Merge pull request #225 from kayjan/abstract-functions

Abstract functions

CHANGELOG.md

@@ -5,6 +5,11 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ## [Unreleased]
+### Changed:
+- DAG Constructor: `list_to_dag` and `dict_to_dag` does not rely on `dataframe_to_dag` as pandas dataframe operation
+is phased out.
+### Fixed:
+- DAG Constructor: Handle cases where reserved keywords are part of attribute upon creation and throw error accordingly.
 
 ## [0.17.1] - 2024-04-23
 ### Fixed

bigtree/binarytree/construct.py

@@ -45,10 +45,7 @@ def list_to_binarytree(
     node_list = [root_node]
     for idx, num in enumerate(heapq_list):
         if idx:
-            if idx % 2:
-                parent_idx = int((idx - 1) / 2)
-            else:
-                parent_idx = int((idx - 2) / 2)
+            parent_idx = int((idx + 1) / 2) - 1
             node = node_type(num, parent=node_list[parent_idx])  # type: ignore
             node_list.append(node)
     return root_node

bigtree/dag/construct.py

@@ -6,7 +6,7 @@
 from bigtree.utils.assertions import (
     assert_dataframe_no_duplicate_attribute,
     assert_dataframe_not_empty,
-    assert_dictionary_not_empty,
+    assert_key_not_in_dict_or_df,
     assert_length_not_empty,
     filter_attributes,
     isnull,
@@ -21,7 +21,6 @@
 __all__ = ["list_to_dag", "dict_to_dag", "dataframe_to_dag"]
 
 
-@optional_dependencies_pandas
 def list_to_dag(
     relations: List[Tuple[str, str]],
     node_type: Type[DAGNode] = DAGNode,
@@ -45,13 +44,26 @@ def list_to_dag(
     """
     assert_length_not_empty(relations, "Input list", "relations")
 
-    relation_data = pd.DataFrame(relations, columns=["parent", "child"])
-    return dataframe_to_dag(
-        relation_data, child_col="child", parent_col="parent", node_type=node_type
-    )
+    node_dict: Dict[str, DAGNode] = dict()
+    parent_node = DAGNode()
+
+    for parent_name, child_name in relations:
+        if parent_name not in node_dict:
+            parent_node = node_type(parent_name)
+            node_dict[parent_name] = parent_node
+        else:
+            parent_node = node_dict[parent_name]
+        if child_name not in node_dict:
+            child_node = node_type(child_name)
+            node_dict[child_name] = child_node
+        else:
+            child_node = node_dict[child_name]
+
+        child_node.parents = [parent_node]
+
+    return parent_node
 
 
-@optional_dependencies_pandas
 def dict_to_dag(
     relation_attrs: Dict[str, Any],
     parent_key: str = "parents",
@@ -83,22 +95,36 @@ def dict_to_dag(
     Returns:
         (DAGNode)
     """
-    assert_dictionary_not_empty(relation_attrs, "relation_attrs")
+    assert_length_not_empty(relation_attrs, "Dictionary", "relation_attrs")
+
+    node_dict: Dict[str, DAGNode] = dict()
+    parent_node: DAGNode | None = None
+
+    for child_name, node_attrs in relation_attrs.items():
+        node_attrs = node_attrs.copy()
+        parent_names: List[str] = []
+        if parent_key in node_attrs:
+            parent_names = node_attrs.pop(parent_key)
+        assert_key_not_in_dict_or_df(node_attrs, ["parent", "parents", "children"])
+
+        if child_name in node_dict:
+            child_node = node_dict[child_name]
+            child_node.set_attrs(node_attrs)
+        else:
+            child_node = node_type(child_name, **node_attrs)
+            node_dict[child_name] = child_node
+
+        for parent_name in parent_names:
+            parent_node = node_dict.get(parent_name, node_type(parent_name))
+            node_dict[parent_name] = parent_node
+            child_node.parents = [parent_node]
 
-    # Convert dictionary to dataframe
-    data = pd.DataFrame(relation_attrs).T.rename_axis("_tmp_child").reset_index()
-    if parent_key not in data:
+    if parent_node is None:
         raise ValueError(
             f"Parent key {parent_key} not in dictionary, check `relation_attrs` and `parent_key`"
         )
 
-    data = data.explode(parent_key)
-    return dataframe_to_dag(
-        data,
-        child_col="_tmp_child",
-        parent_col=parent_key,
-        node_type=node_type,
-    )
+    return parent_node
 
 
 @optional_dependencies_pandas
@@ -164,6 +190,7 @@ def dataframe_to_dag(
         attribute_cols = list(data.columns)
         attribute_cols.remove(child_col)
         attribute_cols.remove(parent_col)
+    assert_key_not_in_dict_or_df(attribute_cols, ["parent", "parents", "children"])
 
     data = data[[child_col, parent_col] + attribute_cols].copy()
 

bigtree/dag/export.py

@@ -3,6 +3,7 @@
 from typing import Any, Dict, List, Tuple, TypeVar, Union
 
 from bigtree.node.dagnode import DAGNode
+from bigtree.utils.assertions import assert_tree_type
 from bigtree.utils.exceptions import (
     optional_dependencies_image,
     optional_dependencies_pandas,
@@ -265,10 +266,7 @@ def dag_to_dot(
         dag = [dag]
 
     for _dag in dag:
-        if not isinstance(_dag, DAGNode):
-            raise TypeError(
-                "Tree should be of type `DAGNode`, or inherit from `DAGNode`"
-            )
+        assert_tree_type(_dag, DAGNode, "DAGNode")
         _dag = _dag.copy()
 
         for parent_node, child_node in dag_iterator(_dag):

bigtree/tree/construct.py

@@ -10,7 +10,6 @@
     assert_dataframe_no_duplicate_attribute,
     assert_dataframe_no_duplicate_children,
     assert_dataframe_not_empty,
-    assert_dictionary_not_empty,
     assert_length_not_empty,
     filter_attributes,
     isnull,
@@ -185,7 +184,7 @@ def add_dict_to_tree_by_path(
     Returns:
         (Node)
     """
-    assert_dictionary_not_empty(path_attrs, "path_attrs")
+    assert_length_not_empty(path_attrs, "Dictionary", "path_attrs")
 
     root_node = tree.root
 
@@ -232,7 +231,7 @@ def add_dict_to_tree_by_name(tree: Node, name_attrs: Dict[str, Dict[str, Any]])
     """
     from bigtree.tree.search import findall
 
-    assert_dictionary_not_empty(name_attrs, "name_attrs")
+    assert_length_not_empty(name_attrs, "Dictionary", "name_attrs")
 
     attr_dict_names = set(name_attrs.keys())
 
@@ -642,7 +641,7 @@ def dict_to_tree(
     Returns:
         (Node)
     """
-    assert_dictionary_not_empty(path_attrs, "path_attrs")
+    assert_length_not_empty(path_attrs, "Dictionary", "path_attrs")
 
     # Initial tree
     root_name = list(path_attrs.keys())[0].lstrip(sep).rstrip(sep).split(sep)[0]
@@ -724,7 +723,7 @@ def nested_dict_to_tree(
     Returns:
         (Node)
     """
-    assert_dictionary_not_empty(node_attrs, "node_attrs")
+    assert_length_not_empty(node_attrs, "Dictionary", "node_attrs")
 
     def _recursive_add_child(
         child_dict: Dict[str, Any], parent_node: Optional[Node] = None

bigtree/tree/export.py

@@ -8,6 +8,7 @@
     assert_key_in_dict,
     assert_str_in_list,
     assert_style_in_dict,
+    assert_tree_type,
     isnull,
 )
 from bigtree.utils.constants import ExportConstants, MermaidConstants, NewickCharacter
@@ -1223,8 +1224,7 @@ def tree_to_dot(
         tree = [tree]
 
     for _tree in tree:
-        if not isinstance(_tree, Node):
-            raise TypeError("Tree should be of type `Node`, or inherit from `Node`")
+        assert_tree_type(_tree, Node, "Node")
 
         name_dict: Dict[str, List[str]] = collections.defaultdict(list)
 

bigtree/tree/helper.py

@@ -7,6 +7,7 @@
 from bigtree.tree.construct import add_dict_to_tree_by_path, dataframe_to_tree
 from bigtree.tree.export import tree_to_dataframe
 from bigtree.tree.search import find_path
+from bigtree.utils.assertions import assert_tree_type
 from bigtree.utils.exceptions import NotFoundError
 from bigtree.utils.iterators import levelordergroup_iter
 
@@ -34,8 +35,7 @@ def clone_tree(tree: BaseNode, node_type: Type[BaseNodeT]) -> BaseNodeT:
     Returns:
         (BaseNode)
     """
-    if not isinstance(tree, BaseNode):
-        raise TypeError("Tree should be of type `BaseNode`, or inherit from `BaseNode`")
+    assert_tree_type(tree, BaseNode, "BaseNode")
 
     # Start from root
     root_info = dict(tree.root.describe(exclude_prefix="_"))

bigtree/utils/assertions.py

@@ -1,12 +1,27 @@
 from __future__ import annotations
 
-import math
-from typing import Any, Dict, List, Union
+from typing import TYPE_CHECKING, Any, Dict, List, Sized, Type, Union
 
-try:
+if TYPE_CHECKING:
     import pandas as pd
-except ImportError:  # pragma: no cover
-    pd = None
+
+    from bigtree.node.basenode import BaseNode
+    from bigtree.node.dagnode import DAGNode
+    from bigtree.node.node import Node
+
+
+__all__ = [
+    "assert_style_in_dict",
+    "assert_str_in_list",
+    "assert_key_in_dict",
+    "assert_length_not_empty",
+    "assert_dataframe_not_empty",
+    "assert_dataframe_no_duplicate_attribute",
+    "assert_dataframe_no_duplicate_children",
+    "assert_tree_type",
+    "isnull",
+    "filter_attributes",
+]
 
 
 def assert_style_in_dict(
@@ -43,6 +58,23 @@ def assert_str_in_list(
         )
 
 
+def assert_key_not_in_dict_or_df(
+    parameter_dict: Union[Dict[str, Any], pd.DataFrame],
+    not_accepted_parameters: List[str],
+) -> None:
+    """Raise ValueError is parameter is in key of dictionary
+
+    Args:
+        parameter_dict (Dict[str, Any]/pd.DataFrame): argument input for parameter
+        not_accepted_parameters (List[str]): list of not accepted parameters
+    """
+    for parameter in parameter_dict:
+        if parameter in not_accepted_parameters:
+            raise ValueError(
+                f"Invalid input, check `{parameter}` is not a valid key as it is a reserved keyword"
+            )
+
+
 def assert_key_in_dict(
     parameter_name: str,
     parameter: Any,
@@ -61,13 +93,11 @@ def assert_key_in_dict(
         )
 
 
-def assert_length_not_empty(
-    data: Union[str, List[Any]], argument_name: str, argument: str
-) -> None:
-    """Raise ValueError if data (str, list, or iterable) does not have length
+def assert_length_not_empty(data: Sized, argument_name: str, argument: str) -> None:
+    """Raise ValueError if data does not have length
 
     Args:
-        data (str/List[Any]): data to check
+        data (Sized): data to check
         argument_name: argument name for data, for error message
         argument (str): argument for data, for error message
     """
@@ -77,17 +107,6 @@ def assert_length_not_empty(
         )
 
 
-def assert_dictionary_not_empty(data_dict: Dict[Any, Any], argument: str) -> None:
-    """Raise ValueError is dictionary is empty
-
-    Args:
-        data_dict (Dict[Any, Any]): dictionary to check
-        argument (str): argument for dictionary, for error message
-    """
-    if not len(data_dict):
-        raise ValueError(f"Dictionary does not contain any data, check `{argument}`")
-
-
 def assert_dataframe_not_empty(data: pd.DataFrame) -> None:
     """Raise ValueError is dataframe is empty
 
@@ -158,6 +177,24 @@ def assert_dataframe_no_duplicate_children(
         )
 
 
+def assert_tree_type(
+    tree: Union[BaseNode, Node, DAGNode],
+    tree_type: Union[Type[BaseNode], Type[Node], Type[DAGNode]],
+    tree_type_name: str,
+) -> None:
+    """Raise TypeError is tree is not of `tree_type`
+
+    Args:
+        tree (Union["BaseNode", "Node", "DAGNode"]): tree to check
+        tree_type: tree type to assert for
+        tree_type_name (str): tree type name
+    """
+    if not isinstance(tree, tree_type):
+        raise TypeError(
+            f"Tree should be of type `{tree_type_name}`, or inherit from `{tree_type_name}`"
+        )
+
+
 def isnull(value: Any) -> bool:
     """Check if value is null
 
@@ -167,6 +204,8 @@ def isnull(value: Any) -> bool:
     Returns:
         (bool)
     """
+    import math
+
     if not value or (isinstance(value, float) and math.isnan(value)):
         return True
     return False

mkdocs.yml

@@ -98,9 +98,9 @@ theme:
 plugins:
   - glightbox
   - search
-  - social:
-      cards_layout_options:
-        logo: docs/_static/favicon.svg
+#  - social:
+#      cards_layout_options:
+#        logo: docs/_static/favicon.svg
   - mkdocstrings:
       handlers:
           python: