Jake/data_pipeline_for_YNAB
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starting to implement callbacks

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Jake
2025-04-05 11:49:15 +01:00
parent b573b3b9bc
commit c9c287aa8a
4 changed files with 190 additions and 175 deletions
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main.py
+1 -1
View File
@@ -60,7 +60,7 @@ if __name__ == '__main__':
# Check if the data was successfully created
data_exists = os.path.exists('data/processed') and os.listdir('data/processed')
if data_exists:
app.run() # debug=True
app.run(debug=True)
else:
logging.error('Data pipeline did not produce any data. Dash app will not run.')
sys.exit(ec.NO_DATA_PRODUCED)
visuals/components.py
+86 -69
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@@ -4,8 +4,7 @@ import pandas as pd
import logging
import sys
import config.exit_codes as ec
import datetime
try:
accounts = pl.read_parquet('data/warehouse/accounts.parquet')
@@ -31,80 +30,98 @@ 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
'''
)
def update_dates(start_date, end_date):
start_year = int(start_date[:4])
start_month = int(start_date[5:7])
start_day = int(start_date[8:10])
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
'''
)
end_year = int(end_date[:4])
end_month = int(end_date[5:7])
end_day = int(end_date[8:10])
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
'''
)
total_spend = master_transactions.sql('''
SELECT ABS(SUM(transaction_amount)) AS total
FROM self
WHERE payee_name != 'Starting Balance'
AND transaction_amount < 0
''').item()
master_data = master_transactions.filter(
(pl.col('year_date') >= start_year ) & (pl.col('year_date') <= end_year) &
(pl.col('month_date') >= start_month ) & (pl.col('month_date') <= end_month) &
(pl.col('day_date') >= start_day ) & (pl.col('day_date') <= end_day)
)
return master_data
def update_data(master_data):
# 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 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)
# 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_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_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'
)
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'
)
return spend_per_day_line, spend_per_category_bar, spend_per_payee_bar, total_spend
visuals/dash_app.py
+11 -23
View File
@@ -4,35 +4,23 @@ import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output
import visuals.layout as layout
import visuals.components as charts
def update_visuals(start_date, end_date):
# Update the data based on the selected date range
master = charts.update_dates(start_date, end_date)
data = charts.update_data(master)
return layout.create_layout(data)
# Initialize the app with a dark theme
app = dash.Dash(external_stylesheets=[dbc.themes.DARKLY])
# App layout
app.layout = layout.create_layout()
app.layout = update_visuals()
# Update toggle visibility of off-canvas section
@app.callback(
Output('off-canvas-section', 'style'),
[Input('toggle-button', 'n_clicks')]
[
Input('date-picker-range', 'start_date'),
Input('date-picker-range', 'end_date')
]
)
def update_off_canvas_section(n_clicks):
if n_clicks is not None:
return {'display': 'block'}
else:
return {'display': 'none'}
# Update off-canvas section with date range picker
@app.callback(
Output('off-canvas-section', 'children'),
[Input('toggle-button', 'n_clicks')]
)
def update_off_canvas_content(n_clicks):
if n_clicks is not None:
# Include a date range picker library (e.g., Dash Bootstrap components) for the off-canvas section
return [
dbc.Input(id='date-picker-start', type='date'),
dbc.Input(id='date-picker-end', type='date')
]
visuals/layout.py
+90 -80
View File
@@ -2,104 +2,114 @@ from dash import html, dcc
from datetime import date
import dash_bootstrap_components as dbc
import visuals.components as charts
def create_layout():
main_body = create_main_body()
sidebar = create_sidebar()
def create_layout(data):
main_body = create_main_body(data)
topbar = create_topbar()
return [html.Div(main_body + sidebar)]
return [html.Div(topbar + main_body)]
def create_sidebar():
def create_topbar():
return [
html.Div(id='off-canvas-section', style={'display': 'none'}),
dbc.Row(
dbc.Col(
dcc.DatePickerRange(
id='date-picker-range',
start_date=date(2024, 1, 1),
end_date=date(2026, 1, 1)
),
width=4
),
align='center'
dbc.Container(
dbc.Row(
[
dbc.Col(
dcc.DatePickerRange(
id="date-picker-range",
start_date=date(2024, 1, 1),
end_date=date(2026, 1, 1),
),
width=4,
),
dbc.Col(
html.Button("Change Date Range", id="date-range-confirm-button"),
width=2,
),
]
)
)
]
def create_main_body():
return [html.Button('Toggle Off-Canvas', id='toggle-button'),
def create_main_body(data):
return [
dbc.Container(
[
dbc.Row(
dbc.Col(
html.Div(
"Data Pipeline For YNAB, Preview Visualisations",
className="text-center text-light",
),
width=12,
)
),
dbc.Row(
[
[
dbc.Row(
dbc.Col(
dbc.Card(
dbc.CardBody(
[
html.H4("Spend Per Day", className="card-title"),
dcc.Graph(figure=charts.spend_per_day_line),
]
),
className="mb-4",
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 Category", className="card-title"
),
dcc.Graph(figure=charts.spend_per_category_bar),
]
),
dbc.Row(
[
dbc.Col(
dbc.Card(
dbc.CardBody(
[
html.H4(
"Spend Per Day", className="card-title"
),
dcc.Graph(figure=data.spend_per_day_line),
]
),
className="mb-4",
),
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),
]
),
className="mb-4",
),
width=5,
),
width=5,
),
dbc.Col(
dbc.Card(
dbc.CardBody(
[
dcc.Markdown(f"""
dbc.Col(
dbc.Card(
dbc.CardBody(
[
dcc.Markdown(f"""
## Total Spend:
### £{charts.total_spend:,}
### £{data.total_spend:,}
"""),
]
]
),
className="mb-4",
),
className="mb-4",
width=2,
),
width=2,
),
dbc.Col(
dbc.Card(
dbc.CardBody(
[
html.H4("Spend Per Payee", className="card-title"),
dcc.Graph(figure=charts.spend_per_payee_bar),
]
dbc.Col(
dbc.Card(
dbc.CardBody(
[
html.H4(
"Spend Per Payee", className="card-title"
),
dcc.Graph(figure=data.spend_per_payee_bar),
]
),
className="mb-4",
),
className="mb-4",
width=5,
),
width=5,
),
]
),
],
fluid=True,
)
]
),
],
fluid=True,
),
]