kt-search

Multi platform kotlin client for Elasticsearch & Opensearch with easily extendable Kotlin DSLs for queries, mappings, bulk, and more.

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Project maintained by jillesvangurp Hosted on GitHub Pages — Theme by mattgraham

Jupyter Notebooks

KT Search Manual	Previous: Using Kotlin Scripting	Next: Migrating from the old Es Kotlin Client
Github	© Jilles van Gurp

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Using kt-search from jupyter and the kotlin kernel is easy! See the jupyter-example directory in the kt-search project.

Install conda

On a mac, use home brew of course.

brew install miniconda

Install jupyter with conda

Once you have conda installed, install jupyter and the kotlin kernel.

conda create -n kjupyter
conda activate kjupyter 
conda install jupyter
conda install -c jetbrains kotlin-jupyter-kernel

Open the notebook

Now you are ready to open the notebook!

cd jupyter-example
jupyter notebook kt-search-example.ipynb

Importing kt-search

Create a cell in your notebook with something like this:

@file:Repository("https://jitpack.io")
@file:DependsOn("com.github.jillesvangurp.kt-search:search-client:1.99.14")

import com.jillesvangurp.ktsearch.*
import kotlinx.coroutines.runBlocking

val client = SearchClient(
    KtorRestClient(
        host = "localhost",
        port = 9200
    )
)

runBlocking {
    val engineInfo = client.engineInfo()
    println(engineInfo.variantInfo.variant.name + ":" + engineInfo.version.number)
}

Note, you need to use runBlocking to use suspending calls on the client.

Otherwise, see the documentation for how to use the kotlin scripting support.

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KT Search Manual	Previous: Using Kotlin Scripting	Next: Migrating from the old Es Kotlin Client
Github	© Jilles van Gurp