Merge pull request #39 from linkml/additional-formats

Additional formats

pyproject.toml

@@ -23,6 +23,7 @@ pystow = "^0.5.4"
 black = { version=">=24.0.0", optional = true }
 ruff = { version=">=0.6.2", optional = true }
 llm = { version="*", optional = true }
+lightrdf = { version="*", optional = true }
 tiktoken = { version="*", optional = true }
 pymongo = "^4.11"
 neo4j = { version="*", optional = true }
@@ -91,6 +92,7 @@ renderer = ["linkml_renderer"]
 fastapi = ["fastapi", "uvicorn"]
 frictionless = ["frictionless"]
 scipy = ["scipy", "scikit-learn"]
+rdf = ["lightrdf"]
 #ibis = ["ibis-framework", "multipledispatch", "gcsfs"]
 bigquery = ["google-cloud-bigquery"]
 all = ["llm", "mongodb", "neo4j", "validation", "map", "renderer", "bigquery"]

src/linkml_store/api/collection.py

@@ -454,7 +454,12 @@ def get_one(self, id: IDENTIFIER, **kwargs) -> Optional[OBJECT]:
             return qr.rows[0]
         return None
 
-    def find(self, where: Optional[Any] = None, **kwargs) -> QueryResult:
+    def find(
+            self,
+            where: Optional[Any] = None,
+            select_cols: Optional[List[str] ] = None,
+            **kwargs,
+    ) -> QueryResult:
         """
         Find objects in the collection using a where query.
 
@@ -484,10 +489,14 @@ def find(self, where: Optional[Any] = None, **kwargs) -> QueryResult:
 
 
         :param where:
+        :param select_cols:
         :param kwargs:
         :return:
         """
-        query = self._create_query(where_clause=where)
+        query = self._create_query(
+            where_clause=where,
+            select_cols=select_cols,
+        )
         self._pre_query_hook(query)
         return self.query(query, **kwargs)
 
@@ -608,6 +617,47 @@ def row2array(row):
         new_qr.rows = [r[1] for r in results]
         return new_qr
 
+    def group_by(
+            self,
+            group_by_fields: List[str],
+            inlined_field = "objects",
+            agg_map: Optional[Dict[str, str]] = None,
+            where: Optional[Dict] = None,
+            **kwargs,
+    ) -> QueryResult:
+        """
+        Group objects in the collection by a column.
+
+        :param group_by:
+        :param where:
+        :param kwargs:
+        :return:
+        """
+        if isinstance(group_by_fields, str):
+            group_by_fields = [group_by_fields]
+        df = self.find(where=where, limit=-1).rows_dataframe
+        pk_fields = agg_map.get("first", []) + group_by_fields
+        list_fields = agg_map.get("list", [])
+        if not list_fields:
+            list_fields = [a for a in df.columns if a not in pk_fields]
+
+        grouped_objs = defaultdict(list)
+        for _, row in df.iterrows():
+            pk = tuple(row[pk_fields])
+            grouped_objs[pk].append({k: row[k] for k in list_fields})
+        results = []
+        for pk, objs in grouped_objs.items():
+            top_obj = {k: v for k, v in zip(pk_fields, pk)}
+            top_obj[inlined_field] = objs
+            results.append(top_obj)
+        r = QueryResult(
+            num_rows=len(results),
+            rows=results
+        )
+        return r
+
+
+
     @property
     def is_internal(self) -> bool:
         """
@@ -1062,7 +1112,7 @@ def induce_class_definition_from_objects(
             multivalued = any(multivalueds)
             inlined = any(inlineds)
             if multivalued and False in multivalueds:
-                raise ValueError(f"Mixed list non list: {vs} // inferred= {multivalueds}")
+                logger.info(f"Mixed list non list: {vs} // inferred= {multivalueds}")
             # if not rngs:
             #    raise AssertionError(f"Empty rngs for {k} = {vs}")
             rng = rngs[0] if rngs else None

src/linkml_store/api/stores/duckdb/duckdb_collection.py

@@ -1,5 +1,5 @@
 import logging
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Dict, List, Optional, Union, Tuple
 
 import sqlalchemy as sqla
 from linkml_runtime.linkml_model import ClassDefinition, SlotDefinition
@@ -94,7 +94,9 @@ def delete_where(self, where: Optional[Dict[str, Any]] = None, missing_ok=True,
 
     def query_facets(
         self, where: Dict = None, facet_columns: List[str] = None, facet_limit=DEFAULT_FACET_LIMIT, **kwargs
-    ) -> Dict[str, Dict[str, int]]:
+    ) -> Dict[Union[str, Tuple[str, ...]], List[Tuple[Any, int]]]:
+        if facet_limit is None:
+            facet_limit = DEFAULT_FACET_LIMIT
         results = {}
         cd = self.class_definition()
         with self.parent.engine.connect() as conn:

src/linkml_store/api/stores/mongodb/mongodb_collection.py

@@ -164,6 +164,8 @@ def query_facets(
         facet_limit=DEFAULT_FACET_LIMIT,
         **kwargs,
     ) -> Dict[Union[str, Tuple[str, ...]], List[Tuple[Any, int]]]:
+        if facet_limit is None:
+            facet_limit = DEFAULT_FACET_LIMIT
         results = {}
         if not facet_columns:
             facet_columns = list(self.class_definition().attributes.keys())

src/linkml_store/api/stores/mongodb/mongodb_database.py

@@ -41,7 +41,6 @@ def _db_name(self) -> str:
         if self.handle:
             parsed_url = urlparse(self.handle)
             path_parts = parsed_url.path.lstrip("/").split("?")[0].split("/")
-            print(path_parts)
             db_name = path_parts[0] if path_parts else "default"
         else:
             db_name = "default"

src/linkml_store/api/stores/solr/solr_collection.py

@@ -62,12 +62,18 @@ def query(self, query: Query, **kwargs) -> QueryResult:
         return QueryResult(query=query, num_rows=num_rows, rows=rows)
 
     def query_facets(
-        self, where: Optional[Dict] = None, facet_columns: List[str] = None, facet_limit=DEFAULT_FACET_LIMIT, **kwargs
+        self,
+            where: Optional[Dict] = None,
+            facet_columns: List[str] = None,
+            facet_limit=DEFAULT_FACET_LIMIT,
+            facet_min_count: int = 1,
+            **kwargs
     ) -> Dict[str, Dict[str, int]]:
         solr_query = self._build_solr_query(where)
         solr_query["facet"] = "true"
         solr_query["facet.field"] = facet_columns
         solr_query["facet.limit"] = facet_limit
+        solr_query["facet.mincount"] = facet_min_count
 
         logger.info(f"Querying Solr collection {self.alias} for facets with query: {solr_query}")