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Learn Elasticsearch 8 with Python Client from scratch

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A comprehensive and practical guide to master the fundamentals and advanced features of Elasticsearch 8 and Python 3


1. Introduction
  • 1. Introduction
  • 2. Course Structure

  • 2. Setting up development environment
  • 1. Installing Elasticsearch 8 with Kibana

  • 3. Understanding Basic Elasticsearch Concepts
  • 1. Introduction to Elasticsearch
  • 2. Shards and Replicas in Elasticsearch
  • 3. Index, Retrieve and Delete index
  • 4. Query context in DSL
  • 5. Filter context and fuzzy search

  • 4. Advance Elasticsearch Concepts
  • 1. Aggregations in Elasticsearch
  • 2. Custom mappings and settings
  • 3. Dynamic Mappings
  • 4. Built in and Custom analyzers
  • 5. Elasticsearch Basics.html

  • 5. Getting Started with Elasticsearch Python Client
  • 1. Installing anaconda and PyCharm IDE
  • 2. Install elasticsearchpy module

  • 6. CRUD Operations and bulk method
  • 1. Index document into the Elasticsearch
  • 2. Update document into the Elasticsearch
  • 3. Deleting Document
  • 4. Using bulk method to index multiple documents
  • 5. Elasticsearch python client CRUD Operations.html

  • 7. Basic search Queries with Elasticsearch
  • 1. Search operations match all and range query
  • 2. combining searches and pagination and sorting

  • 8. Advanced search
  • 1. exploring elasticsearch dsl
  • 2. fuzzy and full text search
  • 3. Working with dates and geo data
  • 4. Optimizing search performance
  • 5. Search in Elasticsearch.html

  • 9. Working with Elasticsearch inside Docker Container
  • 1. Installing Docker with Elasticsearch and Kibana
  • 2. Connect python project to Elasticsearch 8 in docker container

  • 10. Aggregations, Custom Mappings and Analyzers
  • 1. Indexing multiple documents to understand the concept of aggregations
  • 2. Date histogram aggregations
  • 3. Terms aggregations
  • 4. Range aggregations
  • 5. Metrics aggregations
  • 6. Custom mappings
  • 7. Custom Analyzers
  • 8. Advanced Concepts of Elasticsearch.html

  • 11. Flask Application Apis with Elasticsearch
  • 1. Creating flask app and creating products index by using post api
  • 2. Retrieving product by its id
  • 3. Updating product by its id
  • 4. Delete a product by its id
  • 5. Creating api with custom query

  • 12. Error Handling with Elasticsearch
  • 1. Error handling in Elasticsearch

  • 13. Conclusion
  • 1. Conclusion
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