How to display tree structure in python
Hi you may give itertree a try (I'm the author). Show The package goes in the direction of anytree package but with a bit different focus. The performance on huge trees (>100000 items) is much better and it deals with iterators to have effective filter mechanism.
The created tree can be rendered:
E.g. Filtering can be done like this: Tree represents the nodes connected by edges. It is a non-linear data structure. It has the following properties −
We create a tree data structure in python by using the concept os node discussed earlier. We designate one node as root node and then add more nodes as child nodes. Below is program to create the root node. Create RootWe just create a Node class and add assign a value to the node. This becomes tree with only a root node. Exampleclass Node: def __init__(self, data): self.left = None self.right = None self.data = data def PrintTree(self): print(self.data) root = Node(10) root.PrintTree() OutputWhen the above code is executed, it produces the following result − 10 Inserting into a TreeTo insert into a tree we use the same node class created above and add a insert class to it. The insert class compares the value of the node to the parent node and decides to add it as a left node or a right node. Finally the PrintTree class is used to print the tree. Exampleclass Node: def __init__(self, data): self.left = None self.right = None self.data = data def insert(self, data): # Compare the new value with the parent node if self.data: if data < self.data: if self.left is None: self.left = Node(data) else: self.left.insert(data) elif data > self.data: if self.right is None: self.right = Node(data) else: self.right.insert(data) else: self.data = data # Print the tree def PrintTree(self): if self.left: self.left.PrintTree() print( self.data), if self.right: self.right.PrintTree() # Use the insert method to add nodes root = Node(12) root.insert(6) root.insert(14) root.insert(3) root.PrintTree() OutputWhen the above code is executed, it produces the following result − 3 6 12 14 Traversing a TreeThe tree can be traversed by deciding on a sequence to visit each node. As we can clearly see we can start at a node then visit the left sub-tree first and right sub-tree next. Or we can also visit the right sub-tree first and left sub-tree next. Accordingly there are different names for these tree traversal methods. Tree Traversal AlgorithmsTraversal is a process to visit all the nodes of a tree and may print their values too. Because, all nodes are connected via edges (links) we always start from the root (head) node. That is, we cannot randomly access a node in a tree. There are three ways which we use to traverse a tree.
In-order TraversalIn this traversal method, the left subtree is visited first, then the root and later the right sub-tree. We should always remember that every node may represent a subtree itself. In the below python program, we use the Node class to create place holders for the root node as well as the left and right nodes. Then, we create an insert function to add data to the tree. Finally, the In-order traversal logic is implemented by creating an empty list and adding the left node first followed by the root or parent node. At last the left node is added to complete the In-order traversal. Please note that this process is repeated for each sub-tree until all the nodes are traversed. Exampleclass Node: def __init__(self, data): self.left = None self.right = None self.data = data # Insert Node def insert(self, data): if self.data: if data < self.data: if self.left is None: self.left = Node(data) else: self.left.insert(data) else data > self.data: if self.right is None: self.right = Node(data) else: self.right.insert(data) else: self.data = data # Print the Tree def PrintTree(self): if self.left: self.left.PrintTree() print( self.data), if self.right: self.right.PrintTree() # Inorder traversal # Left -> Root -> Right def inorderTraversal(self, root): res = [] if root: res = self.inorderTraversal(root.left) res.append(root.data) res = res + self.inorderTraversal(root.right) return res root = Node(27) root.insert(14) root.insert(35) root.insert(10) root.insert(19) root.insert(31) root.insert(42) print(root.inorderTraversal(root)) OutputWhen the above code is executed, it produces the following result − [10, 14, 19, 27, 31, 35, 42] Pre-order TraversalIn this traversal method, the root node is visited first, then the left subtree and finally the right subtree. In the below python program, we use the Node class to create place holders for the root node as well as the left and right nodes. Then, we create an insert function to add data to the tree. Finally, the Pre-order traversal logic is implemented by creating an empty list and adding the root node first followed by the left node. At last, the right node is added to complete the Pre-order traversal. Please note that, this process is repeated for each sub-tree until all the nodes are traversed. Exampleclass Node: def __init__(self, data): self.left = None self.right = None self.data = data # Insert Node def insert(self, data): if self.data: if data < self.data: if self.left is None: self.left = Node(data) else: self.left.insert(data) elif data > self.data: if self.right is None: self.right = Node(data) else: self.right.insert(data) else: self.data = data # Print the Tree def PrintTree(self): if self.left: self.left.PrintTree() print( self.data), if self.right: self.right.PrintTree() # Preorder traversal # Root -> Left ->Right def PreorderTraversal(self, root): res = [] if root: res.append(root.data) res = res + self.PreorderTraversal(root.left) res = res + self.PreorderTraversal(root.right) return res root = Node(27) root.insert(14) root.insert(35) root.insert(10) root.insert(19) root.insert(31) root.insert(42) print(root.PreorderTraversal(root)) OutputWhen the above code is executed, it produces the following result − [27, 14, 10, 19, 35, 31, 42] Post-order TraversalIn this traversal method, the root node is visited last, hence the name. First, we traverse the left subtree, then the right subtree and finally the root node. In the below python program, we use the Node class to create place holders for the root node as well as the left and right nodes. Then, we create an insert function to add data to the tree. Finally, the Post-order traversal logic is implemented by creating an empty list and adding the left node first followed by the right node. At last the root or parent node is added to complete the Post-order traversal. Please note that, this process is repeated for each sub-tree until all the nodes are traversed. Exampleclass Node: def __init__(self, data): self.left = None self.right = None self.data = data # Insert Node def insert(self, data): if self.data: if data < self.data: if self.left is None: self.left = Node(data) else: self.left.insert(data) else if data > self.data: if self.right is None: self.right = Node(data) else: self.right.insert(data) else: self.data = data # Print the Tree def PrintTree(self): if self.left: self.left.PrintTree() print( self.data), if self.right: self.right.PrintTree() # Postorder traversal # Left ->Right -> Root def PostorderTraversal(self, root): res = [] if root: res = self.PostorderTraversal(root.left) res = res + self.PostorderTraversal(root.right) res.append(root.data) return res root = Node(27) root.insert(14) root.insert(35) root.insert(10) root.insert(19) root.insert(31) root.insert(42) print(root.PostorderTraversal(root)) OutputWhen the above code is executed, it produces the following result − [10, 19, 14, 31, 42, 35, 27] How do you print tree structure in Python?To print all nodes of a tree using depth-first search, only few lines are required:. def printTree(root, level=0):. print(" " * level, root.x). for child in root.children:. printTree(child, level + 1). #tree = Node(..., children=[Node(...., ...), Node(...,....)] ... . printTree(tree). How do you represent a tree in Python data structure?First, we traverse the left subtree, then the right subtree and finally the root node. In the below python program, we use the Node class to create place holders for the root node as well as the left and right nodes. Then, we create an insert function to add data to the tree.
How do you draw tree structures in Python?Tree-plots in Python. Set Up Tree with igraph. Install igraph with pip install python-igraph .. Create Plotly Traces.. Create Text Inside the Circle via Annotations.. Add Axis Specifications and Create the Layout.. Reference.. Are trees used in Python?Because Python doesn't implement trees for us, we'll define them using dictionaries. Each node of the tree will be a dictionary that has two keys. The first key is the string "value", which maps to the value in the node.
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