From eec94d5b765a1516a0df06ae04e7a162477b279d Mon Sep 17 00:00:00 2001
From: Toby Drane <tdrane@no10.gov.uk>
Date: Tue, 22 Aug 2023 09:52:26 +0100
Subject: [PATCH] convert layer to string

---
 sdk/rapid/items/schema.py    |  4 +---
 sdk/rapid/rapid.py           | 18 +++++++++---------
 sdk/rapid/utils/constants.py | 18 ------------------
 sdk/requirements.txt         |  1 -
 4 files changed, 10 insertions(+), 31 deletions(-)

diff --git a/sdk/rapid/items/schema.py b/sdk/rapid/items/schema.py
index ce6d2ea..9217946 100644
--- a/sdk/rapid/items/schema.py
+++ b/sdk/rapid/items/schema.py
@@ -2,8 +2,6 @@
 from typing import Dict, List, Optional, Union
 from pydantic.main import BaseModel
 
-from rapid.utils.constants import Layer
-
 
 class SensitivityLevel(Enum):
     PUBLIC = "PUBLIC"
@@ -22,7 +20,7 @@ class Owner(BaseModel):
 
 
 class SchemaMetadata(BaseModel):
-    layer: Layer
+    layer: str
     domain: str
     dataset: str
     sensitivity: SensitivityLevel
diff --git a/sdk/rapid/rapid.py b/sdk/rapid/rapid.py
index c58c063..3bb06b7 100644
--- a/sdk/rapid/rapid.py
+++ b/sdk/rapid/rapid.py
@@ -12,7 +12,7 @@
 from rapid.auth import RapidAuth
 from rapid.items.schema import Schema
 from rapid.items.query import Query
-from rapid.utils.constants import TIMEOUT_PERIOD, Layer
+from rapid.utils.constants import TIMEOUT_PERIOD
 from rapid.exceptions import (
     DataFrameUploadFailedException,
     DataFrameUploadValidationException,
@@ -99,7 +99,7 @@ def wait_for_job_outcome(self, _id: str, interval: int = 1):
 
     def download_dataframe(
         self,
-        layer: Layer,
+        layer: str,
         domain: str,
         dataset: str,
         version: Optional[int] = None,
@@ -109,7 +109,7 @@ def download_dataframe(
         Downloads data to a pandas DataFrame based on the domain, dataset and version passed.
 
         Args:
-            layer (Layer): The layer of the dataset to download the DataFrame from.
+            layer (str): The layer of the dataset to download the DataFrame from.
             domain (str): The domain of the dataset to download the DataFrame from.
             dataset (str): The dataset from the domain to download the DataFrame from.
             version (int, optional): Version of the dataset to download.
@@ -142,7 +142,7 @@ def download_dataframe(
 
     def upload_dataframe(
         self,
-        layer: Layer,
+        layer: str,
         domain: str,
         dataset: str,
         df: DataFrame,
@@ -152,7 +152,7 @@ def upload_dataframe(
         Uploads a pandas DataFrame to a specified dataset in the API.
 
         Args:
-            layer (Layer): The layer of the dataset to upload the DataFrame to.
+            layer (str): The layer of the dataset to upload the DataFrame to.
             domain (str): The domain of the dataset to upload the DataFrame to.
             dataset (str): The name of the dataset to upload the DataFrame to.
             df (DataFrame): The pandas DataFrame to upload.
@@ -190,13 +190,13 @@ def upload_dataframe(
             data["details"],
         )
 
-    def generate_info(self, df: DataFrame, layer: Layer, domain: str, dataset: str):
+    def generate_info(self, df: DataFrame, layer: str, domain: str, dataset: str):
         """
         Generates metadata information for a pandas DataFrame and a specified dataset in the API.
 
         Args:
             df (DataFrame): The pandas DataFrame to generate metadata for.
-            layer (Layer): The layer of the dataset to generate metadata for.
+            layer (str): The layer of the dataset to generate metadata for.
             domain (str): The domain of the dataset to generate metadata for.
             dataset (str): The name of the dataset to generate metadata for.
 
@@ -239,14 +239,14 @@ def convert_dataframe_for_file_upload(self, df: DataFrame):
         }
 
     def generate_schema(
-        self, df: DataFrame, layer: Layer, domain: str, dataset: str, sensitivity: str
+        self, df: DataFrame, layer: str, domain: str, dataset: str, sensitivity: str
     ) -> Schema:
         """
         Generates a schema for a pandas DataFrame and a specified dataset in the API.
 
         Args:
             df (DataFrame): The pandas DataFrame to generate a schema for.
-            layer (Layer): The layer of the dataset to generate a schema for.
+            layer (str): The layer of the dataset to generate a schema for.
             domain (str): The domain of the dataset to generate a schema for.
             dataset (str): The name of the dataset to generate a schema for.
             sensitivity (str): The sensitivity level of the schema to generate.
diff --git a/sdk/rapid/utils/constants.py b/sdk/rapid/utils/constants.py
index dcdf8f8..e86af19 100644
--- a/sdk/rapid/utils/constants.py
+++ b/sdk/rapid/utils/constants.py
@@ -1,19 +1 @@
-import os
-from strenum import StrEnum
-
 TIMEOUT_PERIOD = 30
-
-LAYERS = "LAYERS"
-DEFAULT = "default"
-
-
-def get_layers_from_environment():
-    input = os.environ.get(LAYERS, DEFAULT)
-    layers = [layer.lower() for layer in input.split(",")]
-    return layers
-
-
-# Dynamically creates the Layer Enum from the environment variables
-Layer = StrEnum(
-    "Layer", dict([(layer, layer) for layer in get_layers_from_environment()])
-)
diff --git a/sdk/requirements.txt b/sdk/requirements.txt
index 06bf981..c086b21 100644
--- a/sdk/requirements.txt
+++ b/sdk/requirements.txt
@@ -7,4 +7,3 @@ requests
 requests-mock
 twine
 pydantic
-strenum