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README

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Metaxy

PyPI version Python versions PyPI downloads CI codecov Ruff Ty prek

Metaxy is a metadata layer for multimodal Data and ML pipelines. Metaxy tracks lineage and versioning across complex computational graphs for multimodal datasets. Metaxy can cache every single sample and scale to handle millions of them.

Metaxy manages metadata while data typically lives elsewhere:

┌─────────────────────────────────┐          ┌─────────────────────────┐
│      Metadata (Metaxy)          │          │   Data (e.g., S3)       │
├──────┬──────────┬──────┬────────┤          │                         │
│  ID  │   path   │ size │version │          │  📦 s3://my-bucket/     │
├──────┼──────────┼──────┼────────┤          │                         │
│ img1 │ s3://... │ 2.1M │a3fdsf  │ ────────>│    ├─ img1.jpg          │
│ img2 │ s3://... │ 1.8M │b7e123  │ ────────>│    ├─ img2.jpg          │
└──────┴──────────┴──────┴────────┘          └─────────────────────────┘

The feature that makes Metaxy stand out is the ability to track partial data dependencies and detect prunable updates — updates that don't trigger change propagation through certain paths in the dependency graph because they modify fields that aren't dependencies of those downstream features. For example, updating audio upstream of a face recognition step allows pruning the face recognition branch since it only depends on video frames. This problem is specific to multimodal pipelines and doesn't typically emerge in traditional data engineering.

Metaxy's goal is to provide a standard instrument for any kind of multimodal (or purely tabular) incremental pipelines, standardizing dependency specification, versioning, partial data dependencies, and manipulations over metadata. Or, in short, to be a universal glue for incremental data pipelines.

Metaxy is very reliable and is fanatically tested across all supported Python versions and platforms [^1].

Documentation

Read the docs to learn more.

Installation

Install Metaxy from PyPI:

uv add metaxy

Using Metaxy

Metaxy is highly pluggable and generally can be used with any kind of incremental pipelines, storage, metadata storage, and dataframe libraries.

Metaxy provides integrations with popular tools such as Dagster, Ray, ClickHouse, DeltaLake, SQLModel.

The full list can be found here.

Blog Posts

Contributing

See CONTRIBUTING.md.

[^1]: The CLI is not tested on Windows yet.

Core symbols most depended-on inside this repo

open
called by 488
src/metaxy/metadata_store/base.py
write
called by 386
src/metaxy/ext/ray/datasink.py
spec
called by 378
src/metaxy/models/feature.py
get
called by 348
src/metaxy/cli/context.py
use
called by 327
src/metaxy/models/feature.py
to_string
called by 303
src/metaxy/models/types.py
read
called by 276
src/metaxy/metadata_store/base.py
to_polars
called by 272
src/metaxy/versioning/types.py

Shape

Method 1,897
Function 1,598
Class 1,184
Route 27

Languages

Python100%
TypeScript1%

Modules by API surface

tests/ext/dagster/test_metaxify.py174 symbols
tests/models/test_feature_graph.py107 symbols
tests/metadata_stores/shared/resolve_update.py87 symbols
tests/models/types/test_types.py85 symbols
tests/graph/test_graph_diff_unit.py84 symbols
tests/ext/sqlmodel/test_native.py83 symbols
tests/cli/test_cli_metadata.py83 symbols
tests/test_config.py82 symbols
tests/metadata_stores/core/test_load_feature_definitions.py70 symbols
tests/test_entrypoints.py62 symbols
tests/provenance/test_lineage_relationships.py62 symbols
tests/ext/postgres/test_native.py60 symbols

Datastores touched

dbDatabase · 1 repos
(mysql)Database · 1 repos
dbDatabase · 1 repos
metaxyDatabase · 1 repos
postgresDatabase · 1 repos
test_dbDatabase · 1 repos

For agents

$ claude mcp add metaxy \
  -- python -m otcore.mcp_server <graph>

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