Elasticsearch Autocomplete

Description

This project contains a backend to send fake customer data to Elasticsearch using Faker in Python, as well as a frontend in Vue.js to query the data in autocomplete mode via a user interface.

The ElasticSearch server is run via Docker Compose and comes with Kibana to visualize and manage the indexes.

The Kibana instances is available on port 5601 by default.

Requirements

• Docker and Docker Compose
• Python 3.x
• Vue.js (if the frontend is implemented)

Installation

1. Clone the project:

   git clone https://github.com/myaccount/my-elasticsearch-project.git
   cd my-elasticsearch-project
   

2. Set up the virtual environment:

   make venv

3. Start the Elasticsearch service with Docker Compose:

   cd back
   docker-compose up -d

   or

   make run-back

4. Run the Python script to index fake customer data (created with Faker):

   python index_faker_data.py

   or

   make insert-index

5. Run the front (Vue.JS) :

   cd front
   npm run dev

   or

   make run-front