# duckdb-simple
`duckdb-simple` provides a high-level Haskell interface to DuckDB inspired by
the APIs of [`sqlite-simple`](https://hackage.haskell.org/package/sqlite-simple) and
[`postgresql-simple`](https://hackage.haskell.org/package/postgresql-simple).
It builds on the low-level bindings exposed by [`duckdb-ffi`](../duckdb-ffi) and
provides a focused API for opening connections, running queries, binding
parameters, and decoding typed results—including the full set of DuckDB scalar
types (signed/unsigned integers, decimals, hugeints, intervals, precise and
timezone-aware temporals, blobs, enums, bit strings, and bignums).
## Getting Started
```haskell
{-# LANGUAGE OverloadedStrings #-}
import Database.DuckDB.Simple
import Database.DuckDB.Simple.Types (Only (..))
main :: IO ()
main =
withConnection ":memory:" \conn -> do
_ <- execute_ conn "CREATE TABLE items (id INTEGER, name TEXT)"
_ <- execute conn "INSERT INTO items VALUES (?, ?)" (1 :: Int, "banana" :: String)
rows <- query_ conn "SELECT id, name FROM items ORDER BY id"
mapM_ print (rows :: [(Int, String)])
```
### Key Modules
- `Database.DuckDB.Simple` – connections, prepared statements, execution,
queries, metadata, and error handling.
- `Database.DuckDB.Simple.ToField` / `ToRow` – typeclasses and helpers for
preparing positional or named parameters.
- `Database.DuckDB.Simple.FromField` / `FromRow` – typeclasses for decoding
query results, with generic deriving support for product types.
- `Database.DuckDB.Simple.Generic` – automatic encoding/decoding of Haskell
ADTs as DuckDB STRUCTs and UNIONs via GHC generics and the `ViaDuckDB`
deriving-via helper.
- `Database.DuckDB.Simple.LogicalRep` – structured value types (`StructValue`,
`UnionValue`) for working with DuckDB's composite types.
- `Database.DuckDB.Simple.Types` – shared types (`Query`, `Null`, `Only`,
`(:.)`, `SQLError`).
- `Database.DuckDB.Simple.Function` – register scalar Haskell functions that
can be invoked directly from SQL.
## Querying Data
```haskell
import Database.DuckDB.Simple
import Database.DuckDB.Simple.Types (Only (..))
fetchNames :: Connection -> IO [Maybe String]
fetchNames conn = do
_ <- execute_ conn "CREATE TABLE names (value TEXT)"
_ <- executeMany conn "INSERT INTO names VALUES (?)"
[Only (Just "Alice"), Only (Nothing :: Maybe String)]
fmap fromOnly <$> query_ conn "SELECT value FROM names ORDER BY value IS NULL, value"
```
The execution helpers return the number of affected rows (`Int`) so callers can
assert on data changes when needed.
## Named Parameters
duckdb-simple supports both positional (`?`) and named parameters. Named
parameters are bound with the `(:=)` helper exported from
`Database.DuckDB.Simple.ToField`.
```haskell
import Database.DuckDB.Simple
import Database.DuckDB.Simple.ToField (NamedParam ((:=)))
insertNamed :: Connection -> IO Int
insertNamed conn =
executeNamed conn
"INSERT INTO events VALUES ($kind, $payload)"
["$kind" := ("metric" :: String), "$payload" := ("ok" :: String)]
```
DuckDB does not allow mixing positional and named placeholders within the same
SQL statement; the library preserves DuckDB’s error message in that situation.
DuckDB does not support savepoints. This library does not provide `withSavepoint`.
If the number of supplied parameters does not match the statement’s declared
placeholders—or if you attempt to bind named arguments to a positional-only
statement—`duckdb-simple` raises a `FormatError` before executing the query.
### Decoding rows
`FromRow` is powered by a `RowParser`, which means instances can be written in a
monadic/Applicative style and even derived generically for product types:
```haskell
{-# LANGUAGE DeriveAnyClass #-}
{-# LANGUAGE DeriveGeneric #-}
import Database.DuckDB.Simple
import GHC.Generics (Generic)
data Person = Person
{ personId :: Int
, personName :: Text
}
deriving stock (Show, Generic)
deriving anyclass (FromRow)
fetchPeople :: Connection -> IO [Person]
fetchPeople conn = query_ conn "SELECT id, name FROM person ORDER BY id"
```
Helper combinators such as `field`, `fieldWith`, and `numFieldsRemaining` are
available when a custom instance needs fine-grained control.
## Generic Encoding with ViaDuckDB
The `Database.DuckDB.Simple.Generic` module provides automatic encoding and
decoding of Haskell algebraic data types as DuckDB STRUCTs and UNIONs via
GHC generics.
### Product Types as STRUCTs
Product types (records) are automatically encoded as DuckDB STRUCT values:
```haskell
{-# LANGUAGE DeriveGeneric #-}
{-# LANGUAGE DerivingVia #-}
import Data.Int (Int64)
import Data.Text (Text)
import Database.DuckDB.Simple
import Database.DuckDB.Simple.Generic (ViaDuckDB (..))
import GHC.Generics (Generic)
data User = User
{ userId :: Int64
, userName :: Text
}
deriving stock (Eq, Show, Generic)
deriving (DuckDBColumnType, ToField, FromField) via (ViaDuckDB User)
-- Round-trip through the database
storeAndFetchUser :: Connection -> User -> IO [User]
storeAndFetchUser conn user = do
_ <- execute_ conn "CREATE TABLE users (data STRUCT(userId BIGINT, userName TEXT))"
_ <- execute conn "INSERT INTO users VALUES (?)" (Only user)
fmap fromOnly <$> query_ conn "SELECT data FROM users"
```
### Sum Types as UNIONs
Sum types are encoded as DuckDB UNION values, with each constructor becoming a
union member:
```haskell
data Shape
= Circle Double
| Rectangle Double Double
| Point
deriving stock (Eq, Show, Generic)
deriving (DuckDBColumnType, ToField, FromField) via (ViaDuckDB Shape)
-- Store and retrieve shape data
storeShape :: Connection -> Shape -> IO [Shape]
storeShape conn shape = do
_ <- execute_ conn
"CREATE TABLE shapes (s UNION(Circle STRUCT(field1 DOUBLE), \
\Rectangle STRUCT(field1 DOUBLE, field2 DOUBLE), Point STRUCT()))"
_ <- execute conn "INSERT INTO shapes VALUES (?)" (Only shape)
fmap fromOnly <$> query_ conn "SELECT s FROM shapes"
```
Nullary constructors (like `Point`) are encoded with a null payload.
Non-record constructors use positional field names (`field1`, `field2`, etc.).
### Arrays and Lists
DuckDB arrays (fixed-length) and lists (variable-length) are also supported:
```haskell
import Data.Array (Array, listArray)
storeArray :: Connection -> IO [Array Int Int]
storeArray conn = do
_ <- execute_ conn "CREATE TABLE arrays (vals INTEGER[3])"
let arr = listArray (0, 2) [1, 2, 3]
_ <- execute conn "INSERT INTO arrays VALUES (?)" (Only arr)
fmap fromOnly <$> query_ conn "SELECT vals FROM arrays"
storeList :: Connection -> IO [[Int]]
storeList conn = do
_ <- execute_ conn "CREATE TABLE lists (vals INTEGER[])"
_ <- execute conn "INSERT INTO lists VALUES (?)" (Only [1, 2, 3])
fmap fromOnly <$> query_ conn "SELECT vals FROM lists"
```
### Infinite dates and timestamps
Use `Database.DuckDB.Simple.Time` when a column can contain temporal infinity.
Its `Date`, `LocalTimestamp`, and `UTCTimestamp` types wrap `Day`, `LocalTime`,
and `UTCTime` in `Unbounded`: `NegInfinity`, `Finite value`, or `PosInfinity`.
These types support parameters, results, and fields in generic composites.
`UTCTimestamp` binds as TIMESTAMPTZ.
```haskell
import Database.DuckDB.Simple.Time
infiniteDates :: Connection -> IO [Only Date]
infiniteDates conn = query conn "SELECT ?::DATE" (Only (PosInfinity :: Date))
```
The ordinary `Day`, `LocalTime`, and `UTCTime` instances reject infinity with
a conversion error. Use `Maybe Date` to distinguish SQL NULL from infinity.
Floating-point NaN and infinities remain valid `Float` and `Double` values.
### Manual STRUCT and UNION Handling
Temporal fields retain their SQL units when composite values are rebound.
The `FieldDate`, `FieldTimestamp`, and `FieldTimestampTZ` constructors hold
`Unbounded` values. Wrap finite payloads in `Finite` when constructing them.
For TIMESTAMP_S or TIMESTAMP_MS values outside the TIMESTAMP range, use an
explicit parameter cast, such as `SELECT ?::STRUCT(value TIMESTAMP_S)`.
DuckDB otherwise attempts to convert these parameters to microseconds.
For more control, you can work directly with `StructValue` and `UnionValue`
from `Database.DuckDB.Simple.LogicalRep`:
```haskell
import Database.DuckDB.Simple.LogicalRep (StructValue (..), UnionValue (..))
import Database.DuckDB.Simple.FromField (FieldValue (..))
manualStruct :: Connection -> IO [(StructValue FieldValue, UnionValue FieldValue)]
manualStruct conn = do
_ <- execute_ conn
"CREATE TABLE composite (s STRUCT(a INT, b INT), \
\u UNION(x INT, y VARCHAR))"
[(s, u)] <- query_ conn
"SELECT {'a': 1, 'b': 2}, \
\CAST(union_value(x := 42) AS UNION(x INT, y VARCHAR))"
_ <- execute conn "INSERT INTO composite VALUES (?, ?)" (s, u)
query_ conn "SELECT s, u FROM composite"
```
### Resource Management
- `withConnection` and `withStatement` wrap the open/close lifecycle and guard
against exceptions; use them whenever possible to avoid leaking C handles.
- All intermediate DuckDB objects (results, prepared statements, values) are
released immediately after use. Query helpers return a Haskell list of all
rows. Folds and cursors decode rows incrementally, while DuckDB retains the
materialized native result until it is exhausted, reset, or closed.
- `execute`/`query` variants reset statement bindings each run so prepared
statements can be reused safely.
For concurrent workers, use a separate connection per worker. A connection
can move between threads or be shared when the application serializes access.
Hold that lock for the whole transaction or cursor lifetime, including `close`.
DuckDB serializes native query calls, but this does not protect the Haskell
handle state or prevent another call from interfering with an active cursor.
Statements and connections do not provide their own lock. A callback must not
execute another query on its active connection or close that connection.
Link your executable with `ghc-options: -threaded` to allow prompt cancellation
of native queries, including Ctrl-C. On cancellation, the library interrupts
DuckDB and waits for the native call to return before it releases resources
and propagates the exception. Cancellation is cooperative: native code and
Haskell callbacks must return before cleanup can finish.
Close or reset an abandoned statement to release its result. DuckDB can retain
native result buffers until that result is destroyed.
Use `withStatement` for manual iteration. `fold` releases the result after
success or an exception. The accumulator determines Haskell memory use.
### Metadata helpers
- `columnCount` and `columnName` expose prepared-statement metadata so you can
inspect result shapes before executing a query.
- `execute` returns the number of affected rows. Use SQL `RETURNING` clauses
when you need generated identifiers.
### Cursors and folds
`fold`, `fold_`, and `foldNamed` decode one row at a time from DuckDB's result
chunks. DuckDB 1.5 materializes the native result before the first row is
returned. These functions avoid a complete Haskell row list, but native memory
use still depends on the result size. The native API for starting a streaming
result is deprecated; the default interface uses the supported execution API.
```haskell
import Database.DuckDB.Simple.Types (Only (..))
sumValues :: Connection -> IO Int
sumValues conn =
fold_ conn "SELECT n FROM stream_fold ORDER BY n" 0 $ \acc (Only n) ->
pure (acc + n)
```
For manual cursor-style iteration, use `nextRow`/`nextRowWith` on an open
`Statement` to pull rows one at a time and decide when to stop.
Cursors support the same column types as eager queries, including STRUCT
and UNION values with nested collections and NULLs.
#### Optional native streaming
`Database.DuckDB.Simple.Deprecated.Streaming` provides `fold`, `fold_`,
`foldNamed`, `nextRow`, and `nextRowWith` with native streaming enabled.
Import it qualified:
```haskell
import qualified Database.DuckDB.Simple.Deprecated.Streaming as Streaming
streamSum :: Connection -> IO Int
streamSum conn =
Streaming.fold_ conn "SELECT i FROM range(1000000) t(i)" 0 $ \acc (Only n) ->
pure (acc + n)
```
The import emits a deprecation warning because DuckDB has deprecated the
execution entry point. DuckDB can still materialize some queries. Streaming
does not bound the memory used by query operators.
The first cursor fetch selects the execution mode until an explicit reset.
Switching between default and streaming `nextRow` calls retains that mode.
Keep the connection dedicated to the active stream; another query on that
connection can invalidate it. Cancellation interrupts native chunk fetching
as well as execution.
This module also provides `foldArrow` and `foldArrow_` for streaming Arrow
batches. They use the same supported Arrow conversion and scoped ownership
as `Database.DuckDB.Simple.Arrow`.
### Arrow batches
`Database.DuckDB.Simple.Arrow` provides `foldArrow` and `foldArrow_` for clients
that consume the Arrow C Data Interface. Each callback receives a separate
schema and array batch. It can read them or pass them to an Arrow consumer
that releases or moves them. The fold releases any remaining contents on
success, failure, or cancellation. The consumer owns any contents it moves.
The original pointers are valid only during the callback. To retain contents,
a consumer must move the root structs into its own storage and set the source
release fields to NULL. Moved contents remain valid after the query and
connection close. Empty results do not produce a callback.
For example, the `dataframe-arrow-bridge` package can copy each batch into a
Haskell `DataFrame` and release the Arrow objects:
```haskell
import qualified DataFrame.IO.Arrow as DataFrame
import qualified Database.DuckDB.Simple.Arrow as Arrow
import Foreign.Ptr (castPtr)
frames <- Arrow.foldArrow_ conn "SELECT id::BIGINT, name::VARCHAR FROM people" [] $ \acc schema array -> do
frame <- DataFrame.arrowToDataframe (castPtr schema) (castPtr array)
pure (frame : acc)
-- Reverse frames to recover the query's batch order.
```
The bridge currently imports signed 32-bit and 64-bit integers, Float, Double,
and text columns. It is a test dependency of this repository; applications
that use it must declare their own dependency on `dataframe-arrow-bridge`.
Arrow export uses DuckDB's schema and chunk conversion API. DuckDB materializes
the native result before callbacks start, so its memory use depends on the
result size. The older Arrow query and scan bindings remain available through
`Database.DuckDB.FFI.Deprecated` and emit deprecation warnings.
### Feature Coverage
- Connections, prepared statements, positional/named parameter binding.
- High-level execution (`execute*`) and eager queries (`query*`, `queryNamed`).
- Cursor and fold helpers (`fold`, `foldNamed`, `fold_`, `nextRow`) that decode
native result chunks one row at a time.
- Comprehensive scalar type support: signed/unsigned integers, HUGEINT/UHUGEINT,
decimals (with width/scale), intervals, precise and timezone-aware temporals,
enums, bit strings, blobs, bignums, and UUIDs.
- Composite types: STRUCTs, UNIONs, LISTs, fixed-length ARRAYs, and MAPs with
full encoding/decoding support.
- Generic encoding/decoding: automatic STRUCT/UNION mapping for Haskell ADTs via
GHC generics and the `ViaDuckDB` deriving-via helper.
- Row decoding via `FromField`/`FromRow`, with generic deriving for product types.
- User-defined scalar functions backed by Haskell functions (including IO and
nullable arguments).
- Transaction helpers (`withTransaction`) and metadata accessors (`columnCount`,
`columnName`).
## User-Defined Functions
Scalar Haskell functions can be registered with DuckDB connections and used in
SQL expressions. Argument and result types reuse the existing `FromField` and
`FunctionResult` machinery, so `Maybe` values and `IO` actions work out of the
box.
```haskell
import Data.Int (Int64)
import Database.DuckDB.Simple
import Database.DuckDB.Simple.Function (createFunction, deleteFunction)
import Database.DuckDB.Simple.Types (Only (..))
registerAndUse :: Connection -> IO [Only Int64]
registerAndUse conn = do
createFunction conn "hs_times_two" (\(x :: Int64) -> x * 2)
result <- query_ conn "SELECT hs_times_two(21)" :: IO [Only Int64]
deleteFunction conn "hs_times_two"
pure result
```
Exceptions raised while the function executes are propagated back to DuckDB as
`SQLError` values, and `deleteFunction` issues a `DROP FUNCTION IF EXISTS`
statement to remove the registration. DuckDB registers C API scalar functions
as internal entries; attempting to drop them this way will yield an error, which
the library surfaces as an `SQLError`.
## Tests
The test suite is built with [tasty](https://hackage.haskell.org/package/tasty)
and covers connection management, statement lifecycle, parameter binding, and
query execution.
```
cabal test duckdb-simple-test --test-show-details=direct
```