kuroko/README.md

752 lines
21 KiB
Markdown
Raw Normal View History

2020-12-26 10:59:43 +03:00
# Kuroko - A bytecode-compiled scripting language
2020-12-29 09:39:34 +03:00
Kuroko is a bytecode-interpreted, dynamic, strongly-typed language with syntax similar to Python.
2020-12-28 10:08:06 +03:00
2020-12-29 09:39:34 +03:00
The bytecode VM / compiler is substantially based on Robert Nystrom's [_Crafting Interpreters_](https://craftinginterpreters.com/).
2020-12-26 10:59:43 +03:00
2020-12-29 09:39:34 +03:00
At the moment, the intent for this project is to add a proper scripting language to [Bim](https://github.com/klange/bim), to which both configuration scripts and syntax highlighting will be ported.
2021-01-02 06:29:30 +03:00
Kuroko, [as its name should imply](https://toarumajutsunoindex.fandom.com/wiki/Shirai_Kuroko), will also be made available in [ToaruOS](https://github.com/klange/toaruos) as a general-purpose user language, and some utilities may end up being written in it.
## Features
2020-12-29 09:39:34 +03:00
Kuroko inherits some core features by virtue of following _Crafting Interpreters_, including its basic type system, classes/methods/functions, and the design of its compiler and bytecode VM.
On top of this, Kuroko has:
2020-12-31 06:26:17 +03:00
- Python-style indentation-based block syntax.
- A syntax-highlighted repl, using ToaruOS's `rline` line editing library.
- Collection types including `list`s and `dict`s, with `[]` indexing syntax and inline declarations.
- List comprehensions (`[foo(x) for x in [1,2,3,4]]` and similar expressions).
- Iterator for loops (`for i in l: ...`).
- Exception handling with `try`/`except`/`raise`.
2020-12-31 06:26:17 +03:00
- A module `import` system for including additional code at runtime.
## Examples
_**NOTE**: Due to limitations with Github's markdown renderer, these snippets will be highlighted as Python code._
### Hello World
```py
print("Hello, world!")
# → Hello, world!
```
2020-12-31 06:26:17 +03:00
Multiple expressions can be supplied to `print` and will be concatenated with spaces:
```py
print("Hello", 42, "!")
2020-12-31 06:26:17 +03:00
# → Hello 42 !
```
The string used to combine arguments can be changed with `sep=`.
```py
print("Hello", 42, "!", sep="...")
# → Hello...42...!
```
2020-12-30 04:22:10 +03:00
### Basic Types
Kuroko's basic types are integers (which use the platform `long` type), double-precision floats, booleans (`True` and `False`), and `None`.
```py
print(1 + 2 + 3)
# → 6
```
2020-12-30 04:22:10 +03:00
When integer values are used in arithmetic operations, such as division, the result will be an integer as well:
```py
print(1 / 2)
2020-12-30 04:22:10 +03:00
# → 0
```
To get floating-point results, one of the arguments should be explicitly typed or converted:
```py
print(1 / 2.0)
2020-12-30 04:22:10 +03:00
# → 0.5
```
Implicit type conversion occurs late in evaluation, so be careful of integer overflows:
```py
# Probably not what you want:
print(1000000000 * 1000000000 * 1000000000 * 3.0)
2020-12-30 04:22:10 +03:00
# → -2.07927e+19
# Try something like this instead:
print(1000000000.0 * 1000000000 * 1000000000 * 3.0)
2020-12-30 04:22:10 +03:00
# → 3e+27
```
### Objects
Objects are values which live on the heap. Basic objects include strings, functions, classes, and instances.
Objects are passed by reference, though strings are immutable so this property is only relevant for other object types.
### Strings
Strings can be concatenated, and other values can be appended to them.
```py
print("Hello, " + 42 + "!")
# → Hello, 42!
```
### Functions
Function syntax is essentially the same as in Python:
```py
def greet(name):
print("Hello, " + name + "!")
greet("user")
# → Hello, user!
```
Default arguments can be specified as follows:
```py
def greet(name=None):
if not name:
print("Hello, world!")
else:
print("Hello, " + name + "!")
greet()
gree("user")
# → Hello, world!
# Hello, user!
```
If a default argument value is not provided, the expression assigned to it will be evaluated as if it were at the top of the body of the function, like in Ruby (and _not like in Python_).
2020-12-31 06:26:17 +03:00
Blocks, including function `def` blocks and control flow structures like `if` and `for`, must be indented with spaces to a level greater than the enclosing block.
You may indent blocks to whatever level you desire, so long as ordering remains consistent, though the recommendtation indentation size is 4 spaces.
Tabs are not valid as indentation and will be ignored. It is recommended that you use an editor which provides a clear visual distinction between tabs and spaces, such as [Bim](https://github.com/klange/bim).
```py
if False:
print("Oh no, that was a tab.")
2020-12-31 06:26:17 +03:00
# → Oh no, that was a tab.
```
Blocks can also accept a single inline statement:
```py
if True: print("The first rule of Tautology Club is the first rule of Tautology Club.")
2020-12-31 06:26:17 +03:00
# → The first rule of Tautology Club is the first rule of Tautology Club.
```
### Variables
In a departure from Python, Kuroko has explicit variable declaration and traditional scoping rules. Variables are declared with the `let` keyword and take the value `None` if not defined at declaration time:
```py
let foo
print(foo)
# → None
foo = 1
print(foo)
# → 1
```
2020-12-30 04:22:10 +03:00
### Closures
Functions are first-class values and may be returned from functions and stored in variables, producing _closures_.
When a function references local values from an outter scope, such as in the example below, the referenced variables will be captured.
```py
def foo():
let i = 1 # Local to this call to foo()
def bar():
print(i) # Reference to outer variable
2020-12-30 04:22:10 +03:00
i = i + 1
return bar # Produces a closure
let a = foo() # Each copy of `bar` gets its own `i`
let b = foo()
let c = foo()
2020-12-30 04:22:10 +03:00
a() # So these all print "1" as the first call,
b() # but each one also increments its own copy of i
c()
a() # So further calls will reference that copy
a()
a()
# → 1
# 1
# 1
# 2
# 3
# 4
```
### Basic Objects and Classes
Objects and classes in Kuroko work a lot like Python or similar languages in that they have an arbitrary and mutable set of fields, which may be methods or other values.
To create a basic object without methods, the `object` class is provided:
```py
let o = object()
o.foo = "bar"
print(o.foo)
# → bar
```
To supply methods, define a class:
```py
class Foo():
def printFoo():
print(self.foo)
let o = Foo()
o.foo = "bar"
o.printFoo()
# → bar
```
The `self` keyword is implicit in all methods and does not need to be supplied in the argument list. You may optionally include it in the method declaration anyway:
```py
class Foo():
def printFoo(self):
print(self.foo)
let o = Foo()
o.foo = "bar"
o.printFoo()
# → bar
```
When a class is instantiated, if it has an `__init__` method it will be called automatically. `__init__` may take arguments as well.
```py
class Foo():
def __init__(bar):
self.foo = bar
def printFoo(self):
print(self.foo)
let o = Foo("bar")
o.printFoo()
# → bar
```
Some other special method names include `__get__`, `__set__`, and `__str__`, which will be explained later.
2020-12-31 06:26:17 +03:00
_**Note**: Unlike in Python, most types are not actually instances of classes, though many of the same operations still apply to them._
### Inheritence
Classes may inherit from a single super class:
```py
class Foo():
def __init__():
self.type = "foo"
def printType():
print(self.type)
2020-12-31 06:26:17 +03:00
class Bar(Foo):
def __init__():
self.type = "bar"
let bar = Bar()
bar.printType()
# → bar
```
Methods can refer to the super class with the `super` keyword:
```py
class Foo():
def __init__():
self.type = "foo"
def printType():
print(self.type)
2020-12-31 06:26:17 +03:00
class Bar(Foo):
def __init__():
self.type = "bar"
def printType():
super().printType()
print("Also, I enjoy long walks on the beach.")
2020-12-31 06:26:17 +03:00
let bar = Bar()
bar.printType()
# → bar
# Also, I enjoy long walks on the beach.
```
You can determine at runtime if an object is an instance of a class, either directly or through its inheretince chain, with the `isinstance` builtin function:
```py
class Foo:
class Bar:
class Baz(Bar):
let b = Baz()
print(isinstance(b,Baz), isinstance(b,Bar), isinstance(b,Foo), isinstance(b,object))
2020-12-31 06:26:17 +03:00
# → True, True, False, True
```
All classes eventually inherit from the base class `object`, which provides default implementations of some special instance methods.
### Collections
Kuroko has built-in classes for flexible arrays (`list`) and hashmaps (`dict`):
```py
let l = list()
l.append(1)
l.append(2)
l.append("three")
l.append(False)
print(l)
# → [1, 2, three, False]
l[1] = 5
print(l)
# → [1, 5, three, False]
let d = dict()
d["foo"] = "bar"
d[1] = 2
print(d)
# → {1: 2, foo: bar}
```
2020-12-30 03:05:20 +03:00
These built-in collections can also be initialized as expressions, which act as syntactic sugar for the `listOf` and `dictOf` built-in functions:
```py
let l = [1,2,"three",False] # or listOf(1,2,"three",False)
print(l)
2020-12-30 03:05:20 +03:00
# → [1, 2, three, False]
let d = {"foo": "bar", 1: 2} # or dictOf("foo","bar",1,2)
print(d)
2020-12-30 03:05:20 +03:00
# → {1: 2, foo: bar}
```
Lists can also be generated dynamically:
```py
let fives = [x * 5 for x in [1,2,3,4,5]]
print(fives)
# → [5, 10, 15, 20, 25]
```
### Exceptions
Kuroko provides a mechanism for handling errors at runtime. If an error is not caught, the interpreter will end and print a traceback.
```py
def foo(bar):
print("I expect an argument! " + bar)
foo() # I didn't provide one!
# → Traceback, most recent first, 1 call frame:
# File "<stdin>", line 1, in <module>
# ArgumentError: foo() takes exactly 1 argument (0 given)
```
To catch exceptions, use `try`/`except`:
```py
def foo(bar):
print("I expect an argument! " + bar)
try:
foo() # I didn't provide one!
except:
print("oh no!")
# → oh no!
```
Runtime exceptions are passed to the `except` block as a special variable `exception`. As of this writing, runtime exceptions from the VM are strings.
```py
def foo(bar):
print("I expect an argument! " + bar)
try:
foo() # I didn't provide one!
except:
print("oh no, there was an exception:", exception.arg)
# → oh no, there was an exception: foo() takes exactly 1 argument (0 given)
```
Exceptions can also be generated from code:
```py
def login(password):
if password != "supersecret":
raise "Wrong password, try again!"
print("[Hacker voice] I'm in.")
login("foo")
# → Traceback, most recent first, 2 call frames:
# File "<stdin>", line 5, in <module>
# File "<stdin>", line 3, in login
# Wrong password, try again!
```
The `except` block is optional, and an exception may be caught and ignored.
```py
def login(password):
if password != "supersecret":
raise "Wrong password, try again!"
print("[Hacker voice] I'm in.")
try:
login("foo")
# (no output)
```
### Modules
Modules allow scripts to call other scripts.
```py
# modules/demomodule.krk
foo = "bar"
```
```py
# demo.krk
import demomodule
print(demomodule.foo)
# → bar
```
Modules are run once and then cached, so if they preform actions like printing or complex computation this will happen once when first imported. The globals table from the module is the fields table of an object. Further imports of the same module will return the same object.
### Loops
Kuroku supports C-style for loops, while loops, and Python-style iterator for loops.
```py
for i = 1, i < 5, i = i + 1:
print(i)
# → 1
# 2
# 3
# 4
```
```py
let i = 36
while i > 1:
i = i / 2
print(i)
# → 18
# 9
# 4
# 2
# 1
```
```py
let l = [1,2,3]
for i in l:
print(i)
# → 1
# 2
# 3
```
### Iterators
The special method `__iter__` should return an iterator. An iterator should be a function which increments an internal state and returns the next value. If there are no values remaining, return the iterator itself.
An example of an iterator is the `range` built-in class, which is defined like this:
```py
class range:
"Helpful iterable."
def __init__(self, min, max):
self.min = min
self.max = max
def __iter__(self):
let i=self.min
let l=self.max
def _():
if i>=l:
return _
let o=i
i++
return o
return _
```
Objects which have an `__iter__` method can then be used with the `for ... in ...` syntax:
```py
for i in range(1,5):
print(i)
# → 1
# 2
# 3
# 4
```
### Indexing
Objects with the methods `__get__` and `__set__` can be used with square brackets `[]`:
```py
class Foo:
def __get__(ind):
print("You asked for ind=" + ind)
return ind * 5
def __set__(ind, val):
print("You asked to set ind=" + ind + " to " + val)
let f = Foo()
print(f[4])
f[7] = "bar"
# → You asked for ind=4
# 20
# You asked to set ind=7 to bar
```
### String Slicing
Substrings can be extracted from strings via slicing:
```py
print("Hello world!"[3:8])
# → lo wo
print("Hello world!"[:-1])
# → Hello world
print("Hello world!"[-1:])
# → !
```
_**NOTE**: Slicing is not yet provided for other types, and step values are currently not supported._
### String Conversion
If an object implements the `__str__` method, it will be called to produce string values when concatenating or printing.
```py
class Foo:
def __str__():
return "(I am a Foo!)"
let f = Foo()
print(f)
# → (I am a Foo!)
```
### File I/O
The module `fileio` provides an interface for opening, reading, and writing files, including `stdin`/`stdout`/`stderr`.
To open and read the contents of a file:
```py
import fileio
let f = fileio.open("README.md","r")
print(f.read())
f.close()
```
To write to `stdout` (notably, without automatic line feeds):
```py
import fileio
fileio.stdout.write("hello, world")
```
To read lines from `stdin`:
```py
import fileio
while True:
fileio.stdout.write("Say something: ")
fileio.stdout.flush()
let data = fileio.stdin.readline()
if data[-1] == '\n':
data = data[:-1]
if data == "exit":
break
print("You said '" + data + "'!")
```
### Decorators
Decorators allow functions and methods to be wrapped.
```py
def decorator(func):
print("I take the function to be decorated as an argument:", func)
def wrapper():
print("And I am the wrapper.")
func()
print("Returned from wrapped function.")
return wrapper
@decorator
def wrappedFunction():
print("Hello, world")
wrappedFunction()
# → I take a function to be decorated as an argument: <function wrappedFunction>
# And I am the wrapper.
# Hello, world
# Returned from wrapped function
```
The resulting function will have the same signature as the original function, so wrappers may take arguments to pass to the wrapped function, or may take their own arguments (or both).
Method wrappers work similarly, though be sure to explicitly provide a name (other than `self`) for the object instance:
```py
def methodDecorator(method):
def methodWrapper(instance, anExtraArgument):
method(instance)
print("I also required this extra argument:", anExtraArgument)
return methodWrapper
class Foo():
@methodDecorator
def theMethod():
print("I am a method, so I can obviously access", self)
print("And I also didn't take any arguments, but my wrapper did:")
let f = Foo()
f.theMethod("the newly required argument")
# → I am a method, so I can obviously access <instance of Foo at ...>
# And I also didn't take any arguments, but my wrapper did:
# I also required this extra argument: the newly required argument
```
Decorators are _expressions_, just like in Python, so to make a decorator with arguments create a function that takes those arguments and returns a decorator:
```py
def requirePassword(password):
print("I am creating a decorator.")
def decorator(func):
print("I am wrapping", func, "and attaching",password)
def wrapper(secretPassword):
if secretPassword != password:
print("You didn't say the magic word.")
return
func()
return wrapper
return decorator
@requirePassword("hunter2")
def superSecretFunction():
print("Welcome!")
superSecretFunction("a wrong password")
print("Let's try again.")
superSecretFunction("hunter2")
# → I am wrapping <function superSecretFunction> and attaching hunter2
# You didn't say the magic word.
# Let's try again.
# Welcome!
```
### Keyword Arguments
Arguments may be passed to a function by specifying their name instead of using their positional location.
```py
def aFunction(a,b,c):
print(a,b,c)
aFunction(1,2,3)
aFunction(1,c=3,b=2)
aFunction(b=2,c=3,a=1)
# → 1 2 3
# 1 2 3
# 1 2 3
```
This will be slower in execution than a normal function call, as the interpreter will need to figure out where to place arguments in the requested function by examining it at runtime, but it allows for functions to take many default arguments without forcing the caller to specify the values for everything leading up to one they want to specifically set.
```py
def aFunction(with=None,lots=None,of=None,default=None,args=None):
print(with,lots,of,default,args)
aFunction(of="hello!")
# → None None hello! None None
```
### `*args` and `**kwargs`
When used as parameters in a function signature, `*` and `**` before an identifier indicate that the function will accept arbitrary additional positional arguments and keyword arguments respectively. These options are typically applied to variables named `args` and `kwargs`, and they must appear last (and in this order) in the function signature if used.
The variable marked with `*` will be provided as an ordered `list`, and `**` will be an unordered `dict` of keyword names to values.
```py
def takesArgs(*args):
print(args)
takesArgs(1,2,3)
# → [1, 2, 3]
def takesKwargs(**kwargs):
print(kwargs)
takesKwargs(a=1,b=2,c=3)
# → {'a': 1, 'b': 2, 'c': 3}
def takesEither(*args,**kwargs):
print(args, kwargs)
takesEither(1,2,a=3,b=4)
# → [1, 2] {'a': 3, 'b': 4}
def takesARequiredAndMore(a,*args):
print(a, args)
takesARequiredAndMore(1,2,3,4)
# → 1 [2, 3, 4]
```
### Argument Expansion
When used in a function argument list, `*` and `**` before a list and dict expression respectively, will expand those values into the argument list.
```py
let l = [1,2,3]
def foo(a,b,c):
print(a,b,c)
foo(*l)
# → 1 2 3
let d = {"foo": "a", "bar": 1}
def func(foo,bar):
print(foo, bar)
func(**d)
# → a 1
```
If an expanded list provides too many, or too few, arguments, an ArgumentError will be raised.
If an expanded dict provides parameters which are not requested, an ArgumentError will be raised.
If an expanded dict provides an argument which has already been defined, either as a positional argument or through a named parameter, an error will be raised.
_**Note:** Argument expansion is not currently supported for functions provided by C modules._
2020-12-31 06:26:17 +03:00
## About the REPL
Kuroko's repl provides an interactive environment for executing code and seeing results.
When entering code at the repl, lines ending with colons (`:`) are treated specially - the repl will continue to accept input and automatically insert indentation on a new line. Please note that the repl's understanding of colons is naive: Whitespace or comments after a colon which would normally be accepted by Kuroko's parser will not be understood by the repl - if you want to place a comment after the start of a block statement, be sure that it ends in a colon so you can continue to enter statements.
Pressing backspace when the cursor is preceded by whitespace will delete up to the last column divisible by 4, which should generally delete one level of indentation automatically.
The tab key will also produce spaces when the cursor is at the beginning of the line or preceded entirely with white space.
The repl will display indentation level indicators in preceeding whitespace as a helpful guide.
When a blank line or a line consisting entirely of whitespace is entered, the repl will process the full input.
Code executed in the repl runs in a global scope and reused variable names will overwrite previous definitions, allowing function and class names to be reused.
The repl will display the last value popped from the stack before returning. Note that unlike with the `print` statement, objects printed in this way from the repl will not be converted to strings, so they may display differently.
2021-01-03 06:40:00 +03:00
## What's different from Python?
You may be looking at the code examples and thinking Kuroko looks a _lot_ more like Python than "syntax similar to Python" suggests. Still, there are some differences, and they come in two forms: Intentional differences and unintentional differences.
Unintentional differences likely represent incomplete features. Intentional differences are design decisions specifically meant to differentiate Kuroko from Python and usually are an attempt to improve upon or "fix" perceived mistakes.
Two notable intentional differences thus far are:
- Kuroko's variable scoping requires explicit declarations. This was done because Python's function-level scoping, and particularly how it interacts with globals, is often a thorn in the side of beginner and seasoned programmers alike. It's not so much seen as a mistake as it is something we don't wish to replicate.
- Default arguments to functions are evaluated at call time, not at definition time. How many times have you accidentally assigned an empty list as a default argument, only to be burned by its mutated descendent appearing in further calls? Kuroko doesn't do that - it works more like Ruby.