"""
OpenTargets_get_similar_entities_by_target_ensemblID
Retrieve similar entities for a given target ensemblID using a model trained with PubMed.
"""
from typing import Any, Optional, Callable
from ._shared_client import get_shared_client
[docs]
def OpenTargets_get_similar_entities_by_target_ensemblID(
ensemblId: str,
threshold: float,
size: int,
*,
stream_callback: Optional[Callable[[str], None]] = None,
use_cache: bool = False,
validate: bool = True,
) -> dict[str, Any]:
"""
Retrieve similar entities for a given target ensemblID using a model trained with PubMed.
Parameters
----------
ensemblId : str
The ensemblID of the disease.
threshold : float
Threshold similarity between 0 and 1. Only results above threshold are returned.
size : int
Number of similar entities to fetch.
stream_callback : Callable, optional
Callback for streaming output
use_cache : bool, default False
Enable caching
validate : bool, default True
Validate parameters
Returns
-------
dict[str, Any]
"""
# Handle mutable defaults to avoid B006 linting error
# Strip None values so optional parameters don't trigger schema validation errors
_args = {
k: v
for k, v in {
"ensemblId": ensemblId,
"threshold": threshold,
"size": size,
}.items()
if v is not None
}
return get_shared_client().run_one_function(
{
"name": "OpenTargets_get_similar_entities_by_target_ensemblID",
"arguments": _args,
},
stream_callback=stream_callback,
use_cache=use_cache,
validate=validate,
)
__all__ = ["OpenTargets_get_similar_entities_by_target_ensemblID"]
