Release 0.0.2

setup.cfg

@@ -1,15 +1,15 @@
 
 [metadata]
 name = odm2datamodels
-description = "Collection of object-relational mapping (ORM) data models for ODM2"
+description = Collection of object-relational mapping (ORM) data models for ODM2
 long_description = file: README.md
-long_description_content = text/markdown
-version = 0.0.1
-author = "ODM2 Team"
-author_email = ""
+long_description_content_type = text/markdown
+version = 0.0.2
+author = ODM2 Team
+author_email = ptomasula@limno.com
 url = https://github.com/ODM2/ODM2DataModels
 project_urls =
-    bugtracker = https://github.com/ODM2/ODM2DataModels/issueshttps://github.com/pypa/sampleproject/issues
+    bugtracker = https://github.com/ODM2/ODM2DataModels/issues
 keywords='Observations Data Model ODM2'
 
 [options]

src/odm2datamodels/base.py

@@ -28,11 +28,12 @@
 from .models import samplingfeatures
 from .models import simulation
 
+import warnings
+warnings.simplefilter("ignore", category=sqlalchemy.exc.SAWarning)
+
+OUTPUT_FORMATS = ('json', 'dataframe', 'dict')
+
 
-class OutputFormats(Enum):
-    JSON ='JSON'
-    DATAFRAME = 'DATAFRAME'
-    DICT = 'DICT'
 
 class Base():
 
@@ -82,19 +83,25 @@ def __init__(self, session_maker:sqlalchemy.orm.sessionmaker) -> None:
 
     def read_query(self, 
             query: Union[Query, Select],
-            output_format:OutputFormats=OutputFormats.JSON,
+            output_format:str='json',
             orient:str='records') -> Union[str, pd.DataFrame]:
+
+        # guard against invalid output_format strings
+        if output_format not in OUTPUT_FORMATS:
+            raise ValueError(f':argument output_format={output_format}, is not a valid output_format strings: {OUTPUT_FORMATS}')
+
+        # use SQLAlchemy session to read_query and return response in the designated output_format
         with self.session_maker() as session:
             if isinstance(query, Select):
                 df = pd.read_sql(query, session.bind)
             else:
                 df = pd.read_sql(query.statement, session.bind)
 
-            if output_format == OutputFormats.JSON:
+            if output_format == 'json':
                 return df.to_json(orient=orient)
-            elif output_format == OutputFormats.DATAFRAME:
+            elif output_format == 'dataframe':
                 return df
-            elif output_format == OutputFormats.DICT:
+            elif output_format == 'dict':
                 return df.to_dict()
             raise TypeError("Unknown output format")
 
@@ -117,7 +124,7 @@ def create_object(self, obj:object) -> Union[int, str]:
             return pkey_value
 
     def read_object(self, model:Type[Base], pkey:Union[int, str], 
-            output_format: OutputFormats=OutputFormats.DICT, 
+            output_format:str='dict', 
             orient:str='records') -> Dict[str, Any]:
 
         with self.session_maker() as session:
@@ -126,8 +133,14 @@ def read_object(self, model:Type[Base], pkey:Union[int, str],
             if obj is None: raise ObjectNotFound(f"No '{model.__name__}' object found with {pkey_name} = {pkey}")
             session.commit()
 
+            # convert obj_dict to a dictionary if it isn't one already
             obj_dict = obj.to_dict()
-            if output_format == OutputFormats.DICT:
+
+            # guard against invalid output_format strings
+            if output_format not in OUTPUT_FORMATS:
+                raise ValueError(f':param output_format = {output_format}, which is not one of the following valid output_format strings: {OUTPUT_FORMATS}')
+
+            if output_format == 'dict':
                 return obj_dict
 
             else:
@@ -139,9 +152,9 @@ def read_object(self, model:Type[Base], pkey:Union[int, str],
                         obj_dict[key] = new_value
 
                 obj_df = pd.DataFrame.from_dict(obj_dict)
-                if output_format == OutputFormats.DATAFRAME:
+                if output_format == 'dataframe':
                     return obj_df
-                elif output_format == OutputFormats.JSON:
+                elif output_format == 'json':
                     return obj_df.to_json(orient=orient)
                 raise TypeError("Unknown output format")