Eland: DataFrames and Machine Learning backed by Elasticsearch

Date: Nov 16, 2020 Version: 7.10.0b1

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Eland is a Python Elasticsearch client for exploring and analyzing data in Elasticsearch with a familiar Pandas-compatible API.

Where possible the package uses existing Python APIs and data structures to make it easy to switch between numpy, pandas, scikit-learn to their Elasticsearch powered equivalents. In general, the data resides in Elasticsearch and not in memory, which allows Eland to access large datasets stored in Elasticsearch.

Installing Eland

Eland can be installed from PyPI via pip:

$ python -m pip install eland

Eland can also be installed from Conda Forge with Conda:

$ conda install -c conda-forge eland

Getting Started

If it’s your first time using Eland we recommend looking through the Examples documentation for ideas on what Eland is capable of.

If you’re new to Elasticsearch we recommend reading the documentation.