Self return type on from_dict methods (#3702)

def from_dict(cls, dct: dict) -> Self:

Author: janosh

dev_scripts/update_pt_data.py

@@ -128,16 +128,16 @@ def parse_radii():
 def update_ionic_radii():
     data = loadfn(ptable_yaml_path)
 
-    for d in data.values():
-        if "Ionic_radii" in d:
-            d["Ionic radii"] = {k: v / 100 for k, v in d["Ionic_radii"].items()}
-            del d["Ionic_radii"]
-        if "Ionic_radii_hs" in d:
-            d["Ionic radii hs"] = {k: v / 100 for k, v in d["Ionic_radii_hs"].items()}
-            del d["Ionic_radii_hs"]
-        if "Ionic_radii_ls" in d:
-            d["Ionic radii ls"] = {k: v / 100 for k, v in d["Ionic_radii_ls"].items()}
-            del d["Ionic_radii_ls"]
+    for dct in data.values():
+        if "Ionic_radii" in dct:
+            dct["Ionic radii"] = {k: v / 100 for k, v in dct["Ionic_radii"].items()}
+            del dct["Ionic_radii"]
+        if "Ionic_radii_hs" in dct:
+            dct["Ionic radii hs"] = {k: v / 100 for k, v in dct["Ionic_radii_hs"].items()}
+            del dct["Ionic_radii_hs"]
+        if "Ionic_radii_ls" in dct:
+            dct["Ionic radii ls"] = {k: v / 100 for k, v in dct["Ionic_radii_ls"].items()}
+            del dct["Ionic_radii_ls"]
     with open("periodic_table2.yaml", mode="w") as file:
         yaml.dump(data, file)
     with open("../pymatgen/core/periodic_table.json", mode="w") as file:

pymatgen/alchemy/filters.py

@@ -13,6 +13,8 @@
 from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
 
 if TYPE_CHECKING:
+    from typing_extensions import Self
+
     from pymatgen.core import Structure
 
 
@@ -106,7 +108,7 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, dct):
+    def from_dict(cls, dct: dict) -> Self:
         """
         Args:
             dct (dict): Dict representation.
@@ -165,7 +167,7 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, dct):
+    def from_dict(cls, dct: dict) -> Self:
         """
         Args:
             dct (dict): Dict representation.

pymatgen/analysis/chemenv/connectivity/connected_components.py

@@ -4,6 +4,7 @@
 
 import itertools
 import logging
+from typing import TYPE_CHECKING
 
 import matplotlib.pyplot as plt
 import networkx as nx
@@ -18,6 +19,9 @@
 from pymatgen.analysis.chemenv.utils.graph_utils import get_delta
 from pymatgen.analysis.chemenv.utils.math_utils import get_linearly_independent_vectors
 
+if TYPE_CHECKING:
+    from typing_extensions import Self
+
 
 def draw_network(env_graph, pos, ax, sg=None, periodicity_vectors=None):
     """Draw network of environments in a matplotlib figure axes.
@@ -827,29 +831,29 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, d):
+    def from_dict(cls, dct: dict) -> Self:
         """
         Reconstructs the ConnectedComponent object from a dict representation of the
         ConnectedComponent object created using the as_dict method.
 
         Args:
-            d (dict): dict representation of the ConnectedComponent object
+            dct (dict): dict representation of the ConnectedComponent object
 
         Returns:
             ConnectedComponent: The connected component representing the links of a given set of environments.
         """
         nodes_map = {
-            inode_str: EnvironmentNode.from_dict(nodedict) for inode_str, (nodedict, nodedata) in d["nodes"].items()
+            inode_str: EnvironmentNode.from_dict(nodedict) for inode_str, (nodedict, nodedata) in dct["nodes"].items()
         }
-        nodes_data = {inode_str: nodedata for inode_str, (nodedict, nodedata) in d["nodes"].items()}
-        dod = {}
-        for e1, e1dict in d["graph"].items():
-            dod[e1] = {}
+        nodes_data = {inode_str: nodedata for inode_str, (nodedict, nodedata) in dct["nodes"].items()}
+        nested_dict: dict[str, dict] = {}
+        for e1, e1dict in dct["graph"].items():
+            nested_dict[e1] = {}
             for e2, e2dict in e1dict.items():
-                dod[e1][e2] = {
+                nested_dict[e1][e2] = {
                     cls._edgedictkey_to_edgekey(ied): cls._retuplify_edgedata(edata) for ied, edata in e2dict.items()
                 }
-        graph = nx.from_dict_of_dicts(dod, create_using=nx.MultiGraph, multigraph_input=True)
+        graph = nx.from_dict_of_dicts(nested_dict, create_using=nx.MultiGraph, multigraph_input=True)
         nx.set_node_attributes(graph, nodes_data)
         nx.relabel_nodes(graph, nodes_map, copy=False)
         return cls(graph=graph)

pymatgen/analysis/chemenv/connectivity/structure_connectivity.py

@@ -4,6 +4,7 @@
 
 import collections
 import logging
+from typing import TYPE_CHECKING
 
 import networkx as nx
 import numpy as np
@@ -13,6 +14,9 @@
 from pymatgen.analysis.chemenv.connectivity.environment_nodes import get_environment_node
 from pymatgen.analysis.chemenv.coordination_environments.structure_environments import LightStructureEnvironments
 
+if TYPE_CHECKING:
+    from typing_extensions import Self
+
 __author__ = "David Waroquiers"
 __copyright__ = "Copyright 2012, The Materials Project"
 __credits__ = "Geoffroy Hautier"
@@ -299,26 +303,30 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, d):
+    def from_dict(cls, dct: dict) -> Self:
         """
         Args:
-            d ():
+            dct (dict):
 
         Returns:
             StructureConnectivity
         """
         # Reconstructs the graph with integer as nodes (json's as_dict replaces integer keys with str keys)
-        cgraph = nx.from_dict_of_dicts(d["connectivity_graph"], create_using=nx.MultiGraph, multigraph_input=True)
-        cgraph = nx.relabel_nodes(cgraph, int)  # Just relabel the nodes using integer casting (maps str->int)
+        connect_graph = nx.from_dict_of_dicts(
+            dct["connectivity_graph"], create_using=nx.MultiGraph, multigraph_input=True
+        )
+        connect_graph = nx.relabel_nodes(
+            connect_graph, int
+        )  # Just relabel the nodes using integer casting (maps str->int)
         # Relabel multi-edges (removes multi-edges with str keys and adds them back with int keys)
-        edges = set(cgraph.edges())
+        edges = set(connect_graph.edges())
         for n1, n2 in edges:
-            new_edges = {int(iedge): edata for iedge, edata in cgraph[n1][n2].items()}
-            cgraph.remove_edges_from([(n1, n2, iedge) for iedge, edata in cgraph[n1][n2].items()])
-            cgraph.add_edges_from([(n1, n2, iedge, edata) for iedge, edata in new_edges.items()])
+            new_edges = {int(iedge): edata for iedge, edata in connect_graph[n1][n2].items()}
+            connect_graph.remove_edges_from([(n1, n2, iedge) for iedge, edata in connect_graph[n1][n2].items()])
+            connect_graph.add_edges_from([(n1, n2, iedge, edata) for iedge, edata in new_edges.items()])
         return cls(
-            LightStructureEnvironments.from_dict(d["light_structure_environments"]),
-            connectivity_graph=cgraph,
+            LightStructureEnvironments.from_dict(dct["light_structure_environments"]),
+            connectivity_graph=connect_graph,
             environment_subgraphs=None,
         )
         # TODO: also deserialize the environment_subgraphs

pymatgen/analysis/chemenv/coordination_environments/chemenv_strategies.py

@@ -82,13 +82,13 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, d: dict) -> Self:
+    def from_dict(cls, dct: dict) -> Self:
         """Initialize distance cutoff from dict.
 
         Args:
-            d: Dict representation of the distance cutoff.
+            dct (dict): Dict representation of the distance cutoff.
         """
-        return cls(d["value"])
+        return cls(dct["value"])
 
 
 class AngleCutoffFloat(float, StrategyOption):
@@ -116,13 +116,13 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, d):
+    def from_dict(cls, dct: dict) -> Self:
         """Initialize angle cutoff from dict.
 
         Args:
-            d: Dict representation of the angle cutoff.
+            dct (dict): Dict representation of the angle cutoff.
         """
-        return cls(d["value"])
+        return cls(dct["value"])
 
 
 class CSMFloat(float, StrategyOption):
@@ -154,7 +154,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize CSM from dict.
 
         Args:
-            d: Dict representation of the CSM.
+           dct (dict): Dict representation of the CSM.
         """
         return cls(dct["value"])
 
@@ -188,7 +188,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize additional condition from dict.
 
         Args:
-            d: Dict representation of the additional condition.
+           dct (dict): Dict representation of the additional condition.
         """
         return cls(dct["value"])
 
@@ -1350,7 +1350,7 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, dct):
+    def from_dict(cls, dct: dict) -> Self:
         """Construct AngleNbSetWeight from dict representation."""
         return cls(aa=dct["aa"])
 
@@ -1418,7 +1418,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of NormalizedAngleDistanceNbSetWeight.
+            dct (dict): Dict representation of NormalizedAngleDistanceNbSetWeight.
 
         Returns:
             NormalizedAngleDistanceNbSetWeight.
@@ -1722,7 +1722,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of SelfCSMNbSetWeight.
+            dct (dict): Dict representation of SelfCSMNbSetWeight.
 
         Returns:
             SelfCSMNbSetWeight.
@@ -1960,7 +1960,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of DeltaCSMNbSetWeight.
+            dct (dict): Dict representation of DeltaCSMNbSetWeight.
 
         Returns:
             DeltaCSMNbSetWeight.
@@ -2026,7 +2026,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of CNBiasNbSetWeight.
+            dct (dict): Dict representation of CNBiasNbSetWeight.
 
         Returns:
             CNBiasNbSetWeight.
@@ -2096,7 +2096,7 @@ def from_description(cls, dct: dict) -> Self:
         """Initialize weights from description.
 
         Args:
-            dct: Dictionary description.
+            dct (dict): Dictionary description.
 
         Returns:
             CNBiasNbSetWeight.
@@ -2334,7 +2334,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of DistanceAngleAreaNbSetWeight.
+            dct (dict): Dict representation of DistanceAngleAreaNbSetWeight.
 
         Returns:
             DistanceAngleAreaNbSetWeight.
@@ -2404,7 +2404,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of DistancePlateauNbSetWeight.
+            dct (dict): Dict representation of DistancePlateauNbSetWeight.
 
         Returns:
             DistancePlateauNbSetWeight.
@@ -2471,7 +2471,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of AnglePlateauNbSetWeight.
+            dct (dict): Dict representation of AnglePlateauNbSetWeight.
 
         Returns:
             AnglePlateauNbSetWeight.
@@ -2552,7 +2552,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of DistanceNbSetWeight.
+            dct (dict): Dict representation of DistanceNbSetWeight.
 
         Returns:
             DistanceNbSetWeight.
@@ -2636,7 +2636,7 @@ def from_dict(cls, dct: dict) -> Self:
         """Initialize from dict.
 
         Args:
-            dct: Dict representation of DeltaDistanceNbSetWeight.
+            dct (dict): Dict representation of DeltaDistanceNbSetWeight.
 
         Returns:
             DeltaDistanceNbSetWeight.

pymatgen/analysis/chemenv/coordination_environments/coordination_geometries.py

@@ -13,11 +13,15 @@
 import itertools
 import json
 import os
+from typing import TYPE_CHECKING
 
 import numpy as np
 from monty.json import MontyDecoder, MSONable
 from scipy.special import factorial
 
+if TYPE_CHECKING:
+    from typing_extensions import Self
+
 __author__ = "David Waroquiers"
 __copyright__ = "Copyright 2012, The Materials Project"
 __credits__ = "Geoffroy Hautier"
@@ -109,7 +113,7 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, dct):
+    def from_dict(cls, dct: dict) -> Self:
         """
         Reconstruct ExplicitPermutationsAlgorithm from its JSON-serializable dict representation.
         """
@@ -324,7 +328,7 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, dct):
+    def from_dict(cls, dct: dict) -> Self:
         """
         Reconstructs the SeparationPlane algorithm from its JSON-serializable dict representation.
 
@@ -497,7 +501,7 @@ def as_dict(self):
             return {"hints_type": self.hints_type, "options": self.options}
 
         @classmethod
-        def from_dict(cls, dct):
+        def from_dict(cls, dct: dict) -> Self:
             """Reconstructs the NeighborsSetsHints from its JSON-serializable dict representation."""
             return cls(hints_type=dct["hints_type"], options=dct["options"])
 
@@ -592,7 +596,7 @@ def as_dict(self):
         }
 
     @classmethod
-    def from_dict(cls, dct):
+    def from_dict(cls, dct: dict) -> Self:
         """
         Reconstructs the CoordinationGeometry from its JSON-serializable dict representation.
 
@@ -602,7 +606,6 @@ def from_dict(cls, dct):
         Returns:
             CoordinationGeometry
         """
-        dec = MontyDecoder()
         return cls(
             mp_symbol=dct["mp_symbol"],
             name=dct["name"],
@@ -620,7 +623,7 @@ def from_dict(cls, dct):
             deactivate=dct["deactivate"],
             faces=dct["_faces"],
             edges=dct["_edges"],
-            algorithms=[dec.process_decoded(algo_d) for algo_d in dct["_algorithms"]]
+            algorithms=[MontyDecoder().process_decoded(algo_d) for algo_d in dct["_algorithms"]]
             if dct["_algorithms"] is not None
             else None,
             equivalent_indices=dct.get("equivalent_indices"),