diff --git a/.python-version b/.python-version
new file mode 100644
index 0000000..24ee5b1
--- /dev/null
+++ b/.python-version
@@ -0,0 +1 @@
+3.13
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..e69de29
diff --git a/config/custom_json_logger.py b/config/custom_json_logger.py
index f0a9ab3..437dc83 100644
--- a/config/custom_json_logger.py
+++ b/config/custom_json_logger.py
@@ -3,6 +3,7 @@ import json
 import logging
 from typing import override
 
+
 class custom_json_logger(logging.Formatter):
     def __init__(
         self,
@@ -21,7 +22,7 @@ class custom_json_logger(logging.Formatter):
         always_fields = {
             "message" : record.getMessage(),
             "timestamp" : dt.datetime.fromtimestamp(
-                record.created, tz=dt.timezone.utc
+                record.created, tz=dt.UTC
             ).isoformat(),
         }
         if record.exc_info is not None:
diff --git a/dash_app.py b/dash_app.py
index 71e13e7..63aa7bd 100644
--- a/dash_app.py
+++ b/dash_app.py
@@ -1,12 +1,14 @@
 '''Module to create a Dash app that displays visualizations of YNAB data.'''
 
-import polars as pl
-import plotly.express as px
-from dash import Dash, html, dcc
-import dash_bootstrap_components as dbc
-import pandas as pd
 import logging
 import sys
+
+import dash_bootstrap_components as dbc
+import pandas as pd
+import plotly.express as px
+import polars as pl
+from dash import Dash, dcc, html
+
 import config.exit_codes as ec
 
 try:
diff --git a/main.py b/main.py
index 2ef5268..c1e81e1 100644
--- a/main.py
+++ b/main.py
@@ -1,15 +1,17 @@
-import os
-import dotenv
-import logging
-import yaml
-import sys
 import atexit
+import logging
 import logging.config
 import logging.handlers
+import os
+import sys
+
+import dotenv
+import yaml
 
 import config.exit_codes as ec
 from pipeline.pipeline_main import pipeline_main
 
+
 def set_up_logging():
     try:
         with open('config/logging_config.yaml', 'r') as f:
@@ -47,7 +49,7 @@ API_TOKEN = os.getenv('API_TOKEN')
 BUDGET_ID = os.getenv('BUDGET_ID')
 
 if not API_TOKEN or not BUDGET_ID:
-    logging.error('API_TOKEN or BUDGET_ID is not set in .env file')
+    logger.error('API_TOKEN or BUDGET_ID is not set in .env file')
     sys.exit(ec.MISSING_ENV_VARS)
 
 if __name__ == '__main__':
@@ -55,20 +57,20 @@ if __name__ == '__main__':
     config['API_TOKEN'] = API_TOKEN
     config['BUDGET_ID'] = BUDGET_ID
     try:
-        pipeline_main(config)
-        
+        pipeline_main(config, logger)
+
         # Check if the data was successfully created
         data_exists = os.path.exists('data/processed') and os.listdir('data/processed')
         if data_exists:
             from dash_app import app
             app.run() # debug=True
         else:
-            logging.error('Data pipeline did not produce any data. Dash app will not run.')
+            logger.error('Data pipeline did not produce any data. Dash app will not run.')
             sys.exit(ec.NO_DATA_PRODUCED)
     except SystemExit as e:
         exit_code = e.code
         if exit_code == ec.SUCCESS:
-            logging.info('Program exited successfully')
+            logger.info('Program exited successfully')
         else:
-            logging.error(f'Program exited with code {exit_code}')
+            logger.error(f'Program exited with code {exit_code}')
         raise
diff --git a/pipeline/dimensions.py b/pipeline/dimensions.py
index 146e303..49e343a 100644
--- a/pipeline/dimensions.py
+++ b/pipeline/dimensions.py
@@ -1,21 +1,23 @@
-import polars as pl
-import logging
 import os
 from datetime import date
 
+import polars as pl
+
+
 class Dimensions:
-    def __init__(self, config):
+    def __init__(self, config,logger):
         self.config = config
         self.base_file_path = self.config['base_data_path']
         os.makedirs(self.config['warehouse_data_path'], exist_ok=True)
-        
+        self.logger = logger
+
     def get_full_file_path(self, file_name):
         return f"{self.base_file_path}/{file_name}"
-        
-        
+
+
 class DimAccounts(Dimensions):
-    def __init__(self, config):
-        super().__init__(config)
+    def __init__(self, config,logger):
+        super().__init__(config,logger)
         self.file_path = self.get_full_file_path('accounts.parquet')
         self.transform()
 
@@ -24,10 +26,10 @@ class DimAccounts(Dimensions):
         try:
             source_accounts = pl.read_parquet(self.file_path)
         except Exception as e:
-            logging.error(f"Failed to read the base accounts parquet file: {e}")
+            self.logger.error(f"Failed to read the base accounts parquet file: {e}")
             return
 
-        logging.info("Transforming the accounts DataFrame")
+        self.logger.info("Transforming the accounts DataFrame")
         try:
             base_accounts = (
                 source_accounts.select([
@@ -44,7 +46,7 @@ class DimAccounts(Dimensions):
                 ])
             )
         except Exception as e:
-            logging.error(f"Failed to select columns from the categories DataFrame: {e}")
+            self.logger.error(f"Failed to select columns from the categories DataFrame: {e}")
             return
 
         try:
@@ -65,29 +67,29 @@ class DimAccounts(Dimensions):
                 "id", "name", "type"
             ])
         except Exception as e:
-            logging.error(f"Failed to transform the accounts DataFrame: {e}")
+            self.logger.error(f"Failed to transform the accounts DataFrame: {e}")
             return
 
-        logging.info("Writing the transformed accounts DataFrame to parquet file")
+        self.logger.info("Writing the transformed accounts DataFrame to parquet file")
         try:
             drop_accounts_columns.write_parquet(self.config['warehouse_data_path'] + '/accounts.parquet')
         except Exception as e:
-            logging.error(f"Failed to write the transformed accounts DataFrame to parquet file: {e}")
+            self.logger.error(f"Failed to write the transformed accounts DataFrame to parquet file: {e}")
             return
 
 class DimCategories(Dimensions):
-    def __init__(self, config):
-        super().__init__(config)
+    def __init__(self, config,logger):
+        super().__init__(config,logger)
         self.file_path = self.get_full_file_path('categories.parquet')
         self.transform()
-    
+
     def transform(self):
         try:
             source_categories = pl.read_parquet(self.file_path)
-        except Exception as e: 
-            logging.error(f"Failed to read the base categories parquet file: {e}")
+        except Exception as e:
+            self.logger.error(f"Failed to read the base categories parquet file: {e}")
             return
-        logging.info("Transforming the categories DataFrame")
+        self.logger.info("Transforming the categories DataFrame")
         try:
             base_categories = source_categories.select([
                 'id',
@@ -101,9 +103,9 @@ class DimCategories(Dimensions):
                 'deleted'
             ])
         except Exception as e:
-            logging.error(f"Failed to select columns from the categories DataFrame: {e}")
+            self.logger.error(f"Failed to select columns from the categories DataFrame: {e}")
             return
-        
+
         try:
             add_categories_prefix = base_categories.with_columns([
                 pl.col('id').alias('category_id'),
@@ -121,29 +123,29 @@ class DimCategories(Dimensions):
                 'id', 'name'
             ])
         except Exception as e:
-            logging.error(f"Failed to transform the categories DataFrame: {e}")
+            self.logger.error(f"Failed to transform the categories DataFrame: {e}")
             return
 
-        logging.info("Writing the transformed categories DataFrame to parquet file")
+        self.logger.info("Writing the transformed categories DataFrame to parquet file")
         try:
             drop_categories_columns.write_parquet(self.config['warehouse_data_path'] + '/categories.parquet')
         except Exception as e:
-            logging.error(f"Failed to write the transformed categories DataFrame to parquet file: {e}")
+            self.logger.error(f"Failed to write the transformed categories DataFrame to parquet file: {e}")
             return
 
 class DimPayees(Dimensions):
-    def __init__(self, config):
-        super().__init__(config)
+    def __init__(self, config,logger):
+        super().__init__(config,logger)
         self.file_path = self.get_full_file_path('payees.parquet')
         self.transform()
-    
+
     def transform(self):
         try:
             source_payees = pl.read_parquet(self.file_path)
         except Exception as e:
-            logging.error(f"Failed to read the base payees parquet file: {e}")
+            self.logger.error(f"Failed to read the base payees parquet file: {e}")
             return
-        logging.info("Transforming the payees DataFrame")
+        self.logger.info("Transforming the payees DataFrame")
         try:
             base_payees = source_payees.select([
                 'id',
@@ -151,7 +153,7 @@ class DimPayees(Dimensions):
                 'deleted'
             ])
         except Exception as e:
-            logging.error(f"Failed to select columns from the payees DataFrame: {e}")
+            self.logger.error(f"Failed to select columns from the payees DataFrame: {e}")
             return
 
         try:
@@ -163,28 +165,28 @@ class DimPayees(Dimensions):
                 'id', 'name'
             ])
         except Exception as e:
-            logging.error(f"Failed to rename columns in the payees DataFrame: {e}")
+            self.logger.error(f"Failed to rename columns in the payees DataFrame: {e}")
             return
 
         # Write the DataFrame to a new parquet file
-        logging.info("Writing the transformed payees DataFrame to parquet file")
+        self.logger.info("Writing the transformed payees DataFrame to parquet file")
         try:
             drop_payees_columns.write_parquet(self.config['warehouse_data_path'] + '/payees.parquet')
         except Exception as e:
-            logging.error(f"Failed to write the transformed payees DataFrame to parquet file: {e}")
+            self.logger.error(f"Failed to write the transformed payees DataFrame to parquet file: {e}")
             return
 
 class DimDate(Dimensions):
-    def __init__(self, config):
-        super().__init__(config)
+    def __init__(self, config,logger):
+        super().__init__(config,logger)
         self.transform()
-    
+
     def transform(self):
         # Create a DataFrame with dates from 2020-01-01 to 2030-12-31
         try:
             dates_df = pl.DataFrame({'date':pl.date_range(date(2020, 1, 1), date(2030, 12, 31), "1d", eager=True)})
         except Exception as e:
-            logging.error(f"Failed to create a DataFrame with dates: {e}")
+            self.logger.error(f"Failed to create a DataFrame with dates: {e}")
             return
         # Extract year, month, day, and weekday from the date column
         try:
@@ -195,33 +197,32 @@ class DimDate(Dimensions):
                 pl.col('date').dt.weekday().alias('weekday')
             ])
         except Exception as e:
-            logging.error(f"Failed to extract year, month, day, and weekday from the date column: {e}")
-            return 
+            self.logger.error(f"Failed to extract year, month, day, and weekday from the date column: {e}")
+            return
         try:
             # Create a new column to indicate if the date is a weekday or weekend
             dates_df = dates_df.with_columns([
                 (pl.col('weekday') < 6).alias('is_weekday')  # True for weekdays (Monday to Friday), False for weekends (Saturday and Sunday)
             ])
         except Exception as e:
-            logging.error(f"Failed to create a new column to indicate if the date is a weekday or weekend: {e}")
+            self.logger.error(f"Failed to create a new column to indicate if the date is a weekday or weekend: {e}")
             return
-        
+
         # Create a primary key by concatenating year, month, and day with no separators
         try:
             dates_df = dates_df.with_columns([
-                (pl.col('year').cast(pl.Utf8) + 
+                (pl.col('year').cast(pl.Utf8) +
                  pl.col('month').cast(pl.Utf8).str.zfill(2) +
                  pl.col('day').cast(pl.Utf8).str.zfill(2)
                 ).alias('date_id')
             ])
         except Exception as e:
-            logging.error(f"Failed to create the primary key column: {e}")
+            self.logger.error(f"Failed to create the primary key column: {e}")
             return
         # Write the DataFrame to a new parquet file
-        logging.info("Writing the transformed dates DataFrame to parquet file")
+        self.logger.info("Writing the transformed dates DataFrame to parquet file")
         try:
             dates_df.write_parquet(self.config['warehouse_data_path'] + '/dates.parquet')
         except Exception as e:
-            logging.error(f"Failed to write the transformed dates DataFrame to parquet file: {e}")
+            self.logger.error(f"Failed to write the transformed dates DataFrame to parquet file: {e}")
             return
-
diff --git a/pipeline/facts.py b/pipeline/facts.py
index 1719824..6d1ec7c 100644
--- a/pipeline/facts.py
+++ b/pipeline/facts.py
@@ -1,19 +1,21 @@
-import polars as pl
-import logging
 import os
 
+import polars as pl
+
+
 class Facts:
-    def __init__(self, config):
+    def __init__(self, config,logger):
         self.config = config
         self.base_file_path = self.config['base_data_path']
+        self.logger = logger
         os.makedirs(self.config['warehouse_data_path'], exist_ok=True)
-        
+
     def get_full_file_path(self, file_name):
         return f"{self.base_file_path}/{file_name}"
-    
+
 class FactTransactions(Facts):
-    def __init__(self, config):
-        super().__init__(config)
+    def __init__(self, config,logger):
+        super().__init__(config,logger)
         self.file_path = self.get_full_file_path('transactions.parquet')
         self.transform()
 
@@ -21,7 +23,7 @@ class FactTransactions(Facts):
         try:
             source_transactions = pl.read_parquet(self.file_path)
         except FileNotFoundError:
-            logging.error("The transactions DataFrame does not exist")
+            self.logger.error("The transactions DataFrame does not exist")
             return
 
         try:
@@ -39,16 +41,16 @@ class FactTransactions(Facts):
                 "transfer_account_id"
             ])
         except Exception as e:
-            logging.error(f"Failed to select columns from the transactions DataFrame: {e}")
+            self.logger.error(f"Failed to select columns from the transactions DataFrame: {e}")
             return
 
-        logging.info("Transforming the transactions DataFrame")
+        self.logger.info("Transforming the transactions DataFrame")
         try:
             resolve_transaction_dates = base_transactions.with_columns([
                 pl.col("date").str.strptime(pl.Date, format="%Y-%m-%d").alias("date")
             ])
         except Exception as e:
-            logging.error(f"Failed to covert the date to date format: {e}")
+            self.logger.error(f"Failed to covert the date to date format: {e}")
             return
 
         try:
@@ -70,22 +72,22 @@ class FactTransactions(Facts):
             drop_transaction_columns = fix_transaction_values.drop([
                 "id", "date", "amount"
             ])
-            
+
         except Exception as e:
-            logging.error(f"Failed to transform the transactions DataFrame: {e}")
+            self.logger.error(f"Failed to transform the transactions DataFrame: {e}")
             return
         # Write the DataFrame to a new parquet file
-        logging.info("Writing the transformed transactions DataFrame to parquet file")
+        self.logger.info("Writing the transformed transactions DataFrame to parquet file")
         try:
             drop_transaction_columns.write_parquet(
                 self.config['warehouse_data_path'] + '/transactions.parquet'
             )
         except Exception as e:
-            logging.error(f"Failed to write the transformed transactions DataFrame: {e}")
+            self.logger.error(f"Failed to write the transformed transactions DataFrame: {e}")
 
 class FactScheduledTransactions(Facts):
-    def __init__(self, config):
-        super().__init__(config)
+    def __init__(self, config,logger):
+        super().__init__(config,logger)
         self.file_path = self.get_full_file_path('scheduled_transactions.parquet')
         self.transform()
 
@@ -93,7 +95,7 @@ class FactScheduledTransactions(Facts):
         try:
             source_scheduled = pl.read_parquet(self.file_path)
         except FileNotFoundError:
-            logging.error("The scheduled transactions DataFrame does not exist")
+            self.logger.error("The scheduled transactions DataFrame does not exist")
             return
 
         try:
@@ -111,7 +113,7 @@ class FactScheduledTransactions(Facts):
                 "transfer_account_id"
             ])
         except Exception as e:
-            logging.error(f"Failed to select columns from the scheduled transactions DataFrame: {e}")
+            self.logger.error(f"Failed to select columns from the scheduled transactions DataFrame: {e}")
             return
 
         try:
@@ -120,10 +122,10 @@ class FactScheduledTransactions(Facts):
                 pl.col("date_next").str.strptime(pl.Date, format="%Y-%m-%d").alias("date_next")
             ])
         except Exception as e:
-            logging.error(f"Failed to covert the date to date format: {e}")
+            self.logger.error(f"Failed to covert the date to date format: {e}")
             return
-        
-        logging.info("Transforming the scheduled transactions DataFrame")
+
+        self.logger.info("Transforming the scheduled transactions DataFrame")
         try:
             add_scheduled_prefix = resolve_scheduled_dates.with_columns([
                 pl.col("id").alias("scheduled_transaction_id")
@@ -141,10 +143,10 @@ class FactScheduledTransactions(Facts):
                 "id", "amount"
             ])
         except Exception as e:
-            logging.error(f"Failed to transform the scheduled transactions DataFrame: {e}")
+            self.logger.error(f"Failed to transform the scheduled transactions DataFrame: {e}")
             return
-        logging.info("Writing the transformed scheduled transactions DataFrame to parquet file")
+        self.logger.info("Writing the transformed scheduled transactions DataFrame to parquet file")
         try:
             drop_scheduled_columns.write_parquet(self.config['warehouse_data_path'] + '/scheduled_transactions.parquet')
         except Exception as e:
-            logging.error(f"Failed to write the transformed scheduled transactions DataFrame: {e}")
+            self.logger.error(f"Failed to write the transformed scheduled transactions DataFrame: {e}")
diff --git a/pipeline/ingest.py b/pipeline/ingest.py
index 6b16c39..97a1b60 100644
--- a/pipeline/ingest.py
+++ b/pipeline/ingest.py
@@ -1,15 +1,17 @@
-import os
-import time
 import json
-import logging
-import requests
+import os
 import sys
-from typing import Dict, Any
+import time
+from typing import Any
+
+import requests
+
 import config.exit_codes as ec
 
+
 class Ingest:
 
-    def __init__(self, config: Dict[str, Any]):
+    def __init__(self, config: dict[str, Any],logger):
         """
         Initialize the Ingest class with the provided configuration.
         """
@@ -22,9 +24,10 @@ class Ingest:
         self.headers = {'Authorization': f'Bearer {self.api_token}'}
         self.MAX_RETRIES = config['REQUESTS_MAX_RETRIES']
         self.RETRY_DELAY = config['REQUESTS_RETRY_DELAY']
+        self.logger = logger
 
 
-    def save_entity_data_to_raw(self, entity: str, data: Dict[str, Any]):
+    def save_entity_data_to_raw(self, entity: str, data: dict[str, Any]):
         """
         Save the data for a specific entity to a new cache file.
         """
@@ -33,15 +36,15 @@ class Ingest:
         if not os.path.exists(directory):
             os.makedirs(directory)
         entity_file = f'{directory}/{current_time}.json'
-        logging.info(f"Saving {entity} data to {entity_file}")
+        self.logger.info(f"Saving {entity} data to {entity_file}")
         try:
             with open(entity_file, 'w') as f:
                 json.dump(data, f, indent=4)
         except Exception as e:
-            logging.error(f"Failed to save data for {entity} to {entity_file}")
+            self.logger.error(f"Failed to save data for {entity} to {entity_file}")
             raise e
 
-    def load_knowledge_cache(self) -> Dict[str, Any]:
+    def load_knowledge_cache(self) -> dict[str, Any]:
         """
         Load the knowledge cache from the file if it exists.
         """
@@ -59,7 +62,7 @@ class Ingest:
             with open(self.knowledge_file, 'r') as f:
                 knowledge_cache = json.load(f)
         except FileNotFoundError:
-            logging.info(f"Knowledge file not found. Creating a new one at {self.knowledge_file}. This is normal for the first run.")
+            self.logger.info(f"Knowledge file not found. Creating a new one at {self.knowledge_file}. This is normal for the first run.")
             os.makedirs(os.path.dirname(self.knowledge_file), exist_ok=True)
             knowledge_cache = {}
 
@@ -74,33 +77,33 @@ class Ingest:
             with open(self.knowledge_file, 'w') as f:
                 json.dump(knowledge_cache, f, indent=4)
         except Exception as e:
-            logging.error(f"Failed to update knowledge cache for {entity} in {self.knowledge_file}")
+            self.logger.error(f"Failed to update knowledge cache for {entity} in {self.knowledge_file}")
             raise e
 
     def handle_response(self, response) -> bool:
         if response.status_code == 400:
-            logging.error("Bad request. The request could not be understood by the API due to malformed syntax or validation errors.")
+            self.logger.error("Bad request. The request could not be understood by the API due to malformed syntax or validation errors.")
             sys.exit(ec.BAD_REQUEST)
         elif response.status_code == 401:
-            logging.error("Unauthorized. Please check your API token.")
+            self.logger.error("Unauthorized. Please check your API token.")
             sys.exit(ec.UNAUTHORIZED_API_TOKEN)
         elif response.status_code == 403:
-            logging.error("Forbidden. Access is denied.")
+            self.logger.error("Forbidden. Access is denied.")
             sys.exit(ec.FORBIDDEN)
         elif response.status_code == 404:
-            logging.error("Not found. The specified URL does not exist.")
+            self.logger.error("Not found. The specified URL does not exist.")
             sys.exit(ec.NOT_FOUND)
         elif response.status_code == 409:
-            logging.error("Conflict. The resource cannot be saved due to a conflict.")
+            self.logger.error("Conflict. The resource cannot be saved due to a conflict.")
             sys.exit(ec.CONFLICT)
         elif response.status_code == 429:
-            logging.error("Too many requests. You have made too many requests in a short amount of time.")
+            self.logger.error("Too many requests. You have made too many requests in a short amount of time.")
             return True
         elif response.status_code == 500:
-            logging.error("Internal server error. The API experienced an unexpected error.")
+            self.logger.error("Internal server error. The API experienced an unexpected error.")
             return True
         elif response.status_code == 503:
-            logging.error("Service unavailable. The API is temporarily disabled or a request timeout occurred.")
+            self.logger.error("Service unavailable. The API is temporarily disabled or a request timeout occurred.")
             return True
         else:
             response.raise_for_status()
@@ -113,14 +116,14 @@ class Ingest:
         for entity in self.entities:
             file_path = f'data/raw/{entity}'
             if os.path.exists(file_path) and os.listdir(file_path):
-                logging.warning(f"Raw data exists for {entity} processing any raw data we already have.")
+                self.logger.warning(f"Raw data exists for {entity} processing any raw data we already have.")
                 break # break here instead of continue as we dont want to update our server knowledge cache and potentially miss data.
 
             knowledge_cache = self.load_knowledge_cache()
             last_knowledge = knowledge_cache.get(entity, 0)
             #logging.debug(f'Last Knowledge of {entity}: {last_knowledge}')
 
-            logging.info(f'Fetching {entity} data since last knowledge: {last_knowledge}')
+            self.logger.info(f'Fetching {entity} data since last knowledge: {last_knowledge}')
             url = f'{self.base_url}/{self.budget_id}/{entity}?last_knowledge_of_server={last_knowledge}'
             response = None
             for attempt in range(self.MAX_RETRIES):
@@ -130,17 +133,17 @@ class Ingest:
                     if not should_retry:
                         break  # Exit the loop if the request is successful
                 except requests.exceptions.RequestException as e:
-                    logging.error(f"Error fetching {entity} data (attempt {attempt + 1}/{self.MAX_RETRIES}): {e}")
+                    self.logger.error(f"Error fetching {entity} data (attempt {attempt + 1}/{self.MAX_RETRIES}): {e}")
                     if attempt < self.MAX_RETRIES - 1:
                         time.sleep(self.RETRY_DELAY)  # Wait before retrying
                     else:
-                        logging.error("Max retries reached. Exiting.")
+                        self.logger.error("Max retries reached. Exiting.")
                         sys.exit(ec.REQUESTS_ERROR)
 
             data = response.json()
-            logging.debug(f'response data: {data}')
+            self.logger.debug(f'response data: {data}')
             server_knowledge = data['data'].get('server_knowledge')
-            logging.debug(f'{entity} new server knowledge: {server_knowledge}')
+            self.logger.debug(f'{entity} new server knowledge: {server_knowledge}')
 
             if server_knowledge is not None and server_knowledge != last_knowledge:
                 self.update_server_knowledge_cache(entity, server_knowledge)
@@ -148,4 +151,4 @@ class Ingest:
                 entity_data.pop('server_knowledge', None)
                 self.save_entity_data_to_raw(entity, entity_data)
             else:
-                logging.info(f"No new data for {entity}. Skipping cache update.")
+                self.logger.info(f"No new data for {entity}. Skipping cache update.")
diff --git a/pipeline/pipeline_main.py b/pipeline/pipeline_main.py
index a2e5045..09adaad 100644
--- a/pipeline/pipeline_main.py
+++ b/pipeline/pipeline_main.py
@@ -1,25 +1,19 @@
 '''Module to run the data pipeline'''
 
-import logging
-
-from pipeline.ingest import Ingest
-from pipeline.raw_to_base import RawToBase
-from pipeline.dimensions import DimAccounts, DimCategories, DimPayees, DimDate
-from pipeline.facts import FactTransactions, FactScheduledTransactions
+from pipeline import dimensions, facts, ingest, raw_to_base
 
 
-def pipeline_main(config):
+def pipeline_main(config, logger):
     '''Run the data pipeline'''
-    logging.info('Starting data pipeline')
+    logger.info('Starting data pipeline')
 
-    ingest = Ingest(config)
-    ingest.start_ingestion()
-    RawToBase(config)
-    DimAccounts(config)
-    DimCategories(config)
-    DimPayees(config)
-    DimDate(config)
-    FactTransactions(config)
-    FactScheduledTransactions(config)
+    ingest.Ingest(config,logger).start_ingestion()
+    raw_to_base.RawToBase(config,logger)
+    dimensions.DimAccounts(config,logger)
+    dimensions.DimCategories(config,logger)
+    dimensions.DimPayees(config,logger)
+    dimensions.DimDate(config,logger)
+    facts.FactTransactions(config,logger)
+    facts.FactScheduledTransactions(config,logger)
 
-    logging.info('Data pipeline completed successfully')
+    logger.info('Data pipeline completed successfully')
diff --git a/pipeline/raw_to_base.py b/pipeline/raw_to_base.py
index c1d63d7..1f3cbe1 100644
--- a/pipeline/raw_to_base.py
+++ b/pipeline/raw_to_base.py
@@ -1,14 +1,16 @@
-import os
 import json
-import logging
+import os
 import sys
 from datetime import datetime
-from typing import Dict, Any
-import config.exit_codes as ec
+from typing import Any
+
 import polars as pl
 
+import config.exit_codes as ec
+
+
 class RawToBase:
-    def __init__(self, config: Dict[str, Any]):
+    def __init__(self, config: dict[str, Any],logger):
         self.entities = config['entities']
         self.primary_keys = config['primary_keys']
         self.raw_data_path = config['raw_data_path']
@@ -16,39 +18,40 @@ class RawToBase:
         self.base_data_path = config['base_data_path']
         self.data = {}
         self.base_data = {}
+        self.logger = logger
         self.process_entities()
 
     def process_entities(self):
         for entity in self.entities:
-            logging.info(f"Processing entity: {entity}")
+            self.logger.info(f"Processing entity: {entity}")
             # check the file is in the raw data path, if not skip the entity
             folder_path = os.path.join(self.raw_data_path, entity)
             folder_contents = os.listdir(folder_path)
             if not folder_contents:
-                logging.warning(f"The folder {folder_path} is empty skipping {entity}.")
+                self.logger.warning(f"The folder {folder_path} is empty skipping {entity}.")
                 continue
             if not self._load_raw_data(entity):
-                logging.warning(f"Skipping processing for entity: {entity} due to empty data.")
+                self.logger.warning(f"Skipping processing for entity: {entity} due to empty data.")
                 continue
             self._load_existing_base_data(entity)
             self._combine_data(entity)
             if not self._save_base_data(entity):
-                logging.error(f"Skipping processing for entity: {entity} due to failed saving base data.")
+                self.logger.error(f"Skipping processing for entity: {entity} due to failed saving base data.")
                 continue
             if not self._move_raw_to_processed(entity):
-                logging.error(f"entity: {entity} has been processed, but we could not move the file out of the raw folder, please clear the raw folder for {entity}.")
+                self.logger.error(f"entity: {entity} has been processed, but we could not move the file out of the raw folder, please clear the raw folder for {entity}.")
                 sys.exit(ec.MOVE_FILE_ERROR)
-            logging.info(f"Successfully processed entity: {entity}")
+            self.logger.info(f"Successfully processed entity: {entity}")
 
     def _load_raw_data(self, entity):
         entity_path = os.path.join(self.raw_data_path, entity)
         self.data[entity] = []
-        logging.debug(f"Loading data for entity: {entity} from path: {entity_path}")
+        self.logger.debug(f"Loading data for entity: {entity} from path: {entity_path}")
 
         files = [f for f in os.listdir(entity_path) if f.endswith('.json')]
 
         if len(files) > 1:
-            logging.error(f"""More than one file found in path: {entity_path}. Skipping processing for entity: {entity}.
+            self.logger.error(f"""More than one file found in path: {entity_path}. Skipping processing for entity: {entity}.
 recommended actions is to move the newest file(s) out, re-run main.py.
 Then move the files back in one at a time oldest to newest and run again for each file""")
             return False
@@ -56,12 +59,12 @@ Then move the files back in one at a time oldest to newest and run again for eac
         if len(files) == 1:
             file_name = files[0]
             file_path = os.path.join(entity_path, file_name)
-            logging.debug(f"Reading file: {file_path}")
+            self.logger.debug(f"Reading file: {file_path}")
             try:
                 with open(file_path, 'r') as f:
                     data = json.load(f)
             except Exception as e:
-                logging.error(f"Failed to load data from file: {file_path}, error: {e}")
+                self.logger.error(f"Failed to load data from file: {file_path}, error: {e}")
                 return False
 
             if self._is_data_empty(entity, data, file_path):
@@ -69,37 +72,37 @@ Then move the files back in one at a time oldest to newest and run again for eac
 
             modified_data = self._add_ingestion_date(entity, data, file_name)
             for index, record in enumerate(modified_data):
-                logging.debug(f"processing record: {record}")
+                self.logger.debug(f"processing record: {record}")
                 filtered_record = {k: v for k, v in record.items() if not k.startswith('debt_')}
                 modified_data[index] = filtered_record
-                logging.debug(f"filtered record: {filtered_record}")
-            logging.debug(f"modified data: {modified_data}")
+                self.logger.debug(f"filtered record: {filtered_record}")
+            self.logger.debug(f"modified data: {modified_data}")
 
             self.data[entity].append(modified_data)
-            logging.debug(f"Successfully loaded data from file: {file_path}")
+            self.logger.debug(f"Successfully loaded data from file: {file_path}")
         return True
 
     def _is_data_empty(self, entity, data, file_path):
-        logging.debug(f"Checking if data is empty for entity: {entity}")
+        self.logger.debug(f"Checking if data is empty for entity: {entity}")
         if entity == "categories":
             has_categories = any(group.get("categories") for group in data.get("category_groups", []))
             if not has_categories:
-                logging.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
+                self.logger.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
                 os.remove(file_path)
                 return True
         else:
             if not data.get(entity, []):
-                logging.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
+                self.logger.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
                 os.remove(file_path)
                 return True
-        logging.debug(f"Data is not empty for entity: {entity}")
+        self.logger.debug(f"Data is not empty for entity: {entity}")
         return False
 
     def _add_ingestion_date(self, entity, data, file_name):
         modified_data = []
         ingestion_date = datetime.strptime(file_name.split('.')[0], '%Y%m%d%H%M%S').date()
 
-        logging.debug(f"Adding ingestion date to data for entity: {entity}")
+        self.logger.debug(f"Adding ingestion date to data for entity: {entity}")
         if entity == 'categories':
             for group in data.get('category_groups', []):
                 for category in group.get('categories', []):
@@ -112,22 +115,22 @@ Then move the files back in one at a time oldest to newest and run again for eac
                     modified_data.append(record)
                 else:
                     modified_data.append({'record': record, 'ingestion_date': ingestion_date})
-        logging.debug(f"Successfully added ingestion date to data for entity: {entity}")
+        self.logger.debug(f"Successfully added ingestion date to data for entity: {entity}")
         return modified_data
 
     def _load_existing_base_data(self, entity):
         base_path = os.path.join(self.base_data_path, f'{entity}.parquet')
         if os.path.exists(base_path):
-            logging.debug(f"Loading existing base data for entity: {entity} from path: {base_path}")
+            self.logger.debug(f"Loading existing base data for entity: {entity} from path: {base_path}")
             try:
                 self.base_data[entity] = pl.read_parquet(base_path)
             except Exception as e:
-                logging.error(f"Failed to load existing base data for entity: {entity}, error: {e}, Creating an empty DataFrame")
+                self.logger.error(f"Failed to load existing base data for entity: {entity}, error: {e}, Creating an empty DataFrame")
                 self.base_data[entity] = pl.DataFrame()
-            logging.debug(f"Successfully loaded existing base data for entity: {entity}")
+            self.logger.debug(f"Successfully loaded existing base data for entity: {entity}")
         else:
             self.base_data[entity] = pl.DataFrame()
-            logging.debug(f"No existing base data found for entity: {entity}, starting with an empty DataFrame")
+            self.logger.debug(f"No existing base data found for entity: {entity}, starting with an empty DataFrame")
 
     #Function to cast null Struct({'': Null}) columns to String
     def _cast_struct_to_string(self,df):
@@ -142,7 +145,7 @@ Then move the files back in one at a time oldest to newest and run again for eac
         return df
 
     def _combine_data(self, entity):
-        logging.debug(f"Combining data for entity: {entity}")
+        self.logger.debug(f"Combining data for entity: {entity}")
         combined_data = []
 
         # Combine data from the entity
@@ -159,8 +162,8 @@ Then move the files back in one at a time oldest to newest and run again for eac
         # Ensure the unique id column is preserved
         unique_id = self.primary_keys[entity]['unique_id']
         if unique_id not in new_data_df.columns:
-            logging.error(f"Unique ID column '{unique_id}' not found in the combined data for entity: {entity}")
-            exit(ec.UNIQUE_ID_NOT_FOUND)
+            self.logger.error(f"Unique ID column '{unique_id}' not found in the combined data for entity: {entity}")
+            sys.exit(ec.UNIQUE_ID_NOT_FOUND)
 
         # Cast columns in new_data_df
         new_data_df = self._cast_struct_to_string(new_data_df)
@@ -188,7 +191,7 @@ Then move the files back in one at a time oldest to newest and run again for eac
         else:
             self.base_data[entity] = new_data_df
 
-        logging.debug(f"Successfully combined data for entity: {entity}")
+        self.logger.debug(f"Successfully combined data for entity: {entity}")
 
     def _save_base_data(self, entity):
         os.makedirs(self.base_data_path, exist_ok=True)
@@ -196,9 +199,9 @@ Then move the files back in one at a time oldest to newest and run again for eac
         try:
             self.base_data[entity].write_parquet(file_path)
         except Exception as e:
-            logging.error(f"Failed to save base data for entity: {entity}, error: {e}")
+            self.logger.error(f"Failed to save base data for entity: {entity}, error: {e}")
             return False
-        logging.debug(f"Saved base data for entity: {entity} to path: {file_path}")
+        self.logger.debug(f"Saved base data for entity: {entity} to path: {file_path}")
         return True
 
     def _move_raw_to_processed(self, entity):
@@ -210,24 +213,24 @@ Then move the files back in one at a time oldest to newest and run again for eac
         try:
             files = [f for f in os.listdir(raw_entity_path) if f.endswith('.json')]
             if len(files) != 1:
-                logging.error(f"Expected exactly one file in path: {raw_entity_path}, but found {len(files)}")
+                self.logger.error(f"Expected exactly one file in path: {raw_entity_path}, but found {len(files)}")
                 return False
 
             file_name = files[0]
             raw_file_path = os.path.join(raw_entity_path, file_name)
             processed_file_path = os.path.join(processed_path, file_name)
 
-            logging.debug(f"Moving file: {raw_file_path} to {processed_file_path}")
+            self.logger.debug(f"Moving file: {raw_file_path} to {processed_file_path}")
 
             os.rename(raw_file_path, processed_file_path)
-            logging.debug(f"Moved file: {file_name} to processed")
+            self.logger.debug(f"Moved file: {file_name} to processed")
 
         except FileNotFoundError as e:
-            logging.error(f"File not found: {e}")
+            self.logger.error(f"File not found: {e}")
             return False
         except Exception as e:
-            logging.error(f"Failed to move file for entity: {entity}, error: {e}")
+            self.logger.error(f"Failed to move file for entity: {entity}, error: {e}")
             return False
 
-        logging.debug(f"Moved processed file for entity: {entity} to path: {processed_path}")
+        self.logger.debug(f"Moved processed file for entity: {entity} to path: {processed_path}")
         return True
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..2b3e2f0
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,18 @@
+[project]
+name = "data-pipeline-for-ynab"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "dash>=4.4.1",
+    "dash-bootstrap-components>=2.0.4",
+    "pandas>=3.0.5",
+    "polars>=1.43.0",
+    "pyarrow>=25.0.0",
+    "pytest>=9.1.1",
+    "python-dotenv>=1.2.2",
+    "pyyaml>=6.0.3",
+    "requests>=2.34.2",
+    "ruff>=0.16.0",
+]
diff --git a/tests/test_ingest.py b/tests/test_ingest.py
index e51e86f..ea4abe6 100644
--- a/tests/test_ingest.py
+++ b/tests/test_ingest.py
@@ -1,12 +1,11 @@
-import pytest
-from unittest.mock import patch, mock_open, MagicMock
 import json
 import os
-from typing import Dict, Any
-import logging
+from unittest.mock import MagicMock, mock_open, patch
+
+import pytest
 
-from pipeline.ingest import Ingest
 import config.exit_codes as ec
+from pipeline.ingest import Ingest
 
 # Mock configuration for initializing the Ingest class
 mock_config = {
diff --git a/tests/test_main.py b/tests/test_main.py
index 8842ada..e827f3c 100644
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -1,12 +1,11 @@
-import pytest
-from unittest.mock import patch, mock_open, MagicMock
-import yaml
 import logging
-import atexit
-import sys
+from unittest.mock import MagicMock, mock_open, patch
+
+import yaml
 
-from main import set_up_logging, load_config
 import config.exit_codes as ec
+from main import load_config, set_up_logging
+
 
 # Test for set_up_logging function
 def test_set_up_logging_success():
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..b374665
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,774 @@
+version = 1
+revision = 3
+requires-python = ">=3.13"
+resolution-markers = [
+    "python_full_version >= '3.14' and sys_platform == 'win32'",
+    "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.14' and sys_platform == 'win32'",
+    "python_full_version < '3.14' and sys_platform == 'emscripten'",
+    "python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
+
+[[package]]
+name = "annotated-types"
+version = "0.8.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/5f/56/a8120250d128bed162cd73c76d45f6ef9991f3e068f62a8ee060afa3104a/annotated_types-0.8.0.tar.gz", hash = "sha256:13b2beaad985e05e2d6407ee4c4f35590b11f8d693a258a561055cac8f64cab7", size = 15893, upload-time = "2026-07-23T20:16:13.995Z" }
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+]
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+[[package]]
+name = "blinker"
+version = "1.9.0"
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+]
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+[[package]]
+name = "certifi"
+version = "2026.7.22"
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+]
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+[[package]]
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