pandera-ui
Swagger for your Pandera schemas.
One command — instant searchable documentation for every dataframe schema in your project.
Documentation · Live Demo · PyPI · Changelog
The problem
You have 30 Pandera schemas spread across a data project. New team members ask: "Which columns does OrdersSchema have? Is amount nullable? What checks run on user_id?"
The answer is buried in code. There's no docs page, no searchable index — just grep and hope.
The solution
pip install pandera-ui
pandera-ui /path/to/myproject
pandera-ui scans your project, discovers every DataFrameSchema and DataFrameModel, and opens a Swagger-like UI at http://localhost:8765.
Features
| Feature | Description | |
|---|---|---|
| ⚡ | Zero config | Point at a directory, get a UI. No decorators, no config files. |
| 🔍 | Two-pass extraction | Runtime import for accuracy + AST fallback when imports fail (missing deps, DB connections, etc.) |
| 👁 | Live reload | --watch reloads schemas automatically when .py files change |
| 📄 | Export | --export markdown / --export html — static docs for README or Sphinx |
| 📊 | Coverage | --coverage shows what % of schemas and columns are documented |
| 🔧 | CI-friendly | --json exports structured metadata; /api/coverage for quality gates |
| 🎨 | Rich CLI | Progress spinner and summary table when rich is installed |
| 🌍 | Team-ready | Dark/light theme, EN/RU/FR/DE localization, full-text search |
Quick start
# Install
pip install pandera-ui
# Scan current directory and open the UI
pandera-ui .
# Scan a specific project on a custom port
pandera-ui /path/to/myproject --port 9000
Terminal output (with pandera-ui[rich]):
Found 4 schema(s).
Schema Type File Columns
orders DataFrameSchema dataframe_schemas.py 5
products DataFrameSchema dataframe_schemas.py 4
users DataFrameModel schema_models.py 4
events DataFrameModel schema_models.py 5
UI ready at http://127.0.0.1:8765
Open http://localhost:8765 in the browser — searchable sidebar, column table with dtypes and checks, AST/runtime badge, dark/light theme.
Installation
pip install pandera-ui # core
pip install pandera-ui[rich] # + spinner and summary table
pip install pandera-ui[watch] # + --watch live-reload
pip install pandera-ui[rich,watch] # everything
With uv:
uv add pandera-ui
uv add pandera-ui[rich,watch]
Requires Python 3.10+.
Docker
docker run --rm \
-v /path/to/myproject:/project:ro \
-p 8765:8765 \
ghcr.io/darius-krsk/pandera-ui:latest
All CLI options
# Export schema docs (no server started)
pandera-ui . --export markdown > schemas.md
pandera-ui . --export html > schemas.html
# Check documentation coverage
pandera-ui . --coverage
# Live reload on .py changes
pip install pandera-ui[watch]
pandera-ui . --watch
# Export raw JSON for CI / tooling
pandera-ui . --json > schemas.json
Full CLI reference:
Usage: pandera-ui [OPTIONS] [PROJECT_PATH]
Arguments:
[PROJECT_PATH] Project root to scan [default: .]
Options:
-p, --port INTEGER Port for the UI server [default: 8765]
--host TEXT Host to bind [default: 127.0.0.1]
--json Print JSON to stdout, no server
--export [markdown|html] Export docs to stdout, no server
--coverage Print coverage stats and exit
-w, --watch Auto-reload schemas on .py changes
--help Show this message and exit.
What gets extracted
| Schema style | Example | Support |
|---|---|---|
pa.DataFrameSchema(...) |
orders = pa.DataFrameSchema(...) |
Full |
pa.DataFrameModel subclass |
class Orders(pa.DataFrameModel) |
Full |
| File with import errors | imports a missing library | AST fallback |
Per column: name, dtype, nullable, required, checks (with parameters), title, description.
Per schema: name, coerce, title, description, index, source file, variable/class name.
Python API
from pandera_ui import scan_project
schemas = scan_project("./myproject")
for schema in schemas:
print(schema.name, [c.name for c in schema.columns])
scan_project returns a list of SchemaMetadata Pydantic models — serialize with .model_dump().
# Compute coverage programmatically
from pandera_ui._coverage import compute_coverage, format_coverage
report = compute_coverage(schemas)
print(format_coverage(report))
# Export to Markdown
from pandera_ui._export import to_markdown
print(to_markdown(schemas))
Architecture
pandera_ui/
scanner.py # discovery: walks project, dispatches per file
_extract_runtime.py # pass 1: dynamic import + introspection
_extract_ast.py # pass 2: static AST parse (fallback)
models.py # Pydantic models: SchemaMetadata, ColumnMetadata …
server.py # FastAPI: GET /api/schemas, GET /api/coverage, GET /
cli.py # Typer CLI entry point
_export.py # Markdown and HTML renderers
_coverage.py # Documentation coverage calculator
_console.py # optional rich output (spinner, summary table)
frontend/
index.html # single-page UI (vanilla JS, no build step)
Development
git clone https://github.com/Darius1223/pandera-ui
cd pandera-ui
uv sync
make lint # ruff check
make type # mypy
make test # unit tests
make test-cov # unit tests + coverage report
make run # start UI against test fixtures
See CONTRIBUTING.md for PR guidelines.
Changelog
See CHANGELOG.md.
License
MIT © 2025 Ildar
Metadata
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