cats.effect
Type members
Classlikes
Represents the exit code of an application.
Represents the exit code of an application.
code
is constrained to a range from 0 to 255, inclusive.
- Companion
- object
A pure abstraction representing the intention to perform a side effect, where the result of that side effect may be obtained synchronously (via return) or asynchronously (via callback).
A pure abstraction representing the intention to perform a side effect, where the result of that side effect may be obtained synchronously (via return) or asynchronously (via callback).
IO
values are pure, immutable values and thus preserve
referential transparency, being usable in functional programming.
An IO
is a data structure that represents just a description
of a side effectful computation.
IO
can describe synchronous or asynchronous computations that:
- on evaluation yield exactly one result
- can end in either success or failure and in case of failure
flatMap
chains get short-circuited (IO
implementing the algebra ofMonadError
) - can be canceled, but note this capability relies on the user to provide cancelation logic
Effects described via this abstraction are not evaluated until the "end of the world", which is to say, when one of the "unsafe" methods are used. Effectful results are not memoized, meaning that memory overhead is minimal (and no leaks), and also that a single effect may be run multiple times in a referentially-transparent manner. For example:
val ioa = IO.println("hey!")
val program = for {
_ <- ioa
_ <- ioa
} yield ()
program.unsafeRunSync()
The above will print "hey!" twice, as the effect will be re-run each time it is sequenced in the monadic chain.
IO
is trampolined in its flatMap
evaluation. This means that
you can safely call flatMap
in a recursive function of arbitrary
depth, without fear of blowing the stack.
def fib(n: Int, a: Long = 0, b: Long = 1): IO[Long] =
IO.pure(a + b) flatMap { b2 =>
if (n > 0)
fib(n - 1, b, b2)
else
IO.pure(a)
}
The primary entry point to a Cats Effect application. Extend this
trait rather than defining your own main
method. This avoids the
need to run IO.unsafeRunSync (or similar) on your own.
The primary entry point to a Cats Effect application. Extend this
trait rather than defining your own main
method. This avoids the
need to run IO.unsafeRunSync (or similar) on your own.
IOApp
takes care of the messy details of properly setting up
(and tearing down) the unsafe.IORuntime needed to run the IO
which represents your application. All of the associated thread
pools (if relevant) will be configured with the assumption that
your application is fully contained within the IO
produced by
the run method. Note that the exact details of how the runtime
will be configured are very platform-specific. Part of the point
of IOApp
is to insulate users from the details of the underlying
runtime (whether JVM or JavaScript).
object MyApplication extends IOApp {
def run(args: List[String]) =
for {
_ <- IO.print("Enter your name: ")
name <- IO.readln
_ <- IO.println("Hello, " + name)
} yield ExitCode.Success
}
In the above example, MyApplication
will be a runnable class with
a main
method, visible to Sbt, IntelliJ, or plain-old java
. When
run externally, it will print, read, and print in the obvious way,
producing a final process exit code of 0. Any exceptions thrown within
the IO
will be printed to standard error and the exit code will be
set to 1. In the event that the main Fiber (represented by the IO
returned by run
) is canceled, the runtime will produce an exit code of 1.
Note that exit codes are an implementation-specific feature of the underlying runtime, as are process arguments. Naturally, all JVMs support these functions, as does NodeJS, but some JavaScript execution environments will be unable to replicate these features (or they simply may not make sense). In such cases, exit codes may be ignored and/or argument lists may be empty.
Note that in the case of the above example, we would actually be
better off using IOApp.Simple rather than IOApp
directly, since
we are neither using args
nor are we explicitly producing a custom
ExitCode:
object MyApplication extends IOApp.Simple {
val run =
for {
_ <- IO.print("Enter your name: ")
name <- IO.readln
_ <- IO.println(s"Hello, " + name)
} yield ()
}
It is valid to define val run
rather than def run
because IO
's
evaluation is lazy: it will only run when the main
method is
invoked by the runtime.
In the event that the process receives an interrupt signal (SIGINT
) due
to Ctrl-C (or any other mechanism), it will immediately cancel
the main
fiber. Assuming this fiber is not within an uncancelable
region, this
will result in interrupting any current activities and immediately invoking
any finalizers (see: IO.onCancel and IO.bracket). The process will
not shut down until the finalizers have completed. For example:
object InterruptExample extends IOApp.Simple {
val run =
IO.bracket(startServer)(
_ => IO.never)(
server => IO.println("shutting down") *> server.close)
}
If we assume the startServer
function has type IO[Server]
(or similar),
this kind of pattern is very common. When this process receives a SIGINT
,
it will immediately print "shutting down" and run the server.close
effect.
One consequence of this design is it is possible to build applications which
will ignore process interrupts. For example, if server.close
runs forever,
the process will ignore interrupts and will need to be cleaned up using
SIGKILL
(i.e. kill -9
). This same phenomenon can be demonstrated by using
IO.uncancelable to suppress all interruption within the application
itself:
object Zombie extends IOApp.Simple {
val run = IO.never.uncancelable
}
The above process will run forever and ignore all interrupts. The only way
it will shut down is if it receives SIGKILL
.
It is possible (though not necessary) to override various platform-specific
runtime configuration options, such as computeWorkerThreadCount
(which only
exists on the JVM). Please note that the default configurations have been
extensively benchmarked and are optimal (or close to it) in most conventional
scenarios.
However, with that said, there really is no substitute to benchmarking your
own application. Every application and scenario is unique, and you will
always get the absolute best results by performing your own tuning rather
than trusting someone else's defaults. IOApp
's defaults are very ''good'',
but they are not perfect in all cases. One common example of this is
applications which maintain network or file I/O worker threads which are
under heavy load in steady-state operations. In such a performance profile,
it is usually better to reduce the number of compute worker threads to
"make room" for the I/O workers, such that they all sum to the number of
physical threads exposed by the kernel.
- See also
- Companion
- object
A convenience trait for defining applications which are entirely within Resource. This is implemented as a relatively straightforward wrapper around IOApp and thus inherits most of its functionality and semantics.
A convenience trait for defining applications which are entirely within Resource. This is implemented as a relatively straightforward wrapper around IOApp and thus inherits most of its functionality and semantics.
This trait should generally be used for any application which would otherwise trivially end with cats.effect.kernel.Resource!.use (or one of its variants). For example:
object HttpExample extends IOApp {
def run(args: List[String]) = {
val program = for {
config <- Resource.eval(loadConfig(args.head))
postgres <- Postgres[IO](config.jdbcUri)
endpoints <- ExampleEndpoints[IO](config, postgres)
_ <- HttpServer[IO](config.host, config.port, endpoints)
} yield ()
program.useForever.as(ExitCode.Success)
}
}
This example assumes some underlying libraries like Skunk
and Http4s, but otherwise it represents a relatively
typical example of what the main class for a realistic Cats Effect application
might look like. Notably, the whole thing is enclosed in Resource
, which is
use
d at the very end. This kind of pattern is so common that ResourceApp
defines a special trait which represents it. We can rewrite the above example:
object HttpExample extends ResourceApp.Forever {
def run(args: List[String]) =
for {
config <- Resource.eval(loadConfig(args.head))
db <- Postgres[IO](config.jdbcUri)
endpoints <- ExampleEndpoints[IO](config, db)
_ <- HttpServer[IO](config.host, config.port, endpoints)
} yield ()
}
These two programs are equivalent.
- See also
- Companion
- object
A pure abstraction representing the intention to perform a side effect, where the result of that side effect is obtained synchronously.
A pure abstraction representing the intention to perform a side effect, where the result of that side effect is obtained synchronously.
SyncIO
is similar to IO, but does not support asynchronous
computations. Consequently, a SyncIO
can be run synchronously
on any platform to obtain a result via unsafeRunSync
. This is unlike
IO#unsafeRunSync
, which cannot be safely called in general --
doing so on the JVM blocks the calling thread while the
async part of the computation is run and doing so on Scala.js
is not supported.
- Companion
- object