Migrating to duckdb

Reviewed-on: #3

README.md

@@ -0,0 +1,18 @@
+# Data Pipeline for YNAB
+
+This project is a Data Pipeline for YNAB that fetches and caches budget-related data from an API. It organizes the data into a dimensional model ready to be reported on.
+
+## [Get Started Guide](docs/Get_Started.md)
+
+## Usage
+
+This tool has been desined to be used to fetch and cache budget-related data from the YNAB API. It can be used multiple times a day or once a year or anything in between. It is designed to be flexible and easy to use.
+Once it is on your local machine, you can run it by executing the `main.py` file. This will handle situations where you have not run the tool before, or where you have run it before and need to update the data. It will not duplicate any data caused by running it multiple times.
+
+## Contributing
+
+Not expecting any contributions at this time.
+
+## License
+
+[GPL-3.0](https://choosealicense.com/licenses/gpl-3.0/)

ReadMe.md

@@ -1,18 +0,0 @@
-# Data Pipeline for YNAB
-
-This project is a Data Pipeline for YNAB that fetches and caches budget-related data from an API. It organizes the data into a dimensional model ready to be reported on.
-
-## [Get Started Guide](docs/Get_Started.md)
-
-## Usage
-
-This tool has been desined to be used to fetch and cache budget-related data from the YNAB API. It can be used multiple times a day or once a year or anything in between. It is designed to be flexible and easy to use.
-Once it is on your local machine, you can run it by executing the `main.py` file. This will handle situations where you have not run the tool before, or where you have run it before and need to update the data. It will not duplicate any data caused by running it multiple times.
-
-## Contributing
-
-Not expecting any contributions at this time.
-
-## License
-
-[GPL-3.0](https://choosealicense.com/licenses/gpl-3.0/)

config/exit_codes.py

@@ -13,4 +13,4 @@ DUPLICATE_RESOLUTION_ERROR = 11
 UNIQUE_ID_NOT_FOUND = 12
 NO_DATA_PRODUCED = 13
 MISSING_DATA_FILES = 14
-BAD_JOIN = 15
+BAD_JOIN = 15

dash_app.py

@@ -1,163 +0,0 @@
-'''Module to create a Dash app that displays visualizations of YNAB data.'''
-
-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:
-    accounts = pl.read_parquet('data/warehouse/accounts.parquet')
-    categories = pl.read_parquet('data/warehouse/categories.parquet')
-    dates = pl.read_parquet('data/warehouse/dates.parquet')
-    payees = pl.read_parquet('data/warehouse/payees.parquet')
-    scheduled_transactions = pl.read_parquet('data/warehouse/scheduled_transactions.parquet')
-    transactions = pl.read_parquet('data/warehouse/transactions.parquet')
-except FileNotFoundError:
-    logging.error('Data warehouse files not found. Run the data pipeline to create them.')
-    sys.exit(ec.MISSING_DATA_FILES)
-
-try:
-    # Join transactions with accounts, categories, and payees to create a master DataFrame
-    master_transactions = transactions.join(categories, left_on='category_id', right_on='category_id', suffix='_category')\
-                        .join(accounts, left_on='account_id', right_on='account_id', suffix='_account')\
-                        .join(payees, left_on='payee_id', right_on='payee_id', suffix='_payee')\
-                        .join(dates, left_on='transaction_date', right_on='date_id', suffix='_date')
-except Exception as e:
-    logging.error(f'Error joining DataFrames: {e}')
-    sys.exit(ec.BAD_JOIN)
-
-# Create aggregations
-spend_per_day = master_transactions.sql('''
-    SELECT 
-        date,
-        year,
-        month,
-        day,
-        ABS(SUM(transaction_amount)) as total
-    FROM self
-    WHERE category_name != 'Inflow: Ready to Assign'
-    GROUP BY date, year, month, day
-    ORDER BY date DESC
-    '''
-)
-
-spend_per_category = master_transactions.sql('''
-    SELECT
-        category_name,
-        ABS(SUM(transaction_amount)) as total
-    FROM self
-    WHERE category_name != 'Inflow: Ready to Assign'
-    GROUP BY category_name
-    ORDER BY total DESC
-    '''
-)
-
-spend_per_payee = master_transactions.sql('''
-    SELECT
-        payee_name,
-        ABS(SUM(transaction_amount)) as total
-    FROM self
-    WHERE payee_name != 'Starting Balance'
-        AND transaction_amount < 0
-    GROUP BY payee_name
-    ORDER BY total DESC
-    '''
-)
-
-# Convert DataFrame to list of dictionaries
-spend_per_day_data = spend_per_day.to_dicts()
-spend_per_category_data = spend_per_category.to_dicts()
-spend_per_payee_data = spend_per_payee.to_dicts()
-
-# Convert list of dictionaries to Pandas DataFrame
-spend_per_day_df = pd.DataFrame(spend_per_day_data)
-spend_per_category_df = pd.DataFrame(spend_per_category_data)
-spend_per_payee_df = pd.DataFrame(spend_per_payee_data)
-
-spend_per_day_line = px.line(spend_per_day_df, x="date", y="total")
-spend_per_day_line.update_layout(
-    plot_bgcolor='black',
-    paper_bgcolor='black',
-    font_color='white'
-)
-
-spend_per_category_bar = px.bar(spend_per_category_df, x="category_name", y="total")
-spend_per_category_bar.update_layout(
-    plot_bgcolor='black',
-    paper_bgcolor='black',
-    font_color='white'
-)
-
-spend_per_payee_bar = px.bar(spend_per_payee_df, x="payee_name", y="total")
-spend_per_payee_bar.update_layout(
-    plot_bgcolor='black',
-    paper_bgcolor='black',
-    font_color='white'
-)
-
-# Initialize the app with a dark theme
-app = Dash(external_stylesheets=[dbc.themes.DARKLY])
-
-# App layout
-app.layout = dbc.Container(
-    [
-        dbc.Row(
-            dbc.Col(
-                html.Div("Data Pipeline For YNAB, Preview Visualisations",
-                        className="text-center text-light"),
-                        width=12
-                )
-        ),
-        dbc.Row(
-            [
-                dbc.Col(
-                    dbc.Card(
-                        dbc.CardBody(
-                            [
-                                html.H4("Spend Per Day", className="card-title"),
-                                dcc.Graph(figure=spend_per_day_line)
-                            ]
-                        ),
-                        className="mb-4"
-                    ),
-                    width=12
-                )
-            ]
-        ),
-        dbc.Row(
-            [
-                dbc.Col(
-                    dbc.Card(
-                        dbc.CardBody(
-                            [
-                                html.H4("Spend Per Category", className="card-title"),
-                                dcc.Graph(figure=spend_per_category_bar)
-                            ]
-                        ),
-                        className="mb-4"
-                    ),
-                    width=6
-                ),
-                dbc.Col(
-                    dbc.Card(
-                        dbc.CardBody(
-                            [
-                                html.H4("Spend Per Payee", className="card-title"),
-                                dcc.Graph(figure=spend_per_payee_bar)
-                            ]
-                        ),
-                        className="mb-4"
-                    ),
-                    width=6
-                )
-            ]
-        )
-    ],
-    fluid=True
-)

data_check.py

@@ -1,17 +1,18 @@
+import duckdb
+import os
 import polars as pl
 
-df = pl.read_parquet('data/warehouse/transactions.parquet')
-print("Data loaded from Parquet file:")
-print(df)
 
-relevant_data = df.sql('''
+db = duckdb.connect('/mnt/bulk/data/ynab_data.duckdb')
-    SELECT 
+
-        date,
+    # SELECT * FROM gold.transactions
+relevant_data = db.sql('''
+    SELECT
+        transaction_date,
         sum(transaction_amount) as total
-    FROM self
+    FROM gold.transactions
-    GROUP BY date
+    GROUP BY transaction_date
-    ORDER BY date DESC
+    ORDER BY transaction_date DESC
-    '''
+''')
-)
 print("Data after SQL query:")
-print(relevant_data)
+print(relevant_data)

main.py

@@ -11,6 +11,7 @@ import yaml
 import config.exit_codes as ec
 from pipeline.pipeline_main import pipeline_main
 
+logger = logging.getLogger("data_pipeline_for_ynab")
 
 def set_up_logging():
     try:
@@ -26,23 +27,21 @@ def set_up_logging():
         queue_handler.listener.start()
         atexit.register(queue_handler.listener.stop)
 
-def load_config():
+def load_config(logger):
     try:
         with open('config/config.yaml', 'r') as file:
             config = yaml.safe_load(file)
         return config
     except FileNotFoundError:
-        logging.error('config.yaml file not found')
+        logger.error('config.yaml file not found')
         sys.exit(ec.MISSING_CONFIG_FILE)
     except yaml.YAMLError as e:
-        logging.error(f'Error loading config.yaml: {e}')
+        logger.error(f'Error loading config.yaml: {e}')
         sys.exit(ec.CORRUPTED_CONFIG_FILE)
 
-logger = logging.getLogger("data_pipeline_for_ynab")
 os.makedirs('logs', exist_ok=True)
 set_up_logging()
 
-# Load environment variables
 dotenv.load_dotenv()
 
 API_TOKEN = os.getenv('API_TOKEN')
@@ -53,17 +52,16 @@ if not API_TOKEN or not BUDGET_ID:
     sys.exit(ec.MISSING_ENV_VARS)
 
 if __name__ == '__main__':
-    config = load_config()
+    config = load_config(logger)
     config['API_TOKEN'] = API_TOKEN
     config['BUDGET_ID'] = BUDGET_ID
     try:
         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
+            logger.info('Processing Successful')
-            app.run() # debug=True
+            sys.exit(ec.SUCCESS)
         else:
             logger.error('Data pipeline did not produce any data. Dash app will not run.')
             sys.exit(ec.NO_DATA_PRODUCED)

pipeline/duckdb_layer.py

@@ -0,0 +1,241 @@
+"""DuckDB-based silver and gold layer for the YNAB data pipeline."""
+
+import os
+from datetime import date, timedelta
+
+import duckdb
+
+
+class DuckDBLayer:
+    """Orchestrates silver (external base) and gold (views + materialized) layers via DuckDB."""
+
+    def __init__(self, base_path: str, warehouse_path: str, logger):
+        self.base_path = base_path
+        self.warehouse_path = warehouse_path
+        self.logger = logger
+        self.db = None
+        os.makedirs(self.warehouse_path, exist_ok=True)
+        self._init()
+
+    def _silver_parquet_expr(self, entity: str) -> str:
+        return f"read_parquet('{self.base_path}/{entity}.parquet')"
+
+    def _init(self):
+        self.db = duckdb.connect('/mnt/bulk/data/ynab_data.duckdb')
+        self._setup_schemas()
+        self._create_silver_external_tables()
+        self._drop_gold()
+        self._create_gold_views()
+        self._create_gold_dates()
+        self._create_gold_facts()
+
+    def _setup_schemas(self):
+        self.db.execute("CREATE SCHEMA IF NOT EXISTS silver")
+        self.db.execute("CREATE SCHEMA IF NOT EXISTS gold")
+
+    def _create_silver_external_tables(self):
+        entities = ['accounts', 'categories', 'payees', 'transactions', 'scheduled_transactions']
+        for entity in entities:
+            sql = f"CREATE TABLE IF NOT EXISTS silver.{entity} AS SELECT * FROM {self._silver_parquet_expr(entity)}"
+            try:
+                self.db.execute(sql)
+                self.logger.info(f"Created silver.{entity}")
+            except Exception as e:
+                self.logger.error(f"Failed to create silver.{entity}: {e}")
+        self.logger.info("Silver layer initialized")
+
+    def _drop_gold(self):
+        for name in ['accounts', 'categories', 'payees']:
+            self.db.execute(f"DROP VIEW IF EXISTS gold.{name}")
+        self.db.execute("DROP TABLE IF EXISTS gold.dates")
+        self.db.execute("DROP TABLE IF EXISTS gold.transactions")
+        self.db.execute("DROP TABLE IF EXISTS gold.scheduled_transactions")
+
+    # ── gold views (dimensions) ─────
+
+    def _create_gold_accounts_view(self):
+        self.logger.info("Transforming and creating gold.accounts view")
+        sql = """
+            SELECT
+                id AS account_id,
+                name AS account_name,
+                "type" AS account_type,
+                on_budget,
+                closed,
+                COALESCE(CAST(note AS VARCHAR), 'none') AS note,
+                balance / 1000.0 AS balance,
+                cleared_balance / 1000.0 AS cleared_balance,
+                uncleared_balance / 1000.0 AS uncleared_balance,
+                deleted
+            FROM silver.accounts
+        """
+        try:
+            self.db.execute(f"CREATE VIEW gold.accounts AS {sql}")
+            self.logger.info("Created gold.accounts view")
+        except Exception as e:
+            self.logger.error(f"Failed to create gold.accounts view: {e}")
+
+    def _create_gold_categories_view(self):
+        self.logger.info("Transforming and creating gold.categories view")
+        sql = """
+            SELECT
+                id AS category_id,
+                name AS category_name,
+                category_group_name,
+                hidden,
+                COALESCE(CAST(note AS VARCHAR), 'none') AS note,
+                budgeted / 1000.0 AS budgeted,
+                activity / 1000.0 AS activity,
+                balance / 1000.0 AS balance,
+                deleted
+            FROM silver.categories
+        """
+        try:
+            self.db.execute(f"CREATE VIEW gold.categories AS {sql}")
+            self.logger.info("Created gold.categories view")
+        except Exception as e:
+            self.logger.error(f"Failed to create gold.categories view: {e}")
+
+    def _create_gold_payees_view(self):
+        self.logger.info("Transforming and creating gold.payees view")
+        sql = """
+            SELECT
+                id AS payee_id,
+                name AS payee_name,
+                deleted
+            FROM silver.payees
+        """
+        try:
+            self.db.execute(f"CREATE VIEW gold.payees AS {sql}")
+            self.logger.info("Created gold.payees view")
+        except Exception as e:
+            self.logger.error(f"Failed to create gold.payees view: {e}")
+
+    def _create_gold_views(self):
+        self._create_gold_accounts_view()
+        self._create_gold_categories_view()
+        self._create_gold_payees_view()
+
+    # ── gold dates (materialized as Parquet, loaded into DuckDB) ─────
+
+    def _create_gold_dates(self):
+        dates_path = os.path.join(self.warehouse_path, 'dates.parquet')
+        self.logger.info("Creating gold.dates dimension")
+        try:
+            start = date(2020, 1, 1)
+            end = date(2030, 12, 31)
+            days = (end - start).days + 1
+            rows = []
+            for i in range(days):
+                d = start + timedelta(days=i)
+                month_z = str(d.month).zfill(2)
+                day_z = str(d.day).zfill(2)
+                rows.append({
+                    'date_id': f"{d.year}{month_z}{day_z}",
+                    'date': d,
+                    'year': int(d.year),
+                    'month': int(d.month),
+                    'day': int(d.day),
+                    'weekday': int(d.isoweekday()),
+                    'is_weekday': 1 if d.isoweekday() < 6 else 0,
+                })
+
+            import pyarrow as pa
+            import pyarrow.parquet as pq
+            dates_df = pa.Table.from_pylist(rows)
+            dates_df = dates_df.cast(pa.schema([
+                ('date_id', pa.string()),
+                ('date', pa.date32()),
+                ('year', pa.int32()),
+                ('month', pa.int8()),
+                ('day', pa.int8()),
+                ('weekday', pa.int8()),
+                ('is_weekday', pa.int8()),
+            ]))
+            pq.write_table(dates_df, dates_path)
+
+            self.db.execute(f"CREATE TABLE gold.dates AS SELECT * FROM read_parquet('{dates_path}')")
+            self.logger.info(f"Created gold.dates and persisted to {dates_path}")
+        except Exception as e:
+            self.logger.error(f"Failed to create gold.dates: {e}")
+
+    # ── gold facts (materialized as Parquet) ─────
+
+    def _create_gold_transactions_fact(self):
+        transactions_path = os.path.join(self.warehouse_path, 'transactions.parquet')
+        self.logger.info("Transforming and persisting gold.transactions fact")
+        sql = f"""
+            COPY (
+                SELECT
+                    memo,
+                    cleared,
+                    approved,
+                    COALESCE(CAST(flag_color AS VARCHAR), 'none') AS flag_color,
+                    account_id,
+                    payee_id,
+                    category_id,
+                    transfer_account_id,
+                    id AS transaction_id,
+                    CAST(YEAR(CAST(date AS DATE)) AS VARCHAR)
+                        || LPAD(CAST(MONTH(CAST(date AS DATE)) AS VARCHAR), 2, '0')
+                        || LPAD(CAST(DAY(CAST(date AS DATE)) AS VARCHAR), 2, '0') AS transaction_date,
+                    amount / 1000.0 AS transaction_amount,
+                    deleted
+                FROM silver.transactions
+            ) TO '{transactions_path}' (FORMAT PARQUET)
+        """
+        try:
+            self.db.execute(sql)
+            self.logger.info(f"Persisted transactions.fact to {transactions_path}")
+        except Exception as e:
+            self.logger.error(f"Failed to create transactions.fact: {e}")
+
+    def _create_gold_scheduled_transactions_fact(self):
+        st_path = os.path.join(self.warehouse_path, 'scheduled_transactions.parquet')
+        self.logger.info("Transforming and persisting gold.scheduled_transactions fact")
+        sql = f"""
+            COPY (
+                SELECT
+                    CAST(date_first AS DATE) AS date_first,
+                    CAST(date_next AS DATE) AS date_next,
+                    frequency,
+                    COALESCE(memo, 'none') AS memo,
+                    COALESCE(CAST(flag_color AS VARCHAR), 'none') AS flag_color,
+                    account_id,
+                    payee_id,
+                    category_id,
+                    transfer_account_id,
+                    id AS scheduled_transaction_id,
+                    amount / 1000.0 AS scheduled_transaction_amount
+                FROM silver.scheduled_transactions
+            ) TO '{st_path}' (FORMAT PARQUET)
+        """
+        try:
+            self.db.execute(sql)
+            self.logger.info(f"Persisted scheduled_transactions.fact to {st_path}")
+        except Exception as e:
+            self.logger.error(f"Failed to create scheduled_transactions.fact: {e}")
+
+    def _create_gold_facts(self):
+        self._create_gold_transactions_fact()
+        self._create_gold_scheduled_transactions_fact()
+        # Create DuckDB tables from the persistent Parquet files so they're queryable
+        self._register_facts()
+
+    def _register_facts(self):
+        """Register the fact Parquet files as DuckDB tables."""
+        try:
+            self.db.execute(f"CREATE TABLE gold.transactions AS SELECT * FROM read_parquet('{os.path.join(self.warehouse_path, 'transactions.parquet')}')")
+            self.db.execute(f"CREATE TABLE gold.scheduled_transactions AS SELECT * FROM read_parquet('{os.path.join(self.warehouse_path, 'scheduled_transactions.parquet')}')")
+            self.logger.info("Registered fact tables in DuckDB")
+        except Exception as e:
+            self.logger.error(f"Failed to register fact tables: {e}")
+
+    def close(self):
+        if self.db:
+            self.db.close()
+
+
+def get_duckdb_layer(base_path: str, warehouse_path: str, logger) -> DuckDBLayer:
+    """Factory function to create a DuckDB layer and perform all transformations."""
+    return DuckDBLayer(base_path, warehouse_path, logger)

pipeline/pipeline_main.py

@@ -1,19 +1,19 @@
 '''Module to run the data pipeline'''
 
-from pipeline import dimensions, facts, ingest, raw_to_base
+from pipeline import duckdb_layer, ingest, raw_to_base
 
 
 def pipeline_main(config, logger):
     '''Run the data pipeline'''
     logger.info('Starting data pipeline')
 
-    ingest.Ingest(config,logger).start_ingestion()
+    ingest.Ingest(config, logger).start_ingestion()
-    raw_to_base.RawToBase(config,logger)
+    raw_to_base.RawToBase(config, logger)
-    dimensions.DimAccounts(config,logger)
+
-    dimensions.DimCategories(config,logger)
+    duckdb_layer.get_duckdb_layer(
-    dimensions.DimPayees(config,logger)
+        config['base_data_path'],
-    dimensions.DimDate(config,logger)
+        config['warehouse_data_path'],
-    facts.FactTransactions(config,logger)
+        logger
-    facts.FactScheduledTransactions(config,logger)
+    )
 
     logger.info('Data pipeline completed successfully')

pyproject.toml

@@ -5,8 +5,7 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
-    "dash>=4.4.1",
+    "duckdb>=1.5.5",
-    "dash-bootstrap-components>=2.0.4",
     "pandas>=3.0.5",
     "polars>=1.43.0",
     "pyarrow>=25.0.0",

requirements.txt

@@ -1,11 +0,0 @@
-python-dotenv
-polars
-requests
-pyyaml
-#visualisation requirements below
-dash
-pandas
-pyarrow 
-dash-bootstrap-components
-# testing requirements below
-pytest

uv.lock

@@ -10,24 +10,6 @@ resolution-markers = [
     "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" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/99/91/8acff4f5e50511b911bbccb72b8628a49c68ce14148cd9f6431094859a90/annotated_types-0.8.0-py3-none-any.whl", hash = "sha256:f072f4d804ea359e4eaf198b1af7a8b0943881a87f31bb764f8bf219bb9419e0", size = 13427, upload-time = "2026-07-23T20:16:12.938Z" },
-]
-
-[[package]]
-name = "blinker"
-version = "1.9.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/21/28/9b3f50ce0e048515135495f198351908d99540d69bfdc8c1d15b73dc55ce/blinker-1.9.0.tar.gz", hash = "sha256:b4ce2265a7abece45e7cc896e98dbebe6cead56bcf805a3d23136d145f5445bf", size = 22460, upload-time = "2024-11-08T17:25:47.436Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl", hash = "sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc", size = 8458, upload-time = "2024-11-08T17:25:46.184Z" },
-]
-
 [[package]]
 name = "certifi"
 version = "2026.7.22"
@@ -85,18 +67,6 @@ wheels = [
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