diff --git a/databricks.yml b/databricks.yml
index 03ccce6..de31443 100644
--- a/databricks.yml
+++ b/databricks.yml
@@ -84,11 +84,11 @@ variables:
   prod_env_sp_id:
     default: "my-sp-id-jfsdkjhfjsdhfkjh"
 
-# qqqq will want later if many python files
+# for external package maybe qqqq i dont think we will export there are poetry bundle example repos if we decide to
 # artifacts:
-  # python_artifact:
-    # type: whl
-    # build: uv build --wheel
+#   python_artifact:
+#     type: whl
+#     build: uv build --wheel
 
 # Deployment environments
 targets:
diff --git a/pyproject.toml b/pyproject.toml
index 1707b8a..940124b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,32 +1,33 @@
-[project]
-name = "Workflow_POC"
-version = "0.0.1"
-authors = [{ name = "philip.tate@nhs.net" }]
-requires-python = ">=3.10,<=3.13"
-dependencies = [
-    # Any dependencies for jobs and pipelines in this project can be added here
-    # See also https://docs.databricks.com/dev-tools/bundles/library-dependencies
-    #
-    # LIMITATION: for pipelines, dependencies are cached during development;
-    # add dependencies to the 'environment' section of your pipeline.yml file instead
-]
-
-[dependency-groups]
-dev = [
-    "pytest",
-    "databricks-dlt",
-    "databricks-connect>=15.4,<15.5",
-]
-
-[project.scripts]
-main = "Workflow_POC.main:main"
-
-[build-system]
-requires = ["hatchling"]
-build-backend = "hatchling.build"
-
-[tool.hatch.build.targets.wheel]
-packages = ["src"]
-
-[tool.black]
-line-length = 125
+[project]
+name = "Workflow_POC"
+version = "0.0.1"
+authors = [{ name = "philip.tate@nhs.net" }]
+requires-python = ">=3.10,<=3.13"
+dependencies = [
+    # Any dependencies for jobs and pipelines in this project can be added here
+    # See also https://docs.databricks.com/dev-tools/bundles/library-dependencies
+    #
+    # LIMITATION: for pipelines, dependencies are cached during development;
+    # add dependencies to the 'environment' section of your pipeline.yml file instead
+]
+
+[dependency-groups]
+dev = [
+    "pytest",
+    "databricks-dlt",
+    "databricks-connect>=15.4,<15.5",
+]
+
+[project.scripts]
+main = "Workflow_POC.main:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+# Wheel packing came in the template :) qqqq
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[tool.black]
+line-length = 125
diff --git a/resources/pipeline/ods_ingestion.yml b/resources/pipeline/ods_ingestion.yml
index 7c91c29..8a6a1ea 100644
--- a/resources/pipeline/ods_ingestion.yml
+++ b/resources/pipeline/ods_ingestion.yml
@@ -60,7 +60,9 @@ resources:
             # if doing a pipeline per layer would do something like
             # include: ../../src/ingestion/ - might work
             # include: ../../src/ingestion/*.py   - doesnt work 
-            include: ../../src/ingestion/ods_ingest.py 
+            include: ../../src/ingestion/ods_ingest.py # -worked
+            # include: ../../src/**/*.py
+        #- folder: ../../src/utils
       photon: true
       # qqqq good practice to specify its something to do with dlt having beta version?
       channel: current
diff --git a/src/ingestion/ods_ingest.py b/src/ingestion/ods_ingest.py
index 9812f39..4abe78e 100644
--- a/src/ingestion/ods_ingest.py
+++ b/src/ingestion/ods_ingest.py
@@ -1,8 +1,21 @@
 # for making spark tables
 # qqqq problem i am having is that we are setting the schema, and dev has schema set as user names
 # i want to use the databricks.yml schema name for dev, and for staging and prod i want to set it to bronze_ods in this script
-from pyspark import pipelines as dp
 
+# This does work, but dont know how the file is working generally when bundle files are not generated anymore, so its not working from within the bundle.
+# ultimately probably still want to be in a wheel will see what happens with unit testing it
+import sys
+import os
+sys.path.append(os.path.abspath('..'))
+
+### TRY  ###
+# import sys
+# bundle_src_path = sys.argv[1]
+# sys.path.append(bundle_src_path)
+
+from pyspark import pipelines as dp
+#from utils.loaders import load_csv_table #use wheel instead
+from utils.loaders import load_csv_table
 
 # Fixed System Constants these and some of this stuff should be going in a helper i think
 #ADLS_PROTOCOL = "abfss://"
@@ -35,151 +48,264 @@
 # domain_folder ?? qqqq
 folder_name = spark.conf.get("pipeline.domain") # ods
 #folder_location_path = f"{ADLS_PROTOCOL}{container}@{storage_account}{ADLS_SUFFIX}/{folder_name}/"
-folder_location_path = f"{storage_container_path }/{folder_name}/"
+folder_location_path = f"{storage_container_path}/{folder_name}/"
 # "abfss://bronze@unifiedrptdeltalake.dfs.core.windows.net/ods
 print(folder_location_path)
+# qqqq this could be far simpler hardcode "import raw" the just list the names but we want it a bit more flexible
+
+# List of table names
+TABLE_NAMES = [
+    "Additional_Attributes_Details",
+    "Code_System_Details",
+    "Contact_Details",
+    "Manifest_Details",
+    "Organisation_Details",
+    "OtherID_Details",
+    "PrimaryRole_Details",
+    "Relationship_Details",
+    "Role_Details",
+    "Successor_Details",
+]
+
+
+# Define all ODS tables with their configurations
+# tables as keys because unique
+# only using dictionary because expect future use to have more to it
+
+# Generate table configurations dynamically
+ODS_TABLES = {
+    table_name: {
+        "csv_filename": f"{table_name}.csv",
+        "comment": f"Import raw {table_name}"
+    }
+    for table_name in TABLE_NAMES
+}
+
+# ODS_TABLES = {
+#     "Additional_Attributes_Details": {
+#         "csv_filename": "Additional_Attributes_Details.csv",
+#         "comment": "Import raw Additional_Attributes_Details"
+#     },
+#     "Code_System_Details": {
+#         "csv_filename": "Code_System_Details.csv",
+#         "comment": "Import raw Code_System_Details"
+#     },
+#     "Contact_Details": {
+#         "csv_filename": "Contact_Details.csv",
+#         "comment": "Import raw Contact_Details"
+#     },
+#     "Manifest_Details": {
+#         "csv_filename": "Manifest_Details.csv",
+#         "comment": "Import raw Manifest_Details"
+#     },
+#     "Organisation_Details": {
+#         "csv_filename": "Organisation_Details.csv",
+#         "comment": "Import raw Organisation_Details"
+#     },
+#     "OtherID_Details": {
+#         "csv_filename": "OtherID_Details.csv",
+#         "comment": "Import raw OtherID_Details"
+#     },
+#     "PrimaryRole_Details": {
+#         "csv_filename": "PrimaryRole_Details.csv",
+#         "comment": "Import raw PrimaryRole_Details"
+#     },
+#     "Relationship_Details": {
+#         "csv_filename": "Relationship_Details.csv",
+#         "comment": "Import raw Relationship_Details"
+#     },
+#     "Role_Details": {
+#         "csv_filename": "Role_Details.csv",
+#         "comment": "Import raw Role_Details"
+#     },
+#     "Successor_Details": {
+#         "csv_filename": "Successor_Details.csv",
+#         "comment": "Import raw Successor_Details"
+#     },
+# }
+
+## get from wheel
+# def load_csv_table(base_path, csv_filename):
+#     """Load CSV from Azure storage with standard options"""
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(f"{base_path}{csv_filename}")
+#     )
+
+# Create DLT tables dynamically
+for table_name, config in ODS_TABLES.items():
+    # Create a closure to capture the current loop variables
+    def create_table(name=table_name, cfg=config):
+        @dp.table(name=name, comment=cfg["comment"])
+        def table_loader():
+            return load_csv_table(folder_location_path, cfg["csv_filename"])
+        return table_loader
+    
+    create_table()
+
+
+# def load_csv_table(table_name):
+#     """Load CSV from Azure storage with standard options"""
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(f"{folder_location_path}{table_name}.csv")
+#     )
+
+# # Create DLT tables dynamically
+# for table_name, comment in ODS_TABLES:
+#     # Create a closure to capture the current loop variables
+#     def create_table(name=table_name, desc=comment):
+#         @dp.table(name=name, comment=desc)
+#         def table_loader():
+#             return load_csv_table(name)
+#         return table_loader
+    
+#     create_table()
 
+# @dp.table(
+#     # qqqq was f"{schema_name}.Additional_Attributes_Details" but worked before now need to do it this way???!!!
+#     name="Additional_Attributes_Details",
+#     comment="Import raw Additional_Attributes_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Additional_Attributes_Details.csv"
+#         )
+#     )
+
+# @dp.table(
+#     name="Code_System_Details",
+#     comment="Import raw Code_System_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Code_System_Details.csv"
+#         )
+#     ) 
 
-@dp.table(
-    # qqqq was f"{schema_name}.Additional_Attributes_Details" but worked before now need to do it this way???!!!
-    name="Additional_Attributes_Details",
-    comment="Import raw Additional_Attributes_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Additional_Attributes_Details.csv"
-        )
-    )
-
-@dp.table(
-    name="Code_System_Details",
-    comment="Import raw Code_System_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Code_System_Details.csv"
-        )
-    ) 
-
-@dp.table(
-    name="Contact_Details",
-    comment="Import raw Contact_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Contact_Details.csv"
-        )
-    ) 
-
-@dp.table(
-    name="Manifest_Details",
-    comment="Import raw Manifest_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Manifest_Details.csv"
-        )
-    ) 
-
-@dp.table(
-    name="Organisation_Details",
-    comment="Import raw Organisation_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Organisation_Details.csv"
-        )
-    ) 
-
-@dp.table(
-    name="OtherID_Details",
-    comment="Import raw OtherID_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}OtherID_Details.csv"
-        )
-    ) 
-
-@dp.table(
-    name="PrimaryRole_Details",
-    comment="Import raw PrimaryRole_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}PrimaryRole_Details.csv"
-        )
-    ) 
-
-@dp.table(
-    name="Relationship_Details",
-    comment="Import raw Relationship_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Relationship_Details.csv"
-        )
-    )     
-
-@dp.table(
-    name="Role_Details",
-    comment="Import raw Role_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Role_Details.csv"
-        )
-    )
-
-@dp.table(
-    name="Successor_Details",
-    comment="Import raw Successor_Details"
-)
-def azure_csv_table():
-    return (
-        spark.read.format("csv")
-        .option("header", "true")
-        .option("inferSchema", "true")
-        .load(
-            f"{folder_location_path}Successor_Details.csv"
-        )
-    )
+# @dp.table(
+#     name="Contact_Details",
+#     comment="Import raw Contact_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Contact_Details.csv"
+#         )
+#     ) 
+
+# @dp.table(
+#     name="Manifest_Details",
+#     comment="Import raw Manifest_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Manifest_Details.csv"
+#         )
+#     ) 
+
+# @dp.table(
+#     name="Organisation_Details",
+#     comment="Import raw Organisation_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Organisation_Details.csv"
+#         )
+#     ) 
+
+# @dp.table(
+#     name="OtherID_Details",
+#     comment="Import raw OtherID_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}OtherID_Details.csv"
+#         )
+#     ) 
+
+# @dp.table(
+#     name="PrimaryRole_Details",
+#     comment="Import raw PrimaryRole_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}PrimaryRole_Details.csv"
+#         )
+#     ) 
+
+# @dp.table(
+#     name="Relationship_Details",
+#     comment="Import raw Relationship_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Relationship_Details.csv"
+#         )
+#     )     
+
+# @dp.table(
+#     name="Role_Details",
+#     comment="Import raw Role_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Role_Details.csv"
+#         )
+#     )
+
+# @dp.table(
+#     name="Successor_Details",
+#     comment="Import raw Successor_Details"
+# )
+# def azure_csv_table():
+#     return (
+#         spark.read.format("csv")
+#         .option("header", "true")
+#         .option("inferSchema", "true")
+#         .load(
+#             f"{folder_location_path}Successor_Details.csv"
+#         )
+#     )
 
 
 ###### Try this
diff --git a/src/utils/.gitinclude b/src/utils/.gitinclude
deleted file mode 100644
index e69de29..0000000
diff --git a/src/utils/__init__.py b/src/utils/__init__.py
new file mode 100644
index 0000000..df638bb
--- /dev/null
+++ b/src/utils/__init__.py
@@ -0,0 +1,3 @@
+from utils.loaders import load_csv_table
+
+__all__ = ["load_csv_table"]
\ No newline at end of file
diff --git a/src/utils/loaders.py b/src/utils/loaders.py
new file mode 100644
index 0000000..6fc0719
--- /dev/null
+++ b/src/utils/loaders.py
@@ -0,0 +1,21 @@
+"""Data loading utilities for Databricks pipelines"""
+# i dont think we will want these as a package just as a module we wont be expoting and its just and extra steps for analyst which currently i do not think will provide value until they request it and will get in their way
+def load_csv_table(base_path, csv_filename):
+    """Load CSV from Azure storage with standard options
+    
+    Args:
+        base_path: Base path to the folder containing CSV files
+        csv_filename: Name of the CSV file to load
+        
+    Returns:
+        DataFrame: Spark DataFrame with CSV data
+    """
+    from pyspark.sql import SparkSession
+    spark = SparkSession.builder.getOrCreate()
+    
+    return (
+        spark.read.format("csv")
+        .option("header", "true")
+        .option("inferSchema", "true")
+        .load(f"{base_path}{csv_filename}")
+    )
\ No newline at end of file