ElasticSearch in Python #24 - Analyzers in depth

Hello everyone! Today, I'll talk about analyzers. You will learn how they are used to analyzing text before indexing documents to an index. How are they used when searching for documents and the component that make an analyzer.

An analyzer basically processes text during indexing and searching. The output of an analyzer are a set of terms (tokens) with their corresponding document.

An analyzer is a combination of 3 components
- Character filter (It is not required, and you can specify more than one character filter)
- Tokenizer (It is required, and you should specify just one tokenizer)
- Token filter (It is not required, and you can specify more than one token filter)

In this series, we focus on using the Python client to interact with Elasticsearch.

Here is the link to the GitHub repository:

Useful links:

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⭐️ Contents ⭐️
(00:00) Intro + slides
(03:19) Code time
(15:01) The end

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