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from __future__ import annotations
from emmet.core.molecules.bonds import MoleculeBondingDoc
from emmet.core.mpid import MPculeID
from mp_api.client.core import BaseRester
class MoleculesBondRester(BaseRester[MoleculeBondingDoc]):
suffix = "molecules/bonding"
document_model = MoleculeBondingDoc
primary_key = "property_id"
def search(
self,
molecule_ids: MPculeID | list[MPculeID] | None = None,
property_ids: str | list[str] | None = None,
method: str | None = None,
bond_type: str | None = None,
max_bond_length: float | None = None,
min_bond_length: float | None = None,
charge: int | None = None,
spin_multiplicity: int | None = None,
level_of_theory: str | None = None,
solvent: str | None = None,
lot_solvent: str | None = None,
formula: str | list[str] | None = None,
elements: list[str] | None = None,
exclude_elements: list[str] | None = None,
chemsys: str | list[str] | None = None,
num_chunks: int | None = None,
chunk_size: int = 1000,
all_fields: bool = True,
fields: list[str] | None = None,
):
"""Query molecules bonding docs using a variety of search criteria.
Arguments:
molecule_ids (MPculeID, List[MPculeID]): List of Materials Project Molecule IDs (MPculeIDs) to return data
for.
property_ids (str, List[str]): List of property IDs to return data for.
method (str): Method used to generate bonding data
(e.g. "nbo", "critic2", or "OpenBabelNN + metal_edge_extender")
bond_type (str): Bond type of interest (e.g. "C-O" for carbon-oxygen bonds)
max_bond_length (float): Maximum bond length in the molecule of the specified type
min_bond_length (float): Minimum bond length in the molecule of the specified type
charge (Tuple[int, int]): Minimum and maximum charge for the molecule.
spin_multiplicity (Tuple[int, int]): Minimum and maximum spin for the molecule.
level_of_theory (str): Desired level of theory (e.g. "wB97X-V/def2-TZVPPD/SMD")
solvent (str): Desired solvent (e.g. "SOLVENT=WATER")
lot_solvent (str): Desired combination of level of theory and solvent
(e.g. "wB97X-V/def2-TZVPPD/SMD(SOLVENT=THF)")
formula (str, List[str]): An alphabetical formula or list of formulas
(e.g. "C2 Li2 O4", ["C2 H4", "C2 H6"]).
elements (List[str]): A list of elements.
exclude_elements (List(str)): List of elements to exclude.
chemsys (str, List[str]): A chemical system, list of chemical systems
(e.g., Li-C-O, [C-O-H-N, Li-N]).
num_chunks (int): Maximum number of chunks of data to yield. None will yield all possible.
chunk_size (int): Number of data entries per chunk.
all_fields (bool): Whether to return all fields in the document. Defaults to True.
fields (List[str]): List of fields in MoleculeDoc to return data for.
Default is "molecule_id", "property_id", "solvent", "method", "last_updated"
if all_fields is False.
Returns:
([MoleculeBondingDoc]) List of bonding documents
"""
query_params = {} # type: dict
if molecule_ids:
if isinstance(molecule_ids, str):
molecule_ids = [molecule_ids]
query_params.update({"molecule_ids": ",".join(molecule_ids)})
if property_ids:
if isinstance(property_ids, str):
property_ids = [property_ids]
query_params.update({"property_ids": ",".join(property_ids)})
if method:
query_params.update({"method": method})
if bond_type:
query_params.update({"bond_type": bond_type})
if max_bond_length:
query_params.update({"max_bond_length": max_bond_length})
if min_bond_length:
query_params.update({"min_bond_length": max_bond_length})
if charge:
query_params.update({"charge": charge})
if spin_multiplicity:
query_params.update({"spin_multiplicity": spin_multiplicity})
if level_of_theory:
query_params.update({"level_of_theory": level_of_theory})
if solvent:
query_params.update({"solvent": solvent})
if lot_solvent:
query_params.update({"lot_solvent": lot_solvent})
if formula:
if isinstance(formula, str):
formula = [formula]
query_params.update({"formula": ",".join(formula)})
if chemsys:
if isinstance(chemsys, str):
chemsys = [chemsys]
query_params.update({"chemsys": ",".join(chemsys)})
if elements:
query_params.update({"elements": ",".join(elements)})
if exclude_elements:
query_params.update({"exclude_elements": ",".join(exclude_elements)})
return super()._search(
num_chunks=num_chunks,
chunk_size=chunk_size,
all_fields=all_fields,
fields=fields,
**query_params,
)
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