Mojo🔥 changelog

A history of significant Mojo changes.

This is a running list of significant changes for the Mojo language and tools. It doesn’t include all internal implementation changes.

Update Mojo

If you don’t have Mojo yet, see the get started guide.

To see your current Mojo version, run this:

mojo --version

To update Mojo to the latest release, run this:

modular update mojo

However, if your current version is 0.3.0 or lower, you’ll need these additional commands:

sudo apt-get update
sudo apt-get install modular
modular clean
modular install mojo

v0.6.0 (2023-12-04)

🔥 Legendary

Traits have arrived!

You can now define a trait, which consists of a required set of method prototypes. A struct can conform to the trait by implementing these methods. This lets you write generic functions that work on any structs that conform to a given trait.

The following section gives a brief overview of traits—see the Mojo Manual and this traits blog post for more details!

Traits are declared with the trait keyword. The bodies of traits should contain method signatures declared with ... as their bodies. Default method implementations are not supported yet.
```
trait SomeTrait:
    fn required_method(self, x: Int): ...
```
The trait can be implemented on a struct by inheriting from it.
```
struct SomeStruct(SomeTrait):
    fn required_method(self, x: Int):
        print("hello traits", x)
```
You can then write a generic functions that accepts any type that conforms to the trait. You do this by creating a parameterized function with a trait-typed parameter:
```
fn fun_with_traits[T: SomeTrait](x: T):
    x.required_method(42)
```
Which can be invoked with instances of types that conform to the trait:
```
var thing = SomeStruct()
# Infer the parameter `T`!
fun_with_traits(thing)
```
Traits can also inherit from other traits, which simply requires that implementors of the child trait also conform to all parent traits.
```
trait Parent:
    fn parent_func(self): ...

trait Child(Parent):
    fn child_func(self): ...
```
Then, both child and parent trait methods can be invoked on instances of the trait Child. As well, an instance of the child trait can be converted to an instance of the parent trait.
```
fn the_parents[T: Parent](x: T):
    x.parent_func()

fn the_children[T: Child](x: T):
    x.child_func()
    x.parent_func()
    # Upcast `x` from instance of `Child` to `Parent`.
    the_parents(x)
```
For more information, see the Traits page in the Mojo Manual.
A fundamental Destructable trait has been added to the language. This is a core trait that every trait automatically conforms to. This enables destruction of generic types and generic collections.

Note: We’re aware that this trait might be better spelled Destructible. We’re planning on removing it in the future and moving its functionality to AnyType so that any type that doesn’t provide its own destructor will have a default, no-op destructor.
We’ve added some traits to the standard library, you can implement these on your own types:
We added built-in len(), str(), and int() functions, which work with types that implement the Sized, Stringable, and Intable traits, respectively.
DynamicVector is now a proper generic collection that can use any type that implements the Movable and Copyable traits. This means you can now write, for example, DynamicVector[String]. Also, DynamicVector now invokes its element destructors upon destruction, so _del_old has been deleted.

print now works on any types that implement Stringable by invoking their __str__ method:

@value
struct BoxedInt(Stringable):
    var value: Int

    fn __str__(self) -> String:
        return self.value

print(BoxedInt(11), "hello traits!", BoxedInt(42))

⭐️ New

The Mojo Manual is an all-new, complete Mojo user guide. It doesn’t include everything about Mojo yet, but it includes a lot, and more than the original programming manual (now deprecated).

Plus, the entire Mojo Manual and other Mojo docs are now open-sourced on GitHub, and we’d love to accept contributions to help us improve them!
Mojo now supports partial automatic parameterization: when a function is declared with an argument of a partially bound type, the unbound parameters of that type are implicitly added to the function’s input parameters. For example:
```
@value
struct Fudge[a: Int, b: Int, c: Int = 7]: ...

# These function declarations are roughly equivalent:
fn eat(f: Fudge[5]): ...               # implicitly parameterized
fn eat[_b: Int](f: Fudge[5, _b]): ...  # explicitly parameterized
```
In the first signature for eat(), the b parameter isn’t bound, so it’s implicitly added as an input parameter on the function.

In the second signature for eat(), the author has explicitly defined an input parameter (_b), which is bound to the second parameter on the argument type (which happens to be b).

Both functions can be called like this:
```
eat(Fudge[5, 8]())
```
Mojo infers the value of the b parameter from the argument (in this case, 8).

With the second signature, you can also pass the _b parameter value explicitly:
```
eat[3](Fudge[5, 3]())
```
Moreover, Mojo now allows you to explicitly mark parameters as unbound using the _ as syntax meaning “placeholder for an unbound parameter.” For example:
```
# These function declarations are roughly equivalent:
fn eat(f: Fudge[5, _, c=_]): ...                    # implicitly parameterized
fn eat(f: Fudge[c=_, a=5, b=_]): ...                # implicitly parameterized
fn eat[_b: Int, _c: Int](f: Fudge[5, _b, _c]): ...  # explicitly parameterized
```
The first two signatures explicitly unbind the b and c parameters.

In the last signature, the _b and _c parameters are explicitly declared by the author, and bound to the b and c parameters in the argument type.

Any of these signatures can be called like this:
```
eat(Fudge[5, 8]())
eat(Fudge[5, 8, 9]())
```
Note that the default parameter values of struct parameters are bound, unless explicitly unbound by the user.

For more information, see the Mojo Manual.
Parametric types can now be partially bound in certain contexts. For example, a new Scalar type alias has been added defined as:
```
alias Scalar = SIMD[size=1]
```
Which creates a parametric type alias Scalar with a single parameter of type DType. Types can also be partially or fully bound in other contexts. For instance, alias declarations of type values inside functions now work properly:
```
fn type_aliases():
    alias T = SIMD
    print(T[DType.float32, 1]())
    alias Partial = T[type=DType.int32]
    print(Partial[2]())
```
The __mlir_op feature now supports operations that return multiple results. To use them, you write the _type field as a Tuple of types. For example:
```
# The `ret` variable has type `Tuple[Int, Int]`.
let ret = __mlir_op.`multi_result_op`[ _type = (Int, Int) ]()
```
Mojo now has the ability to read raw bytes from a file using the read_bytes() method. For example:
```
with open("file.binary", "r") as f:
    data = f.read_bytes()
```
A size argument was added to the read() and read_bytes() methods on the builtin file.FileHandle. The size argument defaults to -1 and maintains the previous “read to EOF” behavior when size is negative.
```
with open("file.binary", "r") as f:
    data1 = f.read_bytes(1024)
    data2 = f.read_bytes(256)
```

Path now has read_bytes() and read_text() methods to read file contents from a path:

let text_path = Path("file.txt")
let text = text_path.read_text()

let binary_path = Path("file.binary")
let data = binary_path.read_bytes()

Tensor has new save() and load() methods to save and load to file. These methods preserve shape and datatype information. For example:

let tensor = Tensor[DType.float32]()
tensor.save(path)

let tensor_from_file = Tensor[DType.float32].load(path)

Subscripting added to DTypePointer and Pointer:

let p = DTypePointer[DType.float16].alloc(4)
for i in range(4):
    p[i] = i
    print(p[i])

file.FileHandle now has a seek() method.
String now has an rfind() method analogous to Python’s str.rfind().
String now has an split() method analogous to Python’s str.split().
Path now has a suffix() method analogous to Python’s pathlib.Path.suffix.
The Mojo REPL now supports indented expressions, making it a bit easier to execute expressions copied from an indented block (such as a doc string).
The Mojo Language Server now implements the Document Symbols request. IDEs use this to provide support for Outline View and Go to Symbol. This addresses Issue #960.
The Mojo Language Server now shows documentation when code completing modules or packages in import statements.
The Mojo Language Server now supports processing code examples, defined as markdown Mojo code blocks, inside of doc strings. This enables IDE features while writing examples in API documentation.
The Mojo Language Server now provides semantic token information, providing better highlighting for symbols whose semantics are not statically analyzable.
The Mojo Language Server now classifies doc strings as folding ranges, making them easier to collapse, reducing vertical space while editing.
Command line options for the mojo driver that take arguments can now be written in either of two ways: both --foo FOO and --foo=FOO. Previously, only the former was valid.

🦋 Changed

Variadic list types VariadicList and VariadicListMem are now iterable. Variadic arguments are automatically projected into one of these types inside the function body, so var args can be iterated:
```
fn print_ints(*nums: Int):
    for num in nums:
        print(num)
    print(len(nums))
```
The assert functions in the testing package now raise an Error when the assertion fails instead of returning a Bool for whether the assertion succeeded or not.
Parameters of AnyType type are no longer (implicitly) assumed to be register-passable. A new AnyRegType type is used to represent generic types that are register passable.
Changing the units in a benchmark report is now an argument instead of a parameter:
```
let report = benchmark.run[timer]()
report.print(Unit.ms)
```
Default values on inout arguments are no longer permitted, i.e. the following will now raise an error:
```
fn inout_default(inout x: Int = 2): ...
```
The to_string() function has been removed from PythonObject in favor of the new __str__() function. This composes better with traits so it can be used with the generic str() function.

🛠️ Fixed

#734 - Consumption of struct works only for types with a __del__ method.
#910 - Parser crash when using memory-only generic type as return of function that raises.
#1060 - Mojo happily parses code that has messed up indentation
#1159 - The language server doesn’t warn about bad return type.
#1166 - warning: unreachable code after return statement with context manager
#1098 - The language server doesn’t highlight properties of PythonObjects correctly.
#1153 - The language server crashes when parsing an invalid multi-nested module import.
#1236 - The language server doesn’t show autocomplete in if statements.
#1246 - Warning diagnostics are transient in the presence of caching.

Known Issue

There is an issue affecting Jupyter notebooks that use autotuning and traits. This issue only manifests on macOS, and the same code runs without issue outside of the notebooks. This issue affects the Matrix multiplication in Mojo notebook.

v0.5.0 (2023-11-2)

⭐️ New

The SIMD type now defaults to the architectural SIMD width of the type. This means you can write SIMD[DType.float32] which is equivalent to SIMD[DType.float32, simdwidthof[DType.float32]()].
The SIMD type now contains a join() function that allows you to concatenate two SIMD values together and produce a new SIMD value.

Mojo now supports compile-time keyword parameters, in addition to existing support for keyword arguments. For example:

fn foo[a: Int, b: Int = 42]():
  print(a, "+", b)

foo[a=5]()        # prints '5 + 42'
foo[a=7, b=13]()  # prints '7 + 13'
foo[b=20, a=6]()  # prints '6 + 20'

Keyword parameters are also supported in structs:

struct KwParamStruct[a: Int, msg: String = "🔥mojo🔥"]:
    fn __init__(inout self):
        print(msg, a)

fn use_kw_params():
    KwParamStruct[a=42]()               # prints '🔥mojo🔥 42'
    KwParamStruct[5, msg="hello"]()     # prints 'hello 5'
    KwParamStruct[msg="hello", a=42]()  # prints 'hello 42'

For more detail, see the programming manual.

For the time being, the following notable limitations apply:

Keyword-only parameters are not supported yet:
```
fn baz[*args: Int, b: Int](): pass  # fails
fn baz[a: Int, *, b: Int](): pass  # fails
```
(The analogous keyword-only arguments in Python are described in PEP 3102.)

Variadic keyword parameters are not supported yet:

fn baz[a: Int, **kwargs: Int](): pass  # fails

Mojo now supports “automatic” parameterization of functions. What this means is that if a function argument type is parametric but has no bound parameters, they are automatically added as input parameters on the function. This works with existing features to allow you to write parametric functions with less boilerplate.
```
@value
struct Thing[x: Int, y: Int]:
    pass

fn foo(v: Thing):
    print(v.x)
    print(v.y)

fn main():
    let v = Thing[2, 3]()
    foo(v)
```
However, partial autoparameterization is not supported yet:
```
fn foo(v: Thing[y=7]):  # Partially bound type not allowed yet.
    ...
```

Keyword argument passing is supported when invoking __getitem__ using the bracket syntax:

@value
struct MyStruct:
  fn __getitem__(self, x: Int, y: Int, z: Int) -> Int:
    return x * y + z

MyStruct()[z=7, x=3, y=5]  # returns 22

However, keyword argument passing to __setitem__ using the bracket syntax is not supported yet:

@value
struct OtherStruct:
    fn __setitem__(self, x: Int, y: Int): pass

OtherStruct()[x=1] = 4  # fails

Function argument input parameters can now be referenced within the signature of the function:
```
fn foo(x: SIMD, y: SIMD[x.type, x.size]):
    pass
```

The benchmark module has been simplified and improved so you can now run:

import benchmark
from time import sleep

fn sleeper():
    sleep(.01)

fn main():
    let report = benchmark.run[sleeper]()
    print(report.mean())

It no longer requires a capturing fn so can benchmark functions outside the same scope.

You can print a report with:

report.print()

---------------------
Benchmark Report (s)
---------------------
Mean: 0.012314264957264957
Total: 1.440769
Iters: 117
Warmup Mean: 0.0119335
Warmup Total: 0.023866999999999999
Warmup Iters: 2
Fastest Mean: 0.012227958333333334
Slowest Mean: 0.012442699999999999

Units for all functions default to seconds, but can be changed with:

from benchmark import Unit

report.print[Unit.ms]()

Mojo now supports struct parameter deduction (a.k.a. class template argument deduction, or CTAD) for partially bound types. Struct parameter deduction is also possible from static methods. For example:

@value
struct Thing[v: Int]: pass

struct CtadStructWithDefault[a: Int, b: Int, c: Int = 8]:
    fn __init__(inout self, x: Thing[a]):
        print("hello", a, b, c)

    @staticmethod
    fn foo(x: Thing[a]):
        print("🔥", a, b, c)

fn main():
    _ = CtadStructWithDefault[b=7](Thing[6]())  # prints 'hello 6 7 8'
    CtadStructWithDefault[b=7].foo(Thing[6]())  # prints '🔥 6 7 8'

Tensor has new fromfile() and tofile() methods to save and load as bytes from a file.
The built-in print() function now works on the Tensor type.
TensorShape and TensorSpec now have constructors that take DynamicVector[Int] and StaticIntTuple to initialize shapes.
The String type now has the count() and find() methods to enable counting the number of occurrences or finding the offset index of a substring in a string.
The String type now has a replace() method which allows you to replace a substring with another string.

🦋 Changed

VariadicList and VariadicListMem moved under builtins, and no longer need to be imported.
Variadic arguments are now automatically projected into a VariadicList or VariadicListMem inside the function body. This allows for more flexibility in using var args. For example:
```
  fn print_ints(*nums: Int):
      let len = len(nums)
      for i in range(len):
          print(nums[i])
      print(len)
```
The parameters for InlinedFixedVector have been switched. The parameters are now [type, size] instead of [size, type]. The InlinedFixedVector now has a default size which means that one can just use InlinedFixedVector as InlinedFixedVector[Float32] and the default size is used.
write_file() method in Buffer and NDBuffer is renamed to tofile() to match the Python naming.
Mojo will now utilize all available cores across all NUMA sockets on the host machine by default. The prior default behavior was to use all the cores on the first socket.

❌ Removed

The math.numerics module is now private, because its types (FPUtils and FlushDenormals) should not be used externally.

🛠️ Fixed

#532 - Compiler optimizing while True loop away
#760 - Compilation error: ‘hlcf.for.yield’ op specifies 0 branch inputs but target expected 1 along control-flow edge from here
#849 - The Tensor type is now initialized with zeros at construction time.
#912 - Invalid load for __get_address_as_lvalue.
#916 - Parser crash when specifying default values for inout arguments.
#943 - Mojo hangs if you use continue in the nested loop
#957 - Parser crash when a function call with variadic arguments of a memory-only type is evaluated at compile time.
#990 - Fixes rounding issue with floor division with negative numerator.
#1018 - In some cases the sort function was returning invalid results. This release fixes some of these corner cases.
#1010 - Initializing tensor in alias declaration results in crash.
#1110 - The time.now() function now returns nanoseconds across all operating systems.
#1115 - cannot load non-register passable type into SSA register.

v0.4.0 for Mac (2023-10-19)

🔥 Legendary

Mojo for Mac!

The Mojo SDK now works on macOS (Apple silicon). This is the same version previously released for Linux. Get the latest version of the SDK for your Mac system:

Download Now!

v0.4.0 (2023-10-05)

⭐️ New

Mojo now supports default parameter values. For example:

fn foo[a: Int = 3, msg: StringLiteral = "woof"]():
    print(msg, a)

fn main():
    foo()  # prints 'woof 3'
    foo[5]()  # prints 'woof 5'
    foo[7, "meow"]()  # prints 'meow 7'

Inferred parameter values take precedence over defaults:

@value
struct Bar[v: Int]:
    pass

fn foo[a: Int = 42, msg: StringLiteral = "quack"](bar: Bar[a]):
    print(msg, a)

fn main():
    foo(Bar[9]())  # prints 'quack 9'

Structs also support default parameters:

@value
struct DefaultParams[msg: StringLiteral = "woof"]:
    alias message = msg

fn main():
    print(DefaultParams[]().message)  # prints 'woof'
    print(DefaultParams["meow"]().message)  # prints 'meow'

The new file module adds basic file I/O support. You can now write:

var f = open("my_file.txt", "r")
print(f.read())
f.close()

with open("my_file.txt", "r") as f:
    print(f.read())

Mojo now allows context managers to support an __enter__ method without implementing support for an __exit__ method, enabling idioms like this:
```
# This context manager consumes itself and returns it as the value.
fn __enter__(owned self) -> Self:
    return self^
```
Here Mojo cannot invoke a noop __exit__ method because the context manager is consumed by the __enter__ method. This can be used for types (like file descriptors) that are traditionally used with with statements, even though Mojo’s guaranteed early destruction doesn’t require that.
A very basic version of pathlib has been implemented in Mojo. The module will be improved to achieve functional parity with Python in the next few releases.
The memory.unsafe module now contains a bitcast function. This is a low-level operation that enables bitcasting between pointers and scalars.

The input parameters of a parametric type can now be directly accessed as attribute references on the type or variables of the type. For example:

@value
struct Thing[param: Int]:
    pass

fn main():
    print(Thing[2].param) # prints '2'
    let x = Thing[9]()
    print(x.param) # prints '9'

Input parameters on values can even be accessed in parameter contexts. For example:

fn foo[value: Int]():
    print(value)

let y = Thing[12]()
alias constant = y.param + 4
foo[constant]() # prints '16'

The Mojo REPL now supports code completion. Press Tab while typing to query potential completion results.

Error messages from Python are now exposed in Mojo. For example the following should print No module named 'my_uninstalled_module':

fn main():
    try:
        let my_module = Python.import_module("my_uninstalled_module")
    except e:
        print(e)

Error messages can now store dynamic messages. For example, the following should print “Failed on: Hello”

fn foo(x:String) raises:
    raise Error("Failed on: " + x)

fn main():
    try:
        foo("Hello")
    except e:
        print(e)

🦋 Changed

We have improved and simplified the parallelize function. The function now elides some overhead by caching the Mojo parallel runtime.
The Mojo REPL and Jupyter environments no longer implicitly expose Python, PythonObject, or Pointer. These symbols must now be imported explicitly, for example:
```
from python import Python
from python.object import PythonObject
from memory.unsafe import Pointer
```
The syntax for specifying attributes with the __mlir_op prefix have changed to mimic Python’s keyword argument passing syntax. That is, = should be used instead of :, e.g.:
```
# Old syntax, now fails.
__mlir_op.`index.bool.constant`[value : __mlir_attr.`false`]()
# New syntax.
__mlir_op.`index.bool.constant`[value=__mlir_attr.`false`]()
```
You can now print the Error object directly. The message() method has been removed.

🛠️ Fixed

#794 - Parser crash when using the in operator.
#936 - The Int constructor now accepts other Int instances.
#921 - Better error message when running mojo on a module with no main function.
#556 - UInt64s are now printed correctly.
#804 - Emit error instead of crashing when passing variadic arguments of unsupported types.
#833 - Parser crash when assigning module value.
#752 - Parser crash when calling async def.
#711 - The overload resolution logic now correctly prioritizes instance methods over static methods (if candidates are an equally good match otherwise), and no longer crashed if a static method has a Self type as its first argument.
#859 - Fix confusing error and documentation of the rebind builtin.
#753 - Direct use of LLVM dialect produces strange errors in the compiler.
#926 - Fixes an issue that occurred when a function with a return type of StringRef raised an error. When the function raised an error, it incorrectly returned the string value of that error.
#536 - Report More information on python exception.

v0.3.1 (2023-09-28)

Our first-ever patch release of the Mojo SDK is here! Release v0.3.1 includes primarily installation-related fixes. If you’ve had trouble installing the previous versions of the SDK, this release may be for you.

🛠️ Fixed

#538 - Installation hangs during the testing phase. This issue occurs on machines with a low number of CPU cores, such as free AWS EC2 instances and GitHub Codespaces.
#590 - Installation fails with a “failed to run python” message.
#672 - Language server hangs on code completion. Related to #538, this occurs on machines with a low number of CPU cores.
#913 - In the REPL and Jupyter notebooks, inline comments were being parsed incorrectly.

v0.3.0 (2023-09-21)

There’s more Mojo to love in this, the second release of the Mojo SDK! This release includes new features, an API change, and bug fixes.

There’s also an updated version of the Mojo extension for VS Code.

⭐️ New

Mojo now has partial support for passing keyword arguments to functions and methods. For example the following should work:

fn foo(a: Int, b: Int = 3) -> Int:
    return a * b

fn main():
    print(foo(6, b=7))  # prints '42'
    print(foo(a=6, b=7))  # prints '42'
    print(foo(b=7, a=6))  # prints '42'

Parameters can also be inferred from keyword arguments, for example:

fn bar[A: AnyType, B: AnyType](a: A, b: B):
    print("Hello 🔥")

fn bar[B: AnyType](a: StringLiteral, b: B):
    print(a)

fn main():
    bar(1, 2)  # prints `Hello 🔥`
    bar(b=2, a="Yay!")  # prints `Yay!`

For the time being, the following notable limitations apply:

Keyword-only arguments are not supported:

fn baz(*args: Int, b: Int): pass  # fails
fn baz(a: Int, *, b: Int): pass  # fails

(Keyword-only arguments are described in PEP 3102.)

Variadic keyword arguments are not supported:

fn baz(a: Int, **kwargs: Int): pass  # fails

Mojo now supports the @nonmaterializable decorator. The purpose is to mark data types that should only exist in the parameter domain. To use it, a struct is decorated with @nonmaterializable(TargetType). Any time the nonmaterializable type is converted from the parameter domain, it is automatically converted to TargetType. A nonmaterializable struct should have all of its methods annotated as @always_inline, and must be computable in the parameter domain. In the following example, the NmStruct type can be added in the parameter domain, but are converted to HasBool when materialized.

@value
@register_passable("trivial")
struct HasBool:
  var x: Bool
  fn __init__(x: Bool) -> Self:
    return Self {x: x}
  @always_inline("nodebug")
  fn __init__(nms: NmStruct) -> Self:
    return Self {x: True if (nms.x == 77) else False}

@value
@nonmaterializable(HasBool)
@register_passable("trivial")
struct NmStruct:
  var x: Int
  @always_inline("nodebug")
  fn __add__(self: Self, rhs: Self) -> Self:
    return NmStruct(self.x + rhs.x)

alias stillNmStruct = NmStruct(1) + NmStruct(2)
# When materializing to a run-time variable, it is automatically converted,
# even without a type annotation.
let convertedToHasBool = stillNmStruct

Mojo integer literals now produce the IntLiteral infinite precision integer type when used in the parameter domain. IntLiteral is materialized to the Int type for runtime computation, but intermediate computations at compile time, using supported operators, can now exceed the bit width of the Int type.
The Mojo Language Server now supports top-level code completions, enabling completion when typing a reference to a variable, type, etc. This resolves #679.
The Mojo REPL now colorizes the resultant variables to help distinguish input expressions from the output variables.

🦋 Changed

Mojo allows types to implement two forms of move constructors, one that is invoked when the lifetime of one value ends, and one that is invoked if the compiler cannot prove that. These were previously both named __moveinit__, with the following two signatures:
```
fn __moveinit__(inout self, owned existing: Self): ...
fn __moveinit__(inout self, inout existing: Self): ...
```
We’ve changed the second form to get its own name to make it more clear that these are two separate operations: the second has been renamed to __takeinit__:
```
fn __moveinit__(inout self, owned existing: Self): ...
fn __takeinit__(inout self, inout existing: Self): ...
```
The name is intended to connote that the operation takes the conceptual value from the source (without destroying it) unlike the first one which “moves” a value from one location to another.

For more information, see the Mojo Manual section on move constructors.
The Error type in Mojo has changed. Instead of extracting the error message using error.value you will now extract the error message using error.message().

🛠️ Fixed

#503 - Improve error message for failure lowering kgen.param.constant.
#554 - Alias of static tuple fails to expand.
#500 - Call expansion failed due to verifier error.
#422 - Incorrect comment detection in multiline strings.
#729 - Improve messaging on how to exit the REPL.
#756 - Fix initialization errors of the VS Code extension.
#575 - Build LLDB/REPL with libedit for a nicer editing experience in the terminal.

v0.2.1 (2023-09-07)

The first versioned release of Mojo! 🔥

All earlier releases were considered version 0.1.

🔥 Legendary

First release of the Mojo SDK!

You can now develop with Mojo locally. The Mojo SDK is currently available for Ubuntu Linux systems, and support for Windows and macOS is coming soon. You can still develop from a Windows or Mac computer using a container or remote Linux system.

The Mojo SDK includes the Mojo standard library and the Mojo command-line interface (CLI), which allows you to run, compile, and package Mojo code. It also provides a REPL programming environment.

Get the Mojo SDK!
First release of the Mojo extension for VS Code.

This provides essential Mojo language features in Visual Studio Code, such as code completion, code quick fixes, docs tooltips, and more. Even when developing on a remote system, using VS Code with this extension provides a native-like IDE experience.

⭐️ New

A new clobber_memory function has been added to the benchmark module. The clobber memory function tells the system to flush all memory operations at the specified program point. This allows you to benchmark operations without the compiler reordering memory operations.
A new keep function has been added to the benchmark module. The keep function tries to tell the compiler not to optimize the variable away if not used. This allows you to avoid compiler’s dead code elimination mechanism, with a low footprint side effect.
New shift_right and shift_left functions have been added to the simd module. They shift the elements in a SIMD vector right/left, filling elements with zeros as needed.
A new cumsum function has been added to the reduction module that computes the cumulative sum (also known as scan) of input elements.
Mojo Jupyter kernel now supports code completion.

🦋 Changed

Extends rotate_bits_left, rotate_left, rotate_bits_right, and rotate_right to operate on Int values. The ordering of parameters has also been changed to enable type inference. Now it’s possible to write rotate_right[shift_val](simd_val) and have the dtype and simd_width inferred from the argument. This addresses Issue #528.

🛠️ Fixed

Fixed a bug causing the parser to crash when the with statement was written without a colon. This addresses Issue #529.
Incorrect imports no longer crash when there are other errors at the top level of a module. This fixes Issue #531.

August 2023

2023-08-24

Fixed issue where the with expr as x statement within fn behaved as if it were in a def, binding x with function scope instead of using lexical scope.

⭐️ New

Major refactoring of the standard library to enable packaging and better import ergonomics:
- The packages are built as binaries to improve startup speed.
- Package and module names are now lowercase to align with the Python style.
- Modules have been moved to better reflect the purpose of the underlying functions (e.g. Pointer is now within the unsafe module in the memory package).
- The following modules are now included as built-ins: SIMD, DType, IO, Object, and String. This means it’s no longer necessary to explicitly import these modules. Instead, these modules will be implicitly imported for the user. Private methods within the module are still accessible using the builtin.module_name._private_method import syntax.
- New math package has been added to contain the bit, math, numerics, and polynomial modules. The contents of the math.math module are re-exported into the math package.

Mojo now supports using memory-only types in parameter expressions and as function or type parameters:

@value
struct IntPair:
    var first: Int
    var second: Int

fn add_them[value: IntPair]() -> Int:
    return value.first + value.second

fn main():
    print(add_them[IntPair(1, 2)]()) # prints '3'

In addition, Mojo supports evaluating code that uses heap-allocated memory at compile-time and materializing compile-time values with heap-allocated memory into dynamic values:

fn fillVector(lowerBound: Int, upperBound: Int, step: Int) -> DynamicVector[Int]:
    var result = DynamicVector[Int]()
    for i in range(lowerBound, upperBound, step):
        result.push_back(i)
    return result

fn main():
    alias values = fillVector(5, 23, 7)
    for i in range(0, values.__len__()):
        print(values[i]) # prints '5', '12', and then '19'

🦋 Changed

def main():, without the explicit None type, can now be used to define the entry point to a Mojo program.
The assert_param function has been renamed to constrained and is now a built-in function.
The print function now works on Complex values.

🛠️ Fixed

Fixed issues with print formatting for DType.uint16 and DType.int16.
Issue #499 - Two new rotate_right and rotate_left functions have been added to the SIMD module.
Issue #429 - You can now construct a Bool from a SIMD type whose element-type is DType.bool.
Issue #350 - Confusing Matrix implementation
Issue #349 - Missing load_tr in struct Matrix
Issue #501 - Missing syntax error messages in Python expressions.

2023-08-09

🦋 Changed

The ref and mutref identifiers are now treated as keywords, which means they cannot be used as variable, attribute, or function names. These keywords are used by the “lifetimes” features, which is still in development. We can consider renaming these (as well as other related keywords) when the development work gels, support is enabled in public Mojo builds, and when we have experience using them.
The argument handling in def functions has changed: previously, they had special behavior that involved mutable copies in the callee. Now, we have a simple rule, which is that def argument default to the owned convention (fn arguments still default to the borrowed convention).

This change is mostly an internal cleanup and simplification of the compiler and argument model, but does enable one niche use-case: you can now pass non-copyable types to def arguments by transferring ownership of a value into the def call. Before, that would not be possible because the copy was made on the callee side, not the caller’s side. This also allows the explicit use of the borrowed keyword with a def that wants to opt-in to that behavior.

2023-08-03

⭐️ New

A new Tensor type has been introduced. This tensor type manages its own data (unlike NDBuffer and Buffer which are just views). Therefore, the tensor type performs its own allocation and free. Here is a simple example of using the tensor type to represent an RGB image and convert it to grayscale:

from tensor import Tensor, TensorShape
from utils.index import Index
from random import rand

let height = 256
let width = 256
let channels = 3

# Create the tensor of dimensions height, width, channels and fill with
# random value.
let image = rand[DType.float32](height, width, channels)

# Declare the grayscale image.
var gray_scale_image = Tensor[DType.float32](height, width)

# Perform the RGB to grayscale transform.
for y in range(height):
  for x in range(width):
    let r = image[y,x,0]
    let g = image[y,x,1]
    let b = image[y,x,2]
    gray_scale_image[Index(y,x)] = 0.299 * r + 0.587 * g + 0.114 * b

🛠️ Fixed

Issue #53 - Int now implements true division with the / operator. Similar to Python, this returns a 64-bit floating point number. The corresponding in-place operator, /=, has the same semantics as //=.

July 2023

2023-07-26

⭐️ New

Types that define both __getitem__ and __setitem__ (i.e. where sub-scripting instances creates computed LValues) can now be indexed in parameter expressions.
Unroll decorator for loops with constant bounds and steps:
- @unroll: Fully unroll a loop.
- @unroll(n): Unroll a loop by factor of n, where n is a positive integer.
- Unroll decorator requires loop bounds and iteration step to be compiler time constant value, otherwise unrolling will fail with compilation error. This also doesn’t make loop induction variable a parameter.
```
  # Fully unroll the loop.
  @unroll
  for i in range(5):
    print(i)

  # Unroll the loop by a factor of 4 (with remainder iterations of 2).
  @unroll(4)
  for i in range(10):
    print(i)
```
The Mojo REPL now prints the values of variables defined in the REPL. There is full support for scalars and structs. Non-scalar SIMD vectors are not supported at this time.

🛠️ Fixed

Issue #437 - Range can now be instantiated with a PythonObject.
Issue #288 - Python strings can now be safely copied.

2023-07-20

⭐️ New

Mojo now includes a Limits module, which contains functions to get the max and min values representable by a type, as requested in Issue #51. The following functions moved from Math to Limits: inf(), neginf(), isinf(), isfinite().
Mojo decorators are now distinguished between “signature” and “body” decorators and are ordered. Signature decorators, like @register_passable and @parameter, modify the type of declaration before the body is parsed. Body decorators, like @value, modify the body of declaration after it is fully parsed. Due to ordering, a signature decorator cannot be applied after a body decorator. That means the following is now invalid:
```
@register_passable # error: cannot apply signature decorator after a body one!
@value
struct Foo:
  pass
```
Global variables can now be exported in Mojo compiled archives, using the @export decorator. Exported global variables are public symbols in compiled archives and use the variable name as its linkage name, by default. A custom linkage name can be specified with @export("new_name"). This does not affect variable names in Mojo code.

Mojo now supports packages! A Mojo package is defined by placing an __init__.mojo or __init__.🔥 within a directory. Other files in the same directory form modules within the package (this works exactly like it does in Python). Example:

main.🔥
my_package/
  __init__.🔥
  module.🔥
  my_other_package/
    __init__.🔥
    stuff.🔥

# main.🔥
from my_package.module import some_function
from my_package.my_other_package.stuff import SomeType

fn main():
    var x: SomeType = some_function()

Mojo now supports direct module and package imports! Modules and packages can be imported and bound to names. Module and package elements, like functions, types, global variables, and other modules, can be accessed using attribute references, like my_module.foo. Note that modules lack runtime representations, meaning module references cannot be instantiated.
```
import builtin.io as io
import SIMD

io.print("hello world")
var x: SIMD.Float32 = 1.2
```

🦋 Changed

Reverted the feature from 2023-02-13 that allowed unqualified struct members. Use the Self keyword to conveniently access struct members with bound parameters instead. This was required to fix Issue #260.
Updated the RayTracing notebook: added step 5 to create specular lighting for more realistic images and step 6 to add a background image.

🛠️ Fixed

Issue #260 - Definitions inside structs no longer shadow definitions outside of struct definitions.

2023-07-12

⭐️ New

Mojo now has support for global variables! This enables var and let declaration at the top-level scope in Mojo files. Global variable initializers are run when code modules are loaded by the platform according to the order of dependencies between global variables, and their destructors are called in the reverse order.
The Mojo programming manual is now written as a Jupyter notebook, and available in its entirety in the Mojo Playground (programming-manual.ipynb). (Previously, HelloMojo.ipynb included most of the same material, but it was not up-to-date.)
As a result, we’ve also re-written HelloMojo.ipynb to be much shorter and provide a more gentle first-user experience.
Coroutine module documentation is now available. Coroutines form the basis of Mojo’s support for asynchronous execution. Calls to async fns can be stored into a Coroutine, from which they can be resumed, awaited upon, and have their results retrieved upon completion.

🦋 Changed

simd_bit_width in the TargetInfo module has been renamed to simdbitwidth to better align with simdwidthof, bitwidthof, etc.

🛠️ Fixed

The walrus operator now works in if/while statements without parentheses, e.g. if x := function():.
Issue #428 - The FloatLiteral and SIMD types now support conversion to Int via the to_int or __int__ method calls. The behavior matches that of Python, which rounds towards zero.

2023-07-05

⭐️ New

Tuple expressions now work without parentheses. For example, a, b = b, a works as you’d expect in Python.
Chained assignments (e.g. a = b = 42) and the walrus operator (e.g. some_function(b := 17)) are now supported.

🦋 Changed

The simd_width and dtype_simd_width functions in the TargetInfo module have been renamed to simdwidthof.
The dtype_ prefix has been dropped from alignof, sizeof, and bitwidthof. You can now use these functions (e.g. alignof) with any argument type, including DType.
The inf, neginf, nan, isinf, isfinite, and isnan functions were moved from the Numerics module to the Math module, to better align with Python’s library structure.

🛠️ Fixed

Issue #253 - Issue when accessing a struct member alias without providing parameters.
Issue #404 - The docs now use snake_case for variable names, which more closely conforms to Python’s style.
Issue #379 - Tuple limitations have been addressed and multiple return values are now supported, even without parentheses.
Issue #347 - Tuples no longer require parentheses.
Issue #320 - Python objects are now traversable via for loops.

June 2023

2023-06-29

⭐️ New

You can now share .ipynb notebook files in Mojo Playground. Just save a file in the shared directory, and then right-click the file and select Copy Sharable link. To open a shared notebook, you must already have access to Mojo Playground; when you open a shared notebook, click Import at the top of the notebook to save your own copy. For more details about this feature, see the instructions inside the help directory, in the Mojo Playground file browser.

🦋 Changed

The unroll2() and unroll3() functions in the Functional module have been renamed to overload the unroll() function. These functions unroll 2D and 3D loops and unroll() can determine the intent based on the number of input parameters.

🛠️ Fixed

Issue #229 - Issue when throwing an exception from __init__ before all fields are initialized.
Issue #74 - Struct definition with recursive reference crashes.
Issue #285 - The TargetInfo module now includes is_little_endian() and is_big_endian() to check if the target host uses either little or big endian.
Issue #254 - Parameter name shadowing in nested scopes is now handled correctly.

2023-06-21

⭐️ New

Added support for overloading on parameter signature. For example, it is now possible to write the following:
```
fn foo[a: Int](x: Int):
    pass

fn foo[a: Int, b: Int](x: Int):
    pass
```
For details on the overload resolution logic, see the Mojo Manual section on parameters.
A new cost_of() function has been added to Autotune. This meta-function must be invoked at compile time, and it returns the number of MLIR operations in a function (at a certain stage in compilation), which can be used to build basic heuristics in higher-order generators.
```
from autotune import cost_of

fn generator[f: fn(Int) -> Int]() -> Int:
    @parameter
    if cost_of[fn(Int) -> Int, f]() < 10:
        return f()
    else:
        # Do something else for slower functions...
```
Added a new example notebook with a basic Ray Tracing algorithm.

🦋 Changed

The constrained_msg() in the Assert module has been renamed to constrained().

🛠️ Fixed

Overloads marked with @adaptive now correctly handle signatures that differ only in declared parameter names, e.g. the following now works correctly:
```
@adaptive
fn foobar[w: Int, T: DType]() -> SIMD[T, w]: ...

@adaptive
fn foobar[w: Int, S: DType]() -> SIMD[S, w]: ...
```
Issue #219 - Issue when redefining a function and a struct defined in the same cell.
Issue #355 - The loop order in the Matmul notebook for Python and naive mojo have been reordered for consistency. The loop order now follows (M, K, N) ordering.
Issue #309 - Use snake case naming within the testing package and move the asserts out of the TestSuite struct.

2023-06-14

⭐️ New

Tuple type syntax is now supported, e.g. the following works:
```
fn return_tuple() -> (Int, Int):
    return (1, 2)
```

🦋 Changed

The TupleLiteral type was renamed to just Tuple, e.g. Tuple[Int, Float].

🛠️ Fixed

Issue #354 - Returning a tuple doesn’t work even with parens.
Issue #365 - Copy-paste error in FloatLiteral docs.
Issue #357 - Crash when missing input parameter to variadic parameter struct member function.

2023-06-07

⭐️ New

Tuple syntax now works on the left-hand side of assignments (in “lvalue” positions), enabling things like (a, b) = (b, a). There are several caveats: the element types must exactly match (no implicit conversions), this only works with values of TupleLiteral type (notably, it will not work with PythonObject yet) and parentheses are required for tuple syntax.

❌ Removed

Mojo Playground no longer includes the following Python packages (due to size, compute costs, and environment complications): torch, tensorflow, keras, transformers.

🦋 Changed

The data types and scalar names now conform to the naming convention used by numpy. So we use Int32 instead of SI32, similarly using Float32 instead of F32. Closes Issue #152.

🛠️ Fixed

Issue #287 - computed lvalues don’t handle raising functions correctly
Issue #318 - Large integers are not being printed correctly
Issue #326 - Float modulo operator is not working as expected
Issue #282 - Default arguments are not working as expected
Issue #271 - Confusing error message when converting between function types with different result semantics

May 2023

2023-05-31

⭐️ New

Mojo Playground now includes the following Python packages (in response to popular demand): torch, tensorflow, polars, opencv-python, keras, Pillow, plotly, seaborn, sympy, transformers.
A new optimization is applied to non-trivial copyable values that are passed as an owned value without using the transfer (^) operator. Consider code like this:
```
  var someValue : T = ...
  ...
  takeValueAsOwned(someValue)
  ...
```
When takeValueAsOwned() takes its argument as an owned value (this is common in initializers for example), it is allowed to do whatever it wants with the value and destroy it when it is finished. In order to support this, the Mojo compiler is forced to make a temporary copy of the someValue value, and pass that value instead of someValue, because there may be other uses of someValue after the call.

The Mojo compiler is now smart enough to detect when there are no uses of someValue later, and it will elide the copy just as if you had manually specified the transfer operator like takeValueAsOwned(someValue^). This provides a nice “it just works” behavior for non-trivial types without requiring manual management of transfers.

If you’d like to take full control and expose full ownership for your type, just don’t make it copyable. Move-only types require the explicit transfer operator so you can see in your code where all ownership transfer happen.
Similarly, the Mojo compiler now transforms calls to __copyinit__ methods into calls to __moveinit__ when that is the last use of the source value along a control flow path. This allows types which are both copyable and movable to get transparent move optimization. For example, the following code is compiled into moves instead of copies even without the use of the transfer operator:
```
  var someValue = somethingCopyableAndMovable()
  use(someValue)
  ...
  let otherValue = someValue      # Last use of someValue
  use(otherValue)
  ...
  var yetAnother = otherValue     # Last use of otherValue
  mutate(yetAnother)
```
This is a significant performance optimization for things like PythonObject (and more complex value semantic types) that are commonly used in a fluid programming style. These don’t want extraneous reference counting operations performed by its copy constructor.

If you want explicit control over copying, it is recommended to use a non-dunder .copy() method instead of __copyinit__, and recall that non-copyable types must always use of the transfer operator for those that want fully explicit behavior.

🛠️ Fixed

Issue #231 - Unexpected error when a Python expression raises an exception
Issue #119 - The REPL fails when a python variable is redefined

2023-05-24

⭐️ New

finally clauses are now supported on try statements. In addition, try statements no longer require except clauses, allowing try-finally blocks. finally clauses contain code that is always executed from control-flow leaves any of the other clauses of a try statement by any means.

🦋 Changed

with statement emission changed to use the new finally logic so that
```
with ContextMgr():
    return
```
Will correctly execute ContextMgr.__exit__ before returning.

🛠️ Fixed

Issue #204 - Mojo REPL crash when returning a String at compile-time
Issue #143 - synthesized init in @register_passable type doesn’t get correct convention.
Issue #201 - String literal concatenation is too eager.
Issue #209 - [QoI] Terrible error message trying to convert a type to itself.
Issue #32 - Include struct fields in docgen
Issue #50 - Int to string conversion crashes due to buffer overflow
Issue #132 - PythonObject to_int method has a misleading name
Issue #189 - PythonObject bool conversion is incorrect
Issue #65 - Add SIMD constructor from Bool
Issue #153 - Meaning of Time.now function result is unclear
Issue #165 - Type in Pointer.free documentation
Issue #210 - Parameter results cannot be declared outside top-level in function
Issue #214 - Pointer offset calculations at compile-time are incorrect
Issue #115 - Float printing does not include the right number of digits
Issue #202 - kgen.unreachable inside nested functions is illegal
Issue #235 - Crash when register passable struct field is not register passable
Issue #237 - Parameter closure sharp edges are not documented

2023-05-16

⭐️ New

Added missing dunder methods to PythonObject, enabling the use of common arithmetic and logical operators on imported Python values.
PythonObject is now printable from Mojo, instead of requiring you to import Python’s print function.

🛠️ Fixed

Issue #98: Incorrect error with lifetime tracking in loop.
Issue #49: Type inference issue (?) in ‘ternary assignment’ operation (FloatLiteral vs. ‘SIMD[f32, 1]’).
Issue #48: and/or don’t work with memory-only types.
Issue #11: setitem Support for PythonObject.

2023-05-11

⭐️ New

NDBuffer and Buffer are now constructable via Pointer and DTypePointer.
String now supports indexing with either integers or slices.
Added factorial function to the Math module.

🦋 Changed

The “byref” syntax with the & sigil has changed to use an inout keyword to be more similar to the borrowed and owned syntax in arguments. Please see Issue #7 for more information.
Optimized the Matrix multiplication implementation in the notebook. Initially we were optimizing for expandability rather than performance. We have found a way to get the best of both worlds and now the performance of the optimized Matmul implementation is 3x faster.
Renamed the ^ postfix operator from “consume” to “transfer.”

🛠️ Fixed

Fixed missing overloads for Testing.assertEqual so that they work on Integer and String values.
Issue #6: Playground stops evaluating cells when a simple generic is defined.
Issue #18: Memory leak in Python interoperability was removed.

2023-05-02

📢 Released

Mojo publicly launched! This was epic, with lots of great coverage online including a wonderful post by Jeremy Howard. The team is busy this week.

⭐️ New

Added a Base64 encoding function to perform base64 encoding on strings.

🦋 Changed

Decreased memory usage of serialization of integers to strings.
Speedup the sort function.

🛠️ Fixed

Fixed time unit in the sleep function.

April 2023

Week of 2023-04-24

📢 The default behavior of nested functions has been changed. Mojo nested functions that capture are by default are non-parametric, runtime closures, meaning that:
```
def foo(x):
    # This:
    def bar(y): return x*y
    # Is the same as:
    let bar = lambda y: x*y
```
These closures cannot have input or result parameters, because they are always materialized as runtime values. Values captured in the closure (x in the above example), are captured by copy: values with copy constructors cannot be copied and captures are immutable in the closure.

Nested functions that don’t capture anything are by default “parametric” closures: they can have parameters and they can be used as parameter values. To restore the previous behavior for capturing closures, “parametric, capture-by-unsafe-reference closures”, tag the nested function with the @parameter decorator.
📢 Mojo now has full support for “runtime” closures: nested functions that capture state materialized as runtime values. This includes taking the address of functions, indirect calls, and passing closures around through function arguments. Note that capture-by-reference is still unsafe!

You can also take references to member functions with instances of that class using foo.member_function, which creates a closure with foo bound to the self argument.
📢 Mojo now supports Python style with statements and context managers.

These things are very helpful for implementing things like our trace region support and things like Runtime support.

A context manager in Mojo implements three methods:
```
fn __enter__(self) -> T:
fn __exit__(self):
fn __exit__(self, err: Error) -> Bool:
```
The first is invoked when the context is entered, and returns a value that may optionally be bound to a target for use in the with body. If the with block exits normally, the second method is invoked to clean it up. If an error is raised, the third method is invoked with the Error value. If that method returns true, the error is considered handled, if it returns false, the error is re-thrown so propagation continues out of the ‘with’ block.
📢 Mojo functions now support variable scopes! Explicit var and let declarations inside functions can shadow declarations from higher “scopes”, where a scope is defined as any new indentation block. In addition, the for loop iteration variable is now scoped to the loop body, so it is finally possible to write
```
for i in range(1): pass
for i in range(2): pass
```
📢 Mojo now supports an @value decorator on structs to reduce boilerplate and encourage best practices in value semantics. The @value decorator looks to see the struct has a memberwise initializer (which has arguments for each field of the struct), a __copyinit__ method, and a __moveinit__ method, and synthesizes the missing ones if possible. For example, if you write:
```
@value
struct MyPet:
  var name: String
  var age: Int
```
The @value decorator will synthesize the following members for you:
```
  fn __init__(inout self, owned name: String, age: Int):
     self.name = name^
     self.age = age
  fn __copyinit__(inout self, existing: Self):
     self.name = existing.name
     self.age = existing.age
  fn __moveinit__(inout self, owned existing: Self):
     self.name = existing.name^
     self.age = existing.age
```
This decorator can greatly reduce the boilerplate needed to define common aggregates, and gives you best practices in ownership management automatically. The @value decorator can be used with types that need custom copy constructors (your definition wins). We can explore having the decorator take arguments to further customize its behavior in the future.
📚 Memcpy and memcmp now consistently use count as the byte count.
📚 Add a variadic sting join on strings.
📚 Introduce a reduce_bit_count method to count the number of 1 across all elements in a SIMD vector.
📚 Optimize the pow function if the exponent is integral.
📚 Add a len function which dispatches to __len__ across the different structs that support it.

Week of 2023-04-17

📢 Error messages have been significantly improved, thanks to prettier printing for Mojo types in diagnostics.
📢 Variadic values can now be indexed directly without wrapping them in a VariadicList!
📢 let declarations in a function can now be lazily initialized, and var declarations that are never mutated get a warning suggesting they be converted to a let declaration. Lazy initialization allows more flexible patterns of initialization than requiring the initializer be inline, e.g.:
```
let x : Int
if cond:
    x = foo()
else:
    x = bar()
use(x)
```
📢 Functions defined with def now return object by default, instead of None. This means you can return values (convertible to object) inside def functions without specifying a return type.
📢 The @raises decorator has been removed. Raising fn should be declared by specifying raises after the function argument list. The rationale is that raises is part of the type system, instead of a function modifier.
📢 The BoolLiteral type has been removed. Mojo now emits True and False directly as Bool.
📢 Syntax for function types has been added. You can now write function types with fn(Int) -> String or async def(&String, *Int) -> None. No more writing !kgen.signature types by hand!
📢 Float literals are not emitted as FloatLiteral instead of an MLIR f64 type!
📢 Automatic destructors are now supported by Mojo types, currently spelled fn __del___(owned self): (the extra underscore will be dropped shortly). These destructors work like Python object destructors and similar to C++ destructors, with the major difference being that they run “as soon as possible” after the last use of a value. This means they are not suitable for use in C++-style RAII patterns (use the with statement for that, which is currently unsupported).

These should be generally reliable for both memory-only and register-passable types, with the caveat that closures are known to not capture values correctly. Be very careful with interesting types in the vicinity of a closure!
A new (extremely dangerous!) builtin function is available for low-level ownership muckery. The __get_address_as_owned_value(x) builtin takes a low-level address value (of !kgen.pointer type) and returns an owned value for the memory that is pointed to. This value is assumed live at the invocation of the builtin, but is “owned” so it needs to be consumed by the caller, otherwise it will be automatically destroyed. This is an effective way to do a “placement delete” on a pointer.
```
# "Placement delete": destroy the initialized object begin pointed to.
_ = __get_address_as_owned_value(somePointer.value)

# Result value can be consumed by anything that takes it as an 'owned'
# argument as well.
consume(__get_address_as_owned_value(somePointer.value))
```
Another magic operator, named __get_address_as_uninit_lvalue(x) joins the magic LValue operator family. This operator projects a pointer to an LValue like __get_address_as_lvalue(x). The difference is that __get_address_as_uninit_lvalue(x) tells the compiler that the pointee is uninitialized on entry and initialized on exit, which means that you can use it as a “placement new” in C++ sense. __get_address_as_lvalue(x) tells the compiler that the pointee is initialized already, so reassigning over it will run the destructor.
```
# "*Re*placement new": destroy the existing SomeHeavy value in the memory,
# then initialize a new value into the slot.
__get_address_as_lvalue(somePointer.value) = SomeHeavy(4, 5)

# Ok to use an lvalue, convert to borrow etc.
use(__get_address_as_lvalue(somePointer.value))

# "Placement new": Initialize a new value into uninitialied memory.
__get_address_as_uninit_lvalue(somePointer.value) = SomeHeavy(4, 5)

# Error, cannot read from uninitialized memory.
use(__get_address_as_uninit_lvalue(somePointer.value))
```
Note that __get_address_as_lvalue assumes that there is already a value at the specified address, so the assignment above will run the SomeHeavy destructor (if any) before reassigning over the value.
📢 Implement full support for __moveinit__ (aka move constructors)

This implements the ability for memory-only types to define two different types of move ctors if they’d like:
1. fn __moveinit__(inout self, owned existing: Self): Traditional Rust style moving constructors that shuffles data around while taking ownership of the source binding.
2. fn __moveinit__(inout self, inout existing: Self):: C++ style “stealing” move constructors that can be used to take from an arbitrary LValue.
This gives us great expressive capability (better than Rust/C++/Swift) and composes naturally into our lifetime tracking and value categorization system.
The __call__ method of a callable type has been relaxed to take self by borrow, allow non-copyable callees to be called.
Implicit conversions are now invoked in raise statements properly, allowing converting strings to Error type.
Automatic destructors are turned on for __del__ instead of __del___.
📚 Add the builtin FloatLiteral type.
📚 Add integral floordiv and mod for the SIMD type that handle negative values.
📚 Add an F64 to String converter.
📚 Make the print function take variadic inputs.

Week of 2023-04-10

📢 Introduce consume operator x^

This introduces the postfix consume operator, which produces an RValue given a lifetime tracked object (and, someday, a movable LValue).
Mojo now automatically synthesizes empty destructor methods for certain types when needed.
The object type has been built out into a fully-dynamic type, with dynamic function dispatch, with full error handling support.
```
def foo(a) -> object:
    return (a + 3.45) < [1, 2, 3] # raises a TypeError
```
📢 The @always_inline decorator is no longer required for passing capturing closures as parameters, for both the functions themselves as functions with capturing closures in their parameters. These functions are still inlined but it is an implementation detail of capturing parameter closures. Mojo now distinguishes between capturing and non-capturing closures. Nested functions are capturing by default and can be made non-capturing with the @noncapturing decorator. A top-level function can be passed as a capturing closure by marking it with the @closure decorator.
📢 Support for list literals has been added. List literals [1, 2, 3] generate a variadic heterogeneous list type.
Variadics have been extended to work with memory-primary types.
Slice syntax is now fully-supported with a new builtin slice object, added to the compiler builtins. Slice indexing with a[1:2:3] now emits calls to __setitem__ and __getitem__ with a slice object.
Call syntax has been wired up to __call__. You can now f() on custom types!
Closures are now explicitly typed as capturing or non-capturing. If a function intends to accept a capturing closure, it must specify the capturing function effect.
📚 Add a Tile2D function to enable generic 2D tiling optimizations.
📚 Add the slice struct to enable getting/setting spans of elements via getitem/setitem.
📚 Add syntax sugar to autotuning for both specifying the autotuned values, searching, and declaring the evaluation function.

Week of 2023-04-03

The AnyType and NoneType aliases were added and auto-imported in all files.
📢 The Mojo VS Code extension has been improved with docstring validation. It will now warn when a function’s docstring has a wrong argument name, for example.
📢 A new built-in literal type TupleLiteral was added in _CompilerBuiltin. It represents literal tuple values such as (1, 2.0) or ().
📢 The Int type has been moved to a new Builtin module and is auto-imported in all code. The type of integer literals has been changed from the MLIR index type to the Int type.
Mojo now has a powerful flow-sensitive uninitialized variable checker. This means that you need to initialize values before using them, even if you overwrite all subcomponents. This enables the compiler to reason about the true lifetime of values, which is an important stepping stone to getting automatic value destruction in place.
📢 Call syntax support has been added. Now you can directly call an object that implements the __call__ method, like foo(5).
📢 The name for copy constructors got renamed from __copy__ to __copyinit__. Furthermore, non-@register_passable types now implement it like they do an init method where you fill in a by-reference self, for example:
```
fn __copyinit__(inout self, existing: Self):
    self.first = existing.first
    self.second = existing.second
```
This makes copy construction work more similarly to initialization, and still keeps copies x = y distinct from initialization x = T(y).
📢 Initializers for memory-primary types are now required to be in the form __init__(inout self, ...): with a None result type, but for register primary types, it remains in the form __init__(...) -> Self:. The T{} initializer syntax has been removed for memory-primary types.
Mojo String literals now emit a builtin StringLiteral type! One less MLIR type to worry about.
New __getattr__ and __setattr__ dunder methods were added. Mojo calls these methods on a type when attempting member lookup of a non-static member. This allows writing dynamic objects like x.foo() where foo is not a member of x.
Early destructor support has been added. Types can now define a special destructor method __del___ (note three underscores). This is an early feature and it is still being built out. There are many caveats, bugs, and missing pieces. Stay tuned!
📚 Integer division and mod have been corrected for rounding in the presence of negative numbers.
📚 Add scalar types (UI8, SI32, F32, F64, etc.) which are aliases to SIMD[1, type].

March 2023

Week of 2023-03-27

📢 Parameter names are no longer load-bearing in function signatures. This gives more flexibility in defining higher-order functions, because the functions passed as parameters do not need their parameter names to match.

# Define a higher-order function...
fn generator[
   func: __mlir_type[`!kgen.signature<`, Int, `>() -> !kgen.none`]
]():
   pass

# Int parameter is named "foo".
fn f0[foo: Int]():
   pass

# Int parameter is named "bar".
fn f1[bar: Int]():
   pass

fn main():
   # Both can be used as `func`!
   generator[f0]()
   generator[f1]()

Stay tuned for improved function type syntax…

📢 Two magic operators, named __get_lvalue_as_address(x) and __get_address_as_lvalue convert stored LValues to and from !kgen.pointer types (respectively). This is most useful when using the Pointer[T] library type. The Pointer.address_of(lvalue) method uses the first one internally. The second one must currently be used explicitly, and can be used to project a pointer to a reference that you can pass around and use as a self value, for example:
```
# "Replacement new" SomeHeavy value into the memory pointed to by a
# Pointer[SomeHeavy].
__get_address_as_lvalue(somePointer.value) = SomeHeavy(4, 5)
```
Note that __get_address_as_lvalue assumes that there is already a value at the specified address, so the assignment above will run the SomeHeavy destructor (if any) before reassigning over the value.
The (((x))) syntax is __mlir_op has been removed in favor of __get_lvalue_as_address which solves the same problem and is more general.
📢 When using a mutable self argument to a struct __init__ method, it now must be declared with &, like any other mutable method. This clarifies the mutation model by making __init__ consistent with other mutating methods.
📚 Add variadic string join function.
📚 Default initialize values with 0 or null if possible.
📚 Add compressed, aligned, and mask store intrinsics.

Week of 2023-03-20

Initial String type is added to the standard library with some very basic methods.
Add DimList to remove the need to use an MLIR list type throughout the standard library.
📢 The __clone__ method for copying a value is now named __copy__ to better follow Python term of art.
📢 The __copy__ method now takes its self argument as a “borrowed” value, instead of taking it by reference. This makes it easier to write, works for @register_passable types, and exposes more optimization opportunities to the early optimizer and dataflow analysis passes.
```
# Before:
fn __clone__(inout self) -> Self: ...

# After:
fn __copy__(self) -> Self: ...
```
📢 A new @register_passable("trivial") may be applied to structs that have no need for a custom __copy__ or __del__ method, and whose state is only made up of @register_passable("trivial") types. This eliminates the need to define __copy__ boilerplate and reduces the amount of IR generated by the compiler for trivial types like Int.
You can now write back to attributes of structs that are produced by a computed lvalue expression. For example a[i].x = .. works when a[i] is produced with a __getitem__/__setitem__ call. This is implemented by performing a read of a[i], updating the temporary, then doing a writeback.
The remaining hurdles to using non-parametric, @register_passable types as parameter values have been cleared. Types like Int should enjoy full use as parameter values.
Parameter pack inference has been added to function calls. Calls to functions with parameter packs can now elide the pack types:
```
fn foo[*Ts: AnyType](*args: *Ts): pass

foo(1, 1.2, True, "hello")
```
Note that the syntax for parameter packs has been changed as well.
📚 Add the runtime string type.
📚 Introduce the DimList struct to remove the need to use low-level MLIR operations.

Week of 2023-03-13

📢 Initializers for structs now use __init__ instead of __new__, following standard practice in Python. You can write them in one of two styles, either traditional where you mutate self:
```
fn __init__(self, x: Int):
    self.x = x
```
or as a function that returns an instance:
```
fn __init__(x: Int) -> Self:
    return Self {x: x}
```
Note that @register_passable types must use the later style.
📢 The default argument convention is now the borrowed convention. A “borrowed” argument is passed like a C++ const& so it doesn’t need to invoke the copy constructor (aka the __clone__ method) when passing a value to the function. There are two differences from C++ const&:
1. A future borrow checker will make sure there are no mutable aliases with an immutable borrow.
2. @register_passable values are passed directly in an SSA register (and thus, usually in a machine register) instead of using an extra reference wrapper. This is more efficient and is the ‘right default’ for @register_passable values like integers and pointers.
This also paves the way to remove the reference requirement from __clone__ method arguments, which will allow us to fill in more support for them.
Support for variadic pack arguments has been added to Mojo. You can now write heterogeneous variadic packs like:
```
fn foo[*Ts: AnyType](args*: Ts): pass

foo[Int, F32, String, Bool](1, 1.5, "hello", True)
```
The owned argument convention has been added. This argument convention indicates that the function takes ownership of the argument and is responsible for managing its lifetime.
The borrowed argument convention has been added. This convention signifies the callee gets an immutable shared reference to a value in the caller’s context.
📚 Add the getenv function to the OS module to enable getting environment variables.
📚 Enable the use of dynamic strides in NDBuffer.

Week of 2023-03-06

📢 Support added for using capturing async functions as parameters.

📢 Returning result parameters has been moved from return statements to a new param_return statement. This allows returning result parameters from throwing functions:

@raises
fn foo[() -> out: Int]():
    param_return[42]
    raise Error()

And returning different parameters along @parameter if branches:

fn bar[in: Bool -> out: Int]():
    @parameter
    if in:
        param_return[1]
    else:
        param_return[2]

📢 Mojo now supports omitting returns at the end of functions when they would not reachable. For instance,

fn foo(cond: Bool) -> Int:
    if cond:
        return 0
    else:
        return 1

fn bar() -> Int:
    while True:
        pass

String literals now support concatenation, so "hello " "world" is treated the same as "hello world".
Empty bodies on functions, structs, and control flow statements are no longer allowed. Please use pass in them to explicitly mark that they are empty, just like in Python.
📢 Structs in Mojo now default to living in memory instead of being passed around in registers. This is the right default for generality (large structures, structures whose pointer identity matters, etc) and is a key technology that enables the borrow model. For simple types like Int and SIMD, they can be marked as @register_passable.

Note that memory-only types currently have some limitations: they cannot be used in generic algorithms that take and return a !mlirtype argument, and they cannot be used in parameter expressions. Because of this, a lot of types have to be marked @register_passable just to work around the limitations. We expect to enable these use-cases over time.
📢 Mojo now supports computed lvalues, which means you can finally assign to subscript expressions instead of having to call __setitem__ explicitly.

Some details on this: Mojo allows you to define multiple __setitem__ overloads, but will pick the one that matches your __getitem__ type if present. It allows you to pass computed lvalues into inout arguments by introducing a temporary copy of the value in question.
Mojo now has much better support for using register-primary struct types in parameter expressions and as the types of parameter values. This will allow migration of many standard library types away from using bare MLIR types like __mlir_type.index and towards using Int. This moves us towards getting rid of MLIR types everywhere and makes struct types first-class citizens in the parameter system.
📚 Add a sort function.
📚 Add non-temporal store to enable cache bypass.

February 2023

Week of 2023-02-27

📢 The @interface, @implements, and @evaluator trio of decorators have been removed, replaced by the @parameter if and @adaptive features.
📢 Parameter inference can now infer the type of variadic lists.
📢 Memory primary types are now supported in function results. A result slot is allocated in the caller, and the callee writes the result of the function into that slow. This is more efficient for large types that don’t fit into registers neatly! And initializers for memory-primary types now initialize the value in-place, instead of emitting a copy!
Support for let decls of memory primary types has been implemented. These are constant, ready-only values of memory primary types but which are allocated on the function stack.
Overload conversion resolution and parameter inference has been improved:
1. Inference now works with let decls in some scenarios that weren’t working before.
2. Parameter bindings can now infer types into parameter expressions. This helps resolve higher-order functions in parameter expressions.
📚 Optimize floor, ceil, and ldexp on X86 hardware.
📚 Implement the log math function.

Week of 2023-02-20

📢 A new @__memory_primary struct decorator has been introduced. Memory primary types must always have an address. For instance, they are always stack-allocated when declared in a function and their values are passed into function calls by address instead of copy. This is in contract with register primary types that may not have an address, and which are passed by value in function calls. Memory-primary fields are not allowed inside register-primary structs, because struct elements are stored in-line.
📢 A new _CompilerBuiltin module was added. This module defines core types and functions of the language that are referenced by the parser, and hence, is auto-imported by all other modules. For example new types for literal values like the boolean True/False will be included in _CompilerBuiltin.
📢 A special __adaptive_set property can be accessed on a function reference marked as @adaptive. The property returns the adaptive overload set of that function. The return type is a !kgen.variadic. This feature is useful to implement a generic evaluate function in the standard library.
📢 A new built-in literal type BoolLiteral was added in _CompilerBuiltin. It represents the literal boolean values True and False. This is the first Mojo literal to be emitted as a standard library type!
📚 Add the prefetch intrinsic to enable HW prefetching a cache line.
📚 Add the InlinedFixedVector, which is optimized for small vectors and stores values on both the stack and the heap.

Week of 2023-02-13

Unqualified lookups of struct members apply contextual parameters. This means for instance that you can refer to static methods without binding the struct parameters.

struct Foo[x: Int]:
    @staticmethod
    bar(): pass

    foo(self):
        bar()         # implicitly binds to Foo[x].bar()
        Foo[2].bar()  # explicitly bind to another parameter

📢 A new Self type refers to the enclosing type with all parameters bound to their current values. This is useful when working with complex parametric types, e.g.:
```
struct MyArray[size: Int, element_type: type]:
   fn __new__() -> Self:
       return Self {...}
```
which is a lot nicer than having to say MyArray[size, element_type] over and over again.

📢 Mojo now supports an @adaptive decorator. This decorator will supersede interfaces, and it represents an overloaded function that is allowed to resolve to multiple valid candidates. In that case, the call is emitted as a fork, resulting in multiple function candidates to search over.

@adaptive
fn sort(arr: ArraySlice[Int]):
    bubble_sort(arr)

@adaptive
fn sort(arr: ArraySlice[Int]):
    merge_sort(arr)

fn concat_and_sort(lhs: ArraySlice[Int], rhs: ArraySlice[Int]):
    let arr = lhs + rhs
    sort(arr) # this forks compilation, creating two instances
              # of the surrounding function

📢 Mojo now requires that types implement the __clone__ special member in order to copy them. This allows the safe definition of non-copyable types like Atomic. Note that Mojo still doesn’t implement destructors, and (due to the absence of non-mutable references) it doesn’t actually invoke the __clone__ member when copying a let value. As such, this forces to you as a Mojo user to write maximal boilerplate without getting much value out of it.

In the future, we will reduce the boilerplate with decorators, and we will actually start using it. This will take some time to build out though.
📢 A special __mlir_region statement was added to provide stronger invariants around defining MLIR operation regions in Mojo. It similar syntax to function declarations, except it there are no results and no input conventions.
📚 Implement the log math function.
📚 Improve the DType struct to enable compile-time equality checks.
📚 Add the Complex struct class.

Week of 2023-02-06

📢 The if statement now supports a @parameter decorator, which requires its condition to be a parameter expression, but which only emits the ‘True’ side of the condition to the binary, providing a “static if” functionality. This should eliminate many uses of @interface that are just used to provide different constraint on the implementations.
📢 fn main(): is now automatically exported and directly runnable by the command-line mojo tool. This is a stop-gap solution to enable script-like use cases until we have more of the language built out.
🪦 The @nodebug_inline feature has been removed, please use @alwaysinline("nodebug") for methods that must be inlined and that we don’t want to step into.
📢 Python chained comparisons, ex. a < b < c, are now supported in Mojo.
📢 Functions can now be defined with default argument values, such as def f(x: Int, y: Int = 5):. The default argument value is used when callers do not provide a value for that argument: f(3), for example, uses the default argument value of y = 5.
Unused coroutine results are now nicely diagnosed as “missing await” warnings.
📚 Introduce a vectorized reduction operations to the SIMD type.

January 2023

Week of 2023-01-30

A basic Mojo language server has been added to the VS Code extension, which parses your code as you write it, and provides warnings, errors, and fix-it suggestions!
💯 The Mojo standard library is now implicitly imported by default.
The coroutine lowering support was reworked and a new Coroutine[T] type was implemented. Now, the result of a call to an async function MUST be wrapped in a Coroutine[T], or else memory will leak. In the future, when Mojo supports destructors and library types as literal types, the results of async function calls will automatically wrapped in a Coroutine[T]. But today, it must be done manually. This type implements all the expected hooks, such as __await__, and get() to retrieve the result. Typical usage:
```
async fn add_three(a: Int, b: Int, c: Int) -> Int:
    return a + b + c

async fn call_it():
    let task: Coroutine[Int] = add_three(1, 2, 3)
    print(await task)
```
⭐️ We now diagnose unused expression values at statement context in fn declarations (but not in defs). This catches bugs with unused values, e.g. when you forget the parens to call a function.
📢 An @always_inline("nodebug") function decorator can be used on functions that need to be force inlined, but when they should not have debug info in the result. This should be used on methods like Int.__add__ which should be treated as builtin.
📢 The @export decorator now supports an explicit symbol name to export to, for example:
```
@export("baz") # exported as 'baz'
fn some_mojo_fn_name():
```
📢 🚧 Subscript syntax is now wired up to the __getitem__ dunder method.

This allows type authors to implement the __getitem__ method to enable values to be subscripted. This is an extended version of the Python semantics (given we support overloading) that allows you to define N indices instead of a single version that takes a tuple (also convenient because we don’t have tuples yet).

Note that this has a very, very important limitation: subscripts are NOT wired up to __setitem__ yet. This means that you can read values with .. = v[i] but you cannot store to them with v[i] = ... For this, please continue to call __setitem__ directly.
📢 Function calls support parameter inference.

For calls to functions that have an insufficient number of parameters specified at the callsite, we can now infer them from the argument list. We do this by matching up the parallel type structure to infer what the parameters must be.

Note that this works left to right in the parameter list, applying explicitly specified parameters before trying to infer new ones. This is similar to how C++ does things, which means that you may want to reorder the list of parameters with this in mind. For example, a dyn_cast-like function will be more elegant when implemented as:

fn dyn_cast[DstType: type, SrcType: type](src: SrcType) -> DstType:

Than with the SrcType/DstType parameters flipped around.
📚 Add the growable Dynamic vector struct.

Week of 2023-01-23

Inplace operations like +=/__iadd__ may now take self by-val if they want to, instead of requiring it to be by-ref.
⭐️ Inplace operations are no longer allowed to return a non-None value. The corresponding syntax is a statement, not an expression.
A new TaskGroup type was added to the standard library. This type can be used to schedule multiple tasks on a multi-threaded workqueue to be executed in parallel. An async function can await all the tasks at once with the taskgroup.
📢 We now support for loops! A type that defines an __iter__ method that returns a type that defines __next__ and __len__ methods is eligible to be used in the statement for el in X(). Control flow exits the loop when the length is zero.

This means things like this now work:
```
for item in range(start, end, step):
    print(item)
```
Result parameters now have names. This is useful for referring to result parameters in the return types of a function:
```
fn return_simd[() -> nelts: Int]() -> SIMD[f32, nelts]:
```
📢 We now support homogeneous variadics in value argument lists, using the standard Python fn thing(*args: Int): syntax! Variadics also have support in parameter lists:
```
fn variadic_params_and_args[*a: Int](*b: Int):
    print(a[0])
    print(b[1])
```
📚 Add the range struct to enable for ... range(...) loops.
📚 Introduce the unroll generator to allow one to unroll loops via a library function.

Week of 2023-01-16

📢 Struct field references are now supported in parameter context, so you can use someInt.value to get the underlying MLIR thing out of it. This should allow using first-class types in parameters more widely.
📢 We now support “pretty” initialization syntax for structs, e.g.:
```
struct Int:
    var value: __mlir_type.index
    fn __new__(value: __mlir_type.index) -> Int:
        return Int {value: value}
```
This eliminates the need to directly use the MLIR lit.struct.create op in struct initializers. This syntax may change in the future when ownership comes in, because we will be able to support the standard __init__ model then.
📢 It is now possible to attach regions to __mlir_op operations. This is done with a hack that allows an optional _region attribute that lists references to the region bodies (max 1 region right now due to lack of list [] literal).

Nested functions now parse, e.g.:

fn foo():
    fn bar():
        pass
    bar()

Python-style async functions should now work and the await expression prefix is now supported. This provides the joy of async/await syntactic sugar when working with asynchronous functions. This is still somewhat dangerous to use because we don’t have proper memory ownership support yet.
String literals are now supported.
Return processing is now handled by a dataflow pass inside the compiler, so it is possible to return early out of if statements.

The parser now supports generating ‘fixit’ hints on diagnostics, and uses them when a dictionary literal uses a colon instead of equal, e.g.:

x.mojo:8:48: error: expected ':' in subscript slice, not '='
    return __mlir_op.`lit.struct.create`[value = 42]()
                                               ^
                                               :

📚 Add reduction methods which operate on buffers.
📚 Add more math functions like sigmoid, sqrt, rsqrt, etc.
📚 Add partial load / store which enable loads and stores that are predicated on a condition.

Week of 2023-01-09

The / and * markers in function signatures are now parsed and their invariants are checked. We do not yet support keyword arguments yet though, so they aren’t very useful.
Functions now support a new @nodebug_inline decorator. (Historical note: this was later replaced with @alwaysinline("nodebug")).

Many of the things at the bottom level of the Mojo stack are trivial zero-abstraction wrappers around MLIR things, for example, the + operator on Int or the __bool__ method on Bool itself. These operators need to be force inlined even at -O0, but they have some additional things that we need to wrestle with:
1. In no case would a user actually want to step into the __bool__ method on Bool or the + method on Int. This would be terrible debugger QoI for unless you’re debugging Int itself. We need something like __always_inline__, __nodebug__ attributes that clang uses in headers like xmmintrin.h.
2. Similarly, these “operators” should be treated by users as primitives: they don’t want to know about MLIR or internal implementation details of Int.
3. These trivial zero abstraction things should be eliminated early in the compiler pipeline so they don’t slow down the compiler, bloating out the call graph with trivial leaves. Such thing slows down the elaborator, interferes with basic MLIR things like fold(), bloats out the IR, or bloats out generated debug info.
4. In a parameter context, we want some of these things to get inlined so they can be simplified by the attribute logic and play more nicely with canonical types. This is just a nice to have thing those of us who have to stare at generated IR.
The solution to this is a new @nodebug_inline decorator. This decorator causes the parser to force-inline the callee instead of generating a call to it. While doing so, it gives the operations the location of the call itself (that’s the “nodebug” part) and strips out let decls that were part of the internal implementation details.

This is a super-power-user-feature intended for those building the standard library itself, so it is intentionally limited in power and scope: It can only be used on small functions, it doesn’t support regions, by-ref, throws, async, etc.
Separately, we now support an @alwaysInline decorator on functions. This is a general decorator that works on any function, and indicates that the function must be inlined. Unlike @nodebug_inline, this kind of inlining is performed later in the compilation pipeline.
The __include hack has been removed now that we have proper import support.
__mlir_op can now get address of l-value:

You can use magic (((x))) syntax in __mlir_op that forces the x expression to be an lvalue, and yields its address. This provides an escape hatch (isolated off in __mlir_op land) that allows unsafe access to lvalue addresses.
We now support __rlshift__ and __rtruediv__.
📢 The parser now resolves scoped alias references. This allows us to support things like SomeType.someAlias, forward substituting the value. This unblocks use of aliases in types like DType. We’d like to eventually preserve the reference in the AST, but this unblocks library development.
📚 Add a now function and Benchmark struct to enable timing and benchmarking.
📚 Move more of the computation in NDBuffer from runtime to compile time if possible (e.g. when the dimensions are known at compile time).

Week of 2023-01-02

📚 Added the print function which works on Integers and SIMD values.

The frontend now has a new diagnostic subsystem used by the kgen tool (but not by kgen-translate for tests) that supports source ranges on diagnostics. Before we’d emit an error like:

x.mojo:13:3: error: invalid call to 'callee': in argument #0, value of type '$F32::F32' cannot be converted to expected type '$int::Int'
  callee(1.0+F32(2.0))
  ^
x.lit:4:1: note: function declared here
fn callee(a: Int):
^

now we produce:

x.mojo:13:3: error: invalid call to 'callee': in argument #0, value of type '$F32::F32' cannot be converted to expected type '$int::Int'
  callee(1.0+F32(2.0))
  ^      ~~~~~~~~~~~~
x.lit:4:1: note: function declared here
fn callee(a: Int):
^

📢 Parameter results are now supported in a proper way. They are now forward declared with an alias declaration and then bound in a call with an arrow, e.g.:
```
alias a : __mlir_type.index
alias b : __mlir_type.index
idx_result_params[xyz*2 -> a, b]()
```
Various minor issues with implicit conversions are fixed. For instances, implicit conversions are now supported in parameter binding contexts and alias declarations with explicit types.
Doc strings are allowed on functions and structs, but they are currently discarded by the parser.
📚 Add a print method!!!
📚 Demonstrate a naive matmul in Mojo.
📚 Initial work on functions that depend on types (e.g. FPUtils, nan, inf, etc.)
📚 Allow one to query hardware properties such as simd_width, os, etc. via TargetInfo at compile time.

December 2022

Week of 2022-12-26

📢 You can now call functions in a parameter context! Calling a function in a parameter context will evaluate the function at compile time. The result can then be used as parameter values. For example,
```
fn fma(x: Int, y: Int, z: Int) -> Int:
    return a + b * c

fn parameter_call():
    alias nelts = fma(32, 2, 16)
    var x: SIMD[f32, nelts]
```
You can now disable printing of types in an __mlir_attr substitution by using unary + expression.
📢 let declarations are now supported in functions. let declarations are local run-time constant values, which are always rvalues. They complement ‘var’ decls (which are mutable lvalues) and are the normal thing to use in most cases. They also generate less IR and are always in SSA form when initialized.

We will want to extend this to support ‘let’ decls in structs at some point and support lazy initialized ‘let’ declarations (using dataflow analysis) but that isn’t supported yet.
📚 Add the NDBuffer struct.
Happy new year.

Week of 2022-12-19

📚 Start of the Standard library:
1. Added Integer and SIMD structs to bootstrap the standard library.
2. Added very basic buffer data structure.
We have basic support for parsing parameter results in function calls! Result parameters are an important Mojo metaprogramming feature. They allow functions to return compile-time constants.
```
fn get_preferred_simdwidthof[() -> nelts: Int]():
    return[2]

fn vectorized_function():
    get_preferred_simdwidthof[() -> nelts]()
    var x: SIMD[f32, nelts]
```
Types can now be used as parameters of !kgen.mlirtype in many more cases.
MLIR operations with zero results don’t need to specify _type: [] anymore.
We support parsing triple quoted strings, for writing docstrings for your functions and structs!
A new __mlir_type[a,b,c] syntax is available for substituting into MLIR types and attributes is available, and the old placeholder approach is removed. This approach has a few advantages beyond what placeholders do:
1. It’s simpler.
2. It doesn’t form the intermediate result with placeholders, which gets rejected by MLIR’s semantic analysis, e.g. the complex case couldn’t be expressed before.
3. It provides a simple way to break long attrs/types across multiple lines.
We now support an @evaluator decorator on functions for KGEN evaluators. This enables specifying user-defined interface evaluators when performing search during compilation.
📢 import syntax is now supported!

This handles packaging imported modules into file ops, enables effective isolation from the other decls. “import” into the desired context is just aliasing decls, with the proper symbols references handle automatically during IR generation. As a starting point, this doesn’t handle any notion of packages (as those haven’t been sketched out enough).
📢 Reversed binary operators (like __radd__) are now looked up and used if the forward version (like __add__) doesn’t work for some reason.
📢 Implicit conversions are now generally available, e.g. in assign statements, variable initializers etc. There are probably a few more places they should work, but we can start eliminating all the extraneous explicit casts from literals now.
Happy Holidays

Week of 2022-12-12

📢 Function overloading now works. Call resolution filters candidate list according to the actual parameter and value argument specified at the site of the call, diagnosing an error if none of the candidates are viable or if multiple are viable and ambiguous. We also consider implicit conversions in overload look:
```
fn foo(x: Int): pass
fn foo(x: F64): pass

foo(Int(1)) # resolves to the first overload
foo(1.0)    # resolves to the second overload
foo(1)      # error: both candidates viable with 1 implicit conversion!
```
The short circuiting binary and and or expressions are now supported.
Unary operator processing is a lot more robust, now handling the not expression and ~x on Bool.
📢 The compiler now generates debug information for use with GDB/LLDB that describes variables and functions.
The first version of the Mojo Visual Studio Code extension has been released! It supports syntax highlighting for Mojo files.
The first version of the Bool type has landed in the new Mojo standard library!
📢 Implicit conversions are now supported in return statements.

Week of 2022-12-05

“Discard” patterns are now supported, e.g. _ = foo()
We now support implicit conversions in function call arguments, e.g. converting an index value to Int automatically. This eliminates a bunch of casts, e.g. the need to say F32(1.0) everywhere.

This is limited for a few reasons that will be improved later:
1. We don’t support overloading, so lots of types aren’t convertible from all the things they should be, e.g. you can’t pass “1” to something that expects F32, because F32 can’t be created from index.
2. This doesn’t “check to see if we can invoke __new__” it force applies it on a mismatch, which leads to poor QoI.
3. This doesn’t fix things that need radd.

November 2022

Week of 2022-11-28

📢 We support the True and False keywords as expressions.
📢 A new alias declaration is supported which allows defining local parameter values. This will eventually subsume type aliases and other things as it gets built out.
📢 We now have end-to-end execution of Mojo files using the kgen tool! Functions exported with @export can be executed.
📢 We have try-except-else and raise statements and implicit error propagation! The error semantics are that def can raise by default, but fn must explicitly declare raising with a @raises decorator. Stub out basic Error type.
The & sigil for by-ref arguments is now specified after the identifier. Postfix works better for ref and move operators on the expression side because it chains an mentally associates correctly: thing.method().result^. We don’t do that yet, but align param decl syntax to it so that things won’t be odd looking when we do. In practice this looks like:
```
def mutate_argument(a&: index):
    a = 25
```

Week of 2022-11-21

📢 The magic index type is gone. Long live __mlir_type.index.
Implement parameter substitution into parametric __mlir_type decls. This allows us to define parametric opaque MLIR types with exposed parameters using a new “placeholder” attribute. This allows us to expose the power of the KGEN type parametric system directly into Mojo.

📢 Fully-parametric custom types can now be defined and work in Mojo, bringing together a lot of the recent work. We can write the SIMD type directly as a wrapper around the KGEN type, for example:

struct SIMD[dt: __mlir_type.`!kgen.dtype`, nelts: __mlir_type.index]:
    var value:
      __mlir_type.`!pop.simd<#lit<placeholder index>,
                             #lit<placeholder !kgen.dtype>>`[nelts, dt]

    fn __add__(self, rhs: SIMD[dt, nelts]) -> SIMD[dt, nelts]:
        return __mlir_op.`pop.add`(self.value, rhs.value)

Week of 2022-11-14

📢 Implement a magic __mlir_type declaration that can be used to access any MLIR type. E.g. __mlir_type.f64.
📢 Add an fn declaration. These are like def declarations, but are more strict in a few ways: they require type annotations on arguments, don’t allow implicit variable declarations in their body, and make their arguments rvalues instead of lvalues.
Implemented Swift-style backtick identifiers, which are useful for code migration where names may collide with new keywords.
📢 A new __include directive has been added that performs source-level textual includes. This is temporary until we have an import model.
Implement IR generation for arithmetic operators like + and * in terms of the __add__ and __mul__ methods.
📢 Added support for break and continue statements, as well as early returns inside loops and conditionals!
📢 Implemented augmented assignment operators, like += and @=.
📢 Mojo now has access to generating any MLIR operations (without regions) with a new __mlir_op magic declaration. We can start to build out the language’s builtin types with this:
```
struct Int:
    var value: __mlir_type.index

    fn __add__(self, rhs: Int) -> Int:
        return __mlir_op.`index.add`(self.value, rhs.value)
```
Attributes can be attached to the declaration with subscript [] syntax, and an explicit result type can be specified with a special _type attribute if it cannot be inferred. Attributes can be accessed via the __mlir_attr magic decl:
```
__mlir_op.`index.cmp`[
    _type: __mlir_type.i1,
    pred: __mlir_attr.`#index<cmp_predicate slt>`
](lhs, rhs)
```
Improved diagnostics emissions with ranges! Now errors highlight the whole section of code and not just the first character.

Week of 2022-11-07

Implemented the @interface and @implements decorators, which provide access to KGEN generator interfaces. A function marked as an @interface has no body, but it can be implemented by multiple other functions.

@interface
def add(lhs: index, rhs: index):

@implements(add)
def normal_add(lhs: index, rhs: index) -> index:
    return lhs + rhs

@implements(add)
def slow_add(lhs: index, rhs: index) -> index:
    wait(1000)
    return normal_add(lhs, rhs)

📢 Support for static struct methods and initializer syntax has been added. Initializing a struct with Foo() calls an implicitly static __new__ method. This method should be used instead of __init__ inside structs.

struct Foo:
    var value: index

    def __new__() -> Foo:
        var result: Foo
        result.value = Foo.return_a_number() # static method!
        return result

    @staticmethod
    def return_a_number() -> index:
        return 42

📢 Full by-ref argument support. It’s now possible to define in-place operators like __iadd__ and functions like swap(x, y) correctly.
📢 Implemented support for field extract from rvalues, like x.value where x is not an lvalue (var declaration or by-ref function argument).

October 2022

Week of 2022-10-31

Revised return handling so that a return statement with no expression is syntax sugar for return None. This enables early exits in functions that implicitly return None to be cleaner:
```
def just_return():
    return
```
Added support for parsing more expressions: if-else, bitwise operators, shift operators, comparisons, floor division, remainder, and matmul.
📢 The type of the self argument can now be omitted on member methods.

Week of 2022-10-24

Added parser support for right-associativity and unary ops, like the power operator a ** b ** c and negation operator -a.
Add support for &expr in Mojo, which allows denoting a by-ref argument in functions. This is required because the self type of a struct method is implicitly a pointer.

Implemented support for parametric function declarations, such as:

struct SIMD[dt: DType, width: index]:
    fn struct_method(self: &SIMD[dt, width]):
        pass

def fancy_add[dt: DType, width: index](
    lhs: SIMD[dt, width], rhs: SIMD[dt, width]) -> index:
  return width

Week of 2022-10-17

Added explicit variable declarations with var, for declaring variables both inside functions and structs, with support for type references. Added index as a temporary built-in type.
```
def foo(lhs: index, rhs: index) -> index:
    var result: index = lhs + rhs
    return result
```
Implemented support for parsing struct declarations and references to type declarations in functions! In def, the type can be omitted to signal an object type.
```
struct Foo:
    var member: index

def bar(x: Foo, obj) -> index:
    return x.member
```

Implemented parser support for if statements and while loops!

def if_stmt(c: index, a: index, b: index) -> index:
    var result: index = 0
    if c:
        result = a
    else:
        result = b
    return result

def while_stmt(init: index):
    while init > 1:
        init = init - 1

Significantly improved error emission and handling, allowing the parser to emit multiple errors while parsing a file.

Week of 2022-10-10

Added support for parsing integer, float, and string literals.
Implemented parser support for function input parameters and results. You can now write parametric functions like,
```
def foo[param: Int](arg: Int) -> Int:
    result = param + arg
    return result
```

Week of 2022-10-03

Added some basic parser scaffolding and initial parser productions, including trivial expressions and assignment parser productions.
Implemented basic scope handling and function IR generation, with support for forward declarations. Simple functions like,
```
def foo(x: Int):
```
Now parse! But all argument types are hard-coded to the MLIR index type.
Added IR emission for simple arithmetic expressions on builtin types, like x + y.

September 2022

Week of 2022-09-26

Mojo’s first patch to add a lexer was Sep 27, 2022.
Settled on [] for Mojo generics instead of <>. Square brackets are consistent with Python generics and don’t have the less than ambiguity other languages have.