This package contains a very tiny implementation of a directed tree, where each node contains list-like data.
pip install git+https://github.com/MrHedmad/bonsai.git
from bonsai import Tree
# Make a new tree
tree = Tree()
# Add new nodes with `create_node(name, parent, data)
# The first node cannot have a parent. There must only be one parentless (root)
# node in the tree.
# The function returns the UUID of the created node.
root_id = tree.create_node("root", None)
# Create a node with data
tree.create_node("node_with_data", root_id, ["some", "list-like", "data"])
Once the tree has some nodes, you can run manipulations on it:
- Copy, slice and dice the tree:
clone()
: Return a copy of the tree.subset(node_id)
: Return a branch of the tree starting fromnode_id
.
- Add or remove branches:
paste(other_tree, node_id, update_data)
: Paste a tree to this tree as a branch fromnode_id
, optionally updating the data in thenode_id
with the one in the root of the pasted node.prune(node_id)
: Remove the branch fromnode_id
(inclusive).
- Retrieve nodes:
all_nodes()
: Get an iterator ofnode_id
/Node
pairs.root
: Get the root of the tree.get_nodes_named(name)
: Get a list of nodes withname
.get_one_node_named(name)
: Get a single node with namename
, or die trying.leaves
: Get a list of all leaf nodes in the tree.get_parent(node_id)
: Get the parent node ofnode_id
.get_path_of(node_id)
: Get a list of IDs from the root to thenode_id
, included.get_paths()
: Get all paths from the root to all the leaves, as a list of tuples.get_direct_children(node_id)
: Get all the children of the node at depth = 1.
- Update the information of existing nodes:
update_data(node_id, new_data)
: Update the data ofnode_id
withnew_data
.update_name(node_id, new_name)
: Update the name ofnode_id
tonew_name
.
- Get information regarding the nodes:
is_leaf(node_id)
:true
ifnode_id
is a leaf.depth_of(node_id)
: Get the depth of thenode_id
as anint
.has_ancestor(node_id, ancestor_id)
: Returntrue
ifancestor_id
is a parent ofnode_id
.
- Save the tree to disk:
to_files(out_dir)
: Save the tree as a series of folders within folders.to_adjacency_matrix(out_stream)
: Save the adjacency matrix of the tree.to_node_json(out_stream)
: Save the list of nodes of this tree, along with the data, in a JSON file.to_representation(out_stream)
: Save a representation of the tree, like callingtree
on a directory.
- Load the tree from disk:
from_node_list()
: Load a JSON file with the node data.