DataFrameLy

2.9.1 verified Mon Apr 27 auth: no python

A declarative, Polars-native data frame validation library for Python 3.10+. Current version 2.9.1, released April 2026. Active development with monthly releases.

pip install dataframely

Common errors

error AttributeError: module 'dataframely' has no attribute 'infer_schema' ↓

cause `infer_schema` was removed from the top-level module's `__all__` in v2.9.1.

fix

Use dy.infer_schema instead of relying on wildcard import. Ensure you have import dataframely as dy.

error PolarsSchemaValidationError: Column 'email' not found in DataFrame ↓

cause `validate` removes columns not in the schema unless `strict=False` is passed.

fix

Add missing columns to schema or pass strict=False to keep extra columns.

error TypeError: unsupported operand type(s) for +: 'Decimal' and 'float' ↓

cause Using float values for Decimal type constraints before v2.7.0.

fix

Upgrade to dataframely >=2.7.0 or use integer values for Decimal constraints.

Warnings

breaking Infer_schema was removed from top-level __all__ in v2.9.1. If you imported `infer_schema` via `from dataframely import *`, it will no longer be available. Use `dy.infer_schema` explicitly. ↓

fix Replace `from dataframely import *` with `import dataframely as dy` and use `dy.infer_schema`.

gotcha `validate` and `filter` remove columns not in the schema by default. If your DataFrame has extra columns, they will be silently dropped. ↓

fix Use `strict=False` parameter to keep extra columns, or define them in the schema.

deprecated The `dy.Decimal` type constraint only accepts integers in some versions (fixed in v2.7.0). If you used float values, upgrade to >=2.7.0. ↓

fix Upgrade to v2.7.0+ or use integer values for Decimal constraints.

Imports

dy
wrong
```
from dataframely import *
```
correct
```
import dataframely as dy
```
Top-level API uses `dy` prefix; wildcard imports pollute namespace and may conflict with `infer_schema` (removed from __all__ in v2.9.1)
Column
wrong
```
from dataframely.column import Column
```
correct
```
from dataframely import Column
```
Column is re-exported at top-level; internal module paths are private and may change
Schema
wrong
```
from dataframely.schema import Schema
```
correct
```
from dataframely import Schema
```
Schema is re-exported at top-level; internal module paths are private and may change

Quickstart

Quickstart: define a schema and validate a Polars DataFrame.

import polars as pl
import dataframely as dy

# Define a schema
schema = dy.Schema({
    "name": dy.String(),
    "age": dy.Int32(),
    "email": dy.String().email(),
})

# Validate a DataFrame
df = pl.DataFrame({
    "name": ["Alice", "Bob"],
    "age": [30, 25],
    "email": ["alice@example.com", "bob@example.com"],
})

result = schema.validate(df)
print(result.valid)  # True
print(result.errors)  # []