Ammonite lets you use the Scala language for scripting purposes: in the REPL or as scripts.
|
A Modernized Scala REPL. With syntax highlighting, multi-line editing, the ability to load maven artifacts directly in the REPL, and many other quality-of-life improvements missing in the default Scala REPL. |
|
Lightweight Programming in Scala. Create scripts that you can run easily from the command line, without the overhead of setting up a "project" or waiting for SBT's slow startup times. |
If you use Ammonite, you will probably find the following book by the Author helpful in using Ammonite to the fullest:
Ammonite is a project by Li Haoyi. If you use Ammonite and enjoyed it, please chip in to support our development at:
Any amount will help us develop Ammonite into the best possible REPL and script runner for the Scala community!
The goal of Ammonite is to liberate your Scala code from heavyweight "projects", using the lightweight Ammonite runtime: if you want to run some Scala, open the Ammonite-REPL and run it, interactively! If you want to run it later, save it into some Scala Scripts and run those later.
For a video overview of the project and it's motivation, check out this talk:
If you are already working in Scala, you no longer have to drop down to Python or Bash for your scripting needs: you can use Scala Scripts for your scripting needs, and avoid the overhead of working in multiple languages.
Each of the above projects is usable standalone; click on the links to jump straight to their docs, or scroll around and browse through the navigation bar on the left. If you're wondering what you can do with Ammonite, there is an
Which contains a bunch of fun things that you can do, whether in the interactive Ammonite-REPL or in some Scala Scripts. You can also take a look at how people are using Ammonite in the wild:
To see what people are doing with it. And there are more talks available below:
The bulk of this page describes the latest stable release of Ammonite,
3.0.0
. If you're willing to live on the edge,
we also publish Unstable Versions from any commits that get pushed
or pull-requests that land in the master branch:
The Ammonite-REPL is an improved Scala REPL, reimplemented from first principles. It is much more featureful than the default REPL and comes with a lot of ergonomic improvements and configurability that may be familiar to people coming from IDEs or other REPLs such as IPython or Zsh.
Ammonite-REPL is a superior version of the default Scala REPL, as a debugging tool, and for many other fun and interesting things!
If you want to use Ammonite as a plain Scala shell, download the standalone Ammonite 3.0.0 executable for Scala 2.13 (also available for Older Scala Versions):
$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.13-3.0.0) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
Or to try out the latest features in our Unstable Release 3.0.0-2-6342755f:
$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.13-3.0.0-2-6342755f) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
You can also download a bootstrap script, that can be downloaded and committed to version control as a file `amm`:
curl -L https://github.com/lihaoyi/ammonite/releases/download/3.0.0/2.13-3.0.0-bootstrap > amm && chmod +x amm
Same as Installation on Linux. Or you can install it via brew:
$ brew install ammonite-repl
Download the Latest version
and rename it to amm.bat
You can then run Ammonite via the `./amm` command.
This will give you access to the Ammonite-REPL:
With Pretty Printing, Syntax Highlighting for input and output, Artifact Loading in-REPL, and all the other nice Features!
If you want to use Ammonite as a filesystem shell, take a look at Ammonite-Shell. If you're not sure what to do with Ammonite, check out the Ammonite Cookbook for some fun ideas!
If you want some initialization code available to the REPL, you can add
it to your ~/.ammonite/predef.sc
.
If you have any questions, come hang out on the mailing list or gitter channel and get help!
You can also try out Ammonite 3.0.0 in an existing
SBT project. To do so, add the following to your build.sbt
libraryDependencies += {
val version = scalaBinaryVersion.value match {
case "2.10" => "1.0.3"
case "2.11" => "1.6.7"
case _ ⇒ "3.0.0"
}
"com.lihaoyi" % "ammonite" % version % "test" cross CrossVersion.full
}
sourceGenerators in Test += Def.task {
val file = (sourceManaged in Test).value / "amm.scala"
IO.write(file, """object amm extends App { ammonite.AmmoniteMain.main(args) }""")
Seq(file)
}.taskValue
// Optional, required for the `source` command to work
(fullClasspath in Test) ++= {
(updateClassifiers in Test).value
.configurations
.find(_.configuration.name == Test.name)
.get
.modules
.flatMap(_.artifacts)
.collect{case (a, f) if a.classifier == Some("sources") => f}
}
Or to try out the latest features in our Unstable Release 3.0.0-2-6342755f:
libraryDependencies += "com.lihaoyi" % "ammonite" % "3.0.0-2-6342755f" % "test" cross CrossVersion.full
After that, simply hit
sbt projectName/test:run
or if there are other main methods in the Test
scope
sbt projectName/test:runMain amm
to activate the Ammonite REPL.
You can also pass a string to the Main
call containing any
commands or imports you want executed at the start of every run, along
with other configuration.
If you want Ammonite to be available in all projects, simply add the
above snippet to a new file ~/.sbt/0.13/global.sbt
.
Ammonite-REPL supports many more features than the default REPL, including:
@ Seq.fill(10)(Seq.fill(3)("Foo"))
res0: Seq[Seq[String]] = List(
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo"),
List("Foo", "Foo", "Foo")
)
@ case class Foo(i: Int, s0: String, s1: Seq[String])
defined class Foo
@ Foo(1, "", Nil)
res2: Foo = ${Print.Foo(i = "1", s0 = "\"\"", s1 = "List()")}
@ Foo(
@ 1234567,
@ "I am a cow, hear me moo",
@ Seq("I weigh twice as much as you", "and I look good on the barbecue")
@ )
res3: Foo = ${Print.Foo(
i = 1234567,
s0 = "\"I am a cow, hear me moo\"",
s1 = "List(\"I weigh twice as much as you\", \"and I look good on the barbecue\")",
indent = " "
)}
Ammonite-REPL uses PPrint to display its output by default. That means that everything is nicely formatted to fit within the width of the terminal, and is copy-paste-able!
By default, Ammonite truncates
the pretty-printed output to avoid flooding your terminal. If you want
to disable truncation, call show(...)
on your expression to
pretty-print its full output. You can also pass in an optional
height = ...
parameter to control how much you want to show
before truncation.
@ Seq.fill(20)(100)
res0: Seq[Int] = List(
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
...
@ show(Seq.fill(20)(100))
res1: ammonite.pprint.Show[Seq[Int]] = List(
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100,
100
)
@ show(Seq.fill(20)(100), height = 3)
res2: ammonite.pprint.Show[Seq[Int]] = List(
100,
100,
...
@ repl.pprinter() = repl.pprinter().copy(defaultHeight = 5)
@ Seq.fill(20)(100)
res4: Seq[Int] = List(
100,
100,
100,
100,
...
Ammonite-REPL intelligently truncates your output when it's beyond a
certain size. You can request for the full output to be printed
on-demand, print a certain number of lines, or even change the implicit
pprintConfig
so subsequent lines all use your new configuration.
Ammonite by default ships with a custom implementation of readline, which provides...
Ammonite syntax highlights both the code you're entering as well as any output being echoed in response. This should make it much easier to work with larger snippets of input.
All colors are configurable, and you can easily turn off colors entirely via the Configuration.
Stack traces are similarly highlighted, for easier reading:
You can use the Up and Down arrows to navigate between lines
within your snippet. Enter
executes the code only when you're
on the last line of a multi-line snippet, meaning you can take your
time, space out your code nicely, and fix any mistakes anywhere in your
snippet. History is multi-line too, meaning re-running a multi-line
snippet is trivial, even with tweaks.
Long gone are the days where you're desperately trying to cram everything in a single line, or curse quietly when you notice a mistake in an earlier line you are no longer able to fix. No more painstakingly crafting a multi-line snippet, and then having to painstakingly fish it line by individual line out of the history so you can run it again!
You can use Alt-Left/Right to move forward/backwards by one word at a time or hold down Shift to select text to delete. These compose as you'd be used to: e.g. Shift-Up selects all the text between your current cursor and the same column one row up.
Tab
and Shift-Tab
now work to block-indent and -dedent
sections of code, as you'd expect in any desktop editor like Sublime
Text or IntelliJ. This further enhances the multi-line editing
experience, letting your nicely lay-out your more-complex REPL commands
the same way you'd format code in any other editor.
All the readline-style navigation hotkeys like Ctrl-W to delete a word or Esc-Left/Right to navigate one word left/right still work. If you're comfortable with consoles like Bash, Python, IPython or even the default Scala console, you should have no trouble as all the exact same hotkeys work in Ammonite
Apart from browsing your command-line history with UP
, you can
also perform a history search by entering some search term and then
pressing UP
. That will pull up the most recent history line with
that term in it, underlined. You can continue to press UP
or
DOWN
to cycle through the matches, or Backspace
or
continue typing characters to refine your search to what you want.
You can press TAB
, or any other command character (LEFT
,
RIGHT
, ...) to end the search and let you continue working with
the currently-displayed command. Pressing ENTER
will end the
search and immediately submit the command to be run.
You can also kick off a history search using Ctrl-R
, and use
Ctrl-R
to cycle through the matches.
To enter block input (many independent lines all at once) into the
Ammonite-REPL, simply wrap the multiple lines in curly braces
{ ... }
, and Ammonite will wait until you close it before
evaluating the contents:
@ {
@ val x = 1
@ val y = 2
@ x + y
@ }
x: Int = 1
y: Int = 2
res0_2: Int = 3
As you can see, the contents of the { ... }
block are
unwrapped and evaluated as top-level statements. You can use this to
e.g. declare mutually recursive functions or classes &
companion-objects without being forced to squeeze everything onto a
single line.
If you don't want this un-wrapping behavior, simply add another set of curlies and the block will be evaluated as a normal block, to a single expression:
@ {{
@ val x = 1
@ val y = 2
@ x + y
@ }}
res0: Int = 3
The Ammonite command-line editor allows you to undo and re-do portions of your edits:
Ctrl -
: Undo last changeAlt/Esc -
: Redo last change
Each block of typing, deletes, or navigation counts as one undo. This should make it much more convenient to recover from botched copy-pastes or bulk-deletions.
Ammonite provides a set of magic imports that let you load additional
code into a REPL session: these are imports which start with a $
,
and are *top-level* inside the REPL command or your
Scala Scripts.
This lets you load Scala Scripts into the REPL. For example given a small script defining one value we want
// MyScript.sc
val elite = 31337
We can load it into our REPL session using:
@ import $file.MyScript
@ MyScript.elite
res1: Int = 31337
If the script is in a sub-folder, simply use:
@ import $file.myfolder.MyScript
Or if the script is in an outer folder,
@ import $file.^.MyScript
Or if we want to import the contents of the script in one go:
@ import $file.MyScript, MyScript._
import $file.$
@ elite
res1: Int = 31337
While this is a trivial example, your MyScript.sc
file can
contain anything you want, not just val
s: function
def
s, class
es object
s or
trait
s, or imports from other scripts. For more
documentation on how these scripts work, check out the
Scala Scripts section.
There are some subtleties when dealing with $file
imports
that are worth remembering
Note you can also perform file imports from your predef file, which are resolved relative to that file's path. This is useful if your predef is large and you want to break it up into multiple files.
Note that script files imported multiple times are re-used; even if
the same script is imported multiple times, it will only be compiled
once, and its top-level definitions or statements will only be
evaluated once. If you want to run code over and over, def
a function in the script you are importing and you can call it
repeatedly.
If you want to re-load a script, you should use Ammonite's
Save/Load Session functionality to sess.save()
the session before importing the script, and sess.load()
ing
to reset the script before re-import
ing it.
You cannot import things from "inside" that script in
one chain:@ import $file.MyScript._
Rather, you must always import the script-object first, and then import things from the script object after:
@ import $file.MyScript, MyScript._
You can re-name scripts on-import if you find their names are colliding:
@ import $file.{MyScript => FooBarScript}, FooBarScript._
Or import multiple scripts at once
@ import $file.{MyScript, MyOtherScript}
These behave as you would expect imports to work. Note that when importing multiple scripts, you have to name them explicitly and cannot use wildcard `._` imports:
@ import $file._ // doesn't work
This is similar to import $file
, except that it dumps the
definitions and imports from the script into your REPL session. This is
useful if you are using a script to hold a set of common imports:
using import $file to import a script doesn't propagate
imports from that script into your REPL.
It is also useful if you want to split up your
~/.ammonite/predef.sc
file into multiple scripts: e.g. if you
want to break up your predef.sc
into two scripts
~/.ammonite/predef.sc
and ~/.ammonite/helper.sc
. While
you could use import $file to
import $file.helper
within your predef.sc
file, it
will only bring the helper
object into scope within
predef.sc
or within your REPL. import $exec.helper
will properly "dump" all the definitions from helper.sc
into
your local scope, which is often what you want when dealing with
predef files.
See the docs for Scala Scripts for more on how script files work in general.
Lets you add files in the class path. You can use either the same syntax as $sect.ref{import $file}, like
@ import $cp.^.scripts.foo // adds ../scripts/foo to the class path
Or you can pass file paths between back-ticks, like
@ import $cp.`../scripts/foo.jar` // adds ../scripts/foo.jar to the class path
*
are also accepted after directory paths, Java properties can be substituted
in values passed to import $cp
, and several values can be passed, provided
they're separated by the standard path separator (;
on Linux and macOS, and
:
on Windows)
@ import $cp.`${spark.home}/jars/*` // adds all JARs under the jars subdirectory of Spark home
Ammonite disambiguates the two syntaxes above the following way: if the import consists in a
single element after import $cp.
, and this element contains /
(on all platforms),
or the local PATH separator (;
on Windows, :
on Linux and macOS), or
a \
if on Windows, then the second syntax above is assumed (class path syntax). Else,
the first syntax is assumed.
Lets you import Ivy dependencies from Maven Central, or anywhere else. For example, here is loading Scalaz and using it in the Ammonite-REPL:
@ import $ivy.`org.scalaz::scalaz-core:7.2.27`, scalaz._, Scalaz._
@ (Option(1) |@| Option(2))(_ + _)
res1: Option[Int] = Some(value = 3)
Note that the different portions of the $ivy
import are
in a org::library:version
format; the ::
is used to represent
Scala dependencies, similar to %%
in SBT's dependency syntax.
If you want Java dependencies, you can load them using the
org:library:version
format, e.g. here we load the
Google Guava Java library
@ import $ivy.`com.google.guava:guava:18.0`, com.google.common.collect._
@ val bimap = ImmutableBiMap.of(1, "one", 2, "two", 3, "three")
@ bimap.get(1)
res2: String = "one"
@ bimap.inverse.get("two")
res3: Int = 2
As well as the org:::library:version
syntax for loading Scala
libraries cross-published against the full Scala version (e.g.
2.12.2
rather than just 2.12
):
@ import org.scalamacros.paradise.Settings._
error: object scalamacros is not a member of package org
@ import $ivy.`org.scalamacros:::paradise:2.1.1`, org.scalamacros.paradise.Settings._
@ boolSetting("key").value
res1: Boolean = false
If you want to load a compiler plugin, you can do so using
import $plugin.$ivy
:
@ // Compiler plugins imported without `.$plugin` are not loaded
@ import $ivy.`org.typelevel:::kind-projector:0.13.3`
@ trait TC0[F[_]]
defined trait TC0
@ type TC0EitherStr = TC0[Either[String, *]]
error: not found: type *
@ // You need to use `import $plugin.$ivy`
@ import $plugin.$ivy.`org.typelevel:::kind-projector:0.13.3`
@ trait TC[F[_]]
defined trait TC
@ type TCEitherStr = TC[Either[String, *]]
defined type TCEitherStr
@ // Importing plugins doesn't affect the run-time classpath
@ import $plugin.$ivy.`com.lihaoyi::scalatags:0.7.0`
@ import scalatags.Text
error: not found: value scalatags
This makes Ammonite ideal for trying out new libraries or tools. You can pull down projects like Scalaz or Shapeless and immediately start working with them in the REPL:
@ import $ivy.`com.chuusai::shapeless:2.3.3`, shapeless._
@ (1 :: "lol" :: List(1, 2, 3) :: HNil)
res1: Int :: String :: List[Int] :: HNil = 1 :: "lol" :: List(1, 2, 3) :: HNil
@ res1(1)
res2: String = "lol"
@ import shapeless.syntax.singleton._
@ 2.narrow
res4: 2 = 2
Even non-trivial web frameworks like Finagle or Akka-HTTP can be simply pulled down and run in the REPL!
@ import $$ivy.`com.twitter::finagle-http:21.4.0 compat`
@ import com.twitter.finagle._, com.twitter.util._
@ var serverCount = 0
@ var clientResponse = 0
@ val service = new Service[http.Request, http.Response] {
@ def apply(req: http.Request): Future[http.Response] = {
@ serverCount += 1
@ Future.value(
@ http.Response(req.version, http.Status.Ok)
@ )
@ }
@ }
@ val server = Http.serve(":$port", service)
@ val client: Service[http.Request, http.Response] = Http.client.newService(":$port")
@ val request = http.Request(http.Method.Get, "/")
@ request.host = "www.scala-lang.org"
@ val response: Future[http.Response] = client(request)
@ response.onSuccess { (resp: http.Response) =>
@ clientResponse = resp.statusCode
@ }
@ Await.ready(response)
@ serverCount
res12: Int = 1
@ clientResponse
res13: Int = 200
@ server.close()
Ammonite-REPL is configured with a set of default resolvers but you can add your own using Coursier's Repository APIs
@ import $ivy.`com.github.jupyter:jvm-repr:0.4.0`
error: Failed to resolve ivy dependencies
@ interp.repositories() ++= Seq(coursierapi.MavenRepository.of(
@ "https://jitpack.io"
@ ))
@ import $ivy.`com.github.jupyter:jvm-repr:0.4.0`
@ import jupyter._
Including repositories which need authentication:
import coursierapi.{Credentials, MavenRepository}
interp.repositories() ++= Seq(
MavenRepository
.of("https://nexus.corp.com/content/repositories/releases")
.withCredentials(Credentials.of("user", "pass"))
)
If you need more detailed control over what you are importing, e.g.
with attributes, classifiers or exclusions, you can fall back to
using the interp.load.ivy(deps: coursierapi.Dependency*)
function and configure each Dependency
to your heart's content:
@ import os._
@ interp.load.module($printedScriptPath/"loadIvyAdvanced.sc")
@ serializer
Lets you statically add Maven or Ivy repositories that will be used during artifact resolution. This mechanism does not (yet) allow for credentials registration. (
@ import $repo.`https://jitpack.io`
@ import $ivy.`com.github.jupyter:jvm-repr:0.4.0`
@ import jupyter._
NB: Prefixing the url pattern with "ivy:", such as
import $repo.`ivy:https://dl.bintray.com/typesafe/ivy-releases/[defaultPattern]`
,
is required for ivy repositories. Maven repositories do not require any prefix
The Ammonite REPL contains a bunch of built-in imports and definitions by default. This includes:
repl
: the object representing the Repl API, aliased as
repl
. This allows you (e.g. repl.history
)
and you can use autocomplete or typeOf
on the
repl
object to see what is available.
All of these are imported by default into any Ammonite REPL, in order to
provide a rich and consistent REPL experience. If you want to disable
these imports and run the REPL with a clean namespace (with only the core
implicits needed for result pretty-printing/type-printing to work) pass
in defaultPredef = false
to the REPL's Main
API or
--no-default-predef
to the REPL from the command-line.
Ammonite contains a range of useful built-ins implemented as normal
functions on the repl
and interp
objects, e.g.
repl.history
, repl.width
, repl.frontEnd()
to
change the front-end terminal implementation, etc.:
trait ReplAPI extends ReplAPIScalaVersionSpecific {
/**
* Read/writable prompt for the shell. Use this to change the
* REPL prompt at any time!
*/
val prompt: Ref[String]
/**
* The front-end REPL used to take user input. Modifiable!
*/
val frontEnd: Ref[FrontEnd]
/**
* Display help text if you don't know how to use the REPL
*/
def help: String
/**
* The last exception that was thrown in the REPL; `null` if nothing has
* yet been thrown. Useful if you want additional information from the
* thrown exception than the printed stack trace (e.g. many exceptions have
* additional metadata attached) or if you want to show the stack trace
* on an exception that doesn't normally print it (e.g. seeing the stack
* when a Ctrl-C interrupt happened) via `lastException.printStackTrace`.
*/
def lastException: Throwable
/**
* History of commands that have been entered into the shell, including
* previous sessions
*/
def fullHistory: History
/**
* History of commands that have been entered into the shell during the
* current session
*/
def history: History
/**
* Throw away the current scala.tools.nsc.Global and get a new one
*/
def newCompiler(): Unit
/**
* Shows all imports added that bring values into scope for the commands a
* user runs; *includes* imports from the built-in predef and user predef files
*/
def fullImports: Imports
/**
* Shows the imports added to scope by the commands a user has entered so far;
* *excludes* imports from the built-in predef and user predef files
*/
def imports: Imports
/**
* If class wrapping is enabled, this lists the names of the previous commands
* that the current commands actually references (as told by the scalac).
*
* E.g. in a session like
* ```
* @ val n = 2
* n: Int = 2
*
* @ val p = 1
* p: Int = 1
*
* @ n + p
* res2: Int = 3
* ```
* this would have returned an empty list if called from the same line as `val n = 2`
* or `val p = 1`. This would have returned `Seq("cmd0", "cmd1")` if called
* from the same line as `n + p`, as both `cmd0`, that defines `n`, and `cmd1`, that
* defines `p`, are referenced from this line.
*/
def usedEarlierDefinitions: Seq[String]
/**
* Controls how things are pretty-printed in the REPL. Feel free
* to shadow this with your own definition to change how things look
*/
implicit def tprintColorsImplicit: pprint.TPrintColors
implicit def codeColorsImplicit: CodeColors
def pprinter: Ref[pprint.PPrinter]
/**
* Current width of the terminal
*/
def width: Int
/**
* Current height of the terminal
*/
def height: Int
def show(t: Any): Unit
/**
* Lets you configure the pretty-printing of a value. By default, it simply
* disables truncation and prints the entire thing, but you can set other
* parameters as well if you want.
*/
def show(t: Any, width: Integer = null, height: Integer = null, indent: Integer = null): Unit
/**
* Functions that can be used to manipulate the current REPL session:
* check-pointing progress, reverting to earlier checkpoints, or deleting
* checkpoints by name.
*
* Frames get pushed on a stack; by default, a saved frame is
* accessible simply by calling `load`. If you provide a name
* when `save`ing a checkpoint, it can later be `load`ed directly
* by providing the same name to `load`
*
* Un-named checkpoints are garbage collected, together with their
* classloader and associated data, when they are no longer accessible
* due to `restore`. Named checkpoints are kept forever; call `delete`
* on them if you really want them to go away.
*/
def sess: Session
def load: ReplLoad
def clipboard: Clipboard
def _compilerManager: ammonite.compiler.iface.CompilerLifecycleManager
}
trait ReplLoad {
/**
* Loads a command into the REPL and
* evaluates them one after another
*/
def apply(line: String): Unit
/**
* Loads and executes the scriptfile on the specified path.
* Compilation units separated by `@\n` are evaluated sequentially.
* If an error happens it prints an error message to the console.
*/
def exec(path: os.Path): Unit
}
trait Session {
/**
* The current stack of frames
*/
def frames: List[Frame]
/**
* Checkpoints your current work, placing all future work into its own
* frames. If a name is provided, it can be used to quickly recover
* that checkpoint later.
*/
def save(name: String = ""): Unit
/**
* Discards the last frames, effectively reverting your session to
* the last `save`-ed checkpoint. If a name is provided, it instead reverts
* your session to the checkpoint with that name.
*/
def load(name: String = ""): SessionChanged
/**
* Resets you to the last save point. If you pass in `num`, it resets
* you to that many savepoints since the last one.
*/
def pop(num: Int = 1): SessionChanged
/**
* Deletes a named checkpoint, allowing it to be garbage collected if it
* is no longer accessible.
*/
def delete(name: String): Unit
}
trait Clipboard {
/**
* Reads contents from the system clipboard.
* @return System clipboard contents if they are readable as `String`,
* empty string otherwise.
*/
def read: String
/**
* Sets the contents of the system clipboard.
*
* @param data New contents for the clipboard.
*/
def write(data: geny.Writable): Unit
}
All of these are available as part of the repl
object
which is imported in scope by default. Additional
functionality available under the interp
object, which is also
available in scripts:
trait InterpAPI {
/**
* When running a script in `--watch` mode, re-run the main script if this
* file changes. By default, this happens for all script files, but you can
* call this to watch arbitrary files your script may depend on
*/
def watch(p: os.Path): Unit
/**
* A generalization of [[watch]], allows watching arbitrary values and not
* just the contents of file paths.
*/
def watchValue[T](v: => T): T
/**
* The colors that will be used to render the Ammonite REPL in the terminal,
* or for rendering miscellaneous info messages when running scripts.
*/
val colors: Ref[Colors]
/**
* Tools related to loading external scripts and code into the REPL
*/
def load: InterpLoad
/**
* resolvers to use when loading jars
*/
def repositories: Ref[List[Repository]]
/**
* Functions that will be chained and called on the coursier
* Fetch object right before they are run
*/
val resolutionHooks: mutable.Buffer[Fetch => Fetch]
/**
* Exit the Ammonite REPL. You can also use Ctrl-D to exit
*/
def exit = throw AmmoniteExit(())
/**
* Exit the Ammonite REPL. You can also use Ctrl-D to exit
*/
def exit(value: Any) = throw AmmoniteExit(value)
/**
* Functions that will be chained and called on the
* exitValue before the repl exits
*/
val beforeExitHooks: mutable.Buffer[Any => Any]
implicit def scalaVersion: ScalaVersion
def _compilerManager: ammonite.compiler.iface.CompilerLifecycleManager
}
trait LoadJar {
/**
* Load a `.jar` file or directory into your JVM classpath
*/
def cp(jar: os.Path): Unit
/**
* Load a `.jar` from a URL into your JVM classpath
*/
def cp(jar: java.net.URL): Unit
/**
* Load one or more `.jar` files or directories into your JVM classpath
*/
def cp(jars: Seq[os.Path]): Unit
/**
* Load a library from its maven/ivy coordinates
*/
def ivy(coordinates: Dependency*): Unit
}
trait InterpLoad extends LoadJar {
def module(path: os.Path): Unit
def plugin: LoadJar
}
Apart from the core Builtins of the REPL, the Ammonite REPL also includes many helpers that are not strictly necessarily but are very useful in almost all REPL sessions. Here are a few of them
The REPL also imports the pipe-operators
from Ammonite-Ops by default to make it easy for you to use tools like
grep interactively, and imports all the Builtins
from the repl
.
These tools are useful but not strictly necessary;
Ammonite provides the src
built-in, which lets you easily
peek at the source code of various functions or classes. You can
use this to read their doc-comments or inspect their implementation,
to help you figure out how to use them.
src
accepts two kinda of inputs:
foo.bar(...)
, in which case it will try to
bring you to concrete implementation of that method bar
.
You can also leave the method arguments empty using `_`.foo
, in which case it will try to
bring you to the implementation of foo
's runtime class
src
works on both Scala and Java APIs, both the standard
library as well as third-party dependencies. src
opens source
files using the less
pager by default; if you wish to change
this, you can pass in a replacement command as a second argument
e.g. src(..., "vim")
or e.g. src(..., Seq("vim", "--flag"))
When used within a SBT project src
requires the following
SBT setting in order to make the source code of third-party
dependencies available:
// Optional, required for the `source` command to work
(fullClasspath in Test) ++= {
(updateClassifiers in Test).value
.configurations
.find(_.configuration.name == Test.name)
.get
.modules
.flatMap(_.artifacts)
.collect{case (a, f) if a.classifier == Some("sources") => f}
}
Ammonite also automatically downloads the source jars of any
libraries you import via import $ivy
, and makes them
browsable via src
.
src
is experimental: it may not always be able to find the
source code of a particular method or class, and the source
location it brings you to may be a few lines away from the source
you really want. Furthermore, src
also does not find sources
that are within your own local scripts or SBT project: you likely
already have access to those via your text editor anyway.
Nevertheless, it should work in the bulk of cases, so try it out and come by the Gitter Channel if you face any issues!
bash$ time ls -a
. .. .git .git-blame-ignore-revs .github .gitignore .mill-version .scalafmt.conf LICENSE amm amm-template.sh build.sbt build.sc ci deploy_key integration internals-docs mill out project readme readme.md sshd target terminal typescript
@ time{ls!}
Just as bash provides a time
command that you can use to see
how long a command took to run, Ammonite-Shell provides a
time
function which serves the same purpose.
While the bash version spits out the time in an ad-hoc table format,
stuck together with the output of the command, Ammonite-Shell's
time
instead returns a tuple containing the expression
that was evaluated, and the time taken to evaluate it.
bash$ ls -a . | grep re
.git-blame-ignore-revs .gitignore readme readme.md
@ ls! wd || grep! "re"
bash$ ls -a . | grep re
.git-blame-ignore-revs .gitignore readme readme.md
@ ls! wd |? grep! "re"
Ammonite provides its own grep
command, which lets you
easily perform ad-hoc searches within a list.
As shown above, Ammonite's grep
can be used via
||
(flatMap
) or |?
(filter
). In the case of ||
, it displays the
matches found, highlighted, with some additional context before and
after the match. When used with |?
, it simply returns the
relevant items. In general, ||
is useful for manual
exploration, while |?
is useful in scripts where you want
to deal with the list of matched results later.
By default, Ammonite's grep
matches a string as a literal.
If you want to match via a regex, append a .r
to the
string literal to turn it into a regex:
bash$ ls -a . | grep -G "re[a-z]\+"
.git-blame-ignore-revs readme readme.md
@ ls! wd || grep! "re[a-z]+".r
Ammonite's grep
isn't limited to "filesystem"-y things;
any collection of objects can be piped through grep
!
For example, here's grep
being used to quickly search
through the JVM system properties:
@ // I'm only interested in OS-related properties, show them to me! @ sys.props || grep! "os|OS".r
You can even use Ammonite's grep
to dig through the
methods of an object, even large messy objects with far-too-many
methods to go over by hand hunting for what you want:
@ typeOf(repl.compiler).members.size // Too many methods to dig through! res0: Int = 1632 @ // I forgot what I want but I think it has Raw in the name @ typeOf(repl.compiler).members || grep! "Raw"
In general, Ammonite's grep
serves the same purpose of
grep
in the Bash shell: a quick and dirty way to explore large
amounts of semi-structured data. You probably don't want to build
your enterprise business logic on top of grep
's string
matching. While you're working, though, grep
can be a
quick way to find items of interest in collections of things
(anything!) too large to sift through by hand, when you're not yet
sure exactly what you want.
browse
is a utility that lets you open up far-too-large
data structures in the less
pager, letting you page through
large quantities of text, navigating around it and searching through
it, without needing to spam your terminal output with its contents
and losing your earlier work to the output-spam. Simple call
browse
on whatever value you want, e.g. this 50 thousand
line ls.rec
result show above.
If you're dealing with large blobs of data that you want to dig
through manually, you might normally format it nicely, write it to
a file, and open it in vim
or less
or an editor such
as Sublime Text. browse
makes that process quick and
convenient.
You can customize the browse
call like you would a
show
call or pprint.pprintln
call, e.g. setting
an optional width
, colors
or indent
.
You can also choose a viewer
program in case you don't
want to use less
: e.g. here's a command that would open it up
in vim
:
haoyi-Ammonite@ browse(res0, viewer="vim", colors = pprint.Colors.BlackWhite)
Apart from using viewer="vim"
, we also set the
colors
to black and white because Vim by default doesn't
display ANSI colors nicely. You can also pass in a Seq
of
strings to viewer
if you want to pass additional flags to
your editor, and of course use any other editor you would like such
as "emacs"
or "nano"
or "subl"
desugar
allows you to easily see what the compiler is
doing with your code before it gets run. For example, in the above
calls to desugar
, you can see:
List(...)
being converted to List.apply(...)
true -> false
being converted to
Predef.ArrayAssoc(true).$minus$greater(false)
default.write$default
, default.SeqishW
, etc.
being injected as implicitsfor
comprehensions with if
filters being
converted into the relevant withFilter
and map
calls
In general, if you are having trouble understanding the combination
of implicit parameters, implicit conversions, macros, and other odd
Scala features, desugar
could you see what is left after
all the magic happens.
Ammonite allows you to save your work half way through, letting you discard any future changes and returning to the state of the world you saved.
Defined some memory-hogging variable you didn't need? Loaded the wrong version of some third-party library? Reluctant to reload the REPL because reloading is slow? Fear not! With Ammonite, you can save your important work, do whatever you want later, and simply discard all the jars you loaded, variables you defined
@ val veryImportant = 1
veryImportant: Int = 1
@ repl.sess.save()
@ val oopsDontWantThis = 2
oopsDontWantThis: Int = 2
@ // Let's try this new cool new library
@ import $$ivy.`com.lihaoyi::scalatags:0.7.0 compat`
@ veryImportant
res4: Int = 1
@ oopsDontWantThis
res5: Int = 2
@ import scalatags.Text.all._
@ div("Hello").render
res7: String = "<div>Hello</div>"
@ // Oh no, maybe we don't want scalatags!
@ repl.sess.load()
@ veryImportant
res9: Int = 1
@ oopsDontWantThis
error: ${check.notFound("oopsDontWantThis")}
@ import scalatags.Text.all._
error: ${check.notFound("scalatags")}
"""
Apart from plain save
s and load
s, which simply
discard everything after the most recent save, you can also provide a
name to these functions. That lets you stop working on a branch, go do
something else for a while, and be able to come back later to continue
where you left off:
@ val (x, y) = (1, 2)
x: Int = 1
y: Int = 2
@ repl.sess.save("xy initialized")
@ val z = x + y
z: Int = 3
@ repl.sess.save("first z")
@ repl.sess.load("xy initialized")
@ val z = x - y
z: Int = -1
@ repl.sess.save("second z")
@ z
res7: Int = -1
@ repl.sess.load("first z")
@ z
res9: Int = 3
@ repl.sess.load("second z")
@ z
res11: Int = -1
""")
Lastly, you have the repl.sess.pop()
function. Without any
arguments, it behaves the same as repl.sess.load()
, reseting you
to your last savepoint. However, you can pass in a number of session
frames which you'd like to pop, allow you to reset your session to even
earlier save points. repl.sess.pop(2)
would put you two
save-points ago, repl.sess.pop(3)
would put you three save-points
ago, letting you reach earlier save-points even if you did not give
them names. Passing in a large number like repl.sess.pop(999)
would reset your session all the way until the start.
Ammonite's save
and load
functionality is
implemented via Java class-loaders.
The original Scala REPL provides no autocomplete except for the most
basic scenarios of value.<complete>
. In the Ammonite-REPL,
you get the same autocomplete-anywhere support that you get in a modern
IDE.
@ Seq(1, 2, 3).map(x => x.)
getClass ## asInstanceOf isInstanceOf
toString hashCode equals !=
== % / *
- + ^ &
| >= > <=
< >> >>> <<
unary_- unary_+ unary_~ toDouble
toFloat toLong toInt toChar
toShort toByte compareTo doubleValue
...
@ Futu
scala.collection.parallel.FutureThreadPoolTasks
scala.collection.parallel.FutureTasks
scala.concurrent.impl.Future$PromiseCompletingRunnable
scala.concurrent.impl.Future
scala.concurrent.Future
scala.concurrent.FutureTaskRunner
scala.concurrent.Future$InternalCallbackExecutor
scala.concurrent.Future$class
java.util.concurrent.Future
java.util.concurrent.FutureTask$WaitNode
java.util.concurrent.FutureTask
com.sun.corba.se.impl.orbutil.closure.Future
Ammonite also allows you to autocomplete third party dependencies pulled in via import $ivy, to make it easy for you to navigate the public package repositories and find the name and version of a dependency that you want:
None of these examples work in the standard Scala REPL.
@ while(true) ()
... hangs ...
^Ctrl-C
Interrupted!
@
The traditional Scala REPL doesn't handle runaway code, and gives you no option but to kill the process, losing all your work. Ammonite-REPL lets you interrupt the thread, stop the runaway-command and keep going.
@ val x = 1
x: Int = 1
@ /* trigger compiler crash */ trait Bar { super[Object].hashCode }
error: java.lang.AssertionError: assertion failed
@ 1 + x
res1: Int = 2
The default Scala REPL throws away all your work if the compiler
crashes. This doesn't make any sense, because all the compiler is is
a dumb String => Array[Byte]
pipe. In the Ammonite, we
simply swap out the broken compiler for a new one and let you continue
your work.
Apart from the above features, the Ammonite REPL fixes a large number of bugs in the default Scala REPL, including but not limited to:
Ammonite is configured via Scala code, that can live in the
~/.ammonite/predef.sc
file, passed in through SBT's
initialCommands
, or passed to the command-line executable as
--predef='...'
.
Anything that you put in predef.sc
will be executed when you
load the Ammonite REPL. This is a handy place to put common imports,
setup code, or even call import $ivy
to
load third-party jars. The compilation
of the predef is cached, so after the first run it should not noticeably
slow down the initialization of your REPL.
Some examples of things you can configure:
@ // Set the shell prompt to be something else
@ repl.prompt() = ">"
@ // Change the terminal front end; the default is
@ // Ammonite on Linux/OSX and JLineWindows on Windows
@ repl.frontEnd() = frontEnd("unix")
@ repl.frontEnd() = frontEnd("windows")
@ repl.frontEnd() = frontEnd("ammonite")
@ // Changing the colors used by Ammonite; all at once:
@ interp.colors() = ammonite.util.Colors.BlackWhite
@ interp.colors() = ammonite.util.Colors.Default
@ // or one at a time:
@ interp.colors().prompt() = fansi.Color.Red
@ interp.colors().ident() = fansi.Color.Green
@ interp.colors().`type`() = fansi.Color.Yellow
@ interp.colors().literal() = fansi.Color.Magenta
@ interp.colors().prefix() = fansi.Color.Cyan
@ interp.colors().comment() = fansi.Color.Red
@ interp.colors().keyword() = fansi.Bold.On
@ interp.colors().selected() = fansi.Underlined.On
@ interp.colors().error() = fansi.Color.Yellow
By default, all the values you're seeing here with the ()
after
them are Ref
s, defined as
trait StableRef[T] {
/**
* Get the current value of the this [[StableRef]] at this instant in time
*/
def apply(): T
/**
* Set the value of this [[StableRef]] to always be the value `t`
*/
def update(t: T): Unit
}
trait Ref[T] extends StableRef[T] {
/**
* Return a function that can be used to get the value of this [[Ref]]
* at any point in time
*/
def live(): () => T
/**
* Set the value of this [[Ref]] to always be the value of the by-name
* argument `t`, at any point in time
*/
def bind(t: => T): Unit
}
As you can see from the signature, you can basically interact with the
Ref
s in two ways: either getting or setting their values as
values, or binding their values to expressions that will be evaluated
every time the Ref
's value is needed.
As an example of the latter, you can use bind
to set your
prompt
to always include your current working directory
repl.prompt.bind(os.pwd.toString + " @ ")
As is common practice in other shells. Further modifications to make it include e.g. your current branch in Git (which you can call through Ammonite's subprocess API or the current timestamp/user are similarly possible.
Apart from configuration of the rest of the shell through
Refs, configuration of the Scala compiler takes place
separately through the compiler's own configuration mechanism. You have
access to the compiler as compiler
, and can modify its settings
as you see fit. Here's an example of this in action:
@ // Disabling default Scala imports
@ List(1, 2, 3) + "lol"
res0: String = "List(1, 2, 3)lol"
@ interp.configureCompiler(_.settings.noimports.value = true)
@ // interp.preConfigureCompiler(ctx => ctx.setSetting(ctx.settings.YnoImports, true)) // Dotty
@ List(1, 2, 3) + "lol" // predef imports disappear
error: not found: value List
@ interp.configureCompiler(_.settings.noimports.value = false)
@ List(1, 2, 3) + "lol"
res3: String = "List(1, 2, 3)lol"
@ // Disabling Scala language-import enforcement
@ object X extends Dynamic
error: extension of type scala.Dynamic needs to be enabled
@ interp.configureCompiler(_.settings.language.tryToSet(List("dynamics")))
@ object X extends Dynamic
defined object X
@ 1 + 1 // other things still work
@ // Enabling warnings (which are disabled by default)
@ List(1) match { case _: List[Double] => 2 }
res7: Int = 2
@ interp.configureCompiler(_.settings.nowarnings.value = false)
@ List(1) match { case _: List[Double] => 2 }
warning: $fruitlessTypeTestWarningMessageBlahBlahBlah
@ // Note you can refer to `repl.compiler` when interactive in the REPL
@ // But you should use `interp.configureCompiler` in your scripts/predef
@ // because `repl.compiler` may be `null` if the script is cached.
@ repl.compiler.settings.nowarnings.value
res10: Boolean = false
If you want these changes to always be present, place them in your
~/.ammonite/predef.sc
.
Ammonite also supports the JAVA_OPTS
environment variable for
passing arguments to the JVM that it runs inside, e.g. you can pass in
a custom memory limit via
bash$ JAVA_OPTS="-Xmx1024m" amm
To start the REPL while letting it use only up to 1024 megabytes of memory
The Ammonite REPL is just a plain-old-Scala-object, just like any other Scala object, and can be easily used within an existing Scala program. This is useful for things like interactive Debugging or hosting a Remote REPL to interact with a long-lived Scala process, or Instantiating Ammonite inside an existing program to serve as a powerful interactive console.
To use Ammonite inside an existing Scala program, you need to first add it to your dependencies:
libraryDependencies += "com.lihaoyi" % "ammonite" % "3.0.0" cross CrossVersion.full
Then instantiate it with this code anywhere within your program:
package ammonite.integration
object TestMain {
def main(args: Array[String]): Unit = {
val hello = "Hello"
// Break into debug REPL with
ammonite.Main(
predefCode = "println(\"Starting Debugging!\")"
).run(
"hello" -> hello,
"fooValue" -> foo()
)
}
def foo() = 1
}
You can configure the instantiated REPL by passing in arguments to the
Main()
call, e.g. to redirect the input/output streams or to
run a predef
to configure it further.
Ammonite can be used as a tool to debug any other Scala program, by conveniently opening a REPL at any point within your program with which you can interact with live program data, similar to pdb/ipdb in Python. To do so, first add Ammonite to your classpath, e.g. through this SBT snippet:
libraryDependencies += "com.lihaoyi" % "ammonite" % "3.0.0" cross CrossVersion.full
Note that unlike the snippet given above, we
leave out the % "test"
because we may want ammonite to be
available within the "main" project, and not just in the unit tests.
Then, anywhere within your program, you can place a breakpoint via:
package ammonite.integration
object TestMain {
def main(args: Array[String]): Unit = {
val hello = "Hello"
// Break into debug REPL with
ammonite.Main(
predefCode = "println(\"Starting Debugging!\")"
).run(
"hello" -> hello,
"fooValue" -> foo()
)
}
def foo() = 1
}
And when your program reaches that point, it will pause and open up an
Ammonite REPL with the values you provided it bound to the names you
gave it. From there, you can interact with those values as normal Scala
values within the REPL. Use Ctrl-D
or exit
to exit the
REPL and continue normal program execution. Note that the names given
must be plain Scala identifiers.
Here's an example of it being used to debug changes to the WootJS webserver:
In this case, we added thedebug
statement within the
websocket frame handler, so we can inspect the values that are taking
part in the client-server data exchange. You can also put the
run
statement inside a conditional, to make it break only
when certain interesting situations (e.g. bugs) occur.
As you can see, you can bind the values you're interested in to names inside the debug REPL, and once in the REPL are free to explore them interactively.
The debug()
call returns : Any
; by default, this
is (): Unit
, but you can also return custom values by
passing in an argument to exit(...)
when you exit the REPL.
This value will then be returned from debug()
, and can be
used in the rest of your Scala application.
Ammonite can also be used to remotely connect to your running
application and interact with it in real-time, similar to Erlang's
erl -remsh
command.
This is useful if e.g. you have multiple Scala/Java processes running but aren't sure when/if you'd want to inspect them for debugging, and if so which ones. With Ammonite, you can leave a ssh server running in each process. You can then and connect-to/disconnect-from each one at your leisure, working with the in-process Scala/Java objects and methods and classes interactively, without having to change code and restart the process to add breakpoints or instrumentation.
To do this, add ammonite-sshd to your classpath, for example with SBT:
libraryDependencies += "com.lihaoyi" % "ammonite-sshd" % "3.0.0" cross CrossVersion.full
Now add repl server to your application:
import ammonite.sshd._
val replServer = new SshdRepl(
SshServerConfig(
address = "localhost", // or "0.0.0.0" for public-facing shells
port = 22222, // Any available port
passwordAuthenticator = Some(pwdAuth) // or publicKeyAuthenticator
)
)
replServer.start()
And start your application. You will be able to connect to it using ssh
like this: ssh repl@localhost -p22222
and interact with your
running app. Invoke stop()
method whenever you want to
shutdown ammonite sshd server. Here for example sshd repl server is
embedded in the Akka HTTP microservice example:
Here we can interact with code live, inspecting values or calling methods on the running system. We can try different things, see which works and which not, and then put our final bits in application code. In this example app is located on local machine, but you are free to connect to any remote node running your code.
Security notes: It is probably unsafe to run this server publicly
(on host "0.0.0.0"
) in a production, public-facing
application. If you insist on doing so, you probably want key-based
authentication, available by supplying publicKeyAuthenticator
in the SshServerConfig
.
Despite this, it is perfectly possible to run these on production
infrastructure: simply leave the host
set to
"localhost"
, and rely on the machine's own SSH access to
keep out unwanted users: you would first ssh
onto the machine
itself, and then ssh
into the Ammonite REPL running on
localhost
.
Typically most organizations already have bastions, firewalls, and
other necessary infrastructure to allow trusted parties SSH access to
the relevant machines. Running on localhost
lets you leverage
that and gain all the same security properties without having to
reimplement them in Scala.
Scala scripts are lightweight files containing Scala code that can be directly run from the command line. Unlike normal Scala projects, Scala scripts let you save and run code without setting up a "build-file" or "project". Scala Scripts are useful for writing small pieces of code, and are much quicker to write and deploy than a full-fledged SBT project.
Creating an Ammonite Script is just a matter of creating a
MyScript.sc
with some Scala code in it, and running it
from your terminal. Deploying the script is
a matter of copying the script file to wherever you want to run it, and
running it. No project/
folder, no worrying about .jar
files
or uber-jars. No worrying about compiling your code: scripts are
automatically compiled the first time they are run, and subsequently start
quickly with minimal overhead. Writing and running Scala code
doesn't get much easier than that!
As an example, Ammonite's own
Continuous Integration Scripts
are written as .sc
Scala Scripts, as are Haoyi's blog and resume. These are all examples of using
Scala Scripts to do some simple (or not so simple!) tasks in just a few
files, without the hassle of setting up a heavyweight SBT project.
To begin with, download the Ammonite 3.0.0 script-runner for Scala 2.13 (also available for Older Scala Versions):
$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.13-3.0.0) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
Or to try out the latest features in our Unstable Release 3.0.0-2-6342755f:
$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.13-3.0.0-2-6342755f) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
And read on to learn about how Scala scripts work.
Ammonite defines a format that allows you to load external scripts into the REPL; this can be used to save common functionality so it can be used at a later date. In the simplest case, a script file is simply a sequence of Scala statements, e.g.
// MyScript.sc
// print banner
println("Hello World!!")
// common imports
import sys.process._
import collection.mutable
// common initialization code
val x = 123
println("x is " + 123)
...
You can write any Scala code you want in an Ammonite script, including
top-level statements and definitions (e.g. the println
and
val x = 123
above) that are not valid in "normal" Scala
projects. You do not need to wrap these sorts of top-level statements
or expressions in boilerplate object Foo{...}
wrappers:
this is all done automatically for you by Ammonite.
After that, it's a matter of running the script From the REPL or From Bash, e.g.
bash$ amm MyScript.sc
Hello World!!
x is 123
...
No code stands alone; scripts depend on other scripts. Often they depend on third party libraries, as there's so much code out there already written it doesn't make sense to reinvent everything yourself.
Ammonite Scripts allow you to import Other Scripts, just like any Bash or Python scripts do. Furthermore, they let you cleanly depend on third party libraries: since Ammonite runs on the JVM, this means Ivy Dependencies. Ammonite will ensure that the relevant dependencies are always downloaded and used, and you never need to worry about remembering to "install" things before running your scripts!
Like other scripting languages, Ammonite Scripts allow you to break your
script into multiple files, and import them from each other in order to
use what is in each file. Unlike "Normal" Scala projects, there is no
need to set up a src/main/scala
folder, and create a build file,
and all these other things: simply split your script into two files, and
import one from the other using import $file:
// Basic.sc
val basicValue = 31337
// FileImport.sc
import $file.Basic
val fileImportVal = Basic.basicValue + 1
Here, we are defining a simple val
in Basic.sc
, and
then importing it from FileImport.sc
. And of course, we can
use what we defined in FileImport.sc
and import it in another
file
// IndirectFileImport.sc
import $file.FileImport
val indirectFileImportVal = FileImport.fileImportVal + 1
And so on, importing files as many or as deep as you want. You can
use ^
segments at the start of your import $file
to import things from outside the current script's enclosing folder, e.g.
import $file.^.^.foo
will import the script file
../../foo.sc
and make it available for you to use.
$file
imports inside Scala Scripts behave the same as
$file
imports within the Ammonite-REPL, and have the same characteristics:
You can easily make use of external Ivy/Maven artifacts right in your scripts, without needing to set up a separate build file. Simply use a import $ivy, just as you would in the Ammonite-REPL, and it will be available in the script for you to use, e.g. here we make use of the Scalatags library:
import $ivy.`com.lihaoyi::scalatags:0.7.0 compat`, scalatags.Text.all._
val rendered = div("Moo").render
If you need more detailed control over what you are importing, e.g.
with attributes, classifiers or exclusions, you can fall back to
using the interp.load.ivy(deps: coursierapi.Dependency*)
function.
@ import os._
@ interp.load.module($printedScriptPath/"loadIvyAdvanced.sc")
@ serializer
Note that to use this function, your script needs to be a
multi-stage script as listed below, and the interp.load.ivy
call needs to be in an earlier block
By default, everything in a script is compiled and executed as a single block. While you can use Magic Imports to load other scripts or Ivy/Maven artifacts before your script runs, those can only load "hardcoded" scripts or artifacts, and cannot e.g. load different scripts depending on some runtime variables.
If you want to load different scripts or Ivy/Maven artifacts depending on runtime values, you can use the runtime-equivalent of magic imports:
import $cp
becomes interp.load.cp
import $file
becomes interp.load.module
import $ivy
becomes interp.load.ivy
These are plain-old-Scala-functions that let you pass in a
Path
to a script to load, or load different Ivy/Maven artifacts
depending on runtime values. Additionally, there is an overloaded
version of interp.load.cp
which takes a Seq[Path]
of classpath entries. This variant is much more efficient for adding
multiple classpath entries at once.
Since these functions get run *after* the current compilation block is
compiled, you need to split your script into two compilation blocks,
and can only use the results of the load
ed code in
subsequent blocks:
// print banner
println("Welcome to the XYZ custom REPL!!")
val scalazVersion = "7.2.27"
interp.load.ivy("org.scalaz" %% "scalaz-core" % scalazVersion)
// This @ is necessary for Ammonite to process the `interp.load.ivy`
// before continuing
@
// common imports
import scalaz._
import Scalaz._
// use Scalaz!
...
In general, this should not be necessary very often: usually you should
be able to load what you want using Magic Imports.
Nevertheless, sometimes you may find yourself needing to get "under the
hood" and use these load
ing functions directly. When that
happens, using Multi-stage Scripts is the way to go.
Often when calling a script from the external command-line (e.g.
Bash), you need to pass arguments to configure its behavior. With
Ammonite, this is done by defining a @main
method, e.g.
// Args.sc
val x = 1
@main
def main(i: Int, s: String, path: os.Path = os.pwd) = {
s"Hello! ${s * i} ${path.last}."
}
When the script is run from the command line:
$ amm Args.sc 3 Moo
"Hello! MooMooMoo Ammonite."
The top-level definitions execute first (e.g. setting x
),
and then the @main
method is called with the arguments you
passed in. Note that the return-value of the script is pretty-printed
by default, which quotes strings and may nicely format/indent lists or
other data-structures. If you want to avoid this default pretty-printing
behavior, annotate your @main
method as returning
: Unit
and add your own println
s:
// Args.sc
val x = 1
@main
def main(i: Int, s: String, path: os.Path = os.pwd): Unit = {
println(s"Hello! ${s * i} ${path.last}.")
}
$ amm Args2.sc 3 Moo
Hello! MooMooMoo Ammonite
You can also pass in named arguments using --
to demarcate
them:
$ amm Args.sc -i 3 -s Moo
"Hello! MooMooMoo Ammonite."
Default arguments behave as you would expect (i.e. they allow you to
omit it when calling). Arguments are parsed using the
mainargs.Parser*
parsers, which provides parsers for primitives
like Int
, Double
, String
, as well as basic
data-structures like Seq
s (taken as a comma-separated list) and
common types like Paths.
If you pass in the wrong number of arguments, or if an argument fails to deserialize, the script will fail with an error message.
The main
method does not get automatically called when you
load.module
or load.exec
a script from within
the Ammonite REPL. It gets imported into scope like any other method or
value defined in the script, and you can just call it normally.
vararg*
arguments work as you would expect as well, allowing one or
more arguments to be passed from the command-line and aggregated into
a Seq
for your function to use:
@main
def entrypoint(args: String*) = {
...
}
in which case Ammonite will take all arguments and forward them to your
main method unchecked and unvalidated, from which point you can deal
with the raw Seq[String]
however you wish. Note that
vararg*
arguments cannot be passed by-name, e.g. via
--args foo
Ammonite passing any arguments that come before the script file to Ammonite itself, while arguments that come after the script file are given to the script:
$ amm --predef-code 'println("welcome!")' Args.sc 3 Moo
welcome!
"Hello! MooMooMoo Ammonite."
Note that on Windows you have to escape the quotes differently:
C:\> amm --predef-code "println(\"welcome!\")" Args.sc 3 Moo
Here, "Ammonite Arguments" go on the left of the Args.sc
, while
Script Arguments go on the right of the Args.sc
. The script
arguments on the right can also be empty if you don't want to pass
any arguments to the script.
If you want to define a script with a Shebang line that runs Ammonite with particular arguments, you can use
#!/bin/bash
exec amm --predef 'println("welcome!")' "$0" "$@"
!#
And which will pass in the --predef
flag to Ammonite while
running the script via ./Args.sc
. If you want to then pass
in different sets of arguments, you can run the script using amm
e.g. amm --predef 'println("Hello!")' Args.sc 3 Moo
as before.
(Note that while a single-line #!/usr/bin/env amm --predef '...'
shebang may work on some systems such as OS-X, it is not portable and
would not work on Linux)
If you have only a single @main
method, any arguments that
you pass to the script get used as arguments to that @main
.
But if you have multiple @main
methods, the first
argument to the script is used to select which @main
method
to call. e.g. given:
// MultiMain.sc
val x = 1
@main
def mainA() = {
println("Hello! " + x)
}
@main
def functionB(i: Int, s: String, path: os.Path = os.pwd) = {
println(s"Hello! ${s * i} ${path.relativeTo(os.pwd)}.")
}
You can call it via
amm MultiMain.sc mainA
Or
amm MultiMain.sc functionB 2 "Hello"
You can document your scripts with the @arg
annotation. By
default, a script such as
// MultiMain.sc
val x = 1
@main
def mainA() = {
println("Hello! " + x)
}
@main
def functionB(i: Int, s: String, path: os.Path = os.pwd) = {
println(s"Hello! ${s * i} ${path.relativeTo(os.pwd)}.")
}
Will result in a usage message:
| -i <int>
| --path <path>
You can add docs via
// MultiMainDoc.sc
val x = 1
@main
def mainA() = {
println("Hello! " + x)
}
@arg(doc = "This explains what the function does")
@main
def functionB(@arg(doc =
"how many times to repeat the string to make " +
"it very very long, more than it originally was")
i: Int ,
@arg(doc = "the string to repeat")
s: String ,
path: os.Path = os.pwd) = {
println(s"Hello! ${s * i} ${path.relativeTo(os.pwd)}.")
}
Which will be shown as part of the usage message
| -i <int>
| --path <path>
While Ammonite allows you to load any Java or Scala library for use via the import $ivy syntax, it also comes bundled with some basic libraries, e.g. Requests-scala for making HTTP calls, or the uPickle library with its JSON Api for dealing with the common JSON format.
For example, here's a tiny script that offers two main methods, one
to shorten a github link using Requests-Scala and the git.io
API,
and one that pulls out a list of release-names from a given github
project using Requests-Scala, uPickle's JSON package, and the Github API:
#!/usr/bin/env amm
// HttpApi.sc
import $ivy.{
`com.lihaoyi::requests:0.2.0 compat`,
`com.lihaoyi::ujson:0.7.5 compat`
}
lazy val jsonPlaceHolderBase =
Option(System.getenv("JSONPLACEHOLDER")).getOrElse {
"http://jsonplaceholder.typicode.com"
}
@main
def addPost(title: String, body: String) = {
ujson.read(
requests.post(
s"$jsonPlaceHolderBase/posts",
data = Seq(
"title" -> title,
"body" -> body,
"userId" -> "1"
)
).text()
).obj.get("id").map(_.num.toInt).getOrElse(0)
}
@main
def comments(postId: Int) = {
val json = ujson.read(
requests
.get(s"$jsonPlaceHolderBase/comments?postId=$postId")
.text()
)
val names = for{
item <- json.arr
name <- item.obj.get("name")
} yield name.str
names.mkString(",")
}
You can run amm
on the script to see what it can do
> amm HttpApi.sc
Need to specify a sub command: addPost, comments
And you can run the two functions (after using chmod +x
to make
the file executable) via
> ./HttpApi.sc addPost MyTitle MyContent
Or
> ./HttpApi.sc comments 100
"et occaecati asperiores quas voluptas ipsam nostrum,doloribus dolores ut dolores occaecati,dolores minus aut libero,excepturi sunt cum a et rerum quo voluptatibus quia,ex eaque eum natus"
Apart from bundling some third-party libraries for convenience,
Ammonite also provides some builtins you can use from scripts to
inspect and manipulate the interpreter itself. Note that this is
a much smaller set of functionality than the set of
Builtins available to the REPL: it won't have things
like the repl.prompt
, repl.history
, and other things
that only really make sense in the interactive REPL.
trait InterpAPI {
/**
* When running a script in `--watch` mode, re-run the main script if this
* file changes. By default, this happens for all script files, but you can
* call this to watch arbitrary files your script may depend on
*/
def watch(p: os.Path): Unit
/**
* A generalization of [[watch]], allows watching arbitrary values and not
* just the contents of file paths.
*/
def watchValue[T](v: => T): T
/**
* The colors that will be used to render the Ammonite REPL in the terminal,
* or for rendering miscellaneous info messages when running scripts.
*/
val colors: Ref[Colors]
/**
* Tools related to loading external scripts and code into the REPL
*/
def load: InterpLoad
/**
* resolvers to use when loading jars
*/
def repositories: Ref[List[Repository]]
/**
* Functions that will be chained and called on the coursier
* Fetch object right before they are run
*/
val resolutionHooks: mutable.Buffer[Fetch => Fetch]
/**
* Exit the Ammonite REPL. You can also use Ctrl-D to exit
*/
def exit = throw AmmoniteExit(())
/**
* Exit the Ammonite REPL. You can also use Ctrl-D to exit
*/
def exit(value: Any) = throw AmmoniteExit(value)
/**
* Functions that will be chained and called on the
* exitValue before the repl exits
*/
val beforeExitHooks: mutable.Buffer[Any => Any]
implicit def scalaVersion: ScalaVersion
def _compilerManager: ammonite.compiler.iface.CompilerLifecycleManager
}
trait LoadJar {
/**
* Load a `.jar` file or directory into your JVM classpath
*/
def cp(jar: os.Path): Unit
/**
* Load a `.jar` from a URL into your JVM classpath
*/
def cp(jar: java.net.URL): Unit
/**
* Load one or more `.jar` files or directories into your JVM classpath
*/
def cp(jars: Seq[os.Path]): Unit
/**
* Load a library from its maven/ivy coordinates
*/
def ivy(coordinates: Dependency*): Unit
}
trait InterpLoad extends LoadJar {
def module(path: os.Path): Unit
def plugin: LoadJar
}
If you want code to be loaded before you run any script, you can place
it in ~/.ammonite/predefScript.sc
. This is distinct from the REPL
pre-defined code which lives in ~/.ammonite/predef.sc
.
There are two way main ways to run Ammonite scripts: From the REPL and From Bash.
Apart from loading scripts within the Ammonite-REPL, You can also run scripts using the Ammonite executable from an external shell (e.g. bash):
$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.13-3.0.0) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
$ amm path/to/script.sc
All types, values and imports defined in scripts are available to commands entered in REPL after loading the script.
You can also make an Ammonite script self-executable by using a shebang
#!
. This is an example script named hello
. There
is no need to add the .sc
extension. The amm
command needs to be in the PATH
:
#!/usr/bin/env amm
println("hello world")
make it executable and run it from an external shell (e.g. bash):
$ chmod +x /path/to/script
$ /path/to/script
Ammonite also supports the JAVA_OPTS
environment variable for
passing arguments to the JVM that it runs inside, e.g. you can pass in
a custom memory limit via
bash$ JAVA_OPTS="-Xmx1024m" amm path/to/script.sc
To let it use only up to 1024 megabytes of memory
Ammonite provides the -w
/--watch
flag, which tells it to
not exit when a script completes, but instead watch the files that were
run, and re-run them when any of them change. You can use this flag via
$ amm -w foo.sc
Within your scripts, you can also flag other files you want Ammonite
to watch, via the interp.watch(p: Path)
function. This is useful
if you are iterating on a script together with some external data files
the script depends on, and you want to
When a script is not working as intended, it is useful to be able to
poke around in a REPL after the script has run, in order to see what
values are stored in which variables or what methods are available via
autocomplete. To do so, you can run the script using the
--predef
/-p
flag.
$ amm --predef foo.sc
This will run the script as normal, but on completion open up a REPL which has all the values defined in that script imported and ready to use. You can then poke around within the REPL as you wish.
Using --predef
/-p
to run a script and then open an
interactive REPL can be combined with the --watch
/-w
flag:
$ amm --watch --predef foo.sc
This will open up a REPL after the script runs, and when you exit the REPL it will watch the script file and the files that the script depends on, re-running the script and REPL if any of them change.
--predef
/-p
can be used to include a script file as a
predef before running any script or REPL, which is useful for a range
of things apart from serving as a debug REPL on any script.
You can load any script into the Ammonite REPL using the
import $file
syntax, for example here we import the above
MyScript.sc
file to access its x
value:
@ x // doesn't work yet
Compilation Failed
cmd0.sc:1: not found: value x
val res0 = x // doesn't work yet
^
@ import $file.MyScript
Welcome to the XYZ custom REPL!!
@ MyScript.x // You can refer to definitions from that module
res1: Int = 123
@ import MyScript._
@ x // works
res2: Int = 123
You can also import the module, and any associated definitions you want, in the same import:
@ x // doesn't work yet
Compilation Failed
cmd0.sc:1: not found: value x
val res0 = x // doesn't work yet
^
@ import $file.MyScript, MyScript._
Welcome to the XYZ custom REPL!!
@ x
res1: Int = 123
Note that by default, scripts imported via $file
are
encapsulated, so any imports inside that MyScript
performs are
not available outside of MyScript.sc
:
@ import $file.MyScript, MyScript._
Welcome to the XYZ custom REPL!!
import $file.$
@ mutable.Buffer(x)
cmd1.sc:1: not found: value mutable
val res1 = mutable.Buffer(x)
^
Compilation Failed
As you can see, even though collection.mutable
was imported inside
MyScript.sc
, you cannot use them outside after importing it.
If you want to make everything (both imports and definitions) available
by default after importing, you can use an $exec
import instead of
$file
:
@ import $exec.MyScript
Welcome to the XYZ custom REPL!!
import $exec.$
@ mutable.Buffer(x)
res1: mutable.Buffer[Int] = ArrayBuffer(123)
As you can see, now mutable
is available, and so is x
even
though we did not directly import it.
While $file
imports are useful for defining re-usable modules with
common functions and definitions, $exec
imports are useful as
aliases for common setup to get your REPL environment just the way you
want it. Of course, any files you import via import $file
or
import $exec
can themselves import other Scala scripts in the
same way, and the same rules apply.
Ammonite's Scala Scripts run as normal Scala code, though with some
simple source-to-source transformations applied first to turn the
script syntax (which allows top-level expressions, def
s,
val
s, etc.) into valid Scala syntax (which doesn't). What
happens is roughly:
~/.ammonite/cache
. If not, the script is parsed but not
yet compiled.package
/object
wrapper, corresponding to the
path to the script from the current script's enclosing folder.
For example, a script at path foo/bar/baz/Qux.sc
will be
wrapped in:
package foo.bar.baz
object Qux{
// script code
}
In general, due to Scala's slow compiler, Scala Scripts rely heavily on caching to achieve reasonable performance. While the first run of a modified script has a few-seconds overhead due to the Scala compiler, subsequent runs of the same script should be fast-ish, with only a few 100ms overhead for spinning up a JVM.
Although this is much slower than other scripting languages like Bash
(which starts up in ~4ms) or Python (~30ms), in practice it is
acceptable for many use cases. You probably do not want to
find . | xargs amm Foo.sc
on large numbers of files, where
the 100ms overhead will add up, but for individual scripts it should
be fine.
Furthermore, Ammonite makes it really easy to include that sort of
recursive/iterative logic inside a single script: you can use
ls!
or ls.rec!
from Ammonite-Ops to
traverse the filesystem and work on multiple files all within the same
process, which avoids duplicating the startup overhead on all the files
you are manipulating.
If you have an existing SBT project and you'd like to access those
classes from an ammonite script, you can achieve this by running
your script through SBT itself. This requires adding ammonite to your
SBT project and creating a "bridge" class to pass arguments from SBT
into an ammonite Main
class.
Add the ammonite 3.0.0 dependency to build.sbt
:
libraryDependencies += "com.lihaoyi" % "ammonite" % "3.0.0" % "test" cross CrossVersion.full
In your test directory, create a class like:
package ammonite.integration
object AmmoniteBridge {
def main(args: Array[String]): Unit = {
ammonite.AmmoniteMain.main(args)
}
}
Run your script using sbt "test:run /path/to/script.sc arg1 arg2 arg3"
.
If you have already started an SBT repl, then you can run the above without the quotes:
test:run /path/to/script.sc arg1 arg2 arg3
Running a script from your SBT project can be achieved with
ammonite.AmmoniteMain.main(Array("--predef-code", """println("welcome!")""", "file.sc"))
The Ammonite Scala REPL and Scripts are meant to be extended: you can load in arbitrary Java/Scala modules from the internet via import $ivy. Using this third-party code, you extend the REPL to do anything you wish to do. Simple install Java, download Ammonite onto any Linux/OSX machine, and try out one of these fun snippets! They work directly in the Ammonite-REPL, or you can save them to Scala Scripts if you want something more permanent.
Ammonite does not come with a built-in way to make HTTP requests, but there are Java /Scala modules that do this quite well! Here's an example:
Welcome to the Ammonite Repl
@ val resp = requests.get("https://api.github.com/repos/scala/scala")
@ val parsed = upickle.json.read(resp.text()).asInstanceOf[upickle.Js.Obj]
parsed: upickle.Js.Obj = Obj(
ArrayBuffer(
("id", Num(2888818.0)),
("name", Str("scala")),
("full_name", Str("scala/scala")),
(
"owner",
Obj(
ArrayBuffer(
("login", Str("scala")),
...
@ for((k, v) <- parsed.value) os.write(os.pwd/'target/'temp/k, upickle.json.write(v))
@ os.list(os.pwd/'target/'temp)
res6: LsSeq = LsSeq(
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/temp/archive_url,
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/temp/assignees_url,
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/temp/blobs_url,
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/temp/branches_url,,
...
In this example, we use the Requests-Scala library to download a URL, and we use uPickle and OS-Lib to parse the JSON and write it into files. uPickle and Ammonite-Ops are bundled with the Ammonite REPL and are used internally.
This is a small example, but it illustrates the potential: if you find yourself needing to scrape some website or bulk-download large quantities of data from some website's HTTP/JSON API, you can start doing so within a matter of seconds using Ammonite. The results are given to you in nicely structured data, and you can deal with them using any Java or Scala libraries or tools you are used to rather than being forced to munge around in Bash. Sometimes, you may find that you need to get data from somewhere without a nice JSON API, which means you'd need to fall back to Scraping HTML...
Not every website has an API, and not every website is meant to be accessed programmatically. That doesn't mean you can't do it! Using libraries like JSoup, you can quickly and easily get the computer to extract useful information from HTML that was meant to humans. Using the Ammonite REPL, you can do it interactively and without needing to set up annoying project scaffolding.
@ import $ivy.`org.jsoup:jsoup:1.7.2`
@ import org.jsoup._ // import Jsoup
@ import collection.JavaConversions._ // make Java collections easier to use
@ val doc = Jsoup.connect("http://en.wikipedia.org/").get()
@ doc.select("h1")
res54: select.Elements = <h1 id="firstHeading" class="firstHeading" lang="en">Main Page</h1>
@ doc.select("h2") // this is huge and messy
res55: select.Elements = <h2 id="mp-tfa-h2" style="margin:3px; background:#cef2e0; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; text-align:left; color:#000; padding:0.2em 0.4em;"><span class="mw-headline" id="From_today.27s_featured_article">From today's featured article</span></h2>
<h2 id="mp-dyk-h2" style="margin:3px; background:#cef2e0; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3bfb1; text-align:left; color:#000; padding:0.2em 0.4em;"><span class="mw-headline" id="Did_you_know...">Did you know...</span></h2>
...
@ doc.select("h2").map(_.text) // but you can easily pull out the bits you want
res56: collection.mutable.Buffer[String] = ArrayBuffer(
"From today's featured article",
"Did you know...",
"In the news",
"On this day...",
"From today's featured list",
"Today's featured picture",
"Other areas of Wikipedia",
"Wikipedia's sister projects",
"Wikipedia languages",
"Navigation menu"
)
If you wanted to scrape headlines off some news-site or scrape video game reviews off of some gaming site, you don't need to worry about setting up a project and installing libraries and all that stuff. You can simply load libraries like Jsoup right into the Ammonite REPL, copy some example from their website, and start scraping useful information in less than a minute.
The Ammonite REPL runs on the Java virtual machine, which means you can use it to create Desktop GUI applications like anyone else who uses Java! Here's an example of how to create a hello-world interactive desktop app using Swing
@ {
import javax.swing._, java.awt.event._
val frame = new JFrame("Hello World Window")
val button = new JButton("Click Me")
button.addActionListener(new ActionListener{
def actionPerformed(e: ActionEvent) = button.setText("You clicked the button!")
})
button.setPreferredSize(new java.awt.Dimension(200, 100))
frame.getContentPane.add(button)
frame.pack()
frame.setVisible(true)
}
This can be run inside the Ammonite REPL without installing anything, and will show the following window with a single button:
When clicked, it changes text:
Although this is just a small demo, you can use Ammonite yourself to experiment with GUI programming without needing to go through the hassle of setting up an environment and project and all that rigmarole. Just run the code right in the console! You can even interact with the GUI live in the console, e.g. running this snippet of code to add another action listener to keep count of how many times you clicked the button
@ {
var count = 0
button.addActionListener(new ActionListener{
def actionPerformed(e: ActionEvent) = {
count += 1
frame.setTitle("Clicks: " + count)
}
})
}
Which immediately becomes visible in the title of the window:
Even while you're clicking on the button, you can still access count
in the console:
@ count
res12: Int = 6
This is a level of live interactivity which is traditionally hard to come by in the world of desktop GUI applications, but with the Ammonite REPL, it's totally seamless
You can also import JavaFX applications, using ScalaFX. This is easiest if you create a file `jfx.sc` to contain the relevant imports:@ {
import $ivy.{
`org.scalafx::scalafx:16.0.0-R24`
}
lazy val osName = System.getProperty("os.name") match {
case n if n.startsWith("Linux") => "linux"
case n if n.startsWith("Mac") => "mac"
case n if n.startsWith("Windows") => "win"
case _ => throw new Exception("Unknown platform!")
}
val javaFXModules = Seq("base", "controls", "fxml", "graphics", "media", "swing", "web")
javaFXModules.map(m =>
interp.load.ivy(coursierapi.Dependency.of("org.openjfx", s"javafx-$m", "15.0.1").withClassifier(osName))
)
}
And then you can use `import $file.jfx` with the ScalaFX DSL.
@ {
import $file.jfx
import scalafx.application.JFXApp3
import scalafx.application.JFXApp3.PrimaryStage
import scalafx.geometry.Insets
import scalafx.scene.Scene
import scalafx.scene.layout.HBox
import scalafx.scene.paint.Color._
import scalafx.scene.paint._
import scalafx.scene.text.Text
import scala.language.implicitConversions
@main
def main() {
JFXApp3Demo.main(Array())
}
object JFXApp3Demo extends JFXApp3 {
override def start(): Unit = {
stage = new PrimaryStage {
title = "ScalaFX Hello World!"
scene = new Scene {
fill = Color.rgb(38, 38, 38)
content = new HBox {
padding = Insets(50, 80, 50, 80)
children = Seq(
new Text {
text = "Hello World!"
style = "-fx-font: normal bold 100pt sans-serif"
fill = new LinearGradient(endX = 0, stops = Stops(Red, DarkRed))
}
)
}
}
}
}
}
}
Apart from writing code, you very often find yourself dealing with documents and spreadsheets of various sorts. This is often rather tedious. Wouldn't it be cool if you could deal with these things programmatically? It turns out that there are open-source Java libraries such as Apache POI that let you do this, and with the Ammonite-REPL you can quickly and easily load these libraries and get to work on your favorite documents. Here's an example extracting some data from my old Resume, in .docx
format:
@ import $ivy.`org.apache.poi:poi-ooxml:3.13`
@ import org.apache.poi.xwpf.usermodel._ // Bring Ms-Word APIs into scope
@ import collection.JavaConversions._ // Make use of Java collections easier
@ val path = pwd/'amm/'src/'test/'resources/'testdata/"Resume.docx"
@ val docx = new XWPFDocument(new java.io.ByteArrayInputStream(os.read.bytes(path)))
@ docx.get<tab>
getAllEmbedds getParagraphArray
getAllPackagePictures getParagraphPos
getAllPictures getParagraphs
getBodyElements getParagraphsIterator
getBodyElementsIterator getParent
getClass getPart
getCommentByID getPartById
getComments getPartType
getDocument getPictureDataByID
...
@ docx.getParagraphs.map(_.getText)
res28: collection.mutable.Buffer[String] = ArrayBuffer(
"""
Haoyi Li
""",
"""
Education Massachusetts Institute of Technology Cambridge, MA
""",
"""
Bachelor of Science degree in Computer Science, GPA 4.8/5.0 Sep 2010 - Jun 2013
""",
"""
Work Dropbox San Francisco, CA
"""
...
@ docx.getHyperlinks.map(_.getURL)
res27: Array[String] = Array(
"http://vimeo.com/87845442",
"http://www.github.com/lihaoyi/scalatags",
"http://www.github.com/lihaoyi/scala.rx",
"http://www.github.com/lihaoyi/scala-js-fiddle",
"http://www.github.com/lihaoyi/metascala",
"https://www.github.com/lihaoyi/macropy",
"http://www.github.com/lihaoyi",
"http://www.github.com/lihaoyi"
)
As you can see, loading the Apache POI library is just a single command, reading in my resume file is just one or two more, and then you can immediately start exploring the document's data model to see what inside interests you. You even get tab-completion on the methods of the document, making it really easy for you to interactively explore all the things that a word document has to offer!
This is just a small example, but you can easily do more things in the same vein: Apache POI lets you create/modify/save .docx
files in addition to reading from them, meaning you can automatically perform batch operations on large numbers of documents. The library also provides mechanisms to load in Excel spreadsheets and Powerpoint slide decks, meaning you have easy, programmable access to the great bulk of any Microsoft-Office files you find yourself dealing with.
You can perform lots of image operations in Java. You can use BufferedImage if you want to access the low-level details or read/write individual pixels, and using Java2D you can draw shapes, perform transforms, or do anything you could possibly want to do with the images.
There are also simple libraries like Thumbnailator if you're doing basic things like renaming/resizing/rotating and don't need pixel-per-pixel access. This is an example of using Thumbnailator to resize a folder of images and put them somewhere else:
@ import $ivy.`net.coobird:thumbnailator:0.4.8`
@ import net.coobird.thumbnailator._
import net.coobird.thumbnailator._
@ val images = ls! pwd/'amm/'src/'test/'resources/'testdata/'images
images: LsSeq = LsSeq(
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/repl/src/test/resources/testdata/images/GettingStarted.png,
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/repl/src/test/resources/testdata/images/Highlighting.png,
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/repl/src/test/resources/testdata/images/SystemShell.png
)
@ val dest = pwd/'target/'thumbnails
dest: Path = /Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/thumbnails
@ mkdir! dest
@ for(i <- images) {
Thumbnails.of(i.toString).size(200, 200).toFile(dest/i.last toString)
}
@ val thumbnails = ls! dest
thumbnails: LsSeq = LsSeq(
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/thumbnails/GettingStarted.png,
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/thumbnails/Highlighting.png,
/Users/haoyi/Dropbox (Personal)/Workspace/Ammonite/target/thumbnails/SystemShell.png
)
@ images.map(_.size) // Original image files are pretty big
res44: Seq[Long] = List(180913L, 208328L, 227570L)
@ thumbnails.map(_.size) // Thumbnailed image files are much smaller
res45: Seq[Long] = List(11129L, 11790L, 11893L)
The word "Machine Learning" sounds big and intimidating, like something you'd need to spend 6 years getting a PhD before you understand. What if you could "do some machine-learning" (whatever that means) in your spare time, in a minute or two? It turns out there are many Java libraries that can help you with basics, and with the Ammonite REPL getting started is easy.
Here's one example of how you can get started using the OpenNLP project to do some natural-language processing in just a few minutes. The example was found online, and shows how to extract English names from a raw String
using NLP:
@ import $ivy.`org.apache.opennlp:opennlp-tools:1.6.0` // load OpenNLP
@ val tokenDataUrl = "http://opennlp.sourceforge.net/models-1.5/en-token.bin"
@ val tokenData = requests.get(tokenDataUrl)
@ import opennlp.tools.tokenize._ // let's get started with OpenNLP!
@ val str = "Hi. How are you? This is Mike. Did you see book about Peter Smith?"
@ import java.io.ByteArrayInputStream
@ val tokenModel = new TokenizerModel(new ByteArrayInputStream(tokenData.text))
@ val tokenizer = new TokenizerME(tokenModel)
@ val tokens = tokenizer.tokenize(str)
tplems: Array[String] = Array(
"Hi",
".",
"How",
"are",
"you"
...
@ import opennlp.tools.namefind._ // Turns out we need more test data...
@ val nameDataUrl = "http://opennlp.sourceforge.net/models-1.5/en-ner-person.bin"
@ val nameData = Http(nameDataUrl).asBytes
nameData: HttpResponse[Array[Byte]] = HttpResponse(
Array(
80,
75,
3,
4,
20,
...
@ val nameModel = new TokenNameFinderModel(new ByteArrayInputStream(nameData.body))
@ val nameFinder = new NameFinderME(nameModel)
nameFinder: NameFinderME = opennlp.tools.namefind.NameFinderME@491eb5ef
@ val names = nameFinder.find(tokens)
names: Array[opennlp.tools.util.Span] = Array([8..9) person, [15..17) person)
@ opennlp.tools.util.Span.spansToStrings(names, tokens) // Woohoo, names!
res96: Array[String] = Array("Mike", "Peter Smith")
This took a while, but only in comparison to the earlier cookbook recipes: this one is still less than 20 steps, which is not bad for something that installs multiple third-party modules, pulls down training data off the internet, and then does natural language processing to extract the English names from a text blob!
Obviously we did not go very deep into the field. If you did, it would definitely be a lot more reading and understanding than just blindly following tutorials like I did above, and you probably would find it worth the time to set up a proper project. Nevertheless, this quick 5-minute run through of how to perform the basics of NLP is a fun way to get started whether or not you decide to take it further, and is only possible because of the Ammonite REPL!
/**
* Single-file play framework application!
*/
import $ivy.{
`com.typesafe.play::play:2.5.0`,
`com.typesafe.play::play-netty-server:2.5.0`,
`com.lihaoyi::requests:0.2.0`
}
import play.core.server._, play.api.routing.sird._, play.api.mvc._
val server = NettyServer.fromRouter(new ServerConfig(
rootDir = new java.io.File("."),
port = Some(19000), sslPort = None,
address = "0.0.0.0", mode = play.api.Mode.Dev,
properties = System.getProperties,
configuration = play.api.Configuration(
"play.server.netty" -> Map(
"maxInitialLineLength" -> 4096,
"maxHeaderSize" -> 8192,
"maxChunkSize" -> 8192,
"log.wire" -> false,
"eventLoopThreads" -> 0,
"transport" -> "jdk",
"option.child" -> Map()
)
)
)) {
case GET(p"/hello/$to") => Action { Results.Ok(s"Hello $to") }
}
try {
println(requests.get("http://localhost:19000/hello/bar").text())
} finally{
server.stop()
}
Ammonite's script-running capabilities can also be used as a way to set up lightweight Scala projects without needing SBT or an IDE to get started. For example, here is a single-file Play Framework test that
And can be run via
./amm PlayFramework.sc
Although this is just a hello world example, you can easily keep the server running (instead of exiting after a test request) and extend it with more functionality, possibly splitting it into multiple Script Files.
Ammonite is great for those database jobs that are too complicated for SQL alone. This example uses ScalikeJDBC to update some rows.
@ import $ivy.{
`org.scalikejdbc::scalikejdbc:3.0.0`,
`ch.qos.logback:logback-classic:1.2.3`,
`mysql:mysql-connector-java:5.1.6`
}
@ Class.forName("com.mysql.jdbc.Driver")
@ import scalikejdbc._
@ ConnectionPool.singleton("jdbc:mysql://localhost/database", "root", "")
@ implicit val session = AutoSession
@ val users =
sql"""select id, email from users"""
.map(rs => rs.long("id") -> rs.string("email")).list.apply()
users: List[(Long, String)] = List((1L, "foo@bar"), (2L, "bar@baz"))
@ def isNormalised(email: String): Boolean = ???
@ def normaliseEmail(email: String): String = ???
@ val usersWithInvalidEmail =
users.filterNot { case (id, email) => isNormalised(email) }
usersWithInvalidEmail: List[(Long, String)] = List((1L, "foo@bar"), (2L, "bar@baz"))
@ usersWithInvalidEmail.foreach { case (id, email) =>
val updatedEmail = normaliseEmail(email)
sql"""update users set email = ${updatedEmail} where id = ${id};""".update.apply()
}
Ammonite is primarily maintained by Li Haoyi, with a lot of help from Laszlo Mero over the summer through Google Summer of Code, and help from many other contributors. We have an active Gitter channel and a mailing list:
While most people would be using Ammonite for the latest version of Scala, 3.2, Ammonite also provides standalone executables for older versions of Scala:
Scala 3.0.0/2.12-3.0.0$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.12-3.0.0) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
Ammonite can also be used in old versions of Scala, embedded in an SBT project, without any special modifications.
I've also given a number of talks about Ammonite at conferences:
Here's the Scaladoc for the various projects:
Although it's best to read the documentation on this page to learn how to use these projects, the Scaladoc is still useful as a reference.
2.5.7
.@main
annotation supportammonite.AmmoniteMain
#1229given
-s as suchSystem.exit
in scripts when running in --watch
-mode (for Java versions below 17)@main
method functionality with the
MainArgs library-i
can no longer be passed via --i
,
the @doc("")
is now @arg(doc = "")
, Seq[T]
parameters
are now passed via repeated --foo
flags rather than comma-separated.@main
method handling in scripts run via --class-based
2.13.0-M5
1.1.0-M13
--class-based
)MissingRequirementError
when starting AmmoniteNoSuchFileException
when starting Ammonite on a clean machineammonite.ops.write
now no longer creates enclosing folders by default;
pass in the createFolders = true
flag to make it do soammonite.ops.ln.s
is swapped, for
consistency with the underlying Java APIs
ammonite.ops
namespace remains for backwards compatibility, and continues to contain
all the extension methods & shorthand syntax that OS-Lib does not, but
for general-purpose scripting and programming you should now use OS-Libamm
is run in different folders, to
avoid unwanted caching if script compilation depends on filesystem pathammonite-repl
module to be properly usable without
the main ammonite
package, thanks to
Alex Archambaultimport $url.{`https://raw.githubusercontent.com/lihaoyi/Ammonite/master/amm/src/test/resources/scripts/Annotation.sc` => remote}
The content at the URL will be wrapped into the remote
object, which
can be accessed later:
remote.product(1, List(2, 3, 4))
Note that this functionality is experimental and may be subject to
change or removal in future.
ls.rec
on path including
inaccessible files would throw java.nio.file.AccessDeniedException
thanks to Piotr Kwiecinski--color
which can be set to
true
or false
to force colors on or off if you
are not happy with the default behavior.
repl.colors
builtin has been moved to interp.colors
,
and allows you to fine-grained customize colors for e.g. error
messages and info messages when running scripts.
import $file
on an empty script files no longer
causes spurious errors
import $file
is deleted
-w
/--watch
now watches predef files as well. This means
if you make changes to your predef (e.g. if it was crashing and you're
trying to fix it), Ammonite will re-run your scripts automatically
<console>
.
Ctrl C
interrupts now place an exception with a useful stack
trace in repl.lastException
, which can help debug where your
code was at when you interrupted it.
Ctrl C
no longer crashes the REPL if you perform it after
entering a command but before your code starts runningimport $ivy
no longer fails if it cannot find source
dependencies, instead merely printing a warning.interp.load.exec
and interp.load.apply
have been moved to repl.load.exec
and repl.load.apply
,
and are now not available when running scripts: they never had a
really well-defined semantic when run within scripts. Using
repl.load.exec
or repl.load.apply
within the
predef.sc
of your REPL is still possible
interp.watch
built-in now works on folders as well as
files, watching all files within that folder and restarting your
script if any of them changeMain#run
--watch
flag more robust against files being deleted
during mtime
ing, and make it properly re-run scripts when a
file in a watched folder is renamed.@arg
annotations on a script's @main
methods as part of the script's help text, thanks to
mgedigian:::
as part of your import $ivy
calls to load Scala libraries cross-published against the full
Scala version (e.g. 2.12.2
rather than just 2.12
, thanks
to aeffrig
--predef
/--predef-file
are now
--predef-code
/--predef
respectively, to reflect that
using a custom predef file is much more common than a custom predef
code snippet.ammonite.Main
's argument predef
has been renamed to
predefCode
, and a new argument predefFile
has been
added to match the command-line interface--predef
(previously --predef-file
) now adds a file
in addition to the existing predef.sc
or predefScript.sc
in ~/.ammonite
. If you want it to replace the predef in
~/.ammonite
, there is a new flag --no-home-predef
that
disables the predef in ~/.ammonite
so your --predef
file stands alone
~/.ammonite/predefShared.sc
is gone; if you want it back, you
can do it yourself by adding import $exec.predefShared
within your predef.sc
and predefScript.sc
files. You
can also import any others files into your predef.sc
and
predefScript.sc
the same way
sys.props
by default, when running as a standalone
executable. When using Ammonite within a SBT project, you will need
to do this manually, e.g. calling
ammonite.main.ProxyFromEnv.setPropProxyFromEnv()
within the
predefCode
that you pass to ammonite.Main
--
, now any arguments before the script file are used by
Ammonite and any arguments after the script file get forwarded
to the script's @main
method
src
builtin to source
to reduce chance of
name collisions--foo
and -foo
stderr
rather than stdout
ammonite
package; this lets us avoid littering the
top-level package namespace with miscellaneous names like $file
and $sess
foo ! bar ! baz
implicit syntax, and
ChainableConversions
implicit. They're cool, but not simple
enough to be worth including by default
foo |> show
syntax in the REPL, which regressed in 0.9.0
Path(...)
no longer automatically expands ~
to your home
directory, for consistency with other filesystem APIs. Use
Path.expandUser
to do so manually.
-w
/--watch
Watch and Reload flag,
which lets you run a script repeatedly every time you change its code,
via amm -w foo.sc
. This is useful when you are actively
working on the script and greatly reduces the iteration time. You can
also manually include files you wish to watch, e.g. if you are
iterating on external data or config files.
$file
s from within your predef now properly makes them
available within your REPL, the same way other imports are #616~/.ammonite/predef.sc
with the new predef code.
show
and browse
built-ins, which
caused their default configuration to be un-usable #613scala.xml.Elem
to use its XML
.toString
rather than treating it as a case class, since the
case-class representation is borked due to weirdness in that class.Path
s, RelPath
s and the
result of sub-processes and file-listings in the default REPL (previously
these improved-pretty-printers were limited to ammonite-shell
)
--
toString
is the empty string.
Spark.sc
and Spark2.sc
scripts in the repository as examples to
get started. Spark support is currently experimental, so feel free
to contribute fixes when you notice something missing or wrong!interp.configureCompiler
builtin, which lets
you configure the compiler in a way that's robust in the case of
caching and late/lazy initialization, fixing #472.
You should use interp.configureCompiler
instead
of repl.compiler
to configure it safely.import $ivy
s in subsequent blocks. Fixes
#491amm
command. Any arguments after the script file get
delegated to the script's @main
method(s) unless
there is a --
present, in which case arguments after the
--
get delegated to the script while those before get
passed to Ammonite. This allows you to define a @main
method with a vararg String*
that accepts in all arguments
by default, letting you use your own custom arg parsers on the input
strings. Fixes #423, #479, #538@main
methods
or exit(...)
calls now gets pretty-printed by default when
the script completes. This make composing scripts much more convenient:
the same @main
methods you use when printing output to the
command-line can also be used from Scala code when imported from
other scripts. To disable this, annotate your main method as returning
: Unit
exit
can now be cleanly used in Scripts without failing
with a NullPointerException
, in addition to its existing use
in the REPL.--no-remote-logging
command-line
flag or the remoteLogging=false
argument to Main
.
@main
(#591)ammonite.ops.Path(s: String)
now resolves ~
to the
home directory of the current userFileAlreadyExistsException
when compiling scripts in
parallel (#567), by armanbilgebeforeExitHooks
so you can register cleanup code (#581), by
emanresusernameShellout.executeStream
to reduce spinning. (#578), by
rorygravesgetClass.getClassLoader.getResource
, thanks to
jhnsmthCtrl-u
and Ctrl-k
now cut to the beginning/end of the
current line (#514), rather than the entire input block, thanks to
Jordan GwynNullPointerException
on no-save-then-load situation in REPL,
thanks to Roman Tkalenko.iter
versions of file operations return
geny Generator
s
rather than Iterator
s, which should avoid problems with
leaking file handles
ammonite.ops.Path
that was allowing invalid
paths with empty segments to be constructed.
cd!
ing into sym-links, thanks to
Roman Tklalenko and
Sergei Winitzki-s
switch, thanks to coderabhishek--predef-file
switch now allows multiple inputs, allowing
you to pass in multiple files that all get evaluated as the predef
import.$ivy
no longer caches -SNAPSHOT
versions,
thanks to Julie Pittammonite.ops.cwd
in preference to ammonite.ops.pwd
,
to help clear up confusion between cwd
and local wd
s,
thanks to Julie Pitt
amm
standalone
executable, so it no longer grows to the "default" of 1/4 your system
memory (typically multiple gigabytes) unnecessarily. If you need to
give it more memory, start it with JAVA_OPTS=-Xmx1500M amm
{...}
blocks in scripts, leaving
the unwrapping of Block Input only a feature of the interactive
REPL
-s
cmd line switch makes ivy logs silent, though failures
will still be thrown as exception. Thanks to coderabhishek.show
and typeOf
back into the default REPL
imports, since they are pretty usefulwrite.over
in Ammonite-Ops should now properly
truncate files if the thing being written is shorter than the
original #441import $file.*
repl
object. This is a backwards incompatible
change!load.*
and
resolvers
in the interp
object)
from those available from the REPL (in the repl
object).
repl
is not available when running scripts, unless you pass in
the --repl-api
flag at the command line.import repl._
in your ~/.ammonite/predef.sc
and
import interp._
in your ~/.ammonite/predefShared.sc
to
bring everything back into scope again.predef.sc
now only applies to the interactive REPL. If you
want predef code that applies to scripts use predefScript.sc
,
or if you want predef code that applies to both you can use
predefShared.sc
.import $file
segments outside your
current directory from import $file.`..`.foo
to
import $file.^.foo
. This makes it a lot shorter and
mitigates a problems caused by the file-name being too long.JAVA_OPTS
environment variable to pass flags
to the JVM when starting Ammonite, thanks to Simon Scarduzio.sc
can now be run directly from the command line
rather than throwing an IndexOutOfBoundsException
, thanks to
coderabhishekammonite
has now
been broken into 5 smaller modules for maintainability. This in
itself should not be visible to the outside world, but be sure to
report any bugs!
.scala
to .sc
, to avoid problems with SBT
discovering and trying (and failing) to compile them as normal Scala
files.Ctrl p
and Ctrl n
have been tweaked to
be more consistent with other readline implementations.@
that the
old load.foo
functions requiredload.module
, load.exec
, load.ivy
are
now largely superseded by import $file
,
import $exec
, and import $ivy
AmmoniteFrontEnd
, thanks to
coderabhishek who worked
on this over GSOC.~/.ammonite/
storage folder, not the InMemory
storage system.
This restores the pre-0.5.9 behavior_root_
to imports from packages, which should
reduce the chance of naming collisionsMain.scala
), and line numbers matching the original line
numbers (instead of the line numbers in the synthetic code) thanks
to coderabhishekload.module
should show only the meaningful error and not
irrelevant internal stacktracesMyScript
) rather than based on the code hash (e.g.
cache5a8890cd7c2ab07eea3fe8d605c7e188
)ammonite.scripts
and code entered at the REPL goes in
ammonite.session
..map
as |
,
.filter
as |?
, etc. to make it more convenient to use
tools like grep from the base REPLkill
command in Ammonite-Ops, thanks to
杨博'\u001b'
escape character removed, rather than messing up the REPL rendering
write
has been generalized to work on any combination of
Array
, Traversable
and Iterator
.
e.g. write(foo: Iterator[Iterator[Array[String]]])
write
no longer inserts newlines between items by default.Path
segments to
make them more specific and suggest alternatives to what a user is
trying to do.FilePath
sub-trait from the
BasePath
trait, to differentiate those
BasePath
s are filesystem paths and can be constructed from
java.nio.file.Path
or java.io.File
s
(RelPath
and Path
)from those which can't
(ResourcePath
)Path.makeTemp
has been renamed tmp()
and
tmp.dir()
\u033O{A,B,C,D}
" codes instead of
\u033[{A,B,C,D}
codesscala.io.Codec
instead of a String
or
Charset
, letting you pass in either of those types and
having it be implicitly converted.
read!
commands to be
competitive with java.nio
(#362)read!
and read.lines!
now take an optional
charset, passed via read(file, charSet: String)
or
read.lines(file, charSet: String)
which defaults to
"utf-8"
read! resource
read from the
Thread.currentThread.getContextClassLoader
by default,
fixing #348Class
s or ClassLoader
sread!
work on InputStream
sInputPath
to Readable
, a more
appropriate name now that it works on two different non-path entities
(resources and InputStream
s)ls
ing large directories./amm
using relative paths #353repl
no longer borks your session.AmmoniteFrontEnd
: Ctrl-T
and Alt-T
now properly transpose characters and words, and the
kill-ring now properly aggregates multiple consecutive kills.rm
cp
and mv
to prevent you
from removing the root folder, or copying/moving folders into
themselves.Ctrl -
and
redo via Esc/Alt -
are now supported.Path
s: they
now wrap a java.nio.file.Path
(#346), and thus can be used on
Windows, on multiple drives, or with virtual filesystems such as
JimFS.Path
s from various types
(String
s, java.nio.file.Path
,
java.io.File
) is much more well behaved & consistent now.read.resource! root/'foo
is now
read! resource/'foo
cp
and mv
now have .into
and
.over
modes #206repl.lastException
variable #289, in case you need more
metadata from it or you want the stack-trace of a
non-printed-by-default exception (e.g. ThreadDeath
due to
Ctrl-C
). Thanks to coderabhishek!Range.Inclusive
#337,
thanks to Sahebtype
s and
val
s #199BACKSPACE
now drops you out of history-browsing
properly, preserving your edits if you then press ENTER
without entering any other characters #338compiler.settings.nowarn.value = false
unknown
resolver null
warnings when resolving dependencies (#144)ls!!
ls.rec!!
and read.lines!!
have been renamed ls.iter!
ls.rec.iter!
and read.lines.iter!
, to help cut
down on cryptic operatorstime
command, allowing easy timing of
simple commandsls.rec
now exposes basic configurability of the recursion,
allowing you to skip directories or controlling the pre/post-order
of resultsPath
s and RelPath
s no longer permit
"."
or ".."
as a path segment #215Path
s and RelPath
s now us
Vector[String]
instead of Seq[String]
as the
segments
data-structure, promising more consistent
semanticsls!
now properly gets
truncated when too large #209CommandResult
type being returned from the
%%
operator, to now properly capture the raw byte output,
stdout, stderr, exit code. #207ammonite.Repl.run
and ammonite.Repl.debug
into
ammonite.Main.run
and ammonite.Main.debug
def<tab>
auto-complete crasher #257, thanks to
Matthew Edwards![Enter]
now only submits the input if your cursor
is at the bottomSeq[String]
s into subprocess argumentscd!
,
wd
, path-completion) has been pulled out of
Ammonite-REPL, and is now available separately as
Ammonite-Shell.ls
and
ls.rec
commandsLoad.ivy
now properly attempts to load artifacts from
the local ~/.ivy/cache
, ~/.ivy/local
and ~/.m2
folders, before fetching from maven centralcache1234567890abcdef1234567890abcdef
objects from
the autocomplete list, because they're not helpfulAny
from the default
import lists.read.lines
and
ls
/ls.rec
@
-delimited block in a script loaded
via load.module
gets its names dumped into the REPL's
environment now, letting you create some semblance of hygiene,
thanks to Laszlo MeropathSeparator
so Ammonite-REPL is at least
basically-runnable on windows, although buggytoString
~/.ammonite
folder. This
includes ~/.ammonite/history
,
~/.ammonite/predef.scala
, and various cache, thanks to
Laszlo Mero~/.ammonite/predef.scala
Configuration file which will be executed the first
thing when the Ammonite REPL is loaded. This is useful for common
imports, load.ivy
ing libraries, or other configuration
for your REPLload.exec
and load.module
, thanks to
Laszlo MeroREPL
s constructor is now done in-REPL,load.ivy
no
longer causes all existing values to be lazily recomputed.Unit
are no longer echo-ed to
the userload.ivy
is now cached
after the first call, letting you e.g. load libraries in your
~/.ammonite/predef.scala
without waiting for the slow
ivy-resolution every startupgit
commands, edit
files via vim
, open ssh
sessions or even start
SBT
or Python
shells right from your Scala REPLPPrint
s are much lazier and will
avoid stringifying the whole collection if it's going to get truncated
anyway.TPrint[T]
s to provide custom
printing for any type.predef
parameter to be passed into
Main.run()
call, letting you configure initialization
commands or importsCtrl-C
and Ctrl-D
handling, to
make it behave more like other REPLs
The page above contains the documentation for the latest stable version
of Ammonite, 3.0.0
. Ammonite also publishes
unstable versions, the latest of which is
3.0.0-2-6342755f
and is available for direct
download:
$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.13-3.0.0-2-6342755f) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
On Cygwin, run the following after the above:
$ sed -i '0,/"\$0"/{s/"\$0"/`cygpath -w "\$0"`/}' /usr/local/bin/amm
The latest build can also be run as Windows batch; just save the following as amm.bat:
https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.13-3.0.0-2-6342755f
For usage in a SBT project:
libraryDependencies += "com.lihaoyi" % "ammonite" % "3.0.0-2-6342755f" % "test" cross CrossVersion.full
Ammonite also provides standalone unstable executables for older versions of Scala:
Scala 3.0.0/2.12-3.0.0-2-6342755f$ sudo sh -c '(echo "#!/usr/bin/env sh" && curl -L https://github.com/com-lihaoyi/Ammonite/releases/download/3.0.0/2.12-3.0.0-2-6342755f) > /usr/local/bin/amm && chmod +x /usr/local/bin/amm' && amm
These unstable versions will contain any brand-new features that are currently being worked on, with the caveat that they are unstable and these features are subject to change or experimentation. They will generally work - the automated test suite is pretty comprehensive - but they are still more-likely to have bugs than numbered releases.
Any pull-request that gets merged into the main branch is published as an unstable version automatically within an hour or two of being merged, so if you notice some problem and know how to fix it, send a PR, get it merged, and you can use the published unstable version with your fix until the next numbered release.