Palimpzest (PZ)
📚 Learn How to Use PZ
Our full documentation is the definitive resource for learning how to use PZ. It contains all of the installation and quickstart materials on this page, as well as user guides, full API documentation (coming soon), and much more.
🚀 Getting started
You can find a stable version of the PZ package on PyPI here. To install the package, run:
$ pip install palimpzest
You can also install PZ with uv for a faster installation:
$ uv pip install palimpzest
Alternatively, to install the latest version of the package from this repository, you can clone this repository and run the following commands:
$ git clone git@github.com:mitdbg/palimpzest.git
$ cd palimpzest
$ pip install .
🙋🏽 Join the PZ Community
We are actively hacking on PZ and would love to have you join our community
Our Discord server is the best place to:
- Get help with your PZ program(s)
- Give feedback to the maintainers
- Discuss the future direction(s) of the project
- Discuss anything related to data processing with LLMs!
We are eager to learn more about your workloads and use cases, and will take them into consideration in planning our future roadmap.
📓 Citation
If you would like to cite our original paper on Palimpzest, please use the following citation:
@inproceedings{palimpzestCIDR,
title={Palimpzest: Optimizing AI-Powered Analytics with Declarative Query Processing},
author={Liu, Chunwei and Russo, Matthew and Cafarella, Michael and Cao, Lei and Chen, Peter Baile and Chen, Zui and Franklin, Michael and Kraska, Tim and Madden, Samuel and Shahout, Rana and Vitagliano, Gerardo},
booktitle = {Proceedings of the {{Conference}} on {{Innovative Database Research}} ({{CIDR}})},
date = 2025,
}
If you would like to cite our paper on Palimpzest's optimizer Abacus, please use the following citation:
@misc{russo2025abacuscostbasedoptimizersemantic,
title={Abacus: A Cost-Based Optimizer for Semantic Operator Systems},
author={Matthew Russo and Sivaprasad Sudhir and Gerardo Vitagliano and Chunwei Liu and Tim Kraska and Samuel Madden and Michael Cafarella},
year={2025},
eprint={2505.14661},
archivePrefix={arXiv},
primaryClass={cs.DB},
url={https://arxiv.org/abs/2505.14661},
}
1 maintainer
Metadata
1 maintainer
Release files for palimpzest 1.5.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| palimpzest-1.5.3.tar.gz | 200.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| palimpzest-1.5.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 443.1 kB
Release files / palimpzest-1.5.3.tar.gz
| Download URL | palimpzest-1.5.3.tar.gz |
|---|---|
| Size | 200.6 kB |
| 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 / palimpzest-1.5.3-py3-none-any.whl
| Download URL | palimpzest-1.5.3-py3-none-any.whl |
|---|---|
| Size | 242.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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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 Apr 13, 2026.
Transparency log
