Integrate Elasticsearch for Enhanced Search Functionality on Startups and Projects - Part 1
Objective: This pull request is part one of a task aimed at integrating Elasticsearch into the project to enhance the search capabilities for the Startup and Project models. By leveraging Elasticsearch, the application can support efficient, fast, and complex search queries, including keyword search, filtering, and sorting functionalities.
Tasks Completed:
Setup and Installation
Installed Elasticsearch and configured a local instance.
Installed django-elasticsearch-dsl and django-elasticsearch-dsl-drf libraries to bridge Django with Elasticsearch.
Define Elasticsearch Settings
Added necessary settings to settings.py for connecting Django to the local Elasticsearch instance.
Create Elasticsearch Documents
Defined Elasticsearch document mappings for Startup and Project models. This includes creating documents.py in the respective apps:
Mapped fields for StartupDocument (e.g., company_name, funding_stage, location).
Mapped fields for ProjectDocument (e.g., title, status, required_amount).
Data Synchronization
Ran a management command to index existing data, allowing current database entries to be searchable in Elasticsearch.
Added Django signals to keep Elasticsearch indexes synchronized with database changes (create, update, delete) on Startup and Project records.
Build DRF Views for Search
Implemented search views leveraging django-elasticsearch-dsl-drf, allowing users to perform searches on both Startup and Project models.
Configured complex filtering and sorting capabilities in these views.
Create Document Serializers
Added serializers for StartupDocument and ProjectDocument to convert Elasticsearch data to JSON format, making it consumable by API clients.
URL Routing for Search Endpoints
Set up URL patterns for the search endpoints. Now, users can access:
startups/search/ to search for startups.
projects/search/ to search for projects.
Summary of Improvements: This integration lays the groundwork for faster and more versatile search capabilities in the application. By indexing data in Elasticsearch and providing endpoints for searching, the application can now handle complex search requirements more efficiently.
Integrate Elasticsearch for Enhanced Search Functionality on Startups and Projects - Part 1
Objective: This pull request is part one of a task aimed at integrating Elasticsearch into the project to enhance the search capabilities for the Startup and Project models. By leveraging Elasticsearch, the application can support efficient, fast, and complex search queries, including keyword search, filtering, and sorting functionalities.
Tasks Completed:
Setup and Installation
Installed Elasticsearch and configured a local instance. Installed django-elasticsearch-dsl and django-elasticsearch-dsl-drf libraries to bridge Django with Elasticsearch. Define Elasticsearch Settings
Added necessary settings to settings.py for connecting Django to the local Elasticsearch instance. Create Elasticsearch Documents
Defined Elasticsearch document mappings for Startup and Project models. This includes creating documents.py in the respective apps: Mapped fields for StartupDocument (e.g., company_name, funding_stage, location). Mapped fields for ProjectDocument (e.g., title, status, required_amount). Data Synchronization
Ran a management command to index existing data, allowing current database entries to be searchable in Elasticsearch. Added Django signals to keep Elasticsearch indexes synchronized with database changes (create, update, delete) on Startup and Project records. Build DRF Views for Search
Implemented search views leveraging django-elasticsearch-dsl-drf, allowing users to perform searches on both Startup and Project models. Configured complex filtering and sorting capabilities in these views. Create Document Serializers
Added serializers for StartupDocument and ProjectDocument to convert Elasticsearch data to JSON format, making it consumable by API clients. URL Routing for Search Endpoints
Set up URL patterns for the search endpoints. Now, users can access: startups/search/ to search for startups. projects/search/ to search for projects. Summary of Improvements: This integration lays the groundwork for faster and more versatile search capabilities in the application. By indexing data in Elasticsearch and providing endpoints for searching, the application can now handle complex search requirements more efficiently.
