nested-dask

ARCHIVE NOTICE: This repository is no longer being maintained. The original purpose of this package was to enable dask with the extended nested-pandas API, with the specific aim of using this to support the LSDB project. In April 2025, the contents of this package were migrated directly into LSDB to allow for tailored behavior to LSDB's specific operational needs. As a result, any needed changes to dask-compatibility for nested-pandas are happening directly within LSDB and not in this repository. Further, maintaining a generalized dask layer for nested-pandas is not directly within the critical path for LINCC-Frameworks effort at this time. If you found your way here and wished there was a maintained package that provided a dask-layer for nested-pandas for something you are working on, please feel free to voice that as an issue filed to nested-pandas.

A dask extension of nested-pandas.

Nested-pandas is a pandas extension package that empowers efficient analysis of nested associated datasets. This package wraps the majority of the nested-pandas API with Dask, which enables easy parallelization and capacity for work at scale.

Dev Guide - Getting Started

Before installing any dependencies or writing code, it's a great idea to create a virtual environment. LINCC-Frameworks engineers primarily use conda to manage virtual environments. If you have conda installed locally, you can run the following to create and activate a new environment.

>> conda create env -n <env_name> python=3.10
>> conda activate <env_name>

Once you have created a new environment, you can install this project for local development using the following commands:

>> pip install -e .'[dev]'
>> pre-commit install
>> conda install pandoc

Notes:

1. The single quotes around '[dev]' may not be required for your operating system.
2. pre-commit install will initialize pre-commit for this local repository, so that a set of tests will be run prior to completing a local commit. For more information, see the Python Project Template documentation on pre-commit
3. Install pandoc allows you to verify that automatic rendering of Jupyter notebooks into documentation for ReadTheDocs works as expected. For more information, see the Python Project Template documentation on Sphinx and Python Notebooks