rhizo 0.1.2

Data, connected. Versioned data with SQL, time travel, and cross-table ACID transactions.

rhizo

Query layer for Rhizo - versioned data with SQL, time travel, and cross-table ACID transactions.

Installation

pip install rhizo

Quick Start

import rhizo
import pandas as pd

# Open or create a database
db = rhizo.open("./mydata")

# Write data
df = pd.DataFrame({"id": [1, 2, 3], "name": ["Alice", "Bob", "Charlie"]})
db.write("users", df)

# SQL queries
result = db.sql("SELECT * FROM users WHERE id > 1")
print(result.to_pandas())

# Time travel to any version
result_v1 = db.sql("SELECT * FROM users", versions={"users": 1})

# Close when done
db.close()

Or use as a context manager:

with rhizo.open("./mydata") as db:
    db.write("users", df)
    result = db.sql("SELECT * FROM users")

Features

• Simple API: rhizo.open() handles all setup automatically
• SQL Queries: DuckDB-powered analytical queries
• Time Travel: Query any historical version
• Cross-Table ACID: Atomic transactions across multiple tables
• Git-like Branching: Zero-copy branches for experimentation
• Change Tracking: Subscribe to data changes

Advanced Usage

For advanced features like branching, transactions, and OLAP queries, access the underlying engine:

db = rhizo.open("./mydata")

# Branching
db.engine.create_branch("experiment")
db.engine.checkout("experiment")

# Transactions
with db.engine.transaction() as tx:
    tx.write_table("users", updated_users)
    tx.write_table("orders", new_orders)
    # Atomic commit

# OLAP queries (DataFusion)
result = db.engine.olap_query("SELECT * FROM users")

Documentation

See rhizodata.dev for full documentation.

License

MIT