mlx-data

library0.2.0pypypiunverified

Universal data loaders for Apple MLX framework. Current version 0.2.0, released on 2024-09-20. Development is active with weekly releases.

ai-ml

pip install mlx-data

github ↗package ↗homepage ↗

INSTALL

IMPORT

SIG · MLX-DATA

mlx-data

ai-mlpythonv0.2.0

Install

6.5s avg

Import

—

Disk

132MB

Pass rate

5/ 10

Env Coverage5 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.1.0 · 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 3.10–3.95 runs

build_error

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 6.5s · import 0.000s · 131MB

132MB installed

● package 132MB

Code

Verified usage

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

DataLoader

✓ from mlx.data import DataLoader

✗ from mlx.data import DataLoader

Create a DataLoader from a simple iterable and iterate over batches.

from mlx.data import DataLoader import mlx.core as mx dataloader = DataLoader.from_iterable([1, 2, 3, 4, 5], batch_size=2) for batch in dataloader: print(batch)

Debug

Known issues

breakingDataLoader.batch() method was removed in v0.2.0; use DataLoader.from_iterable with batch_size argument instead.

fix

Replace `dataloader.batch(4)` with `DataLoader.from_iterable(data, batch_size=4)`.

affects: < 0.2.0

deprecatedThe `shuffle` parameter in `DataLoader` is deprecated; use `.shuffle()` method instead.

fix

Remove shuffle from constructor and call `dataloader.shuffle()` before iteration.

affects: 0.1.0 - 0.2.0

Upgrade

Version history

0.2.0latest on PyPI · released Sep 26, 2025

Audit

Dependencies

No dependency data recorded yet.

Agent activity

18 hits · last 30 days

node

Resources

githubhttps://github.com/ml-explore/mlx-data ↗

packagehttps://pypi.org/project/mlx-data/ ↗

homepagehttps://ml-explore.github.io/mlx-data ↗