Skip to content

docs: add dataframely and patito to comparison table #15

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
w-martin merged 3 commits into from
Jun 13, 2026
Merged

docs: add dataframely and patito to comparison table #15

Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
8803d66
docs: add dataframely and patito to feature comparison table
w-martin May 10, 2026
c4699f2
Merge branch 'main' into worktree-agent-a5170214bdd145a76
w-martin May 27, 2026
66ead29
docs: correct patito backend support based on empirical testing
w-martin Jun 6, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
46 changes: 29 additions & 17 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -596,29 +596,29 @@ See [`examples/schema_algebra_example.py`](examples/schema_algebra_example.py) f
Comprehensive comparison of pandas/DataFrame typing and validation tools. **typedframes focuses on static analysis**
—catching errors at lint-time before your code runs.

| Feature | typedframes | Pandera | Great Expectations | strictly_typed_pandas | pandas-stubs | dataenforce | pandas-type-checks | StaticFrame | narwhals |
|---------------------------------|------------------------|-------------|--------------------|-----------------------|--------------|-------------|--------------------|------------------|----------|
| **Version tested** | 0.2.0 | 0.29.0 | 1.4.3 | 0.3.6 | 3.0.0 | 0.1.2 | 1.1.3 | 3.7.0 | 2.16.0 |
| Feature | typedframes | Pandera | Great Expectations | strictly_typed_pandas | pandas-stubs | dataenforce | pandas-type-checks | StaticFrame | narwhals | dataframely | patito |
|---------------------------------|------------------------|-------------|--------------------|-----------------------|--------------|-------------|--------------------|------------------|----------|------------------|------------------|
| **Version tested** | 0.2.0 | 0.29.0 | 1.4.3 | 0.3.6 | 3.0.0 | 0.1.2 | 1.1.3 | 3.7.0 | 2.16.0 | — | — |
| **Analysis Type** |
| When errors are caught | **Static (lint-time)** | Runtime | Runtime | Static + Runtime | Static | Runtime | Runtime | Static + Runtime | Runtime |
| When errors are caught | **Static (lint-time)** | Runtime | Runtime | Static + Runtime | Static | Runtime | Runtime | Static + Runtime | Runtime | Runtime | Runtime |
| **Static Analysis (our focus)** |
| Mypy plugin | ✅ Yes | ⚠️ Limited | ❌ No | ✅ Yes | ✅ Yes | ❌ No | ❌ No | ⚠️ Basic | ❌ No |
| Standalone checker | ✅ Rust (~1ms) | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Column name checking | ✅ Yes | ⚠️ Limited | ❌ No | ✅ Yes | ❌ No | ❌ No | ❌ No | ✅ Yes | ❌ No |
| Column type checking | ✅ Yes | ⚠️ Limited | ❌ No | ✅ Yes | ❌ No | ❌ No | ❌ No | ✅ Yes | ❌ No |
| Typo suggestions | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Mypy plugin | ✅ Yes | ⚠️ Limited | ❌ No | ✅ Yes | ✅ Yes | ❌ No | ❌ No | ⚠️ Basic | ❌ No | ❌ No | ❌ No |
| Standalone checker | ✅ Rust (~1ms) | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Column name checking | ✅ Yes | ⚠️ Limited | ❌ No | ✅ Yes | ❌ No | ❌ No | ❌ No | ✅ Yes | ❌ No | ❌ No | ❌ No |
| Column type checking | ✅ Yes | ⚠️ Limited | ❌ No | ✅ Yes | ❌ No | ❌ No | ❌ No | ✅ Yes | ❌ No | ❌ No | ❌ No |
| Typo suggestions | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| **Runtime Validation** |
| Data validation | ❌ No | ✅ Excellent | ✅ Excellent | ✅ typeguard | ❌ No | ✅ Yes | ✅ Yes | ✅ Yes | ❌ No |
| Value constraints | ❌ No | ✅ Yes | ✅ Excellent | ❌ No | ❌ No | ❌ No | ❌ No | ✅ Yes | ❌ No |
| Data validation | ❌ No | ✅ Excellent | ✅ Excellent | ✅ typeguard | ❌ No | ✅ Yes | ✅ Yes | ✅ Yes | ❌ No | ✅ Yes | ✅ Yes |
| Value constraints | ❌ No | ✅ Yes | ✅ Excellent | ❌ No | ❌ No | ❌ No | ❌ No | ✅ Yes | ❌ No | ✅ Yes | ✅ Yes |
| **Schema Features** |
| Column grouping | ✅ ColumnGroup | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Regex column matching | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Column grouping | ✅ ColumnGroup | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| Regex column matching | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No |
| **Backend Support** |
| Pandas | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ❌ Own | ✅ Yes |
| Polars | ✅ Yes | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ Own | ✅ Yes |
| DuckDB, cuDF, etc. | ❌ No | ❌ No | ✅ Spark, SQL | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ✅ Yes |
| Pandas | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes | ❌ Own | ✅ Yes | ❌ No | ⚠️ Limited |
| Polars | ✅ Yes | ✅ Yes | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ❌ Own | ✅ Yes | ✅ Yes (only) | ✅ Yes |
| DuckDB, cuDF, etc. | ❌ No | ❌ No | ✅ Spark, SQL | ❌ No | ❌ No | ❌ No | ❌ No | ❌ No | ✅ Yes | ❌ No | ❌ No |
| **Project Status (Feb 2026)** |
| Active development | ✅ Yes | ✅ Yes | ✅ Yes | ⚠️ Low | ✅ Yes | ❌ Inactive | ⚠️ Low | ✅ Yes | ✅ Yes |
| Active development | ✅ Yes | ✅ Yes | ✅ Yes | ⚠️ Low | ✅ Yes | ❌ Inactive | ⚠️ Low | ✅ Yes | ✅ Yes | ✅ Yes | ✅ Yes |

**Legend:** ✅ Full support | ⚠️ Limited/Partial | ❌ Not supported

Expand Down Expand Up @@ -653,6 +653,18 @@ Comprehensive comparison of pandas/DataFrame typing and validation tools. **type
validation, data documentation, and data quality monitoring. No static analysis or column-level type checking in
code. Supports pandas, Spark, and SQL backends.

- **[dataframely](https://github.com/Quantco/dataframely)**: Polars-only runtime validation library from Quantco.
Schemas are defined as classes inheriting `dy.Schema` with typed descriptor fields (`dy.String()`, `dy.Float64()`)
and `@dy.rule()` decorators for cross-column and group-level constraints. Returns `dy.DataFrame[Schema]` generic
types that give call-site narrowing to type checkers, but does not validate column subscript access inside function
bodies. No lint-time or static analysis capability. Supports nullability, string constraints, numeric bounds,
cross-column rules, soft validation, test data generation, and SQLAlchemy/PyArrow export.

- **[patito](https://github.com/JakobGM/patito)**: Runtime validation library using a Pydantic-style `patito.Model`
class. Polars is the primary backend; pandas is supported but works by converting to Polars via PyArrow (an
undeclared dependency). DuckDB is not supported despite appearing in some documentation—validation crashes immediately
on DuckDB relations. No static analysis or standalone checker.

### Type Checkers (Not DataFrame-Specific)

These are general Python type checkers. They don't validate DataFrame column names, but they can be used alongside
Expand Down
Loading