chore: pull up func base64_to_dict

ibis-server/app/mdl/substitute.py

@@ -1,17 +1,15 @@
-import base64
-
-from orjson import orjson
 from sqlglot import exp, parse_one
 from sqlglot.optimizer.scope import build_scope
 
 from app.model import UnprocessableEntityError
 from app.model.data_source import DataSource
+from app.util import base64_to_dict
 
 
 class ModelSubstitute:
     def __init__(self, data_source: DataSource, manifest_str: str):
         self.data_source = data_source
-        self.manifest = orjson.loads(base64.b64decode(manifest_str).decode("utf-8"))
+        self.manifest = base64_to_dict(manifest_str)
         self.model_dict = self._build_model_dict(self.manifest["models"])
 
     def substitute(self, sql: str, write: str | None = None) -> str:

ibis-server/app/model/validator.py

@@ -1,11 +1,9 @@
 from __future__ import annotations
 
-import base64
-import json
-
 from app.mdl.rewriter import Rewriter
 from app.model import NotFoundError, UnprocessableEntityError
 from app.model.connector import Connector
+from app.util import base64_to_dict
 
 rules = ["column_is_valid", "relationship_is_valid"]
 
@@ -48,8 +46,8 @@ async def _validate_relationship_is_valid(
         relationship_name = parameters.get("relationshipName")
         if relationship_name is None:
             raise MissingRequiredParameterError("relationship")
-        decoded_manifest = base64.b64decode(manifest_str).decode("utf-8")
-        manifest = json.loads(decoded_manifest)
+
+        manifest = base64_to_dict(manifest_str)
 
         relationship = list(
             filter(lambda r: r["name"] == relationship_name, manifest["relationships"])

ibis-server/app/util.py

@@ -1,3 +1,4 @@
+import base64
 import datetime
 import decimal
 
@@ -6,6 +7,10 @@
 from pandas.core.dtypes.common import is_datetime64_any_dtype
 
 
+def base64_to_dict(base64_str: str) -> dict:
+    return orjson.loads(base64.b64decode(base64_str).decode("utf-8"))
+
+
 def to_json(df: pd.DataFrame) -> dict:
     for column in df.columns:
         if is_datetime64_any_dtype(df[column].dtype):