elasticsearch/docs/reference/quickstart/index.asciidoc

[[quickstart]]
= Quick starts

Use these quick starts to get hands-on experience with the {es} APIs.
Unless otherwise noted, these examples will use queries written in <<query-dsl,Query DSL>> syntax.

[discrete]
[[quickstart-requirements]]
== Requirements

You'll need a running {es} cluster, together with {kib} to use the Dev Tools API Console.
Run the following command in your terminal to set up a <<run-elasticsearch-locally,single-node local cluster in Docker>>:

[source,sh]
----
curl -fsSL https://elastic.co/start-local | sh
----
// NOTCONSOLE

Alternatively, refer to our <<elasticsearch-intro-deploy,other deployment options>>.

[discrete]
[[quickstart-list]]
== Hands-on quick starts

* <<getting-started,Basics: Index and search data using {es} APIs>>. Learn about indices, documents, and mappings, and perform a basic search using the Query DSL.
* <<full-text-filter-tutorial, Basics: Full-text search and filtering>>. Learn about different options for querying data, including full-text search and filtering, using the Query DSL.
* <<esql-getting-started, {esql} basics>>: Learn how to query and aggregate your data using {esql}.
* <<esql-for-search, {esql} for search>>: Learn how to use {esql} for search use cases, including full-text search, semantic search, and hybrid search.
* <<aggregations-tutorial, Basics: Analyze ecommerce data with aggregations>>. Learn how to analyze data using different types of aggregations, including metrics, buckets, and pipelines.
* <<semantic-search-semantic-text, Semantic search>>: Learn how to create embeddings for your data with `semantic_text` and query using the `semantic` query.
** <<semantic-text-hybrid-search, Hybrid search with `semantic_text`>>: Learn how to combine semantic search with full-text search.
* <<bring-your-own-vectors, Bring your own dense vector embeddings>>: Learn how to ingest dense vector embeddings into {es}.

.Working in Python
******************

If you're interested in using {es} with Python, check out Elastic Search Labs:

* https://github.com/elastic/elasticsearch-labs[`elasticsearch-labs` repository]: Contains a range of Python https://github.com/elastic/elasticsearch-labs/tree/main/notebooks[notebooks] and https://github.com/elastic/elasticsearch-labs/tree/main/example-apps[example apps].
* https://www.elastic.co/search-labs/tutorials/search-tutorial/welcome[Tutorial]: This walks you through building a complete search solution with {es} from the ground up using Flask.
******************

include::getting-started.asciidoc[]
include::full-text-filtering-tutorial.asciidoc[]
include::esql-search-tutorial.asciidoc[]
include::aggs-tutorial.asciidoc[]