Implement modular architecture for Crypto Trading Bot Dashboard

- Introduced a new modular structure for the dashboard, enhancing maintainability and scalability.
- Created main application entry point in `app_new.py`, integrating all components and callbacks.
- Developed layout modules for market data, bot management, performance analytics, and system health in the `layouts` directory.
- Implemented callback modules for navigation, charts, indicators, and system health in the `callbacks` directory.
- Established reusable UI components in the `components` directory, including chart controls and indicator modals.
- Enhanced documentation to reflect the new modular structure and provide clear usage guidelines.
- Ensured all components are under 300-400 lines for better readability and maintainability.
This commit is contained in:
Vasily.onl
2025-06-04 13:30:16 +08:00
parent 476bd67f14
commit 010adb30f0
21 changed files with 2195 additions and 45 deletions

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dashboard/__init__.py Normal file
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"""
Dashboard package for the Crypto Trading Bot Dashboard.
This package contains modular dashboard components:
- layouts: UI layout definitions
- callbacks: Dash callback functions
- components: Reusable UI components
"""
from .app import create_app
__all__ = ['create_app']

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dashboard/app.py Normal file
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"""
Main dashboard application module.
"""
import dash
from dash import html, dcc
from utils.logger import get_logger
from dashboard.layouts import (
get_market_data_layout,
get_bot_management_layout,
get_performance_layout,
get_system_health_layout
)
from dashboard.components import create_indicator_modal
logger = get_logger("dashboard_app")
def create_app():
"""Create and configure the Dash application."""
# Initialize Dash app
app = dash.Dash(__name__, suppress_callback_exceptions=True)
# Define the main layout
app.layout = html.Div([
# Page title
html.H1("🚀 Crypto Trading Bot Dashboard",
style={'text-align': 'center', 'color': '#2c3e50', 'margin-bottom': '30px'}),
# Navigation tabs
dcc.Tabs(id='main-tabs', value='market-data', children=[
dcc.Tab(label='📊 Market Data', value='market-data'),
dcc.Tab(label='🤖 Bot Management', value='bot-management'),
dcc.Tab(label='📈 Performance', value='performance'),
dcc.Tab(label='⚙️ System Health', value='system-health'),
], style={'margin-bottom': '20px'}),
# Tab content container
html.Div(id='tab-content'),
# Hidden button for callback compatibility (real button is in market data layout)
html.Button(id='add-indicator-btn', style={'display': 'none'}),
# Add Indicator Modal
create_indicator_modal(),
# Auto-refresh interval
dcc.Interval(
id='interval-component',
interval=30*1000, # Update every 30 seconds
n_intervals=0
)
])
return app
def register_callbacks(app):
"""Register all dashboard callbacks."""
from dashboard.callbacks import (
register_navigation_callbacks,
register_chart_callbacks,
register_indicator_callbacks,
register_system_health_callbacks
)
# Register all callback modules
register_navigation_callbacks(app)
register_chart_callbacks(app)
register_indicator_callbacks(app)
register_system_health_callbacks(app)
logger.info("All dashboard callbacks registered successfully")

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"""
Callback modules for the dashboard.
"""
from .navigation import register_navigation_callbacks
from .charts import register_chart_callbacks
from .indicators import register_indicator_callbacks
from .system_health import register_system_health_callbacks
__all__ = [
'register_navigation_callbacks',
'register_chart_callbacks',
'register_indicator_callbacks',
'register_system_health_callbacks'
]

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"""
Chart-related callbacks for the dashboard.
"""
from dash import Output, Input
from datetime import datetime
from utils.logger import get_logger
from components.charts import (
create_strategy_chart,
create_chart_with_indicators,
create_error_chart,
get_market_statistics
)
from components.charts.config import get_all_example_strategies
from database.connection import DatabaseManager
from dash import html
logger = get_logger("chart_callbacks")
def register_chart_callbacks(app):
"""Register chart-related callbacks."""
@app.callback(
Output('price-chart', 'figure'),
[Input('symbol-dropdown', 'value'),
Input('timeframe-dropdown', 'value'),
Input('overlay-indicators-checklist', 'value'),
Input('subplot-indicators-checklist', 'value'),
Input('strategy-dropdown', 'value'),
Input('interval-component', 'n_intervals')]
)
def update_price_chart(symbol, timeframe, overlay_indicators, subplot_indicators, selected_strategy, n_intervals):
"""Update the price chart with latest market data and selected indicators."""
try:
# If a strategy is selected, use strategy chart
if selected_strategy and selected_strategy != 'basic':
fig = create_strategy_chart(symbol, timeframe, selected_strategy)
logger.debug(f"Created strategy chart for {symbol} ({timeframe}) with strategy: {selected_strategy}")
else:
# Create chart with dynamically selected indicators
fig = create_chart_with_indicators(
symbol=symbol,
timeframe=timeframe,
overlay_indicators=overlay_indicators or [],
subplot_indicators=subplot_indicators or [],
days_back=7
)
indicator_count = len(overlay_indicators or []) + len(subplot_indicators or [])
logger.debug(f"Created dynamic chart for {symbol} ({timeframe}) with {indicator_count} indicators")
return fig
except Exception as e:
logger.error(f"Error updating price chart: {e}")
return create_error_chart(f"Error loading chart: {str(e)}")
# Strategy selection callback - automatically load strategy indicators
@app.callback(
[Output('overlay-indicators-checklist', 'value'),
Output('subplot-indicators-checklist', 'value')],
[Input('strategy-dropdown', 'value')]
)
def update_indicators_from_strategy(selected_strategy):
"""Update indicator selections when a strategy is chosen."""
if not selected_strategy or selected_strategy == 'basic':
return [], []
try:
# Get strategy configuration
all_strategies = get_all_example_strategies()
if selected_strategy in all_strategies:
strategy_example = all_strategies[selected_strategy]
config = strategy_example.config
# Extract overlay and subplot indicators from strategy
overlay_indicators = config.overlay_indicators or []
# Extract subplot indicators from subplot configs
subplot_indicators = []
for subplot_config in config.subplot_configs or []:
subplot_indicators.extend(subplot_config.indicators or [])
logger.debug(f"Loaded strategy {selected_strategy}: {len(overlay_indicators)} overlays, {len(subplot_indicators)} subplots")
return overlay_indicators, subplot_indicators
else:
logger.warning(f"Strategy {selected_strategy} not found")
return [], []
except Exception as e:
logger.error(f"Error loading strategy indicators: {e}")
return [], []
# Market statistics callback
@app.callback(
Output('market-stats', 'children'),
[Input('symbol-dropdown', 'value'),
Input('interval-component', 'n_intervals')]
)
def update_market_stats(symbol, n_intervals):
"""Update market statistics."""
try:
# Get real market statistics from database
stats = get_market_statistics(symbol)
return html.Div([
html.H3("Market Statistics"),
html.Div([
html.Div([
html.Strong(f"{key}: "),
html.Span(value, style={'color': '#27ae60' if '+' in str(value) else '#e74c3c' if '-' in str(value) else '#2c3e50'})
], style={'margin': '5px 0'}) for key, value in stats.items()
])
])
except Exception as e:
logger.error(f"Error updating market stats: {e}")
return html.Div("Error loading market statistics")
logger.info("Chart callbacks registered successfully")

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"""
Indicator-related callbacks for the dashboard.
"""
import dash
from dash import Output, Input, State, html, dcc, callback_context
import json
from utils.logger import get_logger
logger = get_logger("indicator_callbacks")
def register_indicator_callbacks(app):
"""Register indicator-related callbacks."""
# Modal control callbacks
@app.callback(
[Output('indicator-modal', 'style'),
Output('indicator-modal-background', 'style')],
[Input('add-indicator-btn', 'n_clicks'),
Input('close-modal-btn', 'n_clicks'),
Input('cancel-indicator-btn', 'n_clicks'),
Input('edit-indicator-store', 'data')]
)
def toggle_indicator_modal(add_clicks, close_clicks, cancel_clicks, edit_data):
"""Toggle the visibility of the add indicator modal."""
# Default hidden styles
hidden_modal_style = {
'display': 'none',
'position': 'fixed',
'z-index': '1001',
'left': '0',
'top': '0',
'width': '100%',
'height': '100%',
'visibility': 'hidden'
}
hidden_background_style = {
'display': 'none',
'position': 'fixed',
'z-index': '1000',
'left': '0',
'top': '0',
'width': '100%',
'height': '100%',
'background-color': 'rgba(0,0,0,0.5)',
'visibility': 'hidden'
}
# Visible styles
visible_modal_style = {
'display': 'block',
'position': 'fixed',
'z-index': '1001',
'left': '0',
'top': '0',
'width': '100%',
'height': '100%',
'visibility': 'visible'
}
visible_background_style = {
'display': 'block',
'position': 'fixed',
'z-index': '1000',
'left': '0',
'top': '0',
'width': '100%',
'height': '100%',
'background-color': 'rgba(0,0,0,0.5)',
'visibility': 'visible'
}
ctx = dash.callback_context
# If no trigger or initial load, return hidden
if not ctx.triggered:
return [hidden_modal_style, hidden_background_style]
triggered_id = ctx.triggered[0]['prop_id'].split('.')[0]
# Only open modal if explicitly requested
should_open = False
# Check if add button was clicked (and has a click count > 0)
if triggered_id == 'add-indicator-btn' and add_clicks and add_clicks > 0:
should_open = True
# Check if edit button triggered and should open modal
elif triggered_id == 'edit-indicator-store' and edit_data and edit_data.get('open_modal') and edit_data.get('mode') == 'edit':
should_open = True
# Check if close/cancel buttons were clicked
elif triggered_id in ['close-modal-btn', 'cancel-indicator-btn']:
should_open = False
# Default: don't open
else:
should_open = False
if should_open:
return [visible_modal_style, visible_background_style]
else:
return [hidden_modal_style, hidden_background_style]
# Sync visible button clicks to hidden button
@app.callback(
Output('add-indicator-btn', 'n_clicks'),
Input('add-indicator-btn-visible', 'n_clicks'),
prevent_initial_call=True
)
def sync_add_button_clicks(visible_clicks):
"""Sync clicks from visible button to hidden button."""
return visible_clicks or 0
# Update parameter fields based on indicator type
@app.callback(
[Output('indicator-parameters-message', 'style'),
Output('sma-parameters', 'style'),
Output('ema-parameters', 'style'),
Output('rsi-parameters', 'style'),
Output('macd-parameters', 'style'),
Output('bb-parameters', 'style')],
Input('indicator-type-dropdown', 'value'),
prevent_initial_call=True
)
def update_parameter_fields(indicator_type):
"""Show/hide parameter input fields based on selected indicator type."""
# Default styles
hidden_style = {'display': 'none', 'margin-bottom': '10px'}
visible_style = {'display': 'block', 'margin-bottom': '10px'}
# Default message visibility
message_style = {'display': 'block'} if not indicator_type else {'display': 'none'}
# Initialize all as hidden
sma_style = hidden_style
ema_style = hidden_style
rsi_style = hidden_style
macd_style = hidden_style
bb_style = hidden_style
# Show the relevant parameter section
if indicator_type == 'sma':
sma_style = visible_style
elif indicator_type == 'ema':
ema_style = visible_style
elif indicator_type == 'rsi':
rsi_style = visible_style
elif indicator_type == 'macd':
macd_style = visible_style
elif indicator_type == 'bollinger_bands':
bb_style = visible_style
return message_style, sma_style, ema_style, rsi_style, macd_style, bb_style
# Save indicator callback
@app.callback(
[Output('save-indicator-feedback', 'children'),
Output('overlay-indicators-checklist', 'options'),
Output('subplot-indicators-checklist', 'options')],
Input('save-indicator-btn', 'n_clicks'),
[State('indicator-name-input', 'value'),
State('indicator-type-dropdown', 'value'),
State('indicator-description-input', 'value'),
State('indicator-color-input', 'value'),
State('indicator-line-width-slider', 'value'),
# SMA parameters
State('sma-period-input', 'value'),
# EMA parameters
State('ema-period-input', 'value'),
# RSI parameters
State('rsi-period-input', 'value'),
# MACD parameters
State('macd-fast-period-input', 'value'),
State('macd-slow-period-input', 'value'),
State('macd-signal-period-input', 'value'),
# Bollinger Bands parameters
State('bb-period-input', 'value'),
State('bb-stddev-input', 'value'),
# Edit mode data
State('edit-indicator-store', 'data')],
prevent_initial_call=True
)
def save_new_indicator(n_clicks, name, indicator_type, description, color, line_width,
sma_period, ema_period, rsi_period,
macd_fast, macd_slow, macd_signal,
bb_period, bb_stddev, edit_data):
"""Save a new indicator or update an existing one."""
if not n_clicks or not name or not indicator_type:
return "", dash.no_update, dash.no_update
try:
# Get indicator manager
from components.charts.indicator_manager import get_indicator_manager
manager = get_indicator_manager()
# Collect parameters based on indicator type and actual input values
parameters = {}
if indicator_type == 'sma':
parameters = {'period': sma_period or 20}
elif indicator_type == 'ema':
parameters = {'period': ema_period or 12}
elif indicator_type == 'rsi':
parameters = {'period': rsi_period or 14}
elif indicator_type == 'macd':
parameters = {
'fast_period': macd_fast or 12,
'slow_period': macd_slow or 26,
'signal_period': macd_signal or 9
}
elif indicator_type == 'bollinger_bands':
parameters = {
'period': bb_period or 20,
'std_dev': bb_stddev or 2.0
}
# Check if this is an edit operation
is_edit = edit_data and edit_data.get('mode') == 'edit'
if is_edit:
# Update existing indicator
indicator_id = edit_data.get('indicator_id')
success = manager.update_indicator(
indicator_id,
name=name,
description=description or "",
parameters=parameters,
styling={'color': color or "#007bff", 'line_width': line_width or 2}
)
if success:
success_msg = html.Div([
html.Span("", style={'color': '#28a745'}),
html.Span(f"Indicator '{name}' updated successfully!", style={'color': '#28a745'})
])
else:
error_msg = html.Div([
html.Span("", style={'color': '#dc3545'}),
html.Span("Failed to update indicator. Please try again.", style={'color': '#dc3545'})
])
return error_msg, dash.no_update, dash.no_update
else:
# Create new indicator
new_indicator = manager.create_indicator(
name=name,
indicator_type=indicator_type,
parameters=parameters,
description=description or "",
color=color or "#007bff"
)
if not new_indicator:
error_msg = html.Div([
html.Span("", style={'color': '#dc3545'}),
html.Span("Failed to save indicator. Please try again.", style={'color': '#dc3545'})
])
return error_msg, dash.no_update, dash.no_update
success_msg = html.Div([
html.Span("", style={'color': '#28a745'}),
html.Span(f"Indicator '{name}' saved successfully!", style={'color': '#28a745'})
])
# Refresh the indicator options
overlay_indicators = manager.get_indicators_by_type('overlay')
subplot_indicators = manager.get_indicators_by_type('subplot')
overlay_options = []
for indicator in overlay_indicators:
display_name = f"{indicator.name} ({indicator.type.upper()})"
overlay_options.append({'label': display_name, 'value': indicator.id})
subplot_options = []
for indicator in subplot_indicators:
display_name = f"{indicator.name} ({indicator.type.upper()})"
subplot_options.append({'label': display_name, 'value': indicator.id})
return success_msg, overlay_options, subplot_options
except Exception as e:
logger.error(f"Error saving indicator: {e}")
error_msg = html.Div([
html.Span("", style={'color': '#dc3545'}),
html.Span(f"Error: {str(e)}", style={'color': '#dc3545'})
])
return error_msg, dash.no_update, dash.no_update
# Update custom indicator lists with edit/delete buttons
@app.callback(
[Output('overlay-indicators-list', 'children'),
Output('subplot-indicators-list', 'children')],
[Input('overlay-indicators-checklist', 'options'),
Input('subplot-indicators-checklist', 'options'),
Input('overlay-indicators-checklist', 'value'),
Input('subplot-indicators-checklist', 'value')]
)
def update_custom_indicator_lists(overlay_options, subplot_options, overlay_values, subplot_values):
"""Create custom indicator lists with edit and delete buttons."""
def create_indicator_item(option, is_checked):
"""Create a single indicator item with checkbox and buttons."""
indicator_id = option['value']
indicator_name = option['label']
return html.Div([
# Checkbox and name
html.Div([
dcc.Checklist(
options=[{'label': '', 'value': indicator_id}],
value=[indicator_id] if is_checked else [],
id={'type': 'indicator-checkbox', 'index': indicator_id},
style={'display': 'inline-block', 'margin-right': '8px'}
),
html.Span(indicator_name, style={'display': 'inline-block', 'vertical-align': 'top'})
], style={'display': 'inline-block', 'width': '70%'}),
# Edit and Delete buttons
html.Div([
html.Button(
"✏️",
id={'type': 'edit-indicator-btn', 'index': indicator_id},
title="Edit indicator",
style={
'background': 'none',
'border': 'none',
'cursor': 'pointer',
'margin-left': '5px',
'font-size': '14px',
'color': '#007bff'
}
),
html.Button(
"🗑️",
id={'type': 'delete-indicator-btn', 'index': indicator_id},
title="Delete indicator",
style={
'background': 'none',
'border': 'none',
'cursor': 'pointer',
'margin-left': '5px',
'font-size': '14px',
'color': '#dc3545'
}
)
], style={'display': 'inline-block', 'width': '30%', 'text-align': 'right'})
], style={
'display': 'block',
'padding': '5px 0',
'border-bottom': '1px solid #f0f0f0',
'margin-bottom': '5px'
})
# Create overlay indicators list
overlay_list = []
for option in overlay_options:
is_checked = option['value'] in (overlay_values or [])
overlay_list.append(create_indicator_item(option, is_checked))
# Create subplot indicators list
subplot_list = []
for option in subplot_options:
is_checked = option['value'] in (subplot_values or [])
subplot_list.append(create_indicator_item(option, is_checked))
return overlay_list, subplot_list
# Sync individual indicator checkboxes with main checklist
@app.callback(
Output('overlay-indicators-checklist', 'value', allow_duplicate=True),
[Input({'type': 'indicator-checkbox', 'index': dash.ALL}, 'value')],
[State('overlay-indicators-checklist', 'options')],
prevent_initial_call=True
)
def sync_overlay_indicators(checkbox_values, overlay_options):
"""Sync individual indicator checkboxes with main overlay checklist."""
if not checkbox_values or not overlay_options:
return []
selected_indicators = []
overlay_ids = [opt['value'] for opt in overlay_options]
# Flatten the checkbox values and filter for overlay indicators
for values in checkbox_values:
if values: # values is a list, check if not empty
for indicator_id in values:
if indicator_id in overlay_ids:
selected_indicators.append(indicator_id)
# Remove duplicates
return list(set(selected_indicators))
@app.callback(
Output('subplot-indicators-checklist', 'value', allow_duplicate=True),
[Input({'type': 'indicator-checkbox', 'index': dash.ALL}, 'value')],
[State('subplot-indicators-checklist', 'options')],
prevent_initial_call=True
)
def sync_subplot_indicators(checkbox_values, subplot_options):
"""Sync individual indicator checkboxes with main subplot checklist."""
if not checkbox_values or not subplot_options:
return []
selected_indicators = []
subplot_ids = [opt['value'] for opt in subplot_options]
# Flatten the checkbox values and filter for subplot indicators
for values in checkbox_values:
if values: # values is a list, check if not empty
for indicator_id in values:
if indicator_id in subplot_ids:
selected_indicators.append(indicator_id)
# Remove duplicates
return list(set(selected_indicators))
# Handle delete indicator
@app.callback(
[Output('save-indicator-feedback', 'children', allow_duplicate=True),
Output('overlay-indicators-checklist', 'options', allow_duplicate=True),
Output('subplot-indicators-checklist', 'options', allow_duplicate=True)],
[Input({'type': 'delete-indicator-btn', 'index': dash.ALL}, 'n_clicks')],
[State({'type': 'delete-indicator-btn', 'index': dash.ALL}, 'id')],
prevent_initial_call=True
)
def delete_indicator(delete_clicks, button_ids):
"""Delete an indicator when delete button is clicked."""
ctx = dash.callback_context
if not ctx.triggered or not any(delete_clicks):
return dash.no_update, dash.no_update, dash.no_update
# Find which button was clicked
triggered_id = ctx.triggered[0]['prop_id']
button_info = json.loads(triggered_id.split('.')[0])
indicator_id = button_info['index']
try:
# Get indicator manager and delete the indicator
from components.charts.indicator_manager import get_indicator_manager
manager = get_indicator_manager()
# Load indicator to get its name before deletion
indicator = manager.load_indicator(indicator_id)
indicator_name = indicator.name if indicator else indicator_id
if manager.delete_indicator(indicator_id):
# Refresh the indicator options
overlay_indicators = manager.get_indicators_by_type('overlay')
subplot_indicators = manager.get_indicators_by_type('subplot')
overlay_options = []
for indicator in overlay_indicators:
display_name = f"{indicator.name} ({indicator.type.upper()})"
overlay_options.append({'label': display_name, 'value': indicator.id})
subplot_options = []
for indicator in subplot_indicators:
display_name = f"{indicator.name} ({indicator.type.upper()})"
subplot_options.append({'label': display_name, 'value': indicator.id})
success_msg = html.Div([
html.Span("🗑️ ", style={'color': '#dc3545'}),
html.Span(f"Indicator '{indicator_name}' deleted successfully!", style={'color': '#dc3545'})
])
return success_msg, overlay_options, subplot_options
else:
error_msg = html.Div([
html.Span("", style={'color': '#dc3545'}),
html.Span("Failed to delete indicator.", style={'color': '#dc3545'})
])
return error_msg, dash.no_update, dash.no_update
except Exception as e:
logger.error(f"Error deleting indicator: {e}")
error_msg = html.Div([
html.Span("", style={'color': '#dc3545'}),
html.Span(f"Error: {str(e)}", style={'color': '#dc3545'})
])
return error_msg, dash.no_update, dash.no_update
# Handle edit indicator - open modal with existing data
@app.callback(
[Output('modal-title', 'children'),
Output('indicator-name-input', 'value'),
Output('indicator-type-dropdown', 'value'),
Output('indicator-description-input', 'value'),
Output('indicator-color-input', 'value'),
Output('edit-indicator-store', 'data'),
# Add parameter field outputs
Output('sma-period-input', 'value'),
Output('ema-period-input', 'value'),
Output('rsi-period-input', 'value'),
Output('macd-fast-period-input', 'value'),
Output('macd-slow-period-input', 'value'),
Output('macd-signal-period-input', 'value'),
Output('bb-period-input', 'value'),
Output('bb-stddev-input', 'value')],
[Input({'type': 'edit-indicator-btn', 'index': dash.ALL}, 'n_clicks')],
[State({'type': 'edit-indicator-btn', 'index': dash.ALL}, 'id')],
prevent_initial_call=True
)
def edit_indicator(edit_clicks, button_ids):
"""Load indicator data for editing."""
ctx = dash.callback_context
if not ctx.triggered or not any(edit_clicks):
return dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update
# Find which button was clicked
triggered_id = ctx.triggered[0]['prop_id']
button_info = json.loads(triggered_id.split('.')[0])
indicator_id = button_info['index']
try:
# Load the indicator data
from components.charts.indicator_manager import get_indicator_manager
manager = get_indicator_manager()
indicator = manager.load_indicator(indicator_id)
if indicator:
# Store indicator ID for update
edit_data = {'indicator_id': indicator_id, 'mode': 'edit', 'open_modal': True}
# Extract parameter values based on indicator type
params = indicator.parameters
# Default parameter values
sma_period = 20
ema_period = 12
rsi_period = 14
macd_fast = 12
macd_slow = 26
macd_signal = 9
bb_period = 20
bb_stddev = 2.0
# Update with actual saved values
if indicator.type == 'sma':
sma_period = params.get('period', 20)
elif indicator.type == 'ema':
ema_period = params.get('period', 12)
elif indicator.type == 'rsi':
rsi_period = params.get('period', 14)
elif indicator.type == 'macd':
macd_fast = params.get('fast_period', 12)
macd_slow = params.get('slow_period', 26)
macd_signal = params.get('signal_period', 9)
elif indicator.type == 'bollinger_bands':
bb_period = params.get('period', 20)
bb_stddev = params.get('std_dev', 2.0)
return (
"✏️ Edit Indicator",
indicator.name,
indicator.type,
indicator.description,
indicator.styling.color,
edit_data,
sma_period,
ema_period,
rsi_period,
macd_fast,
macd_slow,
macd_signal,
bb_period,
bb_stddev
)
else:
return dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update
except Exception as e:
logger.error(f"Error loading indicator for edit: {e}")
return dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update
# Reset modal form when closed
@app.callback(
[Output('indicator-name-input', 'value', allow_duplicate=True),
Output('indicator-type-dropdown', 'value', allow_duplicate=True),
Output('indicator-description-input', 'value', allow_duplicate=True),
Output('indicator-color-input', 'value', allow_duplicate=True),
Output('indicator-line-width-slider', 'value'),
Output('modal-title', 'children', allow_duplicate=True),
Output('edit-indicator-store', 'data', allow_duplicate=True),
# Add parameter field resets
Output('sma-period-input', 'value', allow_duplicate=True),
Output('ema-period-input', 'value', allow_duplicate=True),
Output('rsi-period-input', 'value', allow_duplicate=True),
Output('macd-fast-period-input', 'value', allow_duplicate=True),
Output('macd-slow-period-input', 'value', allow_duplicate=True),
Output('macd-signal-period-input', 'value', allow_duplicate=True),
Output('bb-period-input', 'value', allow_duplicate=True),
Output('bb-stddev-input', 'value', allow_duplicate=True)],
[Input('close-modal-btn', 'n_clicks'),
Input('cancel-indicator-btn', 'n_clicks')],
prevent_initial_call=True
)
def reset_modal_form(close_clicks, cancel_clicks):
"""Reset the modal form when it's closed."""
if close_clicks or cancel_clicks:
return "", None, "", "#007bff", 2, "📊 Add New Indicator", None, 20, 12, 14, 12, 26, 9, 20, 2.0
return dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update, dash.no_update
logger.info("Indicator callbacks registered successfully")

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"""
Navigation callbacks for tab switching.
"""
from dash import html, Output, Input
from dashboard.layouts import (
get_market_data_layout,
get_bot_management_layout,
get_performance_layout,
get_system_health_layout
)
def register_navigation_callbacks(app):
"""Register navigation-related callbacks."""
@app.callback(
Output('tab-content', 'children'),
Input('main-tabs', 'value')
)
def render_tab_content(active_tab):
"""Render content based on selected tab."""
if active_tab == 'market-data':
return get_market_data_layout()
elif active_tab == 'bot-management':
return get_bot_management_layout()
elif active_tab == 'performance':
return get_performance_layout()
elif active_tab == 'system-health':
return get_system_health_layout()
else:
return html.Div("Tab not found")

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"""
System health callbacks for the dashboard.
"""
from dash import Output, Input, html
from datetime import datetime
from utils.logger import get_logger
from database.connection import DatabaseManager
from components.charts import create_data_status_indicator, check_data_availability
logger = get_logger("system_health_callbacks")
def register_system_health_callbacks(app):
"""Register system health callbacks."""
@app.callback(
Output('database-status', 'children'),
Input('interval-component', 'n_intervals')
)
def update_database_status(n_intervals):
"""Update database connection status."""
try:
db_manager = DatabaseManager()
# Test database connection
with db_manager.get_session() as session:
# Simple query to test connection
result = session.execute("SELECT 1").fetchone()
if result:
return html.Div([
html.Span("🟢 Connected", style={'color': '#27ae60', 'font-weight': 'bold'}),
html.P(f"Last checked: {datetime.now().strftime('%H:%M:%S')}",
style={'margin': '5px 0', 'color': '#7f8c8d'})
])
else:
return html.Div([
html.Span("🔴 Connection Error", style={'color': '#e74c3c', 'font-weight': 'bold'})
])
except Exception as e:
logger.error(f"Database status check failed: {e}")
return html.Div([
html.Span("🔴 Connection Failed", style={'color': '#e74c3c', 'font-weight': 'bold'}),
html.P(f"Error: {str(e)}", style={'color': '#7f8c8d', 'font-size': '12px'})
])
@app.callback(
Output('collection-status', 'children'),
[Input('symbol-dropdown', 'value'),
Input('timeframe-dropdown', 'value'),
Input('interval-component', 'n_intervals')]
)
def update_data_status(symbol, timeframe, n_intervals):
"""Update data collection status."""
try:
# Check real data availability
status = check_data_availability(symbol, timeframe)
return html.Div([
html.Div(
create_data_status_indicator(symbol, timeframe),
style={'margin': '10px 0'}
),
html.P(f"Checking data for {symbol} {timeframe}",
style={'color': '#7f8c8d', 'margin': '5px 0', 'font-style': 'italic'})
], style={'background-color': '#f8f9fa', 'padding': '15px', 'border-radius': '5px'})
except Exception as e:
logger.error(f"Error updating data status: {e}")
return html.Div([
html.Span("🔴 Status Check Failed", style={'color': '#e74c3c', 'font-weight': 'bold'}),
html.P(f"Error: {str(e)}", style={'color': '#7f8c8d', 'margin': '5px 0'})
])
@app.callback(
Output('redis-status', 'children'),
Input('interval-component', 'n_intervals')
)
def update_redis_status(n_intervals):
"""Update Redis connection status."""
try:
# TODO: Implement Redis status check when Redis is integrated
return html.Div([
html.Span("🟡 Not Configured", style={'color': '#f39c12', 'font-weight': 'bold'}),
html.P("Redis integration pending", style={'color': '#7f8c8d', 'margin': '5px 0'})
])
except Exception as e:
logger.error(f"Redis status check failed: {e}")
return html.Div([
html.Span("🔴 Check Failed", style={'color': '#e74c3c', 'font-weight': 'bold'}),
html.P(f"Error: {str(e)}", style={'color': '#7f8c8d', 'font-size': '12px'})
])
logger.info("System health callbacks registered successfully")

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"""
Reusable UI components for the dashboard.
"""
from .indicator_modal import create_indicator_modal
from .chart_controls import create_chart_config_panel, create_parameter_controls
__all__ = [
'create_indicator_modal',
'create_chart_config_panel',
'create_parameter_controls'
]

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"""
Chart control components for the market data layout.
"""
from dash import html, dcc
from utils.logger import get_logger
logger = get_logger("chart_controls")
def create_chart_config_panel(strategy_options, overlay_options, subplot_options):
"""Create the chart configuration panel with add/edit UI."""
return html.Div([
html.H5("🎯 Chart Configuration", style={'color': '#2c3e50', 'margin-bottom': '15px'}),
# Add New Indicator Button
html.Div([
html.Button(
" Add New Indicator",
id="add-indicator-btn-visible",
className="btn btn-primary",
style={
'background-color': '#007bff',
'color': 'white',
'border': 'none',
'padding': '8px 16px',
'border-radius': '4px',
'cursor': 'pointer',
'margin-bottom': '15px',
'font-weight': 'bold'
}
)
]),
# Strategy Selection
html.Div([
html.Label("Strategy Template:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Dropdown(
id='strategy-dropdown',
options=strategy_options,
value=None,
placeholder="Select a strategy template (optional)",
style={'margin-bottom': '15px'}
)
]),
# Indicator Controls with Edit Buttons
html.Div([
# Overlay Indicators
html.Div([
html.Label("Overlay Indicators:", style={'font-weight': 'bold', 'margin-bottom': '10px', 'display': 'block'}),
html.Div([
# Hidden checklist for callback compatibility
dcc.Checklist(
id='overlay-indicators-checklist',
options=overlay_options,
value=[], # Start with no indicators selected
style={'display': 'none'} # Hide the basic checklist
),
# Custom indicator list with edit buttons
html.Div(id='overlay-indicators-list', children=[
# This will be populated dynamically
])
])
], style={'width': '48%', 'display': 'inline-block', 'margin-right': '4%', 'vertical-align': 'top'}),
# Subplot Indicators
html.Div([
html.Label("Subplot Indicators:", style={'font-weight': 'bold', 'margin-bottom': '10px', 'display': 'block'}),
html.Div([
# Hidden checklist for callback compatibility
dcc.Checklist(
id='subplot-indicators-checklist',
options=subplot_options,
value=[], # Start with no indicators selected
style={'display': 'none'} # Hide the basic checklist
),
# Custom indicator list with edit buttons
html.Div(id='subplot-indicators-list', children=[
# This will be populated dynamically
])
])
], style={'width': '48%', 'display': 'inline-block', 'vertical-align': 'top'})
])
], style={
'border': '1px solid #bdc3c7',
'border-radius': '8px',
'padding': '15px',
'background-color': '#f8f9fa',
'margin-bottom': '20px'
})
def create_parameter_controls():
"""Create the parameter controls section for indicator configuration."""
return html.Div([
html.H5("📊 Indicator Parameters", style={'color': '#2c3e50', 'margin-bottom': '15px'}),
# SMA/EMA Period Controls
html.Div([
html.Label("Moving Average Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Slider(
id='ma-period-slider',
min=5, max=200, step=5, value=20,
marks={i: str(i) for i in [5, 20, 50, 100, 200]},
tooltip={'placement': 'bottom', 'always_visible': True}
)
], style={'margin-bottom': '20px'}),
# RSI Period Control
html.Div([
html.Label("RSI Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Slider(
id='rsi-period-slider',
min=7, max=30, step=1, value=14,
marks={i: str(i) for i in [7, 14, 21, 30]},
tooltip={'placement': 'bottom', 'always_visible': True}
)
], style={'margin-bottom': '20px'}),
# MACD Parameters
html.Div([
html.Label("MACD Parameters:", style={'font-weight': 'bold', 'margin-bottom': '10px'}),
html.Div([
html.Div([
html.Label("Fast:", style={'font-size': '12px'}),
dcc.Input(
id='macd-fast-input',
type='number',
value=12,
min=5, max=50,
style={'width': '60px', 'margin-left': '5px'}
)
], style={'display': 'inline-block', 'margin-right': '15px'}),
html.Div([
html.Label("Slow:", style={'font-size': '12px'}),
dcc.Input(
id='macd-slow-input',
type='number',
value=26,
min=10, max=100,
style={'width': '60px', 'margin-left': '5px'}
)
], style={'display': 'inline-block', 'margin-right': '15px'}),
html.Div([
html.Label("Signal:", style={'font-size': '12px'}),
dcc.Input(
id='macd-signal-input',
type='number',
value=9,
min=3, max=20,
style={'width': '60px', 'margin-left': '5px'}
)
], style={'display': 'inline-block'})
])
], style={'margin-bottom': '20px'}),
# Bollinger Bands Parameters
html.Div([
html.Label("Bollinger Bands:", style={'font-weight': 'bold', 'margin-bottom': '10px'}),
html.Div([
html.Div([
html.Label("Period:", style={'font-size': '12px'}),
dcc.Input(
id='bb-period-input',
type='number',
value=20,
min=5, max=50,
style={'width': '60px', 'margin-left': '5px'}
)
], style={'display': 'inline-block', 'margin-right': '15px'}),
html.Div([
html.Label("Std Dev:", style={'font-size': '12px'}),
dcc.Input(
id='bb-stddev-input',
type='number',
value=2.0,
min=1.0, max=3.0, step=0.1,
style={'width': '70px', 'margin-left': '5px'}
)
], style={'display': 'inline-block'})
])
])
], style={
'border': '1px solid #bdc3c7',
'border-radius': '8px',
'padding': '15px',
'background-color': '#f8f9fa',
'margin-bottom': '20px'
})
def create_auto_update_control():
"""Create the auto-update control section."""
return html.Div([
dcc.Checklist(
id='auto-update-checkbox',
options=[{'label': ' Auto-update charts', 'value': 'auto'}],
value=['auto'],
style={'margin-bottom': '10px'}
),
html.Div(id='update-status', style={'font-size': '12px', 'color': '#7f8c8d'})
])

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"""
Indicator modal component for creating and editing indicators.
"""
from dash import html, dcc
def create_indicator_modal():
"""Create the indicator modal dialog for adding/editing indicators."""
return html.Div([
dcc.Store(id='edit-indicator-store', data=None), # Store for edit mode - explicitly start with None
# Modal Background
html.Div(
id='indicator-modal-background',
style={
'display': 'none',
'position': 'fixed',
'z-index': '1000',
'left': '0',
'top': '0',
'width': '100%',
'height': '100%',
'background-color': 'rgba(0,0,0,0.5)',
'visibility': 'hidden'
}
),
# Modal Content
html.Div([
html.Div([
# Modal Header
html.Div([
html.H4("📊 Add New Indicator", id="modal-title", style={'margin': '0', 'color': '#2c3e50'}),
html.Button(
"",
id="close-modal-btn",
style={
'background': 'none',
'border': 'none',
'font-size': '24px',
'cursor': 'pointer',
'color': '#999',
'float': 'right'
}
)
], style={'display': 'flex', 'justify-content': 'space-between', 'align-items': 'center', 'margin-bottom': '20px', 'border-bottom': '1px solid #eee', 'padding-bottom': '10px'}),
# Modal Body
html.Div([
# Basic Settings
html.Div([
html.H5("Basic Settings", style={'color': '#2c3e50', 'margin-bottom': '15px'}),
# Indicator Name
html.Div([
html.Label("Indicator Name:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='indicator-name-input',
type='text',
placeholder='e.g., "SMA 30 Custom"',
style={'width': '100%', 'padding': '8px', 'margin-bottom': '10px', 'border': '1px solid #ddd', 'border-radius': '4px'}
)
]),
# Indicator Type
html.Div([
html.Label("Indicator Type:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Dropdown(
id='indicator-type-dropdown',
options=[
{'label': 'Simple Moving Average (SMA)', 'value': 'sma'},
{'label': 'Exponential Moving Average (EMA)', 'value': 'ema'},
{'label': 'Relative Strength Index (RSI)', 'value': 'rsi'},
{'label': 'MACD', 'value': 'macd'},
{'label': 'Bollinger Bands', 'value': 'bollinger_bands'}
],
placeholder='Select indicator type',
style={'margin-bottom': '10px'}
)
]),
# Description
html.Div([
html.Label("Description (Optional):", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Textarea(
id='indicator-description-input',
placeholder='Brief description of this indicator configuration...',
style={'width': '100%', 'height': '60px', 'padding': '8px', 'margin-bottom': '15px', 'border': '1px solid #ddd', 'border-radius': '4px', 'resize': 'vertical'}
)
])
], style={'margin-bottom': '20px'}),
# Parameters Section
html.Div([
html.H5("Parameters", style={'color': '#2c3e50', 'margin-bottom': '15px'}),
# Default message
html.Div(
id='indicator-parameters-message',
children=[html.P("Select an indicator type to configure parameters", style={'color': '#7f8c8d', 'font-style': 'italic'})],
style={'display': 'block'}
),
# SMA Parameters (hidden by default)
html.Div([
html.Label("Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='sma-period-input',
type='number',
value=20,
min=1, max=200,
style={'width': '100px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
),
html.P("Number of periods for Simple Moving Average calculation", style={'color': '#7f8c8d', 'font-size': '12px', 'margin-top': '5px'})
], id='sma-parameters', style={'display': 'none', 'margin-bottom': '10px'}),
# EMA Parameters (hidden by default)
html.Div([
html.Label("Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='ema-period-input',
type='number',
value=12,
min=1, max=200,
style={'width': '100px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
),
html.P("Number of periods for Exponential Moving Average calculation", style={'color': '#7f8c8d', 'font-size': '12px', 'margin-top': '5px'})
], id='ema-parameters', style={'display': 'none', 'margin-bottom': '10px'}),
# RSI Parameters (hidden by default)
html.Div([
html.Label("Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='rsi-period-input',
type='number',
value=14,
min=2, max=50,
style={'width': '100px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
),
html.P("Number of periods for RSI calculation (typically 14)", style={'color': '#7f8c8d', 'font-size': '12px', 'margin-top': '5px'})
], id='rsi-parameters', style={'display': 'none', 'margin-bottom': '10px'}),
# MACD Parameters (hidden by default)
html.Div([
html.Div([
html.Label("Fast Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='macd-fast-period-input',
type='number',
value=12,
min=2, max=50,
style={'width': '80px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
)
], style={'margin-bottom': '10px'}),
html.Div([
html.Label("Slow Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='macd-slow-period-input',
type='number',
value=26,
min=5, max=100,
style={'width': '80px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
)
], style={'margin-bottom': '10px'}),
html.Div([
html.Label("Signal Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='macd-signal-period-input',
type='number',
value=9,
min=2, max=30,
style={'width': '80px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
)
]),
html.P("MACD periods: Fast EMA, Slow EMA, and Signal line", style={'color': '#7f8c8d', 'font-size': '12px', 'margin-top': '5px'})
], id='macd-parameters', style={'display': 'none', 'margin-bottom': '10px'}),
# Bollinger Bands Parameters (hidden by default)
html.Div([
html.Div([
html.Label("Period:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='bb-period-input',
type='number',
value=20,
min=5, max=100,
style={'width': '80px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
)
], style={'margin-bottom': '10px'}),
html.Div([
html.Label("Standard Deviation:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='bb-stddev-input',
type='number',
value=2.0,
min=0.5, max=5.0, step=0.1,
style={'width': '80px', 'padding': '8px', 'border': '1px solid #ddd', 'border-radius': '4px'}
)
]),
html.P("Period for middle line (SMA) and standard deviation multiplier", style={'color': '#7f8c8d', 'font-size': '12px', 'margin-top': '5px'})
], id='bb-parameters', style={'display': 'none', 'margin-bottom': '10px'})
], style={'margin-bottom': '20px'}),
# Styling Section
html.Div([
html.H5("Styling", style={'color': '#2c3e50', 'margin-bottom': '15px'}),
html.Div([
# Color Picker
html.Div([
html.Label("Color:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Input(
id='indicator-color-input',
type='text',
value='#007bff',
style={'width': '100px', 'padding': '8px', 'margin-bottom': '10px', 'border': '1px solid #ddd', 'border-radius': '4px'}
)
], style={'width': '48%', 'display': 'inline-block', 'margin-right': '4%'}),
# Line Width
html.Div([
html.Label("Line Width:", style={'font-weight': 'bold', 'margin-bottom': '5px'}),
dcc.Slider(
id='indicator-line-width-slider',
min=1, max=5, step=1, value=2,
marks={i: str(i) for i in range(1, 6)},
tooltip={'placement': 'bottom', 'always_visible': True}
)
], style={'width': '48%', 'display': 'inline-block'})
])
], style={'margin-bottom': '20px'})
]),
# Modal Footer
html.Div([
html.Button(
"Cancel",
id="cancel-indicator-btn",
style={
'background-color': '#6c757d',
'color': 'white',
'border': 'none',
'padding': '10px 20px',
'border-radius': '4px',
'cursor': 'pointer',
'margin-right': '10px'
}
),
html.Button(
"Save Indicator",
id="save-indicator-btn",
style={
'background-color': '#28a745',
'color': 'white',
'border': 'none',
'padding': '10px 20px',
'border-radius': '4px',
'cursor': 'pointer',
'font-weight': 'bold'
}
),
html.Div(id='save-indicator-feedback', style={'margin-top': '10px'})
], style={'text-align': 'right', 'border-top': '1px solid #eee', 'padding-top': '15px'})
], style={
'background-color': 'white',
'margin': '5% auto',
'padding': '30px',
'border-radius': '8px',
'box-shadow': '0 4px 6px rgba(0, 0, 0, 0.1)',
'width': '600px',
'max-width': '90%',
'max-height': '80%',
'overflow-y': 'auto'
})
],
id='indicator-modal',
style={
'display': 'none',
'position': 'fixed',
'z-index': '1001',
'left': '0',
'top': '0',
'width': '100%',
'height': '100%',
'visibility': 'hidden'
})
])

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"""
Layout modules for the dashboard.
"""
from .market_data import get_market_data_layout
from .bot_management import get_bot_management_layout
from .performance import get_performance_layout
from .system_health import get_system_health_layout
__all__ = [
'get_market_data_layout',
'get_bot_management_layout',
'get_performance_layout',
'get_system_health_layout'
]

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"""
Bot management layout for the dashboard.
"""
from dash import html
def get_bot_management_layout():
"""Create the bot management layout."""
return html.Div([
html.H2("🤖 Bot Management", style={'color': '#2c3e50'}),
html.P("Bot management interface will be implemented in Phase 4.0"),
# Placeholder for bot list
html.Div([
html.H3("Active Bots"),
html.Div(id='bot-list', children=[
html.P("No bots currently running", style={'color': '#7f8c8d'})
])
], style={'margin': '20px 0'})
])

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"""
Market data layout for the dashboard.
"""
from dash import html, dcc
from utils.logger import get_logger
from components.charts import get_supported_symbols, get_supported_timeframes
from components.charts.config import get_available_strategy_names
from components.charts.indicator_manager import get_indicator_manager
from components.charts.indicator_defaults import ensure_default_indicators
from dashboard.components.chart_controls import (
create_chart_config_panel,
create_parameter_controls,
create_auto_update_control
)
logger = get_logger("market_data_layout")
def get_market_data_layout():
"""Create the market data visualization layout with indicator controls."""
# Get available symbols and timeframes from database
symbols = get_supported_symbols()
timeframes = get_supported_timeframes()
# Create dropdown options
symbol_options = [{'label': symbol, 'value': symbol} for symbol in symbols]
timeframe_options = [
{'label': '1 Minute', 'value': '1m'},
{'label': '5 Minutes', 'value': '5m'},
{'label': '15 Minutes', 'value': '15m'},
{'label': '1 Hour', 'value': '1h'},
{'label': '4 Hours', 'value': '4h'},
{'label': '1 Day', 'value': '1d'},
]
# Filter timeframe options to only show those available in database
available_timeframes = [tf for tf in ['1m', '5m', '15m', '1h', '4h', '1d'] if tf in timeframes]
if not available_timeframes:
available_timeframes = ['1h'] # Default fallback
timeframe_options = [opt for opt in timeframe_options if opt['value'] in available_timeframes]
# Get available strategies and indicators
try:
strategy_names = get_available_strategy_names()
strategy_options = [{'label': name.replace('_', ' ').title(), 'value': name} for name in strategy_names]
# Get user indicators from the new indicator manager
indicator_manager = get_indicator_manager()
# Ensure default indicators exist
ensure_default_indicators()
# Get indicators by display type
overlay_indicators = indicator_manager.get_indicators_by_type('overlay')
subplot_indicators = indicator_manager.get_indicators_by_type('subplot')
# Create checkbox options for overlay indicators
overlay_options = []
for indicator in overlay_indicators:
display_name = f"{indicator.name} ({indicator.type.upper()})"
overlay_options.append({'label': display_name, 'value': indicator.id})
# Create checkbox options for subplot indicators
subplot_options = []
for indicator in subplot_indicators:
display_name = f"{indicator.name} ({indicator.type.upper()})"
subplot_options.append({'label': display_name, 'value': indicator.id})
except Exception as e:
logger.warning(f"Error loading indicator options: {e}")
strategy_options = [{'label': 'Basic Chart', 'value': 'basic'}]
overlay_options = []
subplot_options = []
# Create components using the new modular functions
chart_config_panel = create_chart_config_panel(strategy_options, overlay_options, subplot_options)
parameter_controls = create_parameter_controls()
auto_update_control = create_auto_update_control()
return html.Div([
# Title and basic controls
html.H3("💹 Market Data Visualization", style={'color': '#2c3e50', 'margin-bottom': '20px'}),
# Main chart controls
html.Div([
html.Div([
html.Label("Symbol:", style={'font-weight': 'bold'}),
dcc.Dropdown(
id='symbol-dropdown',
options=symbol_options,
value=symbols[0] if symbols else 'BTC-USDT',
clearable=False,
style={'margin-bottom': '10px'}
)
], style={'width': '48%', 'display': 'inline-block'}),
html.Div([
html.Label("Timeframe:", style={'font-weight': 'bold'}),
dcc.Dropdown(
id='timeframe-dropdown',
options=timeframe_options,
value='1h',
clearable=False,
style={'margin-bottom': '10px'}
)
], style={'width': '48%', 'float': 'right', 'display': 'inline-block'})
], style={'margin-bottom': '20px'}),
# Chart Configuration Panel
chart_config_panel,
# Parameter Controls Section
parameter_controls,
# Auto-update control
auto_update_control,
# Chart
dcc.Graph(id='price-chart'),
# Market statistics
html.Div(id='market-stats', style={'margin-top': '20px'})
])

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"""
Performance analytics layout for the dashboard.
"""
from dash import html
def get_performance_layout():
"""Create the performance monitoring layout."""
return html.Div([
html.H2("📈 Performance Analytics", style={'color': '#2c3e50'}),
html.P("Performance analytics will be implemented in Phase 6.0"),
# Placeholder for performance metrics
html.Div([
html.H3("Portfolio Performance"),
html.P("Portfolio tracking coming soon", style={'color': '#7f8c8d'})
], style={'margin': '20px 0'})
])

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"""
System health monitoring layout for the dashboard.
"""
from dash import html
def get_system_health_layout():
"""Create the system health monitoring layout."""
return html.Div([
html.H2("⚙️ System Health", style={'color': '#2c3e50'}),
# Database status
html.Div([
html.H3("Database Status"),
html.Div(id='database-status')
], style={'margin': '20px 0'}),
# Data collection status
html.Div([
html.H3("Data Collection Status"),
html.Div(id='collection-status')
], style={'margin': '20px 0'}),
# Redis status
html.Div([
html.H3("Redis Status"),
html.Div(id='redis-status')
], style={'margin': '20px 0'})
])