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Quick Start

1. Install

pip install pandera-ui

2. Start the UI

Point pandera-ui at your project root:

pandera-ui /path/to/myproject

Open http://localhost:8765 — you'll see a searchable list of all discovered schemas.

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

Better terminal output

Install pandera-ui[rich] for a spinner and formatted table instead of plain text.

3. Browse schemas

  • Sidebar — click any schema to open its detail card.
  • Search bar — filter schemas by name, file, or column.
  • Type filter — show only DataFrameSchema or DataFrameModel.
  • Sort — by name, file path, or column count.
  • Theme toggle — dark / light. EN / RU / FR / DE localization.

4. Export docs (no server)

Generate static docs from the command line:

# Markdown — embed in README or Sphinx
pandera-ui . --export markdown > schemas.md

# Standalone HTML
pandera-ui . --export html > schemas.html

5. Check documentation coverage

See how well your schemas are documented:

pandera-ui . --coverage

Documentation Coverage
======================
Schemas : 4
  title       : 0/4 (0.0%)
  description : 2/4 (50.0%)
Columns : 18
  title       : 0/18 (0.0%)
  description : 9/18 (50.0%)

Use in CI to gate on a minimum coverage threshold:

# fail the build if column description coverage < 80 %
pandera-ui . --json | python -c "
import json, sys
schemas = json.load(sys.stdin)
cols = [c for s in schemas for c in s['columns']]
pct = sum(1 for c in cols if c.get('description')) / len(cols) * 100
print(f'Column coverage: {pct:.1f}%')
sys.exit(0 if pct >= 80 else 1)
"

6. Live reload during development

pip install pandera-ui[watch]
pandera-ui . --watch

The server reloads schemas automatically whenever any .py file changes — no restart needed.

7. 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. See Python API for the full reference.