📄️ Simplifying Index Management
Working with search functionality in Python can be a challenging endeavor, often involving complex tasks such as interacting with an index, clearing index data, and integrating search operations. To streamline these processes, HoppySearch introduces its Python client, designed to simplify these tasks and empower Python developers with efficient tools.
📄️ Adding Data to HoppySearch Index
To make your data searchable with HoppySearch, you need to index it first. Indexing involves adding your data to HoppySearch so that it can be efficiently searched and retrieved. Below, you'll find instructions on how to add data to your HoppySearch index using the HoppySearch Python client.
📄️ Search Operations with HoppySearch
Performing searches within your HoppySearch index is a breeze with the HoppySearch Python client. Whether you're new to search queries or want to dive into advanced searches using Lucene syntax, HoppySearch simplifies the process. This guide covers two types of search operations: Normal Search and Lucene Search.
📄️ Retrieve Index Statistics with HoppySearch Python Client
Obtaining statistics about your index is crucial for understanding its performance and health. The HoppySearch Python client provides a convenient way to access important statistics about your index. Follow the instructions below to retrieve index statistics:
📄️ Delete a Document from Index
Deleting specific documents from your index is a crucial part of maintaining your data. The HoppySearch Python client makes it simple to remove individual documents from your index. Follow the instructions below to delete a document:
📄️ Clear All Data from Index
Clearing or deleting all data from your index is a powerful feature when you want to start fresh or clean up your index entirely. The HoppySearch Python client simplifies this process. Follow the instructions below to clear all data from your index: