Dashboard Lego Documentation
A modular Python library for building interactive dashboards using Dash and Plotly.
Dashboard Lego allows you to build complex dashboards from independent, reusable “blocks” like building with LEGO bricks. This simplifies development, improves code readability, and promotes component reusability.
Key Features
Modular Architecture: Build dashboards from independent blocks (KPIs, charts, text)
Reactive State Management: Built-in state manager for easy interactivity between blocks
Flexible Grid System: Position blocks in any configuration using Bootstrap grid system
Data Caching: Built-in caching at the data source level for improved performance
Easy Extension: Easily create custom blocks and data sources using composition pattern
Presets & Layouts: Pre-built EDA and ML visualization blocks, plus layout presets
Comprehensive Testing: Full test coverage with unit, integration, and performance tests
Quick Start
Install Dashboard Lego:
pip install dashboard-lego
Create a simple dashboard:
import dash
import dash_bootstrap_components as dbc
import pandas as pd
from dashboard_lego.core import DashboardPage, DataSource, DataBuilder
from dashboard_lego.blocks import get_metric_row
# Define DataBuilder (v0.15+ pattern)
class MyDataBuilder(DataBuilder):
def __init__(self, file_path):
super().__init__()
self.file_path = file_path
def build(self, params):
return pd.read_csv(self.file_path)
# Create datasource using composition
datasource = DataSource(
data_builder=MyDataBuilder("your_data.csv")
)
# Create blocks using v0.15+ API with factory pattern
metrics, row_opts = get_metric_row(
metrics_spec={
"total": {
"column": "id", # Count rows
"agg": "count",
"title": "Total Records",
"color": "primary"
}
},
datasource=datasource,
subscribes_to="dummy_state"
)
# Create dashboard
page = DashboardPage(
title="My Dashboard",
blocks=[
(metrics, row_opts)
]
)
# Run the app
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
app.layout = page.build_layout()
page.register_callbacks(app)
app.run_server(debug=True)
Contents
Getting Started
Comprehensive Guide
API Reference