v0.5.0 enhance documentation, tidy codes

Author: kayjan

CHANGELOG.md

@@ -8,6 +8,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Work In Progress
 - Node: WeightedNode for weighted edge tree implementation.
 
+## [0.5.0] - 2022-11-09
+### Added
+- Clean codes and documentation.
+
+### Changed
+- Tree Exporter: Printing tree to group multiple arguments together.
+- DAG and Tree Exporter: Export to dot able to plot multiple disjointed trees/dags, rename `bgcolor` to `bg_colour`
+
 ## [0.4.6] - 2022-11-09
 ### Added
 - Tree Constructor: From DataFrame of parent-child columns.
@@ -84,6 +92,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Utility Iterator: Tree traversal methods.
 - Workflow To Do App: Tree use case with to-do list implementation.
 
+[0.5.0]: https://github.com/kayjan/bigtree/compare/v0.4.6...v0.5.0
 [0.4.6]: https://github.com/kayjan/bigtree/compare/v0.4.5...v0.4.6
 [0.4.5]: https://github.com/kayjan/bigtree/compare/v0.4.4...v0.4.5
 [0.4.4]: https://github.com/kayjan/bigtree/compare/v0.4.3...v0.4.4

README.md

@@ -4,11 +4,17 @@ Tree Implementation for Python, integrated with Python list, dictionary, and pan
 
 It is pythonic, making it easy to learn and extendable to many types of workflows.
 
+----
+
 Related Links:
 - [Documentation](https://bigtree.readthedocs.io/en/latest/)
 - [GitHub](https://github.com/kayjan/bigtree/)
 - [Changelog](https://github.com/kayjan/bigtree/blob/master/CHANGELOG.md)
 - [PyPI](https://pypi.org/project/bigtree/)
+- Articles
+  - [Python Tree Implementation with BigTree](https://towardsdatascience.com/python-tree-implementation-with-bigtree-13cdabd77adc#245a-94ae81f0b3f1)
+
+----
 
 ## Components
 There are 2 segments to Big Tree consisting of Tree implementation and Directed Acyclic Graph (DAG) implementation.
@@ -70,15 +76,19 @@ For Directed Acyclic Graph (DAG) implementation, there are 4 main components.
 
 To install `bigtree`, run the following line in command prompt:
 
-```pip install bigtree```
+```shell
+$ pip install bigtree
+```
 
 If tree needs to be exported to image, it requires additional dependencies.
 Run the following lines in command prompt:
 
+```shell
+$ pip install 'bigtree[image]'
+$ brew install gprof2dot
 ```
-pip install 'bigtree[image]'
-brew install gprof2dot
-```
+
+----
 
 ## Tree Demonstration
 
@@ -94,7 +104,7 @@ Nodes can be linked to each other with `parent` and `children` setter methods,
 or using bitshift operator with the convention `parent_node >> child_node` or `child_node << parent_node`.
 
 ```python
-from bigtree import Node, print_tree
+from bigtree import Node, print_tree, tree_to_dot
 
 root = Node("a", age=90)
 b = Node("b", age=65)
@@ -109,8 +119,13 @@ print_tree(root, attr_list=["age"])
 # ├── b [age=65]
 # │   └── d [age=40]
 # └── c [age=60]
+
+graph = tree_to_dot(root, node_colour="gold")
+graph.write_png("assets/tree.png")
 ```
 
+![Sample Tree Output](../../assets/tree.png)
+
 ```python
 from bigtree import Node, print_tree
 
@@ -643,6 +658,8 @@ graph.write_png("assets/demo.png")
 
 ![Sample Tree Output](../../assets/demo.png)
 
+----
+
 ## DAG Demonstration
 
 Compared to nodes in tree, nodes in DAG are able to have multiple parents.
@@ -734,6 +751,8 @@ print([(parent.node_name, child.node_name) for parent, child in dag_iterator(dag
 # [('a', 'd'), ('c', 'd'), ('d', 'e'), ('a', 'c'), ('b', 'c')]
 ```
 
+----
+
 ## Demo Usage
 
 ### To Do Application
@@ -760,4 +779,7 @@ app.show()
 # │   └── Bread [description=Urgent]
 # └── General
 #   └── Cook
+
+app.save("list.json")
+app2 = AppToDo.load("list.json")
 ```

assets/dag_construct.png

@@ -1,4 +1,4 @@
-__version__ = "0.4.6"
+__version__ = "0.5.0"
 
 from bigtree.dag.construct import dataframe_to_dag, dict_to_dag, list_to_dag
 from bigtree.dag.export import dag_to_dataframe, dag_to_dict, dag_to_dot, dag_to_list

assets/tree.png

@@ -28,24 +28,10 @@ def list_to_dag(
     Returns:
         (DAGNode)
     """
-    node_dict = dict()
-    parent_node = None
-
-    for parent_name, child_name in relations:
-        parent_node = node_dict.get(parent_name)
-        if not parent_node:
-            parent_node = node_type(parent_name)
-
-        child_node = node_dict.get(child_name)
-        if not child_node:
-            child_node = node_type(child_name)
-
-        node_dict[parent_name] = parent_node
-        node_dict[child_name] = child_node
-
-        parent_node.children = [child_node]
-
-    return parent_node
+    relation_data = pd.DataFrame(relations, columns=["parent", "child"])
+    return dataframe_to_dag(
+        relation_data, child_col="child", parent_col="parent", node_type=node_type
+    )
 
 
 def dict_to_dag(

assets/tree_construct.png

@@ -1,4 +1,4 @@
-from typing import Any, Dict, List, Tuple
+from typing import Any, Dict, List, Tuple, Union
 
 import pandas as pd
 
@@ -161,14 +161,14 @@ def dag_to_dataframe(
 
 
 def dag_to_dot(
-    dag: DAGNode,
+    dag: Union[DAGNode, List[DAGNode]],
     rankdir: str = "TB",
-    bgcolor: str = None,
+    bg_colour: str = None,
     node_colour: str = None,
     edge_colour: str = None,
     node_attr: str = None,
 ):
-    r"""Export DAG tree to image.
+    r"""Export DAG tree or list of DAG trees to image.
     Note that node names must be unique.
     Posible node attributes include style, fillcolor, shape.
 
@@ -188,12 +188,12 @@ def dag_to_dot(
     Export to string
 
     >>> dag_graph.to_string()
-    'strict digraph G {\nrankdir=TB;\na [label=a];\nc [label=c];\na -> c;\na [label=a];\nd [label=d];\na -> d;\nb [label=b];\nc [label=c];\nb -> c;\nc [label=c];\nd [label=d];\nc -> d;\nd [label=d];\ne [label=e];\nd -> e;\n}\n'
+    'strict digraph G {\nrankdir=TB;\nc [label=c];\na [label=a];\na -> c;\nd [label=d];\na [label=a];\na -> d;\nc [label=c];\nb [label=b];\nb -> c;\nd [label=d];\nc [label=c];\nc -> d;\ne [label=e];\nd [label=d];\nd -> e;\n}\n'
 
     Args:
         dag (DAGNode): tree to be exported
         rankdir (str): set direction of graph layout, defaults to 'TB', can be 'BT, 'LR', 'RL'
-        bgcolor (str): background color of image, defaults to None
+        bg_colour (str): background color of image, defaults to None
         node_colour (str): fill colour of nodes, defaults to None
         edge_colour (str): colour of edges, defaults to None
         node_attr (str): node attribute for style, overrides node_colour, defaults to None
@@ -208,12 +208,9 @@ def dag_to_dot(
             "pydot not available. Please perform a\n\npip install 'bigtree[image]'\n\nto install required dependencies"
         )
 
-    if not isinstance(dag, DAGNode):
-        raise ValueError("Tree should be of type `DAGNode`, or inherit from `DAGNode`")
-
     # Get style
-    if bgcolor:
-        graph_style = dict(bgcolor=bgcolor)
+    if bg_colour:
+        graph_style = dict(bgcolor=bg_colour)
     else:
         graph_style = dict()
 
@@ -227,30 +224,40 @@ def dag_to_dot(
     else:
         edge_style = dict()
 
-    dag = dag.copy()
-
     _graph = pydot.Dot(
         graph_type="digraph", strict=True, rankdir=rankdir, **graph_style
     )
 
-    for parent_node, child_node in dag_iterator(dag):
-        parent_name = parent_node.name
-        parent_node_style = node_style.copy()
-        if node_attr and parent_node.get_attr(node_attr):
-            parent_node_style.update(parent_node.get_attr(node_attr))
-        pydot_parent = pydot.Node(
-            name=parent_name, label=parent_name, **parent_node_style
-        )
-        _graph.add_node(pydot_parent)
+    if not isinstance(dag, list):
+        dag = [dag]
 
-        child_name = child_node.name
-        child_node_style = node_style.copy()
-        if node_attr and child_node.get_attr(node_attr):
-            child_node_style.update(child_node.get_attr(node_attr))
-        pydot_child = pydot.Node(name=child_name, label=child_name, **parent_node_style)
-        _graph.add_node(pydot_child)
+    for _dag in dag:
+        if not isinstance(_dag, DAGNode):
+            raise ValueError(
+                "Tree should be of type `DAGNode`, or inherit from `DAGNode`"
+            )
+        _dag = _dag.copy()
+
+        for parent_node, child_node in dag_iterator(_dag):
+            child_name = child_node.name
+            child_node_style = node_style.copy()
+            if node_attr and child_node.get_attr(node_attr):
+                child_node_style.update(child_node.get_attr(node_attr))
+            pydot_child = pydot.Node(
+                name=child_name, label=child_name, **child_node_style
+            )
+            _graph.add_node(pydot_child)
+
+            parent_name = parent_node.name
+            parent_node_style = node_style.copy()
+            if node_attr and parent_node.get_attr(node_attr):
+                parent_node_style.update(parent_node.get_attr(node_attr))
+            pydot_parent = pydot.Node(
+                name=parent_name, label=parent_name, **parent_node_style
+            )
+            _graph.add_node(pydot_parent)
 
-        edge = pydot.Edge(parent_name, child_name, **edge_style)
-        _graph.add_edge(edge)
+            edge = pydot.Edge(parent_name, child_name, **edge_style)
+            _graph.add_edge(edge)
 
     return _graph

bigtree/__init__.py

@@ -106,7 +106,7 @@ class BaseNode:
     3. ``set_attrs(attrs: dict)``: Set node attribute name(s) and value(s)
     4. ``copy()``: Deep copy BaseNode
 
-    ------------
+    ----
 
     """
 

bigtree/dag/construct.py

@@ -92,7 +92,7 @@ class DAGNode:
     3. ``set_attrs(attrs: dict)``: Set node attribute name(s) and value(s)
     4. ``copy()``: Deep copy DAGNode
 
-    ------------
+    ----
 
     """
 

bigtree/dag/export.py

@@ -57,7 +57,7 @@ class Node(BaseNode):
     1. ``node_name``: Get node name, without accessing `name` directly
     2. ``path_name``: Get path name from root, separated by `sep`
 
-    ------------
+    ----
 
     """