https://github.com/scylladb/shopping-cart
Sample ecommerce shopping cart app with ScyllaDB and Python
https://github.com/scylladb/shopping-cart
api cassandra ecommerce fastapi nosql python scylladb
Last synced: 2 months ago
JSON representation
Sample ecommerce shopping cart app with ScyllaDB and Python
- Host: GitHub
- URL: https://github.com/scylladb/shopping-cart
- Owner: scylladb
- License: apache-2.0
- Created: 2024-02-07T12:22:06.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-17T10:52:18.000Z (4 months ago)
- Last Synced: 2025-03-24T05:51:43.016Z (3 months ago)
- Topics: api, cassandra, ecommerce, fastapi, nosql, python, scylladb
- Language: Python
- Homepage: https://shopping-cart.scylladb.com/
- Size: 388 KB
- Stars: 4
- Watchers: 2
- Forks: 4
- Open Issues: 2
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
Awesome Lists containing this project
README
# Ecommerce API - ScyllaDB & FastAPI sample application
This is a sample ecommerce application built with [ScyllaDB](https://www.scylladb.com/) and [FastAPI](https://fastapi.tiangolo.com/).
## Prerequisites
* [CQLSH](https://cassandra.apache.org/doc/stable/cassandra/tools/cqlsh.html)
* Python 3
* [ScyllaDB Cloud account](https://cloud.scylladb.com)
## Get started
Clone the repository:
```
git clone https://github.com/zseta/shopping-cart
cd shopping-cart
```
## Create database schema
Connect to your ScyllaDB Cloud cluster using CQLSH and create the schema:
```
cqlsh -u scylla -p -f schema.cql xxxx.xxxx.xxxx.clusters.scylla.cloud
```
## Set up API server
Create a new virtual environment:
```
virtualenv env
source env/bin/activate
```
Install Python requirements (FastAPI with Uvicorn server and ScyllaDB driver):
```
pip install fastapi "uvicorn[standard]" scylla-driver requests
```
Modify `config.py` to match your database credentials:
```python
HOST="node-0.aws-us-east-1.xxxx.clusters.scylla.cloud"
USER="scylla"
PASSWORD="xxxxxx"
DATACENTER="AWS_US_EAST_1"
KEYSPACE="ecommerce"
```
Run the server:
```
uvicorn main:app --reload
```
Visit API docs: http://127.0.0.1:8000/docs
## Generate sample data
Insert products to the database:
```bash
cqlsh
COPY ecommerce.product (id, img, name, price) FROM 'product.csv' with HEADER = TRUE;
```
Generate user interactions (adding products to cart, checkout):
1. Run the API server:
```
uvicorn main:app
```
1. Run the python script:
```bash
python generate_requests.py
```
```
Shopping started - User(6773b120-8499-4196-9df8-2c4a60b6f1ac)
(1) Added to cart: abe0e6dc-6ad1-4c3e-8127-80c6176ce99a
(2) Added to cart: ee9b125d-c92f-4555-bdb3-35aa260b6f91
(3) Added to cart: 2bf36d87-9b36-4bd3-a44a-8d167e189ce6
(4) Added to cart: 0c38b0c8-a792-4128-bff9-64c527366202
(5) Added to cart: 609ed832-e565-4f46-830b-5fabc120e1d4
Checkout completed (5 items)!
-----
(1) Added to cart: e8ce5e13-0a7e-4e6e-8858-252f5b1cb1db
(2) Added to cart: 3a33f31b-b37c-413e-81a5-1f4b42cedcf6
(3) Added to cart: ffa5f74c-26f2-4342-a6f4-ee2338dd205f
(4) Added to cart: ef281712-2169-49e4-880a-8da503b0b6de
(5) Added to cart: 1e8abb0c-f558-433c-a8c8-e029f12c0d7d
(6) Added to cart: 609ed832-e565-4f46-830b-5fabc120e1d4
Checkout completed (6 items)!
-----
(1) Added to cart: 0015b10c-0842-4796-840a-2e43a6a719d3
(2) Added to cart: abe0e6dc-6ad1-4c3e-8127-80c6176ce99a
(3) Added to cart: 0c38b0c8-a792-4128-bff9-64c527366202
Checkout completed (3 items)!
-----
```
You can run this script from multiple terminals to generate more data.
## Change Data Capture (CDC)
Change Data Capture (CDC) is a ScyllaDB feature that records every change (insert, update, delete) that happens in your table. CDC provides real-time and historical insights into user behavior, product performance, and activity.
Here are some example CDC queries that can provide insights into user behaviour:
**How many times did users add more than 2 of the same product to the cart?**
```sql
SELECT count(*), toTimestamp(min("cdc$time")) AS "from", toTimestamp(max("cdc$time")) AS "to"
FROM ecommerce.cart_items_scylla_cdc_log
WHERE "cdc$operation"= 2 AND product_quantity > 2
ALLOW FILTERING;
```
**How many carts contain a particular product?**
```sql
SELECT count(*), toTimestamp(min("cdc$time")) AS "from", toTimestamp(max("cdc$time")) AS "to"
FROM ecommerce.cart_items_scylla_cdc_log
WHERE product_id = AND "cdc$operation" = 2
ALLOW FILTERING;
```
Notice how in both cases we put `"cdc$operation"= 2` in the where clause. This is because if the operation is `2` that means it was an `INSERT` operation. Learn more about [ScyllaDB CDC](https://opensource.docs.scylladb.com/stable/features/cdc/cdc-intro.html).
Now, running analytical queries on the CDC table requires you to use `ALLOW FILTERING`. This can caouse unpredictable performance at larger scale use cases. In order to query CDC log data in highly scalable way, use our integration with Kafka. Using The [ScyllaDB CDC Kafka source connector](https://github.com/scylladb/scylla-cdc-source-connector), you can easily extract data from ScyllaDB and push it into an external service like ElasticSearch for further analytics.
## Push ScyllaDB CDC data into Kafka
Run the Kafka Connect container:
```
cd kafka
docker compose up -d
```
This will start up several Docker services needed to run Kafka Connect and the Confluent Control Center.
In case you have an existing Kafka Connect service running, install the ScyllaDB source connector:
```
confluent-hub install --no-prompt scylladb/scylla-cdc-source-connector:latest
```
In the Kafka Control Center, use these parameters to create a new ScyllaDB connection:
```
Add a new ScyllaDB connection with these parameters:
- Name: ScyllaDBConnector
- Key converter class, value converter class: `org.apache.kafka.connect.json.JsonConverter`
- Hosts: ScyllaDB_ADDRESS:9042
- Namespace: ScyllaDBConnectorNamespace
- Table names: ecommerce.cart_items
```
For `ScyllaDB_ADDRESS`, use either the Docker container's address or the ScyllaDB Cloud address depending on where you host your ScyllaDB.
Click launch and the connection should be created successfully.