Skip to main content

Common loaders for MIR datasets.

Project description


common loaders for Music Information Retrieval (MIR) datasets. Find the API documentation here.

CircleCI codecov Documentation Status GitHub

This library provides tools for working with common MIR datasets, including tools for:

  • downloading datasets to a common location and format
  • validating that the files for a dataset are all present
  • loading annotation files to a common format, consistent with the format required by mir_eval
  • parsing track level metadata for detailed evaluations


To install, simply run:

pip install mirdata

Quick example

import mirdata

orchset = mirdata.initialize('orchset')  # download the dataset
orchset.validate()  # validate that all the expected files are there

example_track = orchset.choice_track()  # choose a random example track
print(example_track)  # see the available data

See the documentation for more examples and the API reference.

Currently supported datasets

Supported datasets include AcousticBrainz, DALI, Guitarset, MAESTRO, TinySOL, among many others.

For the complete list of supported datasets, see the documentation


There are two ways of citing mirdata:

If you are using the library for your work, please cite the version you used as indexed at Zenodo:


If you refer to mirdata's design principles, motivation etc., please cite the following paper:


"mirdata: Software for Reproducible Usage of Datasets"
Rachel M. Bittner, Magdalena Fuentes, David Rubinstein, Andreas Jansson, Keunwoo Choi, and Thor Kell
in International Society for Music Information Retrieval (ISMIR) Conference, 2019
  title={mirdata: Software for Reproducible Usage of Datasets},
  author={Bittner, Rachel M and Fuentes, Magdalena and Rubinstein, David and Jansson, Andreas and Choi, Keunwoo and Kell, Thor},
  booktitle={International Society for Music Information Retrieval (ISMIR) Conference},

When working with datasets, please cite the version of mirdata that you are using (given by the DOI above) AND include the reference of the dataset, which can be found in the respective dataset loader using the cite() method.

Contributing a new dataset loader

We welcome contributions to this library, especially new datasets. Please see contributing for guidelines.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for mirdata, version 0.3.3
Filename, size File type Python version Upload date Hashes
Filename, size mirdata-0.3.3-py3-none-any.whl (7.1 MB) File type Wheel Python version py3 Upload date Hashes View
Filename, size mirdata-0.3.3.tar.gz (7.0 MB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page