mirror of
https://github.com/hwchase17/langchain
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72ba738bf5
Fixes linting for PR [19244](https://github.com/langchain-ai/langchain/pull/19244) --------- Co-authored-by: mhavey <mchavey@gmail.com>
297 lines
10 KiB
Python
297 lines
10 KiB
Python
import json
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from types import SimpleNamespace
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from typing import Any, Dict, Optional, Sequence
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import requests
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# Query to find OWL datatype properties
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DTPROP_QUERY = """
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SELECT DISTINCT ?elem
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WHERE {
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?elem a owl:DatatypeProperty .
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}
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"""
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# Query to find OWL object properties
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OPROP_QUERY = """
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SELECT DISTINCT ?elem
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WHERE {
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?elem a owl:ObjectProperty .
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}
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"""
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ELEM_TYPES = {
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"classes": None,
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"rels": None,
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"dtprops": DTPROP_QUERY,
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"oprops": OPROP_QUERY,
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}
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class NeptuneRdfGraph:
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"""Neptune wrapper for RDF graph operations.
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Args:
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host: endpoint for the database instance
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port: port number for the database instance, default is 8182
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use_iam_auth: boolean indicating IAM auth is enabled in Neptune cluster
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use_https: whether to use secure connection, default is True
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client: optional boto3 Neptune client
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credentials_profile_name: optional AWS profile name
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region_name: optional AWS region, e.g., us-west-2
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service: optional service name, default is neptunedata
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sign: optional, whether to sign the request payload, default is True
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Example:
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.. code-block:: python
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graph = NeptuneRdfGraph(
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host='<SPARQL host'>,
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port=<SPARQL port>
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)
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schema = graph.get_schema()
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OR
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graph = NeptuneRdfGraph(
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host='<SPARQL host'>,
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port=<SPARQL port>
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)
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schema_elem = graph.get_schema_elements()
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#... change schema_elements ...
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graph.load_schema(schema_elem)
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*Security note*: Make sure that the database connection uses credentials
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that are narrowly-scoped to only include necessary permissions.
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Failure to do so may result in data corruption or loss, since the calling
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code may attempt commands that would result in deletion, mutation
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of data if appropriately prompted or reading sensitive data if such
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data is present in the database.
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The best way to guard against such negative outcomes is to (as appropriate)
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limit the permissions granted to the credentials used with this tool.
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See https://python.langchain.com/docs/security for more information.
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"""
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def __init__(
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self,
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host: str,
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port: int = 8182,
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use_https: bool = True,
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use_iam_auth: bool = False,
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client: Any = None,
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credentials_profile_name: Optional[str] = None,
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region_name: Optional[str] = None,
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service: str = "neptunedata",
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sign: bool = True,
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) -> None:
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self.use_iam_auth = use_iam_auth
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self.region_name = region_name
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self.query_endpoint = f"https://{host}:{port}/sparql"
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try:
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if client is not None:
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self.client = client
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else:
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import boto3
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if credentials_profile_name is not None:
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self.session = boto3.Session(profile_name=credentials_profile_name)
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else:
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# use default credentials
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self.session = boto3.Session()
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client_params = {}
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if region_name:
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client_params["region_name"] = region_name
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protocol = "https" if use_https else "http"
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client_params["endpoint_url"] = f"{protocol}://{host}:{port}"
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if sign:
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self.client = self.session.client(service, **client_params)
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else:
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from botocore import UNSIGNED
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from botocore.config import Config
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self.client = self.session.client(
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service,
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**client_params,
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config=Config(signature_version=UNSIGNED),
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)
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except ImportError:
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raise ModuleNotFoundError(
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"Could not import boto3 python package. "
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"Please install it with `pip install boto3`."
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)
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except Exception as e:
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if type(e).__name__ == "UnknownServiceError":
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raise ModuleNotFoundError(
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"NeptuneGraph requires a boto3 version 1.28.38 or greater."
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"Please install it with `pip install -U boto3`."
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) from e
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else:
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raise ValueError(
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"Could not load credentials to authenticate with AWS client. "
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"Please check that credentials in the specified "
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"profile name are valid."
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) from e
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# Set schema
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self.schema = ""
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self.schema_elements: Dict[str, Any] = {}
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self._refresh_schema()
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@property
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def get_schema(self) -> str:
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"""
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Returns the schema of the graph database.
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"""
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return self.schema
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@property
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def get_schema_elements(self) -> Dict[str, Any]:
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return self.schema_elements
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def get_summary(self) -> Dict[str, Any]:
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"""
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Obtain Neptune statistical summary of classes and predicates in the graph.
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"""
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return self.client.get_rdf_graph_summary(mode="detailed")
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def query(
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self,
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query: str,
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) -> Dict[str, Any]:
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"""
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Run Neptune query.
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"""
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request_data = {"query": query}
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data = request_data
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request_hdr = None
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if self.use_iam_auth:
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credentials = self.session.get_credentials()
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credentials = credentials.get_frozen_credentials()
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access_key = credentials.access_key
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secret_key = credentials.secret_key
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service = "neptune-db"
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session_token = credentials.token
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params = None
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creds = SimpleNamespace(
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access_key=access_key,
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secret_key=secret_key,
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token=session_token,
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region=self.region_name,
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)
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from botocore.awsrequest import AWSRequest
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request = AWSRequest(
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method="POST", url=self.query_endpoint, data=data, params=params
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)
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from botocore.auth import SigV4Auth
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SigV4Auth(creds, service, self.region_name).add_auth(request)
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request.headers["Content-Type"] = "application/x-www-form-urlencoded"
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request_hdr = request.headers
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else:
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request_hdr = {}
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request_hdr["Content-Type"] = "application/x-www-form-urlencoded"
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queryres = requests.request(
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method="POST", url=self.query_endpoint, headers=request_hdr, data=data
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)
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json_resp = json.loads(queryres.text)
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return json_resp
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def load_schema(self, schema_elements: Dict[str, Any]) -> None:
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"""
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Generates and sets schema from schema_elements. Helpful in
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cases where introspected schema needs pruning.
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"""
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elem_str = {}
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for elem in ELEM_TYPES:
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res_list = []
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for elem_rec in schema_elements[elem]:
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uri = elem_rec["uri"]
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local = elem_rec["local"]
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res_str = f"<{uri}> ({local})"
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res_list.append(res_str)
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elem_str[elem] = ", ".join(res_list)
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self.schema = (
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"In the following, each IRI is followed by the local name and "
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"optionally its description in parentheses. \n"
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"The graph supports the following node types:\n"
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f"{elem_str['classes']}\n"
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"The graph supports the following relationships:\n"
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f"{elem_str['rels']}\n"
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"The graph supports the following OWL object properties:\n"
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f"{elem_str['dtprops']}\n"
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"The graph supports the following OWL data properties:\n"
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f"{elem_str['oprops']}"
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)
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def _get_local_name(self, iri: str) -> Sequence[str]:
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"""
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Split IRI into prefix and local
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"""
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if "#" in iri:
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tokens = iri.split("#")
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return [f"{tokens[0]}#", tokens[-1]]
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elif "/" in iri:
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tokens = iri.split("/")
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return [f"{'/'.join(tokens[0:len(tokens)-1])}/", tokens[-1]]
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else:
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raise ValueError(f"Unexpected IRI '{iri}', contains neither '#' nor '/'.")
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def _refresh_schema(self) -> None:
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"""
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Query Neptune to introspect schema.
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"""
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self.schema_elements["distinct_prefixes"] = {}
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# get summary and build list of classes and rels
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summary = self.get_summary()
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reslist = []
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for c in summary["payload"]["graphSummary"]["classes"]:
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uri = c
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tokens = self._get_local_name(uri)
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elem_record = {"uri": uri, "local": tokens[1]}
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reslist.append(elem_record)
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if tokens[0] not in self.schema_elements["distinct_prefixes"]:
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self.schema_elements["distinct_prefixes"][tokens[0]] = "y"
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self.schema_elements["classes"] = reslist
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reslist = []
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for r in summary["payload"]["graphSummary"]["predicates"]:
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for p in r:
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uri = p
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tokens = self._get_local_name(uri)
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elem_record = {"uri": uri, "local": tokens[1]}
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reslist.append(elem_record)
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if tokens[0] not in self.schema_elements["distinct_prefixes"]:
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self.schema_elements["distinct_prefixes"][tokens[0]] = "y"
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self.schema_elements["rels"] = reslist
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# get dtprops and oprops too
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for elem in ELEM_TYPES:
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q = ELEM_TYPES.get(elem)
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if not q:
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continue
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items = self.query(q)
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reslist = []
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for r in items["results"]["bindings"]:
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uri = r["elem"]["value"]
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tokens = self._get_local_name(uri)
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elem_record = {"uri": uri, "local": tokens[1]}
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reslist.append(elem_record)
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if tokens[0] not in self.schema_elements["distinct_prefixes"]:
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self.schema_elements["distinct_prefixes"][tokens[0]] = "y"
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self.schema_elements[elem] = reslist
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self.load_schema(self.schema_elements)
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