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Introducing the Socket Python SDK
The initial version of the Socket Python SDK is now on PyPI, enabling developers to more easily interact with the Socket REST API in Python projects.
This Python package contains a few abstract base classes for tree data structures. Trees are very common data structure that represents a hierarchy of common nodes. This package defines abstract base classes for these data structure in order to make code reusable.
from abstracttree import to_mermaid
to_mermaid(AbstractTree)
graph TD;
AbstractTree[AbstractTree];
UpTree[UpTree];
Tree[Tree];
MutableTree[MutableTree];
DownTree[DownTree];
Tree[Tree];
MutableTree[MutableTree];
MutableDownTree[MutableDownTree];
MutableTree[MutableTree];
BinaryDownTree[BinaryDownTree]
BinaryTree[BinaryTree]
AbstractTree-->UpTree;
UpTree-->Tree;
Tree-->MutableTree;
AbstractTree-->DownTree;
DownTree-->Tree;
DownTree-->MutableDownTree;
MutableDownTree-->MutableTree;
DownTree-->BinaryDownTree
BinaryDownTree-->BinaryTree
Tree-->BinaryTree
Downtrees are trees that have links to their direct children. Uptrees are trees that link to their parent. A Tree has links in both directions.
ABC | Inherits from | Abstract Methods | Mixin Methods |
---|---|---|---|
AbstractTree | nid , eqv() | ||
UpTree | AbstractTree | parent | root , is_root , ancestors , path |
DownTree | AbstractTree | children | nodes , descendants , leaves , levels , is_leaf , transform() , nodes.preorder() , nodes.postorder() , nodes.levelorder() |
Tree | UpTree , DownTree | siblings | |
MutableDownTree | DownTree | add_child() , remove_child() | add_children() |
MutableTree | Tree , MutableDownTree | detach() | |
BinaryDownTree | DownTree | left_child , right_child | children , nodes.inorder() , descendants.inorder() |
BinaryTree | BinaryDownTree , Tree |
In your own code, you can inherit from these trees. For example, if your tree only has links to children:
import abstracttree
from abstracttree import print_tree
class MyTree(abstracttree.DownTree):
def __init__(self, value, children=()):
self.value = value
self._children = children
def __str__(self):
return "MyTree " + str(self.value)
@property
def children(self):
return self._children
tree = MyTree(1, children=[MyTree(2), MyTree(3)])
print_tree(tree)
# This generates the following output:
# MyTree 1
# ├─ MyTree 2
# └─ MyTree 3
In practice, not all existing tree data structures implement one of these abstract classes.
As a bridge, you can use astree
to convert these trees to a Tree
instance.
However, whenever possible, it's recommended to inherit from Tree
directly for minimal overhead.
Examples:
# Trees from built-ins and standard library
astree(int)
astree(ast.parse("1 + 1 == 2"))
astree(pathlib.Path("abstracttree"))
# Anything that has parent and children attributes (anytree / bigtree / littletree)
astree(anytree.Node())
# Nested list
astree([[1, 2, 3], [4, 5, 6]])
# Tree from json-data
data = {"name": "a",
"children": [
{"name": "b", "children": []},
{"name": "c", "children": []}
]}
astree(data, children=operator.itemgetter["children"])
# pyqt.QtWidget
astree(widget, children=lambda w: w.children(), parent = lambda w: w.parent())
# Tree from treelib
astree(tree.root, children=lambda nid: tree.children(nid), parent=lambda nid: tree.parent(nid))
# itertree
astree(tree, children=iter, parent=lambda t: t.parent)
# Infinite binary tree
inf_binary = astree(0, children=lambda n: (2*n + 1, 2*n + 2))
Pretty printing
tree = astree(seq, children=lambda x: [x[:-2], x[1:]] if x else [])
print_tree(tree)
print(to_string(tree))
# ['a', 'b', 'c', 'd']
# ├─ ['a', 'b']
# │ └─ ['b']
# └─ ['b', 'c', 'd']
# ├─ ['b']
# └─ ['c', 'd']
# └─ ['d']
Plotting with matplotlib
import matplotlib.pyplot as plt
expr = ast.parse("y = x*x + 1")
plot_tree(expr)
plt.show()
Export to various formats
to_dot(tree)
to_mermaid(tree)
to_latex(tree)
to_image(Path('.'), "filetree.png", how="dot")
to_image(AbstractTree, "class_hierarchy.svg", how="mermaid")
to_pillow(tree).show()
import heapq
from abstracttree import HeapTree, Route
tree = HeapTree([5, 4, 3, 2, 1])
heapq.heapify(tree.heap)
left_child = tree.children[0]
right_child = tree.children[1]
route = Route(left_child, right_child)
print(f"{route.lca = }") # => HeapTree([1, 2, 3, 5, 4], 0)
print(f"{route.nodes.count() = }") # => 3
print(f"{route.edges.count() = }") # => 2
FAQs
Abstract base classes for tree data structures
We found that abstracttree demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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