woodwork

library0.31.0pypypiunverified

Woodwork is a data typing library for machine learning, extending pandas DataFrames and Series with semantic and logical typing capabilities. It enables automatic data typing inference, validation, and schema management for robust data pipelines. Currently at version 0.31.0, it is actively maintained by Alteryx with frequent updates.

data ai-ml

pip install woodwork

github ↗package ↗homepage ↗docs ↗changelog ↗

INSTALL

IMPORT

SIG · WOODWORK

woodwork

datapythonv0.31.0

Install

13.6s avg

Import

3395ms

Disk

357MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.31.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

build_error

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 13.6s · import 2.037s · 345MB

357MB installed

● package 357MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

woodwork

✓ import woodwork

✗ import woodwork as ww

This quickstart demonstrates how to initialize Woodwork on a pandas DataFrame, allowing it to automatically infer logical types for your columns. It then prints the inferred schema, logical types, and the specific logical type for the 'email' column.

import pandas as pd import woodwork as ww data = { "id": [1, 2, 3], "name": ["Alice", "Bob", "Charlie"], "age": [25, 30, 35], "email": ["alice@example.com", "bob@example.com", "charlie@example.com"] } df = pd.DataFrame(data) # Initialize Woodwork on the DataFrame to infer types and create a schema df.ww.init() print(df.ww.schema) print(df.ww.logical_types) print(df.ww['email'].ww.logical_type)

Debug

Known issues

breakingThe global `woodwork.init()` function was removed and replaced by the DataFrame accessor method `df.ww.init()`.

fix

Replace `from woodwork.api import init; init(df)` with `import woodwork as ww; df.ww.init()`.

affects: >=0.17.0

breakingThe default value for `infer_box_type_on_init` parameter in `df.ww.init()` changed from `True` to `False`.

fix

If you relied on `woodwork` automatically 'boxing' Series or DataFrames into Woodwork structures upon creation, you may now need to explicitly call `df.ww.init()` or set `infer_box_type_on_init=True` during initialization.

affects: >=0.24.0

breakingSupport for Python 3.8 was dropped.

fix

Upgrade your Python environment to 3.9 or higher. (e.g., Python 3.9, 3.10, 3.11, etc.)

affects: >=0.29.0

deprecatedThe `WoodworkColumnAccessor.set_logical_type()` method was deprecated.

fix

Use `df.ww.set_types(column_logical_types={'column_name': 'NewLogicalType'})` or `df.ww.set_types(logical_types={'column_name': 'NewLogicalType'})` instead.

affects: >=0.28.0

Upgrade

Version history

0.31.0latest on PyPI · released May 14, 2024

Audit

Dependencies

pandasrequiredCore data structure for Woodwork's functionality.

numpyrequiredUnderlying array operations for data handling.

scipyrequiredUsed for some statistical operations and type inference.

Agent activity

39 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/alteryx/woodwork ↗

packagehttps://pypi.org/project/woodwork/ ↗

homepagehttps://woodwork.alteryx.com ↗

docshttps://woodwork.alteryx.com ↗

changeloghttps://woodwork.alteryx.com/en/latest/release_notes.html ↗