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Data Sources

querychat supports several different data sources, including:

  1. Data frames
  2. DBI database connections (e.g., SQLite, PostgreSQL, MySQL, DuckDB)
  3. Custom DataSource interfaces

The sections below describe how to use each type of data source with querychat.

Data frames

You can use any data frame as a data source in querychat. Simply pass it to querychat():

library(querychat)
library(palmerpenguins)

qc <- querychat(mtcars)
qc$app()  # Launch the app

Behind the scenes, querychat creates an in-memory DuckDB database and registers your data frame as a table for SQL query execution.

Database connections

You can also connect querychat directly to a table in any database supported by DBI. This includes popular databases like SQLite, DuckDB, PostgreSQL, MySQL, and many more.

Assuming you have a database set up and accessible, you can create a DBI connection and pass it to querychat(). Below are some examples for common databases.

DuckDB

library(DBI)
library(duckdb)
library(querychat)

# Connect to a DuckDB database file
con <- dbConnect(duckdb::duckdb(), dbdir = "my_database.duckdb")

qc <- querychat(con, "my_table")
qc$app()  # Launch the app

# Don't forget to disconnect when done
# dbDisconnect(con)

SQLite

library(DBI)
library(RSQLite)
library(querychat)

# Connect to a SQLite database file
con <- dbConnect(RSQLite::SQLite(), "my_database.db")

qc <- querychat(con, "my_table")
qc$app()  # Launch the app

# Don't forget to disconnect when done
# dbDisconnect(con)

PostgreSQL

library(DBI)
library(RPostgres)
library(querychat)

# Connect to PostgreSQL
con <- dbConnect(
  RPostgres::Postgres(),
  host = "localhost",
  port = 5432,
  dbname = "mydatabase",
  user = "myuser",
  password = "mypassword"
)

qc <- querychat(con, "my_table")
qc$app()  # Launch the app

# Don't forget to disconnect when done
# dbDisconnect(con)

MySQL

library(DBI)
library(RMariaDB)
library(querychat)

# Connect to MySQL
con <- dbConnect(
  RMariaDB::MariaDB(),
  host = "localhost",
  port = 3306,
  dbname = "mydatabase",
  user = "myuser",
  password = "mypassword"
)

qc <- querychat(con, "my_table")
qc$app()  # Launch the app

# Don't forget to disconnect when done
# dbDisconnect(con)

Creating a database from a data frame

If you don’t have a database set up, you can easily create a local DuckDB database from a data frame:

library(DBI)
library(duckdb)

con <- dbConnect(duckdb::duckdb(), dbdir = "my_database.duckdb")

# Write a data frame to the database
dbWriteTable(con, "penguins", penguins)

# Or from CSV
duckdb::duckdb_read_csv(con, "my_table", "path/to/your/file.csv")

Then you can connect to this database using the DuckDB example above.

Custom sources

If you have a custom data source that doesn’t fit into the above categories, you can implement the DataSource interface. See the DataSource reference for more details on implementing this interface.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.