BrickflowUI
BrickflowUI is a Python-first app framework for building dashboards, portals, copilots, landing pages, and secure internal tools with a real frontend runtime behind the scenes.
It is aimed at teams that want to stay in Python while still shipping application surfaces that feel structured, branded, and product-grade.
At a glance
- Python-first authoring
- dashboards, portals, copilots, and internal tools
- Databricks-friendly deployment
- product-style layouts and workflows
- Lucide icon support across navigation and interactive surfaces
- theming, branding, loading screens, and media support
- documentation and examples built for real teams
Canonical package name: brickflowui
Who it is for
BrickflowUI is a strong fit for:
- data platform teams
- AI application teams
- analytics engineering teams
- internal tools teams
- enterprise engineering groups working on dashboards and portals
- Python teams that want richer UI outcomes without maintaining a separate frontend stack
Who it is not for
BrickflowUI may not be the right fit if:
- you want a pure frontend framework with full hand-authored React ownership
- you only need a quick notebook demo and do not care about product polish
- your team already has a strong dedicated frontend workflow and wants full JS/TS control everywhere
Why it exists
Many Python UI frameworks are great for fast demos, but they start to feel restrictive when teams need:
- stronger layout control
- responsive app shells
- better branding
- auth-aware navigation
- workflow-heavy interfaces
- more serious product presentation
BrickflowUI is built for that next step: keeping teams in Python while giving them room to ship applications that feel closer to real product surfaces.
What you can build
- executive dashboards
- analytics command centers
- data engineering pipeline portals
- Databricks Apps
- secure internal operations tools
- chatbot and copilot workspaces
- landing pages and internal product sites
What makes it different
- Python-first component authoring with
import brickflowui as db - session-scoped reactive state
- multi-page routing and shell patterns
- built-in layouts, forms, overlays, media, tables, charts, workflow components, and chat patterns
- open-source Lucide icon support for navigation, buttons, and shell elements
- light/dark theming, branding tokens, and loading-screen customization
- packaged frontend assets that work in stricter environments like Databricks Apps
- examples and docs aimed at real teams, not just toy demos
Product shape
Install
pip install brickflowui
Optional extras:
pip install "brickflowui[databricks]"
pip install "brickflowui[viz]"
pip install "brickflowui[databricks,viz]"
Import:
import brickflowui as db
First app
import brickflowui as db
app = db.App(title="Hello BrickflowUI")
@app.page("/", title="Home")
def home():
count, set_count = db.use_state(0)
return db.Column(
[
db.Text("Hello BrickflowUI", variant="h1"),
db.Text(f"Count: {count}"),
db.Button("Increment", on_click=lambda: set_count(count + 1)),
],
gap=4,
padding=6,
)
if __name__ == "__main__":
app.run()
Run it:
python app.py
Quick start workflow
Scaffold a new app:
brickflowui new my_app
cd my_app
brickflowui dev
If the CLI entrypoint is not available yet:
python -m brickflowui.cli.main new my_app
Runtime model
BrickflowUI works like this:
- Python page functions produce a
VNodetree. - The server serializes that tree and sends it to the frontend runtime.
- The frontend renders the UI and sends interaction events back.
- Python handlers update state and trigger rerenders.
That gives you a React-style interaction loop while keeping the authoring model in Python.
Component surface
Layout and shell
ColumnRowGridCardHeroSectionHeaderStatusStripDividerSpacerSidebarTopNavBreadcrumbs
Inputs, forms, and overlays
ButtonInputSelectMultiSelectCheckboxToggleSliderDateRangePickerFormModalDrawerPopup
Data, workflow, and chat
TableTimelineSparklineStatStepperKanbanBoardPipelineGraphChatMessageChatInput
Charts and visualization
PlotAreaChartBarChartLineChartDonutChartScatterChartComposedChartGaugeChartRadarChartHeatmapFunnelChartTreeMap
Media and embeds
ImageVideoEmbed
Databricks Apps
Minimum requirements.txt:
brickflowui>=0.1.15
Install from GitHub:
brickflowui @ git+https://github.com/AjayAJ2000/brickflowUI.git@main
Minimum app.yaml:
command:
- python
- app.py
Packaging rule:
The installed package must include:
If those assets are missing, Databricks Apps often stop at the loading shell.
Documentation
Recommended examples
examples/local_playground/app.pyfor framework validationexamples/component_studio/app.pyfor broad component coverageexamples/acme_analytics_command_center/app.pyfor a product-style shellexamples/clinical_trial_command_center/app.pyfor a regulated-industry style dashboardexamples/secure_internal_tools/app.pyfor role-aware internal tools
Vibe coding skills
The repo now includes reusable skill files for AI coding tools that help keep generated BrickflowUI apps aligned with the framework's strengths.
skills/brickflowui-app-starter/SKILL.mdskills/brickflowui-data-ai-portal/SKILL.mdskills/brickflowui-polish-and-qa/SKILL.mdskills/brickflowui-databricks-delivery/SKILL.md
Docs walkthrough:
Local development
Run the core checks:
cd frontend
npm ci
npm test -- --run
npm run lint
npm audit --audit-level=high
npm run build
cd ..
python -m pytest -q -p no:cacheprovider
python -m mkdocs build --strict
python -m build
See the Stability Contract, Release Checklist, and Publishing Guide before cutting a release.
Open source standards
Repository map
brickflowui/
app.py
components.py
server.py
state.py
theme.py
version.py
frontend/dist/
cli/
databricks/
frontend/
src/
vite.config.ts
docs/
learning/
components/
ARCHITECTURE.md
EXAMPLES.md
License
MIT
Metadata
Release files for brickflowui 0.1.15
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| File | Size | Uploaded | Provenance | Actions |
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| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| brickflowui-0.1.15-py3-none-any.whl | Python 3 | none | any | Details for brickflowui-0.1.15-py3-none-any.whl |
Total release size: 11.5 MB
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