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Basic CRUD Demo

This example demonstrates basic CRUD (Create, Read, Update, Delete) operations with PyTiDB.

  • Use PyTiDB Client to connect to TiDB
  • Create a table with text, vector, and JSON columns
  • Perform basic CRUD operations on data

Prerequisites

How to run

Step 1: Clone the repository to local

git clone https://github.com/pingcap/pytidb.git
cd pytidb/examples/basic/

Step 2: Install the required packages

python -m venv .venv
source .venv/bin/activate
pip install -r reqs.txt

Step 3: Set up environment to connect to database

Go to TiDB Cloud console and get the connection parameters, then set up the environment variable like this:

cat > .env <<EOF
TIDB_HOST={gateway-region}.prod.aws.tidbcloud.com
TIDB_PORT=4000
TIDB_USERNAME={prefix}.root
TIDB_PASSWORD={password}
TIDB_DATABASE=test
EOF

Step 4: Run the demo

python main.py

Expected output:

=== CREATE TABLE ===
Table created

=== TRUNCATE TABLE ===
Table truncated

=== CREATE ===
Created 3 items

=== READ ===
ID: 1, Content: TiDB is a distributed SQL database, Metadata: {'category': 'database'}
ID: 2, Content: GPT-4 is a large language model, Metadata: {'category': 'llm'}
ID: 3, Content: LlamaIndex is a Python library for building AI-powered applications, Metadata: {'category': 'rag'}

=== UPDATE ===
Updated item #1
After update - ID: 1, Content: TiDB Cloud Serverless is a fully-managed, auto-scaling cloud database service, Metadata: {'category': 'dbass'}

=== DELETE ===
Deleted item #2

=== FINAL STATE ===
ID: 1, Content: TiDB Cloud Serverless is a fully-managed, auto-scaling cloud database service, Metadata: {'category': 'dbass'}
ID: 3, Content: LlamaIndex is a Python library for building AI-powered applications, Metadata: {'category': 'rag'}

=== COUNT ROWS ===
Number of rows: 2

=== DROP TABLE ===
Table dropped

Basic CRUD operations completed!
  • Source Code: View on GitHub

  • Category: Getting-Started

  • Description: Learn fundamental PyTiDB operations including database connection, table creation, and data manipulation.

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