Fix linting errors.

Author: shyuep

src/pymatgen/core/adsorption.py

@@ -109,7 +109,7 @@ def from_bulk_and_miller(
             min_vacuum_size (float): min vacuum size for slab generation
             max_normal_search (int): max normal search for slab generation
             center_slab (bool): whether to center slab in slab generation
-            selective dynamics (bool): whether to assign surface sites
+            selective_dynamics (bool): whether to assign surface sites
                 to selective dynamics
             undercoord_threshold (float): threshold of "undercoordation"
                 to use for the assignment of surface sites. Default is
@@ -486,6 +486,8 @@ def adsorb_both_surfaces(
             repeat (3-tuple or list): repeat argument for supercell generation
             min_lw (float): minimum length and width of the slab, only used
                 if repeat is None
+            translate (bool): flag on whether or not to translate adsorbate
+                to the adsorption site
             reorient (bool): flag on whether or not to reorient adsorbate
                 along the miller index
             find_args (dict): dictionary of arguments to be passed to the
@@ -656,6 +658,7 @@ def plot_slab(
         window (float): window for setting the axes limits, is essentially
             a fraction of the unit cell limits
         draw_unit_cell (bool): flag indicating whether or not to draw cell
+        adsorption_sites (bool): whether to plot adsorption sites
         decay (float): how the alpha-value decays along the z-axis
         inverse (bool): invert z axis to plot opposite surface
     """

src/pymatgen/core/bond_valence.py

@@ -468,6 +468,7 @@ def add_oxidation_state_by_site_fraction(structure: Structure, oxidation_states:
     Add oxidation states to a structure by fractional site.
 
     Args:
+        structure (Structure): Structure to which oxidation states are added.
         oxidation_states (list[list[int]]): List of list of oxidation states for each
             site fraction for each site.
             e.g. [[2, 4], [3], [-2], [-2], [-2]]

src/pymatgen/core/elasticity/elastic.py

@@ -839,9 +839,9 @@ def get_yield_stress(self, n):
 # TODO: abstract this for other tensor fitting procedures
 def diff_fit(strains, stresses, eq_stress=None, order=2, tol: float = 1e-10):
     """
-    Nth order elastic constant fitting function based on.
-    central-difference derivatives with respect to distinct
-    strain states. The algorithm is summarized as follows:
+    Nth order elastic constant fitting function based on central-difference derivatives.
+
+    The algorithm is summarized as follows:
 
     1. Identify distinct strain states as sets of indices
        for which nonzero strain values exist, typically

src/pymatgen/core/elasticity/strain.py

@@ -239,8 +239,9 @@ def von_mises_strain(self):
 
 def convert_strain_to_deformation(strain, shape: Literal["upper", "lower", "symmetric"]):
     """
-    This function converts a strain to a deformation gradient that will.
-    produce that strain. Supports three methods:
+    Convert a strain to a deformation gradient that will produce that strain.
+
+    Supports three methods:
 
     Args:
         strain (3x3 array-like): strain matrix

src/pymatgen/core/entries.py

@@ -14,43 +14,25 @@
 from __future__ import annotations
 
 import abc
-import collections
-import collections.abc
-import csv
-import itertools
 import json
-import logging
 import math
-import multiprocessing as mp
 import os
-import re
 import warnings
 from abc import ABC, abstractmethod
-from collections import defaultdict
-from datetime import UTC, datetime
-from itertools import combinations
 from typing import TYPE_CHECKING, cast
 
 import numpy as np
 import orjson
 from monty.json import MontyDecoder, MontyEncoder, MSONable
-from scipy.interpolate import interp1d
 from uncertainties import ufloat
 
-from pymatgen.util.due import Doi, due
-
 from .composition import Composition
 from .periodic_table import Element
-from .structure_matcher import SpeciesComparator, StructureMatcher
 
 if TYPE_CHECKING:
-
-    from collections.abc import Iterable
     from typing import Literal, Self
 
-    from pymatgen.analysis.phase_diagram import PhaseDiagram
     from pymatgen.core import DummySpecies, Element, Species, Structure
-    from pymatgen.util.typing import SpeciesLike
 
 __author__ = "Ryan Kingsbury, Matt McDermott, Shyue Ping Ong, Anubhav Jain"
 __copyright__ = "Copyright 2011-2020, The Materials Project"
@@ -63,10 +45,6 @@
     G_GASES = orjson.loads(file.read())
 
 
-
-
-
-
 __author__ = "Shyue Ping Ong, Anubhav Jain, Ayush Gupta"
 __copyright__ = "Copyright 2020, The Materials Project"
 __version__ = "1.1"
@@ -851,4 +829,3 @@ def copy(self) -> ComputedStructureEntry:
             data=self.data,
             entry_id=self.entry_id,
         )
-

src/pymatgen/core/graphs.py

@@ -275,6 +275,7 @@ def from_edges(cls, structure: Structure, edges: dict) -> Self:
     @classmethod
     @deprecated(from_edges, "Deprecated on 2024-03-29.", deadline=(2025, 3, 20))
     def with_edges(cls, *args, **kwargs):
+        """Deprecated method. Use from_edges instead."""
         return cls.from_edges(*args, **kwargs)
 
     @classmethod

src/pymatgen/core/molecule_structure_comparator.py

@@ -183,6 +183,9 @@ def __init__(
                 The index should start from 0.
             priority_cap: The ratio of the elongation of the bond to be
                 acknowledged for the priority bonds.
+            ignore_ionic_bond (bool): Whether to ignore ionic bonds.
+            bond_13_cap (float): The ratio of the elongation of the 1-3 bond to be
+                acknowledged.
         """
         self.bond_length_cap = bond_length_cap
         self.covalent_radius = covalent_radius
@@ -206,7 +209,8 @@ def are_equal(self, mol1, mol2) -> bool:
 
     @staticmethod
     def get_13_bonds(priority_bonds):
-        """
+        """Get the 1-3 bonds implied by the given priority bonds.
+
         Args:
             priority_bonds (list[tuple]): 12 bonds
 

src/pymatgen/core/structure_analyzer.py

@@ -244,7 +244,7 @@ def __init__(self, structure: Structure, cutoff=10):
         """
         Args:
             structure (Structure): Input structure
-            cutoff (float) Cutoff distance.
+            cutoff (float): Cutoff distance.
         """
         self.cutoff = cutoff
         self.structure = structure

src/pymatgen/core/structure_prediction/dopant_predictor.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import warnings
+from typing import Any
 
 import numpy as np
 
@@ -127,7 +128,7 @@ def get_dopants_from_shannon_radii(bonded_structure, num_dopants=5, match_oxi_si
 
 def _get_dopants(substitutions, num_dopants, match_oxi_sign) -> dict:
     """Utility method to get n- and p-type dopants from a list of substitutions."""
-    dopants = {k: [] for k in ("n_type", "p_type")}
+    dopants: dict[str, list[dict[str, Any]]] = {k: [] for k in ("n_type", "p_type")}
     for k, dop in dopants.items():
         for pred in substitutions:
             if (

src/pymatgen/core/structure_prediction/substitutor.py

@@ -178,10 +178,11 @@ def _is_from_chemical_system(chemical_system, struct) -> bool:
 
     def pred_from_list(self, species_list) -> list[dict]:
         """
-        There are an exceptionally large number of substitutions to.
-        look at (260^n), where n is the number of species in the
-        list. We need a more efficient than brute force way of going
-        through these possibilities. The brute force method would be:
+        Predict substitutions from a list of species.
+
+        There are an exceptionally large number of substitutions to look at (260^n),
+        where n is the number of species in the list. We need a more efficient than
+        brute force way of going through these possibilities. The brute force method would be:
 
             output = []
             for p in itertools.product(self._sp.species_list, repeat=len(species_list)):