A algorithmic tookit for working with trees in Python

## Project description

`AlgoTree` is a Python package for working with tree structures, including FlatForest and TreeNode representations.

## Introduction

Welcome to the documentation for the `AlgoTree` package. This package provides a suite of utilities for working with tree-like data structures in Python. It supports various tree representations, including:

FlatForest and FlatForestNode for working with flat forest and tree structures

TreeNode for recursive tree structures

Conversion utilities to convert between different tree representations

Utility functions for common tree operations

It also comes with a command-line tool jt that exposes most of the functionality:

Can be used to create, manipulate, query, and visualize trees

It’s like jq but for trees

Uses piping and redirection to make it easy to compose commands

## Getting Started

To install the AlgoTree package, you can use pip:

`pip install AlgoTree`

Once installed, you can start using the various tree structures and utilities provided by the package. Here is a quick example to get you started:

```
from AlgoTree.flat_forest_node import FlatForestNode
from AlgoTree.pretty_tree import pretty_tree
root = FlatForestNode(name="root", data=0)
node1 = FlatForestNode(name="node1", parent=root, data=1)
node2 = FlatForestNode(name="node2", parent=root, data=2)
node3 = FlatForestNode(name="node3", parent=node2, data=3)
node4 = FlatForestNode(name="node4", parent=node3, data=4)
pretty_tree(root)
```

This produces the output:

root ├── node1 └── node2 └── node3 └── node4

This code creates a simple tree with a root node and two child nodes. It then pretty-prints the tree.

The AlgoTree package provides a wide range of tree structures and utilities to help you work with tree-like data structures in Python. You can explore the documentation to learn more about the available features and how to use them.

## Features

Flexible tree structures with FlatForest, FlatForestNode, and TreeNode

Utility functions for common tree operations such as traversal, searching, and manipulation

Conversion utilities to easily convert between different tree representations

Integration with visualization tools to visualize tree structures

## Node-Centric API

We implement two tree data structures:

- FlatForest for working with flat tree structures with
“pointers” to parent nodes. It uses a proxy object FlatForestNode to provide a node-centric API.

- TreeNode for recursive tree structures, in which each node is a dictionary
with an optional list of child nodes.

Each representation has its own strengths and weaknesses. The key design point
for FlatForest and TreeNode is that they are both also dict objects, i.e.,
they provide a *view* of dictionaries as tree-like structures, as long as the
dictionaries are structured in a certain way. We document that structure
elsewhere.

Each tree data structure models the *concept* of a tree node so that the
underlying implementations can be decoupled from any algorithms
or operations that we may want to perform on the tree.

The tree node concept is defined as follows:

**children**propertyRepresents a list of child nodes for the current node that can be accessed and modified[1].

**parent**propertyRepresents the parent node of the current node that can be accessed and modified[2].

Suppose we have the subtree G at node G:

B (root) ├── D └── E (parent) └── G (current node)

Then, G.parent should refer node E. G.root.parent should be None since root is the root node of subtree G and the root node has no parent. This is true even if subtree G is a subtree view of a larger tree.

If we set G.parent = D, then the tree structure changes to:

B (root) ├── D │ └── G (current node) └── E

This also changes the view of the sub-tree, since we changed the underlying tree structure. However, the same nodes are still accessible from the sub-tree.

If we had set G.parent = X where X is not in the subtree G, then we would have an invalid subtree view even if is is a well-defined operation on the underlying tree structure. It is undefined behavior to set a parent that is not in the subtree, but leave it up to each implementation to decide how to handle such cases.

**node(name: str) -> NodeType**method.Returns a node in the current subtree that the current node belongs to. The returned node should be the node with the given name, if it exists. If the node does not exist, it should raise a KeyError.

The node-centric view of the returned node should be consistent with the view of the current node, i.e., if the current node belongs to a specific sub-tree rooted at some other node, the returned node should also belong to the same sub-tree (i.e., with the same root), just pointing to the new node, but it should be possible to use parent and children to go up and down the sub-tree to reach the same nodes. Any node that is an ancestor of the root of the sub-tree remains inaccessible.

Example: Suppose we have the sub-tree t rooted at A and the current node is B:

A (root) ├── B (current node) │ ├── D │ └── E | └── G └── C └── F

If we get node F, t.node(F), then the sub-tree t remains the same, but the current node is now F:

A (root) ├── B │ ├── D │ └── E | └── G └── C └── F (current node)

**subtree(name: Optional[str] = None) -> NodeType**method.This is an optional method that may not be implemented by all tree structures. FlatForestNode implements this method, but TreeNode does not.

Returns a view of another sub-tree rooted at node where node is contained in the original sub-tree view. If node is None, the method will return the sub-tree rooted at the current node.

As a view, the subtree represents a way of looking at the tree structure from a different perspective. If you modify the sub-tree, you are also modifying the underlying tree structure. The sub-tree should be a consistent view of the tree, i.e., it should be possible to use parent and children to navigate between the nodes in the sub-tree and the nodes in the original tree.

subtree is a

*partial function*over the the nodes in the sub-tree, which means it is only well-defined when node is a descendant of the root of the sub-tree. We do not specify how to deal with the case when this condition is not met, but one approach would be to raise an exception.Example: Suppose we have the sub-tree t rooted at A and the current node is C:

A (root) ├── B │ ├── D │ └── E | └── G └── C (current node) └── F

The subtree t.subtree(B) returns a new subtree:

B (root, current node) ├── D └── E └── G

**root**propertyAn immutable property that represents the root node of the (sub)tree.

Suppose we have the subtree G at node G:

B (root) ├── D └── E └── G (current node)

Then, G.root should refer node B.

**payload**propertyReturns the payload of the current node. The payload is the data associated with the node but not with the structure of the tree, e.g., it does not include the parent or children of the node.

**name**propertyReturns the name of the current node. The name is an identifier for the node within the tree. It is not necessarily unique, and nor is it necessarily even a meaningful identifier, e.g., a random UUID.

In TreeNode, for instance, if the name is not set, a UUID is generated.

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