transactor.scala

// Copyright (c) 2013-2020 Rob Norris and Contributors
// This software is licensed under the MIT License (MIT).
// For more information see LICENSE or https://opensource.org/licenses/MIT

package doobie.util

import doobie.free.connection.{ConnectionIO, ConnectionOp, commit, rollback, setAutoCommit, unit}
import doobie.free.KleisliInterpreter
import doobie.util.lens._
import doobie.util.yolo.Yolo
import cats.{Applicative, Defer, Monad, ~>}
import cats.data.Kleisli
import cats.effect.{Async, Blocker, Bracket, ContextShift, ExitCase, Resource, Sync}
import cats.instances.long._
import cats.syntax.show._

import fs2.Stream
import java.sql.{Connection, DriverManager}

import javax.sql.DataSource
import java.util.concurrent.{Executors, ThreadFactory}

import scala.concurrent.ExecutionContext

object transactor  {

  import doobie.free.connection.AsyncConnectionIO

  /** @group Type Aliases */
  type Interpreter[M[_]] = ConnectionOp ~> Kleisli[M, Connection, *]

  /**
   * Data type representing the common setup, error-handling, and cleanup strategy associated with
   * an SQL transaction. A `Transactor` uses a `Strategy` to wrap programs prior to execution.
   * @param before a program to prepare the connection for use
   * @param after  a program to run on success
   * @param oops   a program to run on failure (catch)
   * @param always a program to run in all cases (finally)
   * @group Data Types
   */
  final case class Strategy(
    before: ConnectionIO[Unit],
    after:  ConnectionIO[Unit],
    oops:   ConnectionIO[Unit],
    always: ConnectionIO[Unit]
  ) {
    val resource: Resource[ConnectionIO, Unit] = for {
      _ <- Resource.make(doobie.FC.unit)(_ => always)
      _ <- Resource.makeCase(before) { case (_, exitCase) =>
        exitCase match {
          case ExitCase.Completed => after
          case ExitCase.Error(_) | ExitCase.Canceled => oops
        }
      }
    } yield ()
  }

  object Strategy {

    /** @group Lenses */ val before: Strategy @> ConnectionIO[Unit] = Lens(_.before, (a, b) => a.copy(before = b))
    /** @group Lenses */ val after:  Strategy @> ConnectionIO[Unit] = Lens(_.after,  (a, b) => a.copy(after  = b))
    /** @group Lenses */ val oops:   Strategy @> ConnectionIO[Unit] = Lens(_.oops,   (a, b) => a.copy(oops   = b))
    /** @group Lenses */ val always: Strategy @> ConnectionIO[Unit] = Lens(_.always, (a, b) => a.copy(always = b))

    /**
     * A default `Strategy` with the following properties:
     * - Auto-commit will be set to `false`;
     * - the transaction will `commit` on success and `rollback` on failure;
     * @group Constructors
     */
    val default = Strategy(setAutoCommit(false), commit, rollback, unit)

    /**
     * A no-op `Strategy`. All actions simply return `()`.
     * @group Constructors
     */
    val void = Strategy(unit, unit, unit, unit)

  }

  /**
   * A thin wrapper around a source of database connections, an interpreter, and a strategy for
   * running programs, parameterized over a target monad `M` and an arbitrary wrapped value `A`.
   * Given a stream or program in `ConnectionIO` or a program in `Kleisli`, a `Transactor` can
   * discharge the doobie machinery and yield an effectful stream or program in `M`.
   * @tparam M a target effect type; typically `IO`
   * @group Data Types
   */
  sealed abstract class Transactor[M[_]] { self =>
    /** An arbitrary value that will be handed back to `connect` **/
    type A

    /** An arbitrary value, meaningful to the instance **/
    def kernel: A

    /** A program in `M` that can provide a database connection, given the kernel **/
    def connect: A => Resource[M, Connection]

    /** A natural transformation for interpreting `ConnectionIO` **/
    def interpret: Interpreter[M]

    /** A `Strategy` for running a program on a connection **/
    def strategy: Strategy

    /** Construct a [[Yolo]] for REPL experimentation. */
    def yolo(implicit ev1: Sync[M]): Yolo[M] = new Yolo(this)

    /**
     * Construct a program to perform arbitrary configuration on the kernel value (changing the
     * timeout on a connection pool, for example). This can be the basis for constructing a
     * configuration language for a specific kernel type `A`, whose operations can be added to
     * compatible `Transactor`s via implicit conversion.
     * @group Configuration
     */
    def configure[B](f: A => M[B]): M[B] =
      f(kernel)

    /**
     * Natural transformation equivalent to `exec` that does not use the provided `Strategy` and
     * instead directly binds the `Connection` provided by `connect`. This can be useful in cases
     * where transactional handling is unsupported or undesired.
     * @group Natural Transformations
     */
    def rawExec(implicit ev: Bracket[M, Throwable]): Kleisli[M, Connection, *] ~> M =
      λ[Kleisli[M, Connection, *] ~> M](k => connect(kernel).use(k.run))

    /**
      * Natural transformation that provides a connection and binds through a `Kleisli` program
      * using the given `Strategy`, yielding an independent program in `M`.
      * @group Natural Transformations
      */
    def exec(implicit ev: Bracket[M, Throwable], D: Defer[M]): Kleisli[M, Connection, *] ~> M =
      λ[Kleisli[M, Connection, *] ~> M] { ka =>
        connect(kernel).use { conn =>
          strategy.resource.mapK(run(conn)).use { _ =>
            ka.run(conn)
          }
        }
      }

    /**
     * Natural transformation equivalent to `trans` that does not use the provided `Strategy` and
     * instead directly binds the `Connection` provided by `connect`. This can be useful in cases
     * where transactional handling is unsupported or undesired.
     * @group Natural Transformations
     */
    def rawTrans(implicit ev: Bracket[M, Throwable]): ConnectionIO ~> M =
      λ[ConnectionIO ~> M] { f =>
        connect(kernel).use { conn =>
          f.foldMap(interpret).run(conn)
        }
      }

    /**
     * Natural transformation that provides a connection and binds through a `ConnectionIO` program
     * interpreted via the given interpreter, using the given `Strategy`, yielding an independent
     * program in `M`. This is the most common way to run a doobie program.
     * @group Natural Transformations
     */
    def trans(implicit ev: Bracket[M, Throwable]): ConnectionIO ~> M =
      λ[ConnectionIO ~> M] { f =>
        connect(kernel).use { conn =>
          strategy.resource.use(_ => f).foldMap(interpret).run(conn)
        }
      }

    def rawTransP[T](implicit ev: Monad[M]): Stream[ConnectionIO, *] ~> Stream[M, *] =
      λ[Stream[ConnectionIO, *] ~> Stream[M, *]] { s =>
        Stream.resource(connect(kernel)).flatMap { conn =>
          s.translate(run(conn))
        }.scope
      }

    def transP(implicit ev: Monad[M]): Stream[ConnectionIO, *] ~> Stream[M, *] =
      λ[Stream[ConnectionIO, *] ~> Stream[M, *]] { s =>
        Stream.resource(connect(kernel)).flatMap { c =>
          Stream.resource(strategy.resource).flatMap(_ => s).translate(run(c))
        }.scope
      }

    def rawTransPK[I](implicit ev: Monad[M]): Stream[Kleisli[ConnectionIO, I, *], *] ~> Stream[Kleisli[M, I, *], *] =
      λ[Stream[Kleisli[ConnectionIO, I, *], *] ~> Stream[Kleisli[M, I, *], *]] { s =>
        Stream.resource(connect(kernel)).translate(Kleisli.liftK[M, I]).flatMap { c =>
          s.translate(runKleisli[I](c))
        }.scope
      }

    def transPK[I](implicit ev: Monad[M]): Stream[Kleisli[ConnectionIO, I, *], *] ~> Stream[Kleisli[M, I, *], *] =
      λ[Stream[Kleisli[ConnectionIO, I, *], *] ~> Stream[Kleisli[M, I, *], *]] { s =>
        Stream.resource(connect(kernel)).translate(Kleisli.liftK[M, I]).flatMap { c =>
          Stream.resource(strategy.resource.mapK(Kleisli.liftK[ConnectionIO, I])).flatMap(_ => s)
            .translate(runKleisli[I](c))
        }.scope
      }

    private def run(c: Connection)(implicit ev: Monad[M]): ConnectionIO ~> M =
      λ[ConnectionIO ~> M] { f =>
        f.foldMap(interpret).run(c)
      }

    private def runKleisli[B](c: Connection)(implicit ev: Monad[M]): Kleisli[ConnectionIO, B, *] ~> Kleisli[M, B, *] =
      λ[Kleisli[ConnectionIO, B, *] ~> Kleisli[M, B, *]] { f =>
        Kleisli(f.run(_).foldMap(interpret).run(c))
      }

    @SuppressWarnings(Array("org.wartremover.warts.DefaultArguments"))
    def copy(
      kernel0: A = self.kernel,
      connect0: A => Resource[M, Connection] = self.connect,
      interpret0: Interpreter[M] = self.interpret,
      strategy0: Strategy = self.strategy
    ): Transactor.Aux[M, A] = new Transactor[M] {
      type A = self.A
      val kernel = kernel0
      val connect = connect0
      val interpret = interpret0
      val strategy = strategy0
    }

    /*
     * Convert the effect type of this transactor from M to M0
     */
    def mapK[M0[_]](fk: M ~> M0)(implicit D: Defer[M0], A: Applicative[M0]): Transactor.Aux[M0, A] =
      Transactor[M0, A](
        kernel,
        connect.andThen(_.mapK(fk)),
        interpret.andThen(λ[Kleisli[M, Connection, *] ~> Kleisli[M0, Connection, *]](_.mapK(fk))),
        strategy
      )
  }

  object Transactor {

    def apply[M[_], A0](
      kernel0: A0,
      connect0: A0 => Resource[M, Connection],
      interpret0: Interpreter[M],
      strategy0: Strategy
    ): Transactor.Aux[M, A0] = new Transactor[M] {
      type A = A0
      val kernel = kernel0
      val connect = connect0
      val interpret = interpret0
      val strategy = strategy0
    }

    type Aux[M[_], A0] = Transactor[M] { type A = A0  }

    /** @group Lenses */ def kernel   [M[_], A]: Transactor.Aux[M, A] Lens A                              = Lens(_.kernel,    (a, b) => a.copy(kernel0    = b))
    /** @group Lenses */ def connect  [M[_], A]: Transactor.Aux[M, A] Lens (A => Resource[M, Connection]) = Lens(_.connect,   (a, b) => a.copy(connect0   = b))
    /** @group Lenses */ def interpret[M[_]]: Transactor[M] Lens Interpreter[M]       = Lens(_.interpret, (a, b) => a.copy(interpret0 = b))
    /** @group Lenses */ def strategy [M[_]]: Transactor[M] Lens Strategy             = Lens(_.strategy,  (a, b) => a.copy(strategy0  = b))
    /** @group Lenses */ def before   [M[_]]: Transactor[M] Lens ConnectionIO[Unit]   = strategy[M] >=> Strategy.before
    /** @group Lenses */ def after    [M[_]]: Transactor[M] Lens ConnectionIO[Unit]   = strategy[M] >=> Strategy.after
    /** @group Lenses */ def oops     [M[_]]: Transactor[M] Lens ConnectionIO[Unit]   = strategy[M] >=> Strategy.oops
    /** @group Lenses */ def always   [M[_]]: Transactor[M] Lens ConnectionIO[Unit]   = strategy[M] >=> Strategy.always

    /**
     * Construct a constructor of `Transactor[M, D]` for some `D <: DataSource` by partial
     * application of `M`, which cannot be inferred in general. This follows the pattern described
     * [here](http://tpolecat.github.io/2015/07/30/infer.html).
     * @group Constructors
     */
     object fromDataSource {
       def apply[M[_]] = new FromDataSourceUnapplied[M]

      /**
       * Constructor of `Transactor[M, D]` fixed for `M`; see the `apply` method for details.
       * @group Constructors (Partially Applied)
       */
      class FromDataSourceUnapplied[M[_]] {
        def apply[A <: DataSource](
          dataSource: A,
          connectEC:  ExecutionContext,
          blocker: Blocker
        )(implicit ev: Async[M],
                   cs: ContextShift[M]
        ): Transactor.Aux[M, A] = {
          val connect = (dataSource: A) => {
            val acquire = cs.evalOn(connectEC)(ev.delay(dataSource.getConnection))
            def release(c: Connection) = blocker.blockOn(ev.delay(c.close()))
            Resource.make(acquire)(release)
          }
          val interp  = KleisliInterpreter[M](blocker).ConnectionInterpreter
          Transactor(dataSource, connect, interp, Strategy.default)
        }
      }

    }

    /**
     * Construct a `Transactor` that wraps an existing `Connection`. Closing the connection is the
     * responsibility of the caller.
     * @param connection a raw JDBC `Connection` to wrap
     * @param blocker for blocking database operations
     * @group Constructors
     */
    def fromConnection[M[_]: Async: ContextShift](
      connection: Connection,
      blocker: Blocker
    ): Transactor.Aux[M, Connection] = {
      val connect = (c: Connection) => Resource.pure[M, Connection](c)
      val interp  = KleisliInterpreter[M](blocker).ConnectionInterpreter
      Transactor(connection, connect, interp, Strategy.default)
    }

    /**
     * Module of constructors for `Transactor` that use the JDBC `DriverManager` to allocate
     * connections. Note that `DriverManager` is unbounded and will happily allocate new connections
     * until server resources are exhausted. It is usually preferable to use `DataSourceTransactor`
     * with an underlying bounded connection pool (as with `H2Transactor` and `HikariTransactor` for
     * instance). Blocking operations on `DriverManagerTransactor` are executed on an unbounded
     * cached daemon thread pool by default, so you are also at risk of exhausting system threads.
     * TL;DR this is fine for console apps but don't use it for a web application.
     * @group Constructors
     */
    @SuppressWarnings(Array("org.wartremover.warts.Overloading"))
    object fromDriverManager {

      // An unbounded cached pool of daemon threads.
      private lazy val defaultBlocker: Blocker = Blocker.liftExecutionContext {
        ExecutionContext.fromExecutor(Executors.newCachedThreadPool(
          new ThreadFactory {
            def newThread(r: Runnable): Thread = {
              val th = new Thread(r)
              th.setName(show"doobie-fromDriverManager-pool-${th.getId}")
              th.setDaemon(true)
              th
            }
          }
        ))
      }

      @SuppressWarnings(Array("org.wartremover.warts.NonUnitStatements"))
      private def create[M[_]](
        driver: String,
        conn: () => Connection,
        strategy: Strategy,
        blocker: Blocker
      )(implicit am: Async[M], cs: ContextShift[M]): Transactor.Aux[M, Unit] =
        Transactor(
          (),
          _ => {
            val acquire = blocker.blockOn(am.delay { Class.forName(driver); conn() })
            def release(c: Connection) = blocker.blockOn(am.delay { c.close() })
            Resource.make(acquire)(release)
          },
          KleisliInterpreter[M](blocker).ConnectionInterpreter,
          strategy
        )

      def apply[M[_]: Async: ContextShift](
        driver: String,
        url:    String,
        blocker: Blocker
      ): Transactor.Aux[M, Unit] =
        create(driver, () => DriverManager.getConnection(url), Strategy.default, blocker)

      /**
       * Construct a new `Transactor` that uses the JDBC `DriverManager` to allocate connections.
       * @param driver     the class name of the JDBC driver, like "org.h2.Driver"
       * @param url        a connection URL, specific to your driver
       */
      def apply[M[_]: Async: ContextShift](
        driver: String,
        url:    String
      ): Transactor.Aux[M, Unit] =
        apply(driver, url, defaultBlocker)

      def apply[M[_]: Async: ContextShift](
        driver: String,
        url:    String,
        user:   String,
        pass:   String,
        blocker: Blocker
      ): Transactor.Aux[M, Unit] =
        create(driver, () => DriverManager.getConnection(url, user, pass), Strategy.default, blocker)

      /**
       * Construct a new `Transactor` that uses the JDBC `DriverManager` to allocate connections.
       * @param driver     the class name of the JDBC driver, like "org.h2.Driver"
       * @param url        a connection URL, specific to your driver
       * @param user       database username
       * @param pass       database password
       */
      def apply[M[_]: Async: ContextShift](
        driver: String,
        url:    String,
        user:   String,
        pass:   String
      ): Transactor.Aux[M, Unit] =
        apply(driver, url, user, pass, defaultBlocker)

      /**
       * Construct a new `Transactor` that uses the JDBC `DriverManager` to allocate connections.
       * @param driver     the class name of the JDBC driver, like "org.h2.Driver"
       * @param url        a connection URL, specific to your driver
       * @param info       a `Properties` containing connection information (see `DriverManager.getConnection`)
       */
      def apply[M[_]: Async: ContextShift](
        driver: String,
        url:    String,
        info:   java.util.Properties,
        blocker: Blocker
      ): Transactor.Aux[M, Unit] =
        create(driver, () => DriverManager.getConnection(url, info), Strategy.default, blocker)

      /**
       * Construct a new `Transactor` that uses the JDBC `DriverManager` to allocate connections.
       * @param driver     the class name of the JDBC driver, like "org.h2.Driver"
       * @param url        a connection URL, specific to your driver
       * @param info       a `Properties` containing connection information (see `DriverManager.getConnection`)
       */
      def apply[M[_]: Async: ContextShift](
        driver: String,
        url:    String,
        info:   java.util.Properties
      ): Transactor.Aux[M, Unit] =
        apply(driver, url, info, defaultBlocker)

    }

  }


}