replace AlgorithmResult with NodeState in rust

examples/rust/src/bin/hulongbay/main.rs

@@ -131,7 +131,6 @@ fn try_main() -> Result<(), Box<dyn Error>> {
     let components = weakly_connected_components(&graph, 5, Some(16));
 
     components
-        .result
         .into_iter()
         .counts_by(|(_, cc)| cc)
         .iter()

examples/rust/src/bin/lotr/main.rs

@@ -106,8 +106,7 @@ fn main() {
     assert_eq!(graph.node(gandalf).unwrap().name(), "Gandalf");
 
     let r: Vec<String> = temporally_reachable_nodes(&graph, None, 20, 31930, vec!["Gandalf"], None)
-        .get_all_values()
-        .into_iter()
+        .into_iter_values()
         .flatten()
         .map(|(_, s)| s)
         .collect();

python/python/raphtory/__init__.pyi

@@ -8,7 +8,6 @@
 ###############################################################################
 
 from typing import *
-from raphtory import *
 from raphtory.algorithms import *
 from raphtory.vectors import *
 from raphtory.node_state import *
@@ -6070,143 +6069,6 @@ class WindowSet(object):
             Iterable: the time index"
         """
 
-class AlgorithmResult(object):
-    def __len__(self):
-        """Return len(self)."""
-
-    def __repr__(self):
-        """Return repr(self)."""
-
-    def get(self, key: NodeInput) -> Optional[Any]:
-        """
-        Returns the value corresponding to the provided key
-
-        Arguments:
-            key (NodeInput): The node for which the value is to be retrieved.
-
-        Returns:
-            Optional[Any]: The value for the node or `None` if the value does not exist.
-        """
-
-    def get_all(self) -> dict[Node, Any]:
-        """
-        Returns a Dict containing all the nodes (as keys) and their corresponding values (values) or none.
-
-        Returns:
-            dict[Node, Any]: A dict of nodes and their values
-        """
-
-    def get_all_values(self) -> list[Any]:
-        """
-        Get all values
-
-        Returns:
-            list[Any]: the values for each node as a list
-        """
-
-    def get_all_with_names(self) -> dict[str, Any]:
-        """
-        Returns a dict with node names and values
-
-        Returns:
-            dict[str, Any]: a dict with node names and values
-        """
-
-    def group_by(self) -> dict[Any, list[str]]:
-        """
-        Groups the `AlgorithmResult` by its values.
-
-        Returns:
-            dict[Any, list[str]]: A mapping where keys are unique values from the `AlgorithmResult` and values are lists of nodes
-                                  that share the same value.
-        """
-
-    def max(self) -> Tuple[Node, Any]:
-        """
-        Find node with maximum value
-
-        Returns:
-            Tuple[Node, Any]: The node and maximum value.
-        """
-
-    def median(self):
-        """
-        Returns a tuple of the median result with its key
-
-        Returns:
-        Optional[Tuple[Node, Any]]: The node with median value or `None` if there are no nodes.
-        """
-
-    def min(self) -> Tuple[Node, Any]:
-        """
-        Find node with minimum value
-
-        Returns:
-            Tuple[Node, Any]: The node and minimum value.
-        """
-
-    def sort_by_node(self, reverse: bool = True) -> list[Tuple[Node, Any]]:
-        """
-        Sorts by node id in ascending or descending order.
-
-        Arguments:
-            reverse (bool): If `true`, sorts the result in descending order; otherwise, sorts in ascending order. Defaults to True.
-
-        Returns:
-            list[Tuple[Node, Any]]: A sorted list of tuples containing nodes and values.
-        """
-
-    def sort_by_node_name(self, reverse: bool = True) -> list[Tuple[Node, Any]]:
-        """
-        The function `sort_by_node_name` sorts a vector of tuples containing a node and an optional
-        value by the node name in either ascending or descending order.
-
-        Arguments:
-            reverse (bool): A boolean value indicating whether the sorting should be done in reverse order or not. Defaults to True.
-                If reverse is true, the sorting will be done in descending order, otherwise it will be done in
-                ascending order.
-
-        Returns:
-            list[Tuple[Node, Any]]: The function sort_by_node_name returns a vector of tuples. Each tuple contains a Node and value
-        """
-
-    def sort_by_value(self, reverse: bool = True) -> list[Tuple[Node, Any]]:
-        """
-        Sorts the `AlgorithmResult` by its values in ascending or descending order.
-
-        Arguments:
-            reverse (bool): If `true`, sorts the result in descending order, otherwise, sorts in ascending order. Defaults to True.
-
-        Returns:
-            list[Tuple[Node, Any]]: A sorted vector of tuples containing Nodes and values.
-        """
-
-    def to_df(self) -> DataFrame:
-        """
-        Creates a dataframe from the result
-
-        Returns:
-            DataFrame: A `pandas.DataFrame` containing the result
-        """
-
-    def top_k(
-        self, k: int, percentage: bool = False, reverse: bool = True
-    ) -> list[Tuple[Node, Any]]:
-        """
-        Retrieves the top-k elements from the `AlgorithmResult` based on its values.
-
-        Arguments:
-            k (int): The number of elements to retrieve.
-            percentage (bool): If `True`, the `k` parameter is treated as a percentage of total elements. Defaults to False.
-            reverse (bool): If `True`, retrieves the elements in descending order, otherwise, in ascending order. Defaults to True.
-
-        Returns:
-            list[Tuple[Node, Any]]: List of tuples with keys of nodes and values of type `Y`.
-            If percentage is true, the returned vector contains the top `k` percentage of elements.
-            If percentage is false, the returned vector contains the top `k` elements.
-            Returns None if the result is empty or if `k` is 0.
-        """
-
 class GraphIndex(object):
     """
     A searchable Index for a `Graph`. This allows for fuzzy and exact searches of nodes and edges.