Examples¶
BrickflowUI ships with a few examples that cover different levels of complexity.
Use this page when you want to skip the docs theory and start from something runnable.
Recommended starting points¶
| Example | Path | Best for |
|---|---|---|
| Counter | examples/counter/app.py |
Fastest possible sanity check |
| Auth Portal | examples/auth_portal/app.py |
Login, access control, protected routes |
| Operations + Finance Portal | examples/operations_finance_portal/app.py |
Executive dashboard with a traditional top nav |
| Data Pipeline Command Center | examples/data_pipeline_command_center/app.py |
Industry-style data engineering monitoring with filters, SLA controls, cost, freshness, and Databricks SQL handoff |
| Pipeline Observability 0.1.6 | examples/pipeline_observability_015/app.py |
New 0.1.6 showcase with pipeline graph, chatbot UI, heatmap, treemap, funnel, radar, gauge, kanban, and table export |
| Component Studio | examples/component_studio/app.py |
Interactive all-components app that doubles as documentation |
| Clinical Trial Command Center | examples/clinical_trial_command_center/app.py |
Auth-gated study operations portal with Unity Catalog query patterns and Plotly |
| Secure Internal Tools | examples/secure_internal_tools/app.py |
Role-aware internal tools portal focused on governance and restricted views |
| Chatbot Workspace | examples/chatbot_workspace/app.py |
Assistant-style UI with drawers, toast, timelines, and multi-value inputs |
| Landing Site | examples/landing_site/app.py |
Product-style landing page and launch-site composition |
| Workspace Studio | examples/workspace_studio/app.py |
Rich app structure with filters, tables, tabs, forms, modal flows, charts, and a dedicated themes page |
Data Pipeline Command Center¶
Use this example when your goal is to connect a real Databricks ingestion or transformation pipeline to an operations dashboard.
examples/data_pipeline_command_center/app.pyexamples/data_pipeline_command_center/app.yamlexamples/data_pipeline_command_center/requirements.txt
It demonstrates:
- multiple live controls on one dashboard
- source switching between mock data and Databricks SQL
- top navigation across executive, health, cost, and data model views
- KPI cards for throughput, freshness, cost, and reliability
- charts for SLA trend, incident mix, and cost concentration
- guardrail controls like minimum success-rate threshold and critical-only filtering
- a practical SQL shape for your pipeline metrics table
This is a good starting point for:
- lakehouse ingestion monitoring
- bronze/silver/gold pipeline visibility
- engineering + analytics stakeholder review dashboards
- free-edition Databricks prototypes that later grow into team dashboards
Pipeline Observability 0.1.6¶
Use this example when you want to test the newest visual toolkit and confirm user inputs drive real state changes.
examples/pipeline_observability_015/app.pyexamples/pipeline_observability_015/app.yamlexamples/pipeline_observability_015/requirements.txt
It demonstrates:
PipelineGraphwith node click drilldownsChatMessageandChatInputfor a copilot-style dashboard assistantStatusStrip,Hero, andSectionHeaderfor polished dashboard compositionComposedChart,ScatterChart,GaugeChart,RadarChart,Heatmap,FunnelChart, andTreeMapKanbanBoardfor operational triage- multiple controls driving charts, tables, graph, and chat output
Table(exportable=True)for CSV export
Run it locally:
cd examples/pipeline_observability_015
python app.py
Component Studio¶
Use this example when you want one app that teaches the framework while also stress-testing it.
examples/component_studio/app.pyexamples/component_studio/app.yamlexamples/component_studio/requirements.txt
It demonstrates:
- highly interactive tabs that act as documentation chapters
- local and remote media rendering through
ImageandVideo - custom loading branding
- charts, plotly, pipeline graph, kanban, timeline, and chat surfaces
- toast, popup, modal, and drawer flows in one example
- component-level animation props in realistic usage
Clinical Trial Command Center¶
Use this example when you want a more domain-specific, enterprise-style portal.
examples/clinical_trial_command_center/app.pyexamples/clinical_trial_command_center/app.yamlexamples/clinical_trial_command_center/requirements.txt
It demonstrates:
- auth-gated trial views with role-aware pages
- Unity Catalog and Databricks SQL query patterns with mock fallback
- native Plotly integration via
Plot - safety heatmaps, enrollment trend charts, and pipeline flows
- a page split that feels like a real study operations portal
Local testing note:
Set x-brickflow-user-id and x-brickflow-user-roles headers when testing secured pages.
Secure Internal Tools¶
Use this example when your main priority is governance, access boundaries, and multi-role internal tooling.
examples/secure_internal_tools/app.pyexamples/secure_internal_tools/app.yamlexamples/secure_internal_tools/requirements.txt
It demonstrates:
- per-page role requirements
- governance-aware operational surfaces
- workflow overlays like drawers and popups
- security documentation embedded directly in the UI patterns
Workspace Studio¶
The most complete example right now is:
examples/workspace_studio/app.pyexamples/workspace_studio/app.yamlexamples/workspace_studio/requirements.txt
It demonstrates:
- traditional top navigation instead of a sidebar-only layout
- reusable KPI cards
use_statefor page-level interactivity- filters with
Input,Select,Checkbox,Toggle, andSlider AreaChart,BarChart,LineChart, andDonutChart- multi-section views switched with state
Tabsfor sub-workflows inside a pageTablefor operational and release dataFormposting to a custom@app.route(...)Modalfor secondary flows without leaving the current page- a dedicated
Themessection that shows token mapping and theme-driven UI behavior - inline theming for Databricks-friendly deployment
Chatbot Workspace¶
Use this example when you want to prove BrickflowUI can power assistant-style interfaces as well as dashboards.
examples/chatbot_workspace/app.pyexamples/chatbot_workspace/app.yamlexamples/chatbot_workspace/requirements.txt
It demonstrates:
- conversation layouts built with standard cards and rows
DateRangePickerfor structured prompt scopeMultiSelectfor answer mode selectionToastfor interaction feedbackDrawerfor sources, trace, or tool outputTimelinefor execution trace storytellingAccordionfor prompt guidance and tool context
Landing Site¶
Use this example when you want a product or launch-style page rather than a traditional dashboard.
examples/landing_site/app.pyexamples/landing_site/app.yamlexamples/landing_site/requirements.txt
It demonstrates:
- hero-card composition
- feature grids with elevated surfaces
- FAQ via
Accordion - roadmap storytelling via
Timeline - launch feedback via
Toast - supporting narrative in a
Drawer
Run Workspace Studio locally¶
cd examples/workspace_studio
python app.py
Open:
http://127.0.0.1:8050
Run Workspace Studio in Databricks Apps¶
Put these three files in your Databricks App project:
app.pyrequirements.txtapp.yaml
requirements.txt:
brickflowui>=0.1.6
For the 0.1.6 visualization showcase, use:
brickflowui>=0.1.6
app.yaml:
command:
- python
- app.py
env:
- name: BRICKFLOWUI_ENV
value: production
How to use an example as a template¶
The most effective pattern is:
- Copy the example closest to your real use case.
- Replace the mock data lists with your Databricks SQL or Unity Catalog data.
- Keep the page structure and component composition.
- Move repeated UI patterns into helper functions.
- Add auth and route protection once the page flow is stable.
Which example should I choose?¶
- Choose
counterif you just want to verify installation and runtime. - Choose
auth_portalif your main concern is access control and protected pages. - Choose
operations_finance_portalif you want a polished dashboard-style shell quickly. - Choose
chatbot_workspaceif you want an assistant-style interface with real UI controls around it. - Choose
landing_siteif you want a cleaner marketing or internal product-launch layout. - Choose
workspace_studioif you want the broadest example of how the library fits together. - Choose
data_pipeline_command_centerif your real goal is pipeline observability and operational dashboarding on Databricks. - Choose
pipeline_observability_015if you want the newest chart, pipeline graph, kanban, and chatbot UI primitives. - Choose
component_studioif you want an example that behaves like documentation and showcases nearly every UI surface. - Choose
clinical_trial_command_centerif you want a highly regulated, analytics-heavy portal pattern. - Choose
secure_internal_toolsif you want security, identity governance, and role-aware page design patterns first.