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Author SHA1 Message Date
Jake 5339ea3f97 migration commit 2026-05-11 07:15:55 +01:00
Jake Pullen 33199e35cd style: 🎨 more code style updates 2025-05-30 11:52:44 +01:00
Jake Pullen 5da9ba4b0b style: 🎨 Added UV and Ruff linting 2025-05-30 11:43:47 +01:00
Jake cb5c03ab74 visual for total spend fixed, 2025-04-13 11:02:57 +01:00
Jake 7668f790aa working callback, known minor visual with total spend 2025-04-12 16:19:04 +01:00
Jake a79c245511 almost there 2025-04-12 15:20:05 +01:00
Jake c0b5e95d98 . 2025-04-08 19:43:50 +01:00
Jake c9c287aa8a starting to implement callbacks 2025-04-05 11:49:15 +01:00
Jake b573b3b9bc expanding dash 2025-04-05 11:04:40 +01:00
20 changed files with 1131 additions and 858 deletions
+1
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@@ -10,3 +10,4 @@ __pycache__/*
/logs/*
.vscode/*
*.coverage
.ruff_cache/*
View File
+1 -2
View File
@@ -3,7 +3,6 @@ import json
import logging
from typing import override
class custom_json_logger(logging.Formatter):
def __init__(
self,
@@ -22,7 +21,7 @@ class custom_json_logger(logging.Formatter):
always_fields = {
"message" : record.getMessage(),
"timestamp" : dt.datetime.fromtimestamp(
record.created, tz=dt.UTC
record.created, tz=dt.timezone.utc
).isoformat(),
}
if record.exc_info is not None:
+71 -15
View File
@@ -1,18 +1,74 @@
import duckdb
import os
import polars as pl
import yaml
# 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')
db = duckdb.connect('/mnt/bulk/data/ynab_data.duckdb')
# 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')
# SELECT * FROM gold.transactions
relevant_data = db.sql('''
SELECT
transaction_date,
sum(transaction_amount) as total
FROM gold.transactions
GROUP BY transaction_date
ORDER BY transaction_date DESC
''')
print("Data after SQL query:")
print(relevant_data)
# # 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
# '''
# )
# def update_dates(start_date, end_date):
# print("start date", start_date)
# print("end date", end_date)
# print(master_transactions)
# master_data = master_transactions.filter(
# pl.col("date").is_between(start_date, end_date)
# )
# return master_data
# today = date.today()
# one_year_ago = today - timedelta(days=5)
# data = update_dates(start_date=one_year_ago, end_date=today)
# print(data)
with open('config/config.yaml', 'r') as file:
config = yaml.safe_load(file)
for k,v in config.items():
print(k,v)
+43 -31
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@@ -1,74 +1,86 @@
import atexit
import logging
import logging.config
import logging.handlers
import os
import sys
import dotenv
import logging
import yaml
import sys
import atexit
import logging.config
import config.exit_codes as ec
from pipeline.pipeline_main import pipeline_main
from visuals.dash_app import app
logger = logging.getLogger("data_pipeline_for_ynab")
def set_up_logging():
try:
with open('config/logging_config.yaml', 'r') as f:
with open("config/logging_config.yaml", "r") as f:
log_config = yaml.safe_load(f)
logging.config.dictConfig(log_config)
except yaml.YAMLError as e:
print(f"Error parsing logging configuration file: {e}")
log_config = {} # Initialize log_config to an empty dictionary
logging.basicConfig(level=logging.INFO) # Fallback to a basic configuration
queue_handler = logging.getHandlerByName('queue_handler')
# Fallback to a basic configuration
logging.basicConfig(level=logging.INFO)
queue_handler = logging.getHandlerByName("queue_handler")
if queue_handler is not None:
queue_handler.listener.start()
atexit.register(queue_handler.listener.stop)
def load_config(logger):
def load_config():
try:
with open('config/config.yaml', 'r') as file:
with open("config/config.yaml", "r") as file:
config = yaml.safe_load(file)
return config
except FileNotFoundError:
logger.error('config.yaml file not found')
logging.error("config.yaml file not found")
sys.exit(ec.MISSING_CONFIG_FILE)
except yaml.YAMLError as e:
logger.error(f'Error loading config.yaml: {e}')
except yaml.YAMLError:
# Attempt to print a more informative error message
try:
parsed_yaml = yaml.safe_load_all(file)
for key, value in parsed_yaml:
print(f"Error parsing key '{key}': {value}")
except Exception as e:
logging.error(f"Error loading config.yaml: {e}")
sys.exit(ec.CORRUPTED_CONFIG_FILE)
except Exception as e:
logging.error(f"some other problem {e}")
os.makedirs('logs', exist_ok=True)
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')
BUDGET_ID = os.getenv('BUDGET_ID')
API_TOKEN = os.getenv("API_TOKEN")
BUDGET_ID = os.getenv("BUDGET_ID")
if not API_TOKEN or not BUDGET_ID:
logger.error('API_TOKEN or BUDGET_ID is not set in .env file')
logging.error("API_TOKEN or BUDGET_ID is not set in .env file")
sys.exit(ec.MISSING_ENV_VARS)
if __name__ == '__main__':
config = load_config(logger)
config['API_TOKEN'] = API_TOKEN
config['BUDGET_ID'] = BUDGET_ID
if __name__ == "__main__":
config = load_config()
config["API_TOKEN"] = API_TOKEN
config["BUDGET_ID"] = BUDGET_ID
try:
pipeline_main(config, logger)
# pipeline_main(config)
data_exists = os.path.exists('data/processed') and os.listdir('data/processed')
# Check if the data was successfully created
data_exists = os.path.exists("data/processed") and os.listdir("data/processed")
if data_exists:
logger.info('Processing Successful')
sys.exit(ec.SUCCESS)
app.run(debug=True)
else:
logger.error('Data pipeline did not produce any data. Dash app will not run.')
logging.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:
logger.info('Program exited successfully')
logging.info("Program exited successfully")
else:
logger.error(f'Program exited with code {exit_code}')
logging.error(f"Program exited with code {exit_code}")
raise
+36 -37
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@@ -1,23 +1,21 @@
import polars as pl
import logging
import os
from datetime import date
import polars as pl
class Dimensions:
def __init__(self, config,logger):
def __init__(self, config):
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,logger):
super().__init__(config,logger)
def __init__(self, config):
super().__init__(config)
self.file_path = self.get_full_file_path('accounts.parquet')
self.transform()
@@ -26,10 +24,10 @@ class DimAccounts(Dimensions):
try:
source_accounts = pl.read_parquet(self.file_path)
except Exception as e:
self.logger.error(f"Failed to read the base accounts parquet file: {e}")
logging.error(f"Failed to read the base accounts parquet file: {e}")
return
self.logger.info("Transforming the accounts DataFrame")
logging.info("Transforming the accounts DataFrame")
try:
base_accounts = (
source_accounts.select([
@@ -46,7 +44,7 @@ class DimAccounts(Dimensions):
])
)
except Exception as e:
self.logger.error(f"Failed to select columns from the categories DataFrame: {e}")
logging.error(f"Failed to select columns from the categories DataFrame: {e}")
return
try:
@@ -67,19 +65,19 @@ class DimAccounts(Dimensions):
"id", "name", "type"
])
except Exception as e:
self.logger.error(f"Failed to transform the accounts DataFrame: {e}")
logging.error(f"Failed to transform the accounts DataFrame: {e}")
return
self.logger.info("Writing the transformed accounts DataFrame to parquet file")
logging.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:
self.logger.error(f"Failed to write the transformed accounts DataFrame to parquet file: {e}")
logging.error(f"Failed to write the transformed accounts DataFrame to parquet file: {e}")
return
class DimCategories(Dimensions):
def __init__(self, config,logger):
super().__init__(config,logger)
def __init__(self, config):
super().__init__(config)
self.file_path = self.get_full_file_path('categories.parquet')
self.transform()
@@ -87,9 +85,9 @@ class DimCategories(Dimensions):
try:
source_categories = pl.read_parquet(self.file_path)
except Exception as e:
self.logger.error(f"Failed to read the base categories parquet file: {e}")
logging.error(f"Failed to read the base categories parquet file: {e}")
return
self.logger.info("Transforming the categories DataFrame")
logging.info("Transforming the categories DataFrame")
try:
base_categories = source_categories.select([
'id',
@@ -103,7 +101,7 @@ class DimCategories(Dimensions):
'deleted'
])
except Exception as e:
self.logger.error(f"Failed to select columns from the categories DataFrame: {e}")
logging.error(f"Failed to select columns from the categories DataFrame: {e}")
return
try:
@@ -123,19 +121,19 @@ class DimCategories(Dimensions):
'id', 'name'
])
except Exception as e:
self.logger.error(f"Failed to transform the categories DataFrame: {e}")
logging.error(f"Failed to transform the categories DataFrame: {e}")
return
self.logger.info("Writing the transformed categories DataFrame to parquet file")
logging.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:
self.logger.error(f"Failed to write the transformed categories DataFrame to parquet file: {e}")
logging.error(f"Failed to write the transformed categories DataFrame to parquet file: {e}")
return
class DimPayees(Dimensions):
def __init__(self, config,logger):
super().__init__(config,logger)
def __init__(self, config):
super().__init__(config)
self.file_path = self.get_full_file_path('payees.parquet')
self.transform()
@@ -143,9 +141,9 @@ class DimPayees(Dimensions):
try:
source_payees = pl.read_parquet(self.file_path)
except Exception as e:
self.logger.error(f"Failed to read the base payees parquet file: {e}")
logging.error(f"Failed to read the base payees parquet file: {e}")
return
self.logger.info("Transforming the payees DataFrame")
logging.info("Transforming the payees DataFrame")
try:
base_payees = source_payees.select([
'id',
@@ -153,7 +151,7 @@ class DimPayees(Dimensions):
'deleted'
])
except Exception as e:
self.logger.error(f"Failed to select columns from the payees DataFrame: {e}")
logging.error(f"Failed to select columns from the payees DataFrame: {e}")
return
try:
@@ -165,20 +163,20 @@ class DimPayees(Dimensions):
'id', 'name'
])
except Exception as e:
self.logger.error(f"Failed to rename columns in the payees DataFrame: {e}")
logging.error(f"Failed to rename columns in the payees DataFrame: {e}")
return
# Write the DataFrame to a new parquet file
self.logger.info("Writing the transformed payees DataFrame to parquet file")
logging.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:
self.logger.error(f"Failed to write the transformed payees DataFrame to parquet file: {e}")
logging.error(f"Failed to write the transformed payees DataFrame to parquet file: {e}")
return
class DimDate(Dimensions):
def __init__(self, config,logger):
super().__init__(config,logger)
def __init__(self, config):
super().__init__(config)
self.transform()
def transform(self):
@@ -186,7 +184,7 @@ class DimDate(Dimensions):
try:
dates_df = pl.DataFrame({'date':pl.date_range(date(2020, 1, 1), date(2030, 12, 31), "1d", eager=True)})
except Exception as e:
self.logger.error(f"Failed to create a DataFrame with dates: {e}")
logging.error(f"Failed to create a DataFrame with dates: {e}")
return
# Extract year, month, day, and weekday from the date column
try:
@@ -197,7 +195,7 @@ class DimDate(Dimensions):
pl.col('date').dt.weekday().alias('weekday')
])
except Exception as e:
self.logger.error(f"Failed to extract year, month, day, and weekday from the date column: {e}")
logging.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
@@ -205,7 +203,7 @@ class DimDate(Dimensions):
(pl.col('weekday') < 6).alias('is_weekday') # True for weekdays (Monday to Friday), False for weekends (Saturday and Sunday)
])
except Exception as e:
self.logger.error(f"Failed to create a new column to indicate if the date is a weekday or weekend: {e}")
logging.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
@@ -217,12 +215,13 @@ class DimDate(Dimensions):
).alias('date_id')
])
except Exception as e:
self.logger.error(f"Failed to create the primary key column: {e}")
logging.error(f"Failed to create the primary key column: {e}")
return
# Write the DataFrame to a new parquet file
self.logger.info("Writing the transformed dates DataFrame to parquet file")
logging.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:
self.logger.error(f"Failed to write the transformed dates DataFrame to parquet file: {e}")
logging.error(f"Failed to write the transformed dates DataFrame to parquet file: {e}")
return
-241
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@@ -1,241 +0,0 @@
"""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)
+21 -23
View File
@@ -1,21 +1,19 @@
import polars as pl
import logging
import os
import polars as pl
class Facts:
def __init__(self, config,logger):
def __init__(self, config):
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,logger):
super().__init__(config,logger)
def __init__(self, config):
super().__init__(config)
self.file_path = self.get_full_file_path('transactions.parquet')
self.transform()
@@ -23,7 +21,7 @@ class FactTransactions(Facts):
try:
source_transactions = pl.read_parquet(self.file_path)
except FileNotFoundError:
self.logger.error("The transactions DataFrame does not exist")
logging.error("The transactions DataFrame does not exist")
return
try:
@@ -41,16 +39,16 @@ class FactTransactions(Facts):
"transfer_account_id"
])
except Exception as e:
self.logger.error(f"Failed to select columns from the transactions DataFrame: {e}")
logging.error(f"Failed to select columns from the transactions DataFrame: {e}")
return
self.logger.info("Transforming the transactions DataFrame")
logging.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:
self.logger.error(f"Failed to covert the date to date format: {e}")
logging.error(f"Failed to covert the date to date format: {e}")
return
try:
@@ -74,20 +72,20 @@ class FactTransactions(Facts):
])
except Exception as e:
self.logger.error(f"Failed to transform the transactions DataFrame: {e}")
logging.error(f"Failed to transform the transactions DataFrame: {e}")
return
# Write the DataFrame to a new parquet file
self.logger.info("Writing the transformed transactions DataFrame to parquet file")
logging.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:
self.logger.error(f"Failed to write the transformed transactions DataFrame: {e}")
logging.error(f"Failed to write the transformed transactions DataFrame: {e}")
class FactScheduledTransactions(Facts):
def __init__(self, config,logger):
super().__init__(config,logger)
def __init__(self, config):
super().__init__(config)
self.file_path = self.get_full_file_path('scheduled_transactions.parquet')
self.transform()
@@ -95,7 +93,7 @@ class FactScheduledTransactions(Facts):
try:
source_scheduled = pl.read_parquet(self.file_path)
except FileNotFoundError:
self.logger.error("The scheduled transactions DataFrame does not exist")
logging.error("The scheduled transactions DataFrame does not exist")
return
try:
@@ -113,7 +111,7 @@ class FactScheduledTransactions(Facts):
"transfer_account_id"
])
except Exception as e:
self.logger.error(f"Failed to select columns from the scheduled transactions DataFrame: {e}")
logging.error(f"Failed to select columns from the scheduled transactions DataFrame: {e}")
return
try:
@@ -122,10 +120,10 @@ class FactScheduledTransactions(Facts):
pl.col("date_next").str.strptime(pl.Date, format="%Y-%m-%d").alias("date_next")
])
except Exception as e:
self.logger.error(f"Failed to covert the date to date format: {e}")
logging.error(f"Failed to covert the date to date format: {e}")
return
self.logger.info("Transforming the scheduled transactions DataFrame")
logging.info("Transforming the scheduled transactions DataFrame")
try:
add_scheduled_prefix = resolve_scheduled_dates.with_columns([
pl.col("id").alias("scheduled_transaction_id")
@@ -143,10 +141,10 @@ class FactScheduledTransactions(Facts):
"id", "amount"
])
except Exception as e:
self.logger.error(f"Failed to transform the scheduled transactions DataFrame: {e}")
logging.error(f"Failed to transform the scheduled transactions DataFrame: {e}")
return
self.logger.info("Writing the transformed scheduled transactions DataFrame to parquet file")
logging.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:
self.logger.error(f"Failed to write the transformed scheduled transactions DataFrame: {e}")
logging.error(f"Failed to write the transformed scheduled transactions DataFrame: {e}")
+26 -29
View File
@@ -1,17 +1,15 @@
import json
import os
import sys
import time
from typing import Any
import json
import logging
import requests
import sys
from typing import Dict, Any
import config.exit_codes as ec
class Ingest:
def __init__(self, config: dict[str, Any],logger):
def __init__(self, config: Dict[str, Any]):
"""
Initialize the Ingest class with the provided configuration.
"""
@@ -24,10 +22,9 @@ 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.
"""
@@ -36,15 +33,15 @@ class Ingest:
if not os.path.exists(directory):
os.makedirs(directory)
entity_file = f'{directory}/{current_time}.json'
self.logger.info(f"Saving {entity} data to {entity_file}")
logging.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:
self.logger.error(f"Failed to save data for {entity} to {entity_file}")
logging.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.
"""
@@ -62,7 +59,7 @@ class Ingest:
with open(self.knowledge_file, 'r') as f:
knowledge_cache = json.load(f)
except FileNotFoundError:
self.logger.info(f"Knowledge file not found. Creating a new one at {self.knowledge_file}. This is normal for the first run.")
logging.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 = {}
@@ -77,33 +74,33 @@ class Ingest:
with open(self.knowledge_file, 'w') as f:
json.dump(knowledge_cache, f, indent=4)
except Exception as e:
self.logger.error(f"Failed to update knowledge cache for {entity} in {self.knowledge_file}")
logging.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:
self.logger.error("Bad request. The request could not be understood by the API due to malformed syntax or validation errors.")
logging.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:
self.logger.error("Unauthorized. Please check your API token.")
logging.error("Unauthorized. Please check your API token.")
sys.exit(ec.UNAUTHORIZED_API_TOKEN)
elif response.status_code == 403:
self.logger.error("Forbidden. Access is denied.")
logging.error("Forbidden. Access is denied.")
sys.exit(ec.FORBIDDEN)
elif response.status_code == 404:
self.logger.error("Not found. The specified URL does not exist.")
logging.error("Not found. The specified URL does not exist.")
sys.exit(ec.NOT_FOUND)
elif response.status_code == 409:
self.logger.error("Conflict. The resource cannot be saved due to a conflict.")
logging.error("Conflict. The resource cannot be saved due to a conflict.")
sys.exit(ec.CONFLICT)
elif response.status_code == 429:
self.logger.error("Too many requests. You have made too many requests in a short amount of time.")
logging.error("Too many requests. You have made too many requests in a short amount of time.")
return True
elif response.status_code == 500:
self.logger.error("Internal server error. The API experienced an unexpected error.")
logging.error("Internal server error. The API experienced an unexpected error.")
return True
elif response.status_code == 503:
self.logger.error("Service unavailable. The API is temporarily disabled or a request timeout occurred.")
logging.error("Service unavailable. The API is temporarily disabled or a request timeout occurred.")
return True
else:
response.raise_for_status()
@@ -116,14 +113,14 @@ class Ingest:
for entity in self.entities:
file_path = f'data/raw/{entity}'
if os.path.exists(file_path) and os.listdir(file_path):
self.logger.warning(f"Raw data exists for {entity} processing any raw data we already have.")
logging.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}')
self.logger.info(f'Fetching {entity} data since last knowledge: {last_knowledge}')
logging.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):
@@ -133,17 +130,17 @@ class Ingest:
if not should_retry:
break # Exit the loop if the request is successful
except requests.exceptions.RequestException as e:
self.logger.error(f"Error fetching {entity} data (attempt {attempt + 1}/{self.MAX_RETRIES}): {e}")
logging.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:
self.logger.error("Max retries reached. Exiting.")
logging.error("Max retries reached. Exiting.")
sys.exit(ec.REQUESTS_ERROR)
data = response.json()
self.logger.debug(f'response data: {data}')
logging.debug(f'response data: {data}')
server_knowledge = data['data'].get('server_knowledge')
self.logger.debug(f'{entity} new server knowledge: {server_knowledge}')
logging.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)
@@ -151,4 +148,4 @@ class Ingest:
entity_data.pop('server_knowledge', None)
self.save_entity_data_to_raw(entity, entity_data)
else:
self.logger.info(f"No new data for {entity}. Skipping cache update.")
logging.info(f"No new data for {entity}. Skipping cache update.")
+18 -12
View File
@@ -1,19 +1,25 @@
'''Module to run the data pipeline'''
from pipeline import duckdb_layer, ingest, raw_to_base
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
def pipeline_main(config, logger):
def pipeline_main(config):
'''Run the data pipeline'''
logger.info('Starting data pipeline')
logging.info('Starting data pipeline')
ingest.Ingest(config, logger).start_ingestion()
raw_to_base.RawToBase(config, logger)
ingest = Ingest(config)
ingest.start_ingestion()
RawToBase(config)
DimAccounts(config)
DimCategories(config)
DimPayees(config)
DimDate(config)
FactTransactions(config)
FactScheduledTransactions(config)
duckdb_layer.get_duckdb_layer(
config['base_data_path'],
config['warehouse_data_path'],
logger
)
logger.info('Data pipeline completed successfully')
logging.info('Data pipeline completed successfully')
+41 -44
View File
@@ -1,16 +1,14 @@
import json
import os
import json
import logging
import sys
from datetime import datetime
from typing import Any
from typing import Dict, Any
import config.exit_codes as ec
import polars as pl
import config.exit_codes as ec
class RawToBase:
def __init__(self, config: dict[str, Any],logger):
def __init__(self, config: Dict[str, Any]):
self.entities = config['entities']
self.primary_keys = config['primary_keys']
self.raw_data_path = config['raw_data_path']
@@ -18,40 +16,39 @@ 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:
self.logger.info(f"Processing entity: {entity}")
logging.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:
self.logger.warning(f"The folder {folder_path} is empty skipping {entity}.")
logging.warning(f"The folder {folder_path} is empty skipping {entity}.")
continue
if not self._load_raw_data(entity):
self.logger.warning(f"Skipping processing for entity: {entity} due to empty data.")
logging.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):
self.logger.error(f"Skipping processing for entity: {entity} due to failed saving base data.")
logging.error(f"Skipping processing for entity: {entity} due to failed saving base data.")
continue
if not self._move_raw_to_processed(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}.")
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}.")
sys.exit(ec.MOVE_FILE_ERROR)
self.logger.info(f"Successfully processed entity: {entity}")
logging.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] = []
self.logger.debug(f"Loading data for entity: {entity} from path: {entity_path}")
logging.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:
self.logger.error(f"""More than one file found in path: {entity_path}. Skipping processing for entity: {entity}.
logging.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
@@ -59,12 +56,12 @@ 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)
self.logger.debug(f"Reading file: {file_path}")
logging.debug(f"Reading file: {file_path}")
try:
with open(file_path, 'r') as f:
data = json.load(f)
except Exception as e:
self.logger.error(f"Failed to load data from file: {file_path}, error: {e}")
logging.error(f"Failed to load data from file: {file_path}, error: {e}")
return False
if self._is_data_empty(entity, data, file_path):
@@ -72,37 +69,37 @@ 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):
self.logger.debug(f"processing record: {record}")
logging.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
self.logger.debug(f"filtered record: {filtered_record}")
self.logger.debug(f"modified data: {modified_data}")
logging.debug(f"filtered record: {filtered_record}")
logging.debug(f"modified data: {modified_data}")
self.data[entity].append(modified_data)
self.logger.debug(f"Successfully loaded data from file: {file_path}")
logging.debug(f"Successfully loaded data from file: {file_path}")
return True
def _is_data_empty(self, entity, data, file_path):
self.logger.debug(f"Checking if data is empty for entity: {entity}")
logging.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:
self.logger.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
logging.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, []):
self.logger.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
logging.warning(f"Received empty data for entity: {entity} in file: {file_path}, deleting file.")
os.remove(file_path)
return True
self.logger.debug(f"Data is not empty for entity: {entity}")
logging.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()
self.logger.debug(f"Adding ingestion date to data for entity: {entity}")
logging.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', []):
@@ -115,22 +112,22 @@ 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})
self.logger.debug(f"Successfully added ingestion date to data for entity: {entity}")
logging.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):
self.logger.debug(f"Loading existing base data for entity: {entity} from path: {base_path}")
logging.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:
self.logger.error(f"Failed to load existing base data for entity: {entity}, error: {e}, Creating an empty DataFrame")
logging.error(f"Failed to load existing base data for entity: {entity}, error: {e}, Creating an empty DataFrame")
self.base_data[entity] = pl.DataFrame()
self.logger.debug(f"Successfully loaded existing base data for entity: {entity}")
logging.debug(f"Successfully loaded existing base data for entity: {entity}")
else:
self.base_data[entity] = pl.DataFrame()
self.logger.debug(f"No existing base data found for entity: {entity}, starting with an empty DataFrame")
logging.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):
@@ -145,7 +142,7 @@ 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):
self.logger.debug(f"Combining data for entity: {entity}")
logging.debug(f"Combining data for entity: {entity}")
combined_data = []
# Combine data from the entity
@@ -162,8 +159,8 @@ 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:
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)
logging.error(f"Unique ID column '{unique_id}' not found in the combined data for entity: {entity}")
exit(ec.UNIQUE_ID_NOT_FOUND)
# Cast columns in new_data_df
new_data_df = self._cast_struct_to_string(new_data_df)
@@ -191,7 +188,7 @@ 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
self.logger.debug(f"Successfully combined data for entity: {entity}")
logging.debug(f"Successfully combined data for entity: {entity}")
def _save_base_data(self, entity):
os.makedirs(self.base_data_path, exist_ok=True)
@@ -199,9 +196,9 @@ 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:
self.logger.error(f"Failed to save base data for entity: {entity}, error: {e}")
logging.error(f"Failed to save base data for entity: {entity}, error: {e}")
return False
self.logger.debug(f"Saved base data for entity: {entity} to path: {file_path}")
logging.debug(f"Saved base data for entity: {entity} to path: {file_path}")
return True
def _move_raw_to_processed(self, entity):
@@ -213,24 +210,24 @@ 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:
self.logger.error(f"Expected exactly one file in path: {raw_entity_path}, but found {len(files)}")
logging.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)
self.logger.debug(f"Moving file: {raw_file_path} to {processed_file_path}")
logging.debug(f"Moving file: {raw_file_path} to {processed_file_path}")
os.rename(raw_file_path, processed_file_path)
self.logger.debug(f"Moved file: {file_name} to processed")
logging.debug(f"Moved file: {file_name} to processed")
except FileNotFoundError as e:
self.logger.error(f"File not found: {e}")
logging.error(f"File not found: {e}")
return False
except Exception as e:
self.logger.error(f"Failed to move file for entity: {entity}, error: {e}")
logging.error(f"Failed to move file for entity: {entity}, error: {e}")
return False
self.logger.debug(f"Moved processed file for entity: {entity} to path: {processed_path}")
logging.debug(f"Moved processed file for entity: {entity} to path: {processed_path}")
return True
+10 -9
View File
@@ -5,13 +5,14 @@ description = "Add your description here"
readme = "README.md"
requires-python = ">=3.13"
dependencies = [
"duckdb>=1.5.5",
"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",
"dash>=3.0.4",
"dash-bootstrap-components>=2.0.3",
"pandas>=2.2.3",
"polars>=1.30.0",
"pyarrow>=20.0.0",
"pytest>=8.3.5",
"python-dotenv>=1.1.0",
"pyyaml>=6.0.2",
"requests>=2.32.3",
"ruff>=0.11.12",
]
+134 -85
View File
@@ -1,112 +1,126 @@
import pytest
from unittest.mock import patch, mock_open, MagicMock
import json
import os
from unittest.mock import MagicMock, mock_open, patch
import pytest
import config.exit_codes as ec
from pipeline.ingest import Ingest
import config.exit_codes as ec
# Mock configuration for initializing the Ingest class
mock_config = {
'API_TOKEN': 'test_token',
'BUDGET_ID': 'test_budget_id',
'base_url': 'http://test_base_url',
'knowledge_file': 'data/test_knowledge_file.json',
'entities': ['entity1', 'entity2'],
'raw_data_path': 'test_raw_data_path',
'REQUESTS_MAX_RETRIES': 3,
'REQUESTS_RETRY_DELAY': 1
"API_TOKEN": "test_token",
"BUDGET_ID": "test_budget_id",
"base_url": "http://test_base_url",
"knowledge_file": "data/test_knowledge_file.json",
"entities": ["entity1", "entity2"],
"raw_data_path": "test_raw_data_path",
"REQUESTS_MAX_RETRIES": 3,
"REQUESTS_RETRY_DELAY": 1,
}
# Test for load_knowledge_cache method
def test_load_knowledge_cache_file_exists():
mock_data = {"key": "value"}
with patch('os.path.exists', return_value=True), \
patch('builtins.open', mock_open(read_data=json.dumps(mock_data))) as mock_file:
with (
patch("os.path.exists", return_value=True),
patch("builtins.open", mock_open(read_data=json.dumps(mock_data))) as mock_file,
):
ingest_instance = Ingest(mock_config)
result = ingest_instance.load_knowledge_cache()
mock_file.assert_called_once_with(mock_config['knowledge_file'], 'r')
mock_file.assert_called_once_with(mock_config["knowledge_file"], "r")
assert result == mock_data
def test_load_knowledge_cache_file_not_exists():
with patch('os.path.exists', return_value=False):
def test_load_knowledge_cache_file_not_exists():
with patch("os.path.exists", return_value=False):
ingest_instance = Ingest(mock_config)
result = ingest_instance.load_knowledge_cache()
assert result == {}
# Test for save_entity_data_to_raw method
def test_save_entity_data_to_raw_success():
entity = 'entity1'
entity = "entity1"
data = {"key": "value"}
current_time = '20230101123000'
directory = os.path.join(mock_config['raw_data_path'], entity)
entity_file = f'{directory}/{current_time}.json'
with patch('os.path.exists', return_value=False), \
patch('os.makedirs') as mock_makedirs, \
patch('builtins.open', mock_open()) as mock_file, \
patch('time.strftime', return_value=current_time), \
patch('logging.info') as mock_logging_info:
current_time = "20230101123000"
directory = os.path.join(mock_config["raw_data_path"], entity)
entity_file = f"{directory}/{current_time}.json"
with (
patch("os.path.exists", return_value=False),
patch("os.makedirs") as mock_makedirs,
patch("builtins.open", mock_open()) as mock_file,
patch("time.strftime", return_value=current_time),
patch("logging.info") as mock_logging_info,
):
ingest_instance = Ingest(mock_config)
ingest_instance.save_entity_data_to_raw(entity, data)
mock_makedirs.assert_called_once_with(directory)
mock_file.assert_called_once_with(entity_file, 'w')
mock_file.assert_called_once_with(entity_file, "w")
# Get the file handle and check the written content
handle = mock_file()
handle.write.assert_called()
written_content = ''.join(call.args[0] for call in handle.write.call_args_list)
written_content = "".join(call.args[0] for call in handle.write.call_args_list)
assert written_content == json.dumps(data, indent=4)
mock_logging_info.assert_called_once_with(f"Saving {entity} data to {entity_file}")
mock_logging_info.assert_called_once_with(
f"Saving {entity} data to {entity_file}"
)
def test_save_entity_data_to_raw_existing_directory():
entity = 'entity1'
entity = "entity1"
data = {"key": "value"}
current_time = '20230101123000'
directory = os.path.join(mock_config['raw_data_path'], entity)
entity_file = f'{directory}/{current_time}.json'
with patch('os.path.exists', return_value=True), \
patch('os.makedirs') as mock_makedirs, \
patch('builtins.open', mock_open()) as mock_file, \
patch('time.strftime', return_value=current_time), \
patch('logging.info') as mock_logging_info:
current_time = "20230101123000"
directory = os.path.join(mock_config["raw_data_path"], entity)
entity_file = f"{directory}/{current_time}.json"
with (
patch("os.path.exists", return_value=True),
patch("os.makedirs") as mock_makedirs,
patch("builtins.open", mock_open()) as mock_file,
patch("time.strftime", return_value=current_time),
patch("logging.info") as mock_logging_info,
):
ingest_instance = Ingest(mock_config)
ingest_instance.save_entity_data_to_raw(entity, data)
mock_makedirs.assert_not_called()
mock_file.assert_called_once_with(entity_file, 'w')
mock_file.assert_called_once_with(entity_file, "w")
# Get the file handle and check the written content
handle = mock_file()
handle.write.assert_called()
written_content = ''.join(call.args[0] for call in handle.write.call_args_list)
written_content = "".join(call.args[0] for call in handle.write.call_args_list)
assert written_content == json.dumps(data, indent=4)
mock_logging_info.assert_called_once_with(f"Saving {entity} data to {entity_file}")
mock_logging_info.assert_called_once_with(
f"Saving {entity} data to {entity_file}"
)
def test_save_entity_data_to_raw_error():
entity = 'entity1'
entity = "entity1"
data = {"key": "value"}
current_time = '20230101123000'
directory = os.path.join(mock_config['raw_data_path'], entity)
entity_file = f'{directory}/{current_time}.json'
with patch('os.path.exists', return_value=True), \
patch('builtins.open', mock_open()) as mock_file, \
patch('time.strftime', return_value=current_time), \
patch('logging.info') as mock_logging_info, \
patch('logging.error') as mock_logging_error:
current_time = "20230101123000"
directory = os.path.join(mock_config["raw_data_path"], entity)
entity_file = f"{directory}/{current_time}.json"
with (
patch("os.path.exists", return_value=True),
patch("builtins.open", mock_open()) as mock_file,
patch("time.strftime", return_value=current_time),
patch("logging.info") as mock_logging_info,
patch("logging.error") as mock_logging_error,
):
mock_file.side_effect = Exception("Test error")
ingest_instance = Ingest(mock_config)
@@ -114,39 +128,47 @@ def test_save_entity_data_to_raw_error():
with pytest.raises(Exception, match="Test error"):
ingest_instance.save_entity_data_to_raw(entity, data)
mock_logging_error.assert_called_once_with(f"Failed to save data for {entity} to {entity_file}")
mock_logging_error.assert_called_once_with(
f"Failed to save data for {entity} to {entity_file}"
)
def test_update_server_knowledge_cache_file_exists():
entity = 'entity1'
entity = "entity1"
server_knowledge = {"key": "value"}
existing_cache = {"entity2": {"key": "old_value"}}
updated_cache = {"entity2": {"key": "old_value"}, "entity1": {"key": "value"}}
with patch('builtins.open', mock_open(read_data=json.dumps(existing_cache))) as mock_file, \
patch('os.path.exists', return_value=True), \
patch('logging.error') as mock_logging_error:
with (
patch(
"builtins.open", mock_open(read_data=json.dumps(existing_cache))
) as mock_file,
patch("os.path.exists", return_value=True),
patch("logging.error") as mock_logging_error,
):
ingest_instance = Ingest(mock_config)
ingest_instance.update_server_knowledge_cache(entity, server_knowledge)
mock_file.assert_called_with(mock_config['knowledge_file'], 'w')
mock_file.assert_called_with(mock_config["knowledge_file"], "w")
handle = mock_file()
handle.write.assert_called()
written_content = ''.join(call.args[0] for call in handle.write.call_args_list)
written_content = "".join(call.args[0] for call in handle.write.call_args_list)
assert json.loads(written_content) == updated_cache
mock_logging_error.assert_not_called()
def test_update_server_knowledge_cache_file_not_exists():
entity = 'entity1'
entity = "entity1"
server_knowledge = {"key": "value"}
updated_cache = {"entity1": {"key": "value"}}
with patch('builtins.open', mock_open()) as mock_file, \
patch('os.path.exists', return_value=False), \
patch('os.makedirs') as mock_makedirs, \
patch('logging.info') as mock_logging_info, \
patch('logging.error') as mock_logging_error:
with (
patch("builtins.open", mock_open()) as mock_file,
patch("os.path.exists", return_value=False),
patch("os.makedirs") as mock_makedirs,
patch("logging.info") as mock_logging_info,
patch("logging.error") as mock_logging_error,
):
# Ensure the side_effect list has enough elements to cover all calls to open
mock_file.side_effect = [FileNotFoundError(), mock_open().return_value]
@@ -155,17 +177,25 @@ def test_update_server_knowledge_cache_file_not_exists():
with pytest.raises(FileNotFoundError):
ingest_instance.update_server_knowledge_cache(entity, server_knowledge)
mock_makedirs.assert_called_once_with(os.path.dirname(mock_config['knowledge_file']), exist_ok=True)
mock_file.assert_called_with(mock_config['knowledge_file'], 'w')
mock_logging_error.assert_called_once_with(f"Failed to update knowledge cache for {entity} in {mock_config['knowledge_file']}")
mock_makedirs.assert_called_once_with(
os.path.dirname(mock_config["knowledge_file"]), exist_ok=True
)
mock_file.assert_called_with(mock_config["knowledge_file"], "w")
mock_logging_error.assert_called_once_with(
f"Failed to update knowledge cache for {entity} in {
mock_config['knowledge_file']
}"
)
def test_update_server_knowledge_cache_write_error():
entity = 'entity1'
entity = "entity1"
server_knowledge = {"key": "value"}
with patch('builtins.open', mock_open()) as mock_file, \
patch('logging.error') as mock_logging_error:
with (
patch("builtins.open", mock_open()) as mock_file,
patch("logging.error") as mock_logging_error,
):
mock_file.side_effect = Exception("Test error")
ingest_instance = Ingest(mock_config)
@@ -173,35 +203,43 @@ def test_update_server_knowledge_cache_write_error():
with pytest.raises(Exception, match="Test error"):
ingest_instance.update_server_knowledge_cache(entity, server_knowledge)
mock_logging_error.assert_called_once_with(f"Failed to update knowledge cache for {entity} in {mock_config['knowledge_file']}")
mock_logging_error.assert_called_once_with(
f"Failed to update knowledge cache for {entity} in {
mock_config['knowledge_file']
}"
)
def test_check_rate_limit_above_threshold():
response = MagicMock()
response.headers = {'X-Rate-Limit': '10/100'}
response.headers = {"X-Rate-Limit": "10/100"}
ingest_instance = Ingest(mock_config)
result = ingest_instance.check_rate_limit(response)
assert result is None
def test_check_rate_limit_below_threshold():
response = MagicMock()
response.headers = {'X-Rate-Limit': '90/100'}
response.headers = {"X-Rate-Limit": "90/100"}
ingest_instance = Ingest(mock_config)
result = ingest_instance.check_rate_limit(response)
assert result is None
def test_check_rate_limit_exceeded():
response = MagicMock()
response.headers = {'X-Rate-Limit': '100/100'}
response.headers = {"X-Rate-Limit": "100/100"}
ingest_instance = Ingest(mock_config)
result = ingest_instance.check_rate_limit(response)
assert result is True
def test_check_rate_limit_header_missing():
response = MagicMock()
response.headers = {}
@@ -211,6 +249,7 @@ def test_check_rate_limit_header_missing():
assert result is None
def test_handle_response_bad_request():
response = MagicMock()
response.status_code = 400
@@ -219,9 +258,10 @@ def test_handle_response_bad_request():
with pytest.raises(SystemExit) as e:
ingest_instance.handle_response(response)
assert e.type == SystemExit
assert e.type is SystemExit
assert e.value.code == ec.BAD_REQUEST
def test_handle_response_unauthorized():
response = MagicMock()
response.status_code = 401
@@ -230,9 +270,10 @@ def test_handle_response_unauthorized():
with pytest.raises(SystemExit) as e:
ingest_instance.handle_response(response)
assert e.type == SystemExit
assert e.type is SystemExit
assert e.value.code == ec.UNAUTHORIZED_API_TOKEN
def test_handle_response_forbidden():
response = MagicMock()
response.status_code = 403
@@ -241,9 +282,10 @@ def test_handle_response_forbidden():
with pytest.raises(SystemExit) as e:
ingest_instance.handle_response(response)
assert e.type == SystemExit
assert e.type is SystemExit
assert e.value.code == ec.FORBIDDEN
def test_handle_response_not_found():
response = MagicMock()
response.status_code = 404
@@ -252,9 +294,10 @@ def test_handle_response_not_found():
with pytest.raises(SystemExit) as e:
ingest_instance.handle_response(response)
assert e.type == SystemExit
assert e.type is SystemExit
assert e.value.code == ec.NOT_FOUND
def test_handle_response_conflict():
response = MagicMock()
response.status_code = 409
@@ -263,9 +306,10 @@ def test_handle_response_conflict():
with pytest.raises(SystemExit) as e:
ingest_instance.handle_response(response)
assert e.type == SystemExit
assert e.type is SystemExit
assert e.value.code == ec.CONFLICT
def test_handle_response_too_many_requests():
response = MagicMock()
response.status_code = 429
@@ -275,6 +319,7 @@ def test_handle_response_too_many_requests():
result = ingest_instance.handle_response(response)
assert result is True
def test_handle_response_internal_server_error():
response = MagicMock()
response.status_code = 500
@@ -284,6 +329,7 @@ def test_handle_response_internal_server_error():
result = ingest_instance.handle_response(response)
assert result is True
def test_handle_response_service_unavailable():
response = MagicMock()
response.status_code = 503
@@ -293,6 +339,7 @@ def test_handle_response_service_unavailable():
result = ingest_instance.handle_response(response)
assert result is True
def test_handle_response_ok():
response = MagicMock()
response.status_code = 200
@@ -302,5 +349,7 @@ def test_handle_response_ok():
result = ingest_instance.handle_response(response)
assert result is False
if __name__ == "__main__":
pytest.main()
+3 -5
View File
@@ -1,11 +1,9 @@
import logging
from unittest.mock import MagicMock, mock_open, patch
from unittest.mock import patch, mock_open, MagicMock
import yaml
import logging
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():
Generated
+369 -270
View File
@@ -1,70 +1,57 @@
version = 1
revision = 3
revision = 2
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'",
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import polars as pl
import plotly.express as px
import pandas as pd
import logging
# import datetime
class data_components:
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")
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")
)
def __init__(self):
logging.info("Initializing data components")
pass
def update_dates(start_date, end_date):
logging.info("Updating dates")
logging.debug(f"start_date: {start_date}, end_date: {end_date}")
logging.debug(data_components.master_transactions.columns)
try:
master_data = data_components.master_transactions.filter(
pl.col("date").is_between(start_date, end_date)
)
except Exception as e:
logging.error(f"Error updating dates: {e}")
raise e
return master_data
def update_data(master_data, callback=0):
# Create aggregations
spend_per_day = master_data.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_data.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_data.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
""")
total_spend = master_data.sql("""
SELECT ABS(SUM(transaction_amount)) AS total
FROM self
WHERE payee_name != 'Starting Balance'
AND transaction_amount < 0
""").item()
# 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"
)
total_spend_line = f"### £{total_spend:,.2f}"
data = {
"spend_per_day_line": spend_per_day_line,
"spend_per_category_bar": spend_per_category_bar,
"spend_per_payee_bar": spend_per_payee_bar,
"total_spend": total_spend_line,
}
if callback == 0:
return data
else:
return (
spend_per_day_line,
spend_per_category_bar,
spend_per_payee_bar,
total_spend,
)
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'''Module to create a Dash app that displays visualizations of YNAB data.'''
import dash
from dash.dependencies import Input, Output
import dash_bootstrap_components as dbc
from visuals.layout import create_layout
from visuals.components import data_components
from datetime import date, timedelta
import datetime
today = date.today()
one_year_ago = today - timedelta(days=365)
master_data = data_components.update_dates(start_date=one_year_ago, end_date=today)
data = data_components.update_data(master_data)
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.DARKLY])
@app.callback(
Output("spend_per_day","figure"),
Output("spend_per_category","figure"),
Output("spend_per_payee","figure"),
Output("total_spend","children"),
Input('date-picker-range', 'start_date'),
Input('date-picker-range', 'end_date')
)
def update_date_range(start_date,end_date):
actual_start_date = datetime.date.fromisoformat(start_date)
actual_end_date = datetime.date.fromisoformat(end_date)
master_data = data_components.update_dates(actual_start_date,actual_end_date)
return data_components.update_data(master_data,callback=1)
app.layout = create_layout(data)
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from dash import html, dcc
from datetime import date
import dash_bootstrap_components as dbc
from datetime import timedelta
today = date.today()
one_year_ago = today - timedelta(days=365)
def create_layout(data):
main_body = create_main_body(data)
topbar = create_topbar()
return [html.Div(topbar + main_body)]
def create_topbar():
return [
dbc.Container(
[
dbc.Row(
dbc.Col(
html.Div(
html.H1("Data Pipeline For YNAB, Preview Visualisations"),
className="text-center text-light",
),
width=12,
)
),
dbc.Row(
[
dbc.Col(
dcc.DatePickerRange(
first_day_of_week=1,
display_format="YYYY-MM-DD",
id="date-picker-range",
start_date=one_year_ago,
end_date=today,
),
width=4,
),
dbc.Col(
html.Button(
"Change Date Range", id="date-range-confirm-button"
),
width=2,
),
]
),
]
)
]
def create_main_body(data):
return [
dbc.Container(
[
dbc.Row(
[
dbc.Col(
dbc.Card(
dbc.CardBody(
[
html.H4(
"Spend Per Day", className="card-title"
),
dcc.Graph(
figure=data["spend_per_day_line"],
id="spend_per_day",
),
]
),
className="mb-4",
),
width=12,
)
]
),
dbc.Row(
[
dbc.Col(
dbc.Card(
dbc.CardBody(
[
html.H4(
"Spend Per Category", className="card-title"
),
dcc.Graph(
figure=data["spend_per_category_bar"],
id="spend_per_category",
),
]
),
className="mb-4",
),
width=5,
),
dbc.Col(
dbc.Card(
dbc.CardBody(
[
dcc.Markdown("## Total Spend:"),
dcc.Markdown(
data["total_spend"], id="total_spend"
),
],
),
className="text-center text-light",
),
width=2,
),
dbc.Col(
dbc.Card(
dbc.CardBody(
[
html.H4(
"Spend Per Payee", className="card-title"
),
dcc.Graph(
figure=data["spend_per_payee_bar"],
id="spend_per_payee",
),
]
),
className="mb-4",
),
width=5,
),
]
),
],
fluid=True,
),
]