data and using a separate general purpose tree at least doubles the number of objects that are created as well as making the API harder to program again.
What we want is a way to reuse the standard tree operations, without having to re-implement them for all trees, while at the same time, not having to use a standard tree class. Boost has tried to solve this type of problem for C++, but I yet to see any effect for .NET get adapted.
Because it isn't mentioned I would like you draw attention the now released .net code-base: specifically the code for a SortedSet that implements a Red-Black-Tree:
This is, however, a balanced tree structure. So my answer is more a reference to what I believe is the only native tree-structure in the .net core library.
I have added complete solution and example using NTree class above, also added "AddChild" method...
public class NTree<T>
{
public T data;
public LinkedList<NTree<T>> children;
public NTree(T data)
{
this.data = data;
children = new LinkedList<NTree<T>>();
}
public void AddChild(T data)
{
var node = new NTree<T>(data) { Parent = this };
children.AddFirst(node);
}
public NTree<T> Parent { get; private set; }
public NTree<T> GetChild(int i)
{
foreach (NTree<T> n in children)
if (--i == 0)
return n;
return null;
}
public void Traverse(NTree<T> node, TreeVisitor<T> visitor, string t, ref NTree<T> r)
{
visitor(node.data, node, t, ref r);
foreach (NTree<T> kid in node.children)
Traverse(kid, visitor, t, ref r);
}
}
public static void DelegateMethod(KeyValuePair<string, string> data, NTree<KeyValuePair<string, string>> node, string t, ref NTree<KeyValuePair<string, string>> r)
{
string a = string.Empty;
if (node.data.Key == t)
{
r = node;
return;
}
}
using
NTree<KeyValuePair<string, string>> ret = null;
tree.Traverse(tree, DelegateMethod, node["categoryId"].InnerText, ref ret);
I create a Node class that could be helpfull for other people. The class has properties like:
There is also the possibility to convert a flat list of items with an Id and a ParentId to a tree. The nodes holds a reference to both the children and the parent, so that makes iterating nodes quite fast.
If you would like to write your own, you can start with this six-part document detailing effective usage of C# 2.0 data structures and how to go about analyzing your implementation of data structures in C#. Each article has examples and an installer with samples you can follow along with.
“An Extensive Examination of Data Structures Using C# 2.0” by Scott Mitchell
Because it isn't mentioned I would like you draw attention the now released .net code-base: specifically the code for a SortedSet that implements a Red-Black-Tree:
This is, however, a balanced tree structure. So my answer is more a reference to what I believe is the only native tree-structure in the .net core library.
Here's mine, which is very similar to Aaron Gage's, just a little more conventional, in my opinion. For my purposes, I haven't ran into any performance issues with List<T>. It would be easy enough to switch to a LinkedList if needed.
namespace Overby.Collections
{
public class TreeNode<T>
{
private readonly T _value;
private readonly List<TreeNode<T>> _children = new List<TreeNode<T>>();
public TreeNode(T value)
{
_value = value;
}
public TreeNode<T> this[int i]
{
get { return _children[i]; }
}
public TreeNode<T> Parent { get; private set; }
public T Value { get { return _value; } }
public ReadOnlyCollection<TreeNode<T>> Children
{
get { return _children.AsReadOnly(); }
}
public TreeNode<T> AddChild(T value)
{
var node = new TreeNode<T>(value) {Parent = this};
_children.Add(node);
return node;
}
public TreeNode<T>[] AddChildren(params T[] values)
{
return values.Select(AddChild).ToArray();
}
public bool RemoveChild(TreeNode<T> node)
{
return _children.Remove(node);
}
public void Traverse(Action<T> action)
{
action(Value);
foreach (var child in _children)
child.Traverse(action);
}
public IEnumerable<T> Flatten()
{
return new[] {Value}.Concat(_children.SelectMany(x => x.Flatten()));
}
}
}
I have added complete solution and example using NTree class above, also added "AddChild" method...
public class NTree<T>
{
public T data;
public LinkedList<NTree<T>> children;
public NTree(T data)
{
this.data = data;
children = new LinkedList<NTree<T>>();
}
public void AddChild(T data)
{
var node = new NTree<T>(data) { Parent = this };
children.AddFirst(node);
}
public NTree<T> Parent { get; private set; }
public NTree<T> GetChild(int i)
{
foreach (NTree<T> n in children)
if (--i == 0)
return n;
return null;
}
public void Traverse(NTree<T> node, TreeVisitor<T> visitor, string t, ref NTree<T> r)
{
visitor(node.data, node, t, ref r);
foreach (NTree<T> kid in node.children)
Traverse(kid, visitor, t, ref r);
}
}
public static void DelegateMethod(KeyValuePair<string, string> data, NTree<KeyValuePair<string, string>> node, string t, ref NTree<KeyValuePair<string, string>> r)
{
string a = string.Empty;
if (node.data.Key == t)
{
r = node;
return;
}
}
using
NTree<KeyValuePair<string, string>> ret = null;
tree.Traverse(tree, DelegateMethod, node["categoryId"].InnerText, ref ret);
I am surprised nobody mentioned the possibility to use XML with Linq :
https://docs.microsoft.com/fr-fr/dotnet/standard/linq/create-xml-trees
XML is the most mature and flexible solution when it comes to using trees and Linq provides you with all the tools that you need. The configuration of your tree also gets much cleaner and user-friendly as you can simply use an XML file for the initialization.
If you need to work with objects, you can use XML serialization :
https://docs.microsoft.com/fr-fr/dotnet/standard/serialization/introducing-xml-serialization
Source: Stackoverflow.com