Getting Started¶

Three paths, from a 5-minute first query to a natural-language MCP session. Everything installs from PyPI — no git checkouts, no C compiler.

0. Start CUBRID (all paths)¶

docker compose up -d        # CUBRID 11.2 on localhost:33000, database testdb

Readiness takes up to a minute on first start:

docker exec cubrid-cookbook bash -lc "csql -u dba testdb -c 'SELECT 1;'"

1. Five-minute first query (pycubrid)¶

pip install pycubrid
python fundamentals/pycubrid/01_connect.py

The expected output is checked by CI on CUBRID 11.2 and 11.4 — compare against fundamentals/pycubrid/expected/01_connect.expected. From here, fundamentals/ walks through CRUD, transactions, parameterized queries, collections, LOBs, and window functions — every directory with an expected/ folder is verified by make verify.

2. ORM and application templates (sqlalchemy-cubrid)¶

pip install sqlalchemy-cubrid   # pulls SQLAlchemy 2.x
python fundamentals/sqlalchemy/01_connect_and_session.py

Production-shaped starters live in templates/ — a FastAPI service, Flask app, Django app, Streamlit dashboard, Celery async worker, and a pandas batch ETL. The dashboard is a one-command demo:

cd templates/dashboard
docker compose up -d           # CUBRID 11.4 + Streamlit at http://localhost:8501

3. Natural language over the database (cubrid-mcp-server)¶

uvx cubrid-mcp-server          # stdio MCP server; requires CUBRID_* env vars

Claude Desktop / Claude Code / Cursor config blocks are in the cubrid-mcp-server README. Once connected, ask:

"What tables are in this database?" → all_table_names
"Show the structure of cookbook_sales" → describe_table
"Top 5 products by revenue" → execute_query (read-only)
"Drop the orders table" → rejected by the read-only whitelist (this refusal is the feature)

Verify a full checkout¶

pip install pycubrid sqlalchemy sqlalchemy-cubrid
make verify                   # runs every golden-backed example against your local CUBRID

Where to go next¶

Goal	Start at
Copy-and-customize starters	`templates/`
JDBC-to-Python migration	`migration/java-to-python/`
Performance patterns	`performance/`
Known CUBRID quirks	`pitfalls/`, `KNOWN_ISSUES.md`
Supported versions	`SUPPORT_MATRIX.md`