other models and db setup

Author: sooyounga

db/__init__.py

@@ -0,0 +1,25 @@
+from sqlalchemy import Column, DateTime, ForeignKey, Integer, String, Float
+from sqlalchemy.ext.declarative import declarative_base
+from sqlalchemy.orm import relationship
+from sqlalchemy.sql import func
+
+Base  = declarative_base()
+
+class BioSample(Base):
+    __tablename__ = 'biosample'
+    id  = Column(Integer, primary_key=True, index=True)
+    name = Column(String)
+    time_created = Column(DateTime(timezone=True), server_default=func.now())
+    time_updated = Column(DateTime(timezone=True), onupdate=func.now())
+    biosample_id = Column(Integer, ForeignKey('biosample.id'))
+
+    biosample = relationship('BioSample')
+
+
+class Participant(Base):
+    __tablename__ = 'participant'
+    id = Column(Integer, primary_key=True)
+    name = Column(String)
+    age = Column(Integer)
+    time_created = Column(DateTime(timezone=True), server_default=func.now())
+    time_updated = Column(DateTime(timezone=True), onupdate=func.now())

db/models.py

@@ -0,0 +1,23 @@
+id: https://bican.org/examples/participant
+name: participant
+prefixes:
+  linkml: https://w3id.org/linkml/
+imports:
+  - linkml:types
+default_range: string
+
+classes:
+  Participant:
+    attributes:
+      identifier:
+      altName:
+      strain:
+      cellLine:
+      vendor:
+      age:
+      sex:
+      genotype:
+      species:
+      disorder:
+      relatedParticipant:
+      sameAs:

db/participant.yaml

@@ -0,0 +1,16 @@
+# build a schema using pydantic
+from pydantic import BaseModel
+
+class BioSample(BaseModel):
+    name: str
+    biosample_id: int
+
+    class Config:
+        orm_mode = True
+
+class Participant(BaseModel):
+    name:str
+    age:int
+
+    class Config:
+        orm_mode = True

db/schema.py

@@ -4,6 +4,13 @@
 # from internal import admin
 from routers import biosamples, participants
 
+import uvicorn
+from fastapi_sqlalchemy import DBSessionMiddleware, db
+import os
+from dotenv import load_dotenv
+
+load_dotenv('.env')
+
 app = FastAPI(dependencies=[Depends(get_query_token)])
 
 
@@ -17,7 +24,14 @@
 #     responses={418: {"description": "I'm a teapot"}},
 # )
 
+# to avoid csrftokenError
+app.add_middleware(DBSessionMiddleware, db_url=os.environ['DATABASE_URL'])
 
 @app.get("/")
 async def root():
     return {"message": "Knowledge Graph API"}
+
+
+# To run locally
+if __name__ == '__main__':
+    uvicorn.run(app, host='0.0.0.0', port=8000)

main.py

@@ -0,0 +1,5 @@
+from pydantic import BaseModel
+
+
+class Annotations(BaseModel):
+    name: str

models/__init__.py

@@ -0,0 +1,5 @@
+from pydantic import BaseModel
+
+
+class Assay(BaseModel):
+    name: str

models/annotations.py

@@ -0,0 +1,5 @@
+from pydantic import BaseModel
+
+
+class Atlas(BaseModel):
+    type: Spatial, Dimensional

models/assay.py

@@ -0,0 +1,39 @@
+from dandischema import DandiBaseModel
+
+
+class BioSample(DandiBaseModel):
+    """Description of the sample that was studied"""
+
+    identifier: Identifier = Field(nskey="schema")
+    sampleType: SampleType = Field(
+        description="Identifier for the sample characteristics (e.g., from OBI, Encode).",
+        nskey="dandi",
+    )
+    assayType: Optional[List[AssayType]] = Field(
+        None, description="Identifier for the assay(s) used (e.g., OBI).", nskey="dandi"
+    )
+    anatomy: Optional[List[Anatomy]] = Field(
+        None,
+        description="Identifier for what organ the sample belongs "
+                    "to. Use the most specific descriptor from sources such as UBERON.",
+        nskey="dandi",
+    )
+
+    wasDerivedFrom: Optional[List["BioSample"]] = Field(
+        None,
+        description="Describes the hierarchy of sample derivation or aggregation.",
+        nskey="prov",
+    )
+    wasAttributedTo: Optional[List[Participant]] = Field(
+        None,
+        description="Participant(s) or Subject(s) associated with this sample.",
+        nskey="prov",
+    )
+    sameAs: Optional[List[Identifier]] = Field(None, nskey="schema")
+    hasMember: Optional[List[Identifier]] = Field(None, nskey="prov")
+
+    _ldmeta = {
+        "rdfs:subClassOf": ["schema:Thing", "prov:Entity"],
+        "rdfs:label": "Information about the biosample.",
+        "nskey": "dandi",
+    }