temporaldata is a Python package for easily working with temporal data. It provides advanced data structures and methods to work with multi-modal, multi-resolution time series data.
Installation
temporaldata is available for Python 3.10+ and has minimal dependencies (only numpy, pandas, and h5py).
To install the package, run the following command:
pip install temporaldata
Contributing
If you are planning to contribute to the package, you can install the package in development mode by running the following command:
pip install -e ".[dev]"
Install pre-commit hooks:
pre-commit install
Unit tests are located under test/. Run the entire test suite with
pytest
or test individual files via, e.g., pytest test/test_data.py
Run type-checking with
ty check
Cite
Please cite our paper if you use this code in your own work:
@inproceedings{
azabou2023unified,
title={A Unified, Scalable Framework for Neural Population Decoding},
author={Mehdi Azabou and Vinam Arora and Venkataramana Ganesh and Ximeng Mao and Santosh Nachimuthu and Michael Mendelson and Blake Richards and Matthew Perich and Guillaume Lajoie and Eva L. Dyer},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
}
Metadata
Release files for temporaldata 0.1.6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| temporaldata-0.1.6.tar.gz | 2.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| temporaldata-0.1.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.7 MB
Release files / temporaldata-0.1.6.tar.gz
| Download URL | temporaldata-0.1.6.tar.gz |
|---|---|
| Size | 2.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Yes |
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twine/6.1.0 CPython/3.13.12
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Transparency logRelease files / temporaldata-0.1.6-py3-none-any.whl
| Download URL | temporaldata-0.1.6-py3-none-any.whl |
|---|---|
| Size | 44.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
2dc2ff603a8e744576406dd29af2a91f420113e7db4282f8593bfebe9abffb8c
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on May 29, 2026.
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