Skip to content

README.md

Latest commit

 

History

History
149 lines (122 loc) · 5.14 KB

README.md

File metadata and controls

149 lines (122 loc) · 5.14 KB
path /tutorial-couchbase-streamlit-connector
title Couchbase Connector for Streamlit
short_title Couchbase Connector for Streamlit
description
Learn how to integrate streamlit with Couchbase Capella
Example on CRUD and query operations
content_type tutorial
filter sdk
technology
capella
query
tags
Streamlit
sdk_language
python
length 30 Mins

Couchbase Connector for Streamlit

1. Introduction

This project provides a seamless integration between Streamlit and Couchbase, allowing developers to interact with Couchbase databases effortlessly. It enables users to fetch, insert, update, and delete data within Streamlit applications without needing to switch between different SDKs, enhancing the overall development experience.

For a working demo please checkout src/Demo.py file. You can run it by the command

git clone https://github.com/Couchbase-Ecosystem/couchbase_streamlit_connector.git
cd ./couchbase_streamlit_connector
pip install -r requirements.txt
pip install plotly geopy numpy
streamlit run src/Demo.py

Or you can jave a look at it through this link Demo App

2. Prerequisites

System Requirements

  • Ensure you have Python 3.10 or higher (check compatibility with the Couchbase SDK), a Couchbase Capella account (Docs), and an operational cluster created in a project.
  • Configured cluster access permissions and allowed IP addresses (Docs)
  • Connection string obtained from Couchbase Capella

Installing Dependencies

To install the required dependencies, run:

pip install couchbase-streamlit-connector

3. Usage Guide

Initializing the Connector

You can set up the Couchbase connection using either of the following methods:

Option 1: Using secrets.toml (Recommended)

For better security and convenience, store your credentials in a .streamlit/secrets.toml file at the root of your project. Learn more about Streamlit Secrets Management:

[connections.couchbase]
CONNSTR = "<CONNECTION_STRING>"
USERNAME = "<CLUSTER_ACCESS_USERNAME>"
PASSWORD = "<CLUSTER_ACCESS_PASSWORD>"
BUCKET_NAME = "<BUCKET_NAME>"
SCOPE_NAME = "<SCOPE_NAME>"
COLLECTION_NAME = "<COLLECTION_NAME>"

Then, initialize the connection in your Streamlit application:

import streamlit as st
from couchbase_streamlit_connector.connector import CouchbaseConnector

connection = st.connection(
    "couchbase",
    type=CouchbaseConnector
)
st.help(connection)

Option 2: Passing Credentials Directly (Alternative)

Alternatively, you can pass the connection details as keyword arguments:

import streamlit as st
from couchbase_streamlit_connector.connector import CouchbaseConnector

connection = st.connection(
    "couchbase",
    type=CouchbaseConnector,
    CONNSTR="<CONNECTION_STRING>",
    USERNAME="<USERNAME>",
    PASSWORD="<PASSWORD>",
    BUCKET_NAME="<BUCKET_NAME>",
    SCOPE_NAME="<SCOPE_NAME>",
    COLLECTION_NAME="<COLLECTION_NAME>"
)
st.help(connection)

Performing CRUD Operations

Insert a Document

connection.insert_document("222", {"key": "value"})
st.write(connection.get_document("222"))

Fetch a Document

st.write(connection.get_document("111"))

Replace a Document

connection.replace_document("222", {"new_key": "new_value"})
st.write(connection.get_document("222"))

Delete a Document

connection.remove_document("222")
st.write("Document 222 deleted")

Run a Query

result = connection.query("SELECT * FROM `travel-sample`.`inventory`.`airline` LIMIT 5;")
st.write(result)

4. Appendix

Here are some helpful resources for working with Couchbase and Streamlit:

Couchbase Documentation

Streamlit Documentation

Additional Resources