Getting Started with kuzuR

Introduction

Welcome to kuzuR! This guide will walk you through the basic steps to get started with kuzuR, from installation to running your first query.

Installation

First, ensure you have the kuzuR package installed from GitHub. You will also need reticulate to manage the Python environment.

Development Version

remotes::install_github("WickM/kuzuR")

Cran Version

install.packages("kuzuR")

Basic Usage

1. Create a Connection

The first step is to create a connection to a Kuzu database. You can create an in-memory database or connect to a database on disk.

library(kuzuR)

# Create an in-memory database connection
con <- kuzu_connection(":memory:")

2. Create a Schema

Next, define your graph schema using Cypher queries. Let’s create a simple schema with Person nodes and Knows relationships.

kuzu_execute(con, paste("CREATE NODE TABLE Person(name STRING, age INT64,",
                        "PRIMARY KEY (name))"))
kuzu_execute(con, "CREATE REL TABLE Knows(FROM Person TO Person, since INT64)")

3. Load Data

You can load data from R data frames directly into your Kuzu database.

# Create a data frame of persons
persons_df <- data.frame(
  name = c("Alice", "Bob", "Carol"),
  age = c(35, 45, 25)
)

# Create a data frame of relationships
knows_df <- data.frame(
  from_person = c("Alice", "Bob"),
  to_person = c("Bob", "Carol"),
  since = c(2010, 2015)
)

# Load data into Kuzu
kuzu_copy_from_df(con, persons_df, "Person")
kuzu_copy_from_df(con, knows_df, "Knows")

4. Query Data

Finally, you can query your graph using Cypher and retrieve the results as an R data frame.

# Execute a query
result <- kuzu_execute(con, paste("MATCH (a:Person)-[k:Knows]->(b:Person)",
                                  "RETURN a.name, b.name, k.since"))

# Convert the result to a data frame
df <- as.data.frame(result)
print(df)

This concludes the “Getting Started” guide. For more advanced topics, please see the other articles and the function reference.