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The Mamba programming language 🐍, because we care about safety
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README.md

Safety first!

Travis Appveyor Code Quality Coverage
License Built with Love

Mamba

This is the Mamba programming language. The Documentation can be found here. This documentation outlines the different language features, and also contains a formal specification of the language.

In short, Mamba is like Python, but with a few key features:

  • Strict typing rules, but with type inference so it doesn't get in the way too much, and type refinement features.
  • Null safety features.
  • More explicit error handling.
  • Clear distinction between mutability and immutability.
  • Pure functions, or, functions without side effects.

This is a transpiler, written in Rust, which converts Mamba source code to Python source files. Mamba code should therefore, in theory, be interoperable with Python code. Functions written in Python can be called in Mamba and vice versa.

⌨️ Code Examples

Below are some code examples to showcase the features of Mamba. We highlight how functions work, how de define classes, how types and type refinement features are applied, how Mamba can be used to ensure pureness, and how error handling works. For more extensive examples and explanations check out the documentation.

βž• Functions

We can write a simple script that computes the factorial of a value given by the user.

def factorial(x: Int) => match x
    0 => 1
    n => n * factorial(n - 1)

def num <- input "Compute factorial: "
if num.is_digit then
    def result <- factorial int num
    print "Factorial {num} is: {result}."
else
    print "Input was not an integer."

Notice how here we specify the type of argument x, in this case an Int, by writing x: Int. This means that the compiler will check for us that factorial is only used with integers as argument.

πŸ“‹ Classes and mutability

Classes are similar to classes in Python, though we can for each function state whether we can write to self or not by stating whether it is mutable or not. We showcase this using a simple dummy Server object.

import ipaddress

class ServerError(def message: String) isa Exception(message)

class MyServer(def ip_address: IPv4Address)
    def mut is_connected: Bool           <- false
    def mut private last_message: String <- undefined

    def last_sent(self) raises [ServerError] => if self.last_message /= undefined 
        then message
        else raise ServerError("No last message!")

    def connect(mut self) => self.is_connected <- true

    def send(mut self, message: String) => if self.is_connected 
        then self.last_message <- message
        else Err("Not connected!")

    def disconnect(mut self) => self.is_connected <- true

Notice how:

  • self is not mutable in last_sent, meaning we can only read variables, whereas in connect self is mutable, so we can change properties of self.
  • last_message is private, denoted by the private keyword. This means that we cannot access is directly, meaning we cannot for instance do server.last_message <- "Mischief". Instead, we call server.last_sent.

Which we can then use as follows in our script:

import ipaddress
from server import MyServer

def some_ip   <- ipaddress.ip_address "151.101.193.140"
def my_server <- MyServer(some_ip)

http_server.connect
if my_server.connected then http_server send "Hello World!"

# This statement may raise an error, but for now de simply leave it as-is
# See the error handling section for more detail
print "last message sent before disconnect: \"{my_server.last_sent}\"." raises [ServerError]
my_server.disconnect

πŸ—ƒ Types and type refinement

As shown above Mamba has a type system. Mamba however also has type refinement features to assign additional properties to types.

Lets expand our server example from above, and rewrite it slightly:

import ipaddress

type Server
    def ip_address: IPv4Address

    def connect():     () -> ()       raises [ServerErr]
    def send(message): (String) -> () raises [ServerErr]
    def disconnect():  () -> ()

class ServerError(def message: String) isa Exception(message)

class MyServer(mut self: DisconnectedMyServer, def ip_address: IPv4Address) isa Server
    def mut is_connected: Bool           <- false
    def mut private last_message: String <- undefined

    def last_sent(self): String => if self.last_message /= undefined 
        then message
        else raise ServerError("No last message!")

    def connect(mut self: DisconnectedMyServer) => self.is_connected <- true

    def send(mut self: ConnectedMyServer, message: String) => self.last_message <- message

    def disconnect(mut self: ConnectedMyServer) => self.is_connected <- false

type ConnectedMyServer isa MyServer when
    self.is_connected else raise ServerErr("Not connected.")

type DisconnectedMyServer isa MyServer when
    not self.is_connected else raise ServerErr("Already connected.")

Notice how above, we define the type of self.

Each type effectively denotes another state that self can be in. For each type, we use when to show that it is a type refinement, which certain conditions.

import ipaddress
from server import MyServer

def some_ip   <- ipaddress.ip_address "151.101.193.140"
def my_server <- MyServer(some_ip)

# The default state of http_server is DisconnectedHTTPServer, so we don't need to check that here
http_server.connect

# We check the state
if my_server isa ConnectedMyServer then
    # http_server is a Connected Server if the above is true
    my_server.send "Hello World!"

print "last message sent before disconnect: \"{my_server.last_sent}\"." raises [ServerErr]
if my_server isa ConnectedMyServer then my_server.disconnect

Type refinement also allows us to specify the domain and co-domain of a function, say, one that only takes and returns positive integers:

type PositiveInt isa Int where self >= 0 else Err("Expected positive Int but was {self}.")

def factorial (x: PositiveInt) => match x
    0 => 1
    n => n * factorial (n - 1)

In short, types allow us to specify the domain and co-domain of functions with regards to the type of input, say, Int or String.

Type refinement allows us to to some additional things:

  • It allows us to further specify the domain or co-domain of a function
  • It allows us to explicitly name the possible states of an object. This means that we don't constantly have to check that certain conditions hold. We can simply ask whether a given object is a certain state by checking whether it is a certain type.

πŸ”’ Pure functions

Mamba has features to ensure that functions are pure, meaning that if x = y, for any f, f(x) = f(y). By default, functions are not pure, and can read any variable they want, such as in Python. When we make a function pure, it cannot:

  • Read mutable variables not passed as an argument (with one exception).
  • Read mutable properties of self. Mainly since self is never given as an argument, so a function output only depends on its explicit arguments.
  • Call impure functions.

With the above properties, we can ensure that a function is pure. pure is similar to mut. When a function is pure, its output is always the same for a given input. When a variable is immutable, when we omit mut, it can never change. So, pure is a property of functions, and mut is a property of variables.

def taylor <- 7

# the sin function is pure, its output depends solely on the input
def pure sin(x: Int) =>
    def mut ans <- x
    for i in 1 ..= taylor step 2 do
        ans <- (x ^ (i + 2)) / (factorial (i + 2))
    ans

We can add pure to the top of a file, which ensures all functions in said file are pure. This is useful when we want to write multiple pure functions.

pure

def taylor <- 7

def sin(x: Int): Real =>
    def mut ans <- x
    for i in 1 ..= taylor step 2 do ans <- (x ^ (i + 2)) / (factorial (i + 2))
    ans
    
def cos(x: Int): Real =>
    def mut ans <- x
    for i in 0 .. taylor step 2 do ans <- (x ^ (i + 2)) / (factorial (i + 2))
    ans

Generally speaking, global variables can cause a lot of headaches. Immutable variables and pure functions make it easy to write declarative programs with no hidden dependencies.

⚠ Error handling

Unlike Python, Mamba does not have try except and finally (or try catch as it is sometimes known). Instead, we aim to directly handle errors on-site so the origin of errors is more tracable. The following is only a brief example. Error handling can at times becomes quite verbose, so we do recommend checking out the docs on error handling to get a better feel for error handling.

We can modify the above script such that we don't check whether the server is connected or not. In that case, we must handle the case where my_server throws a ServerErr:

import ipaddress
from server import MyServer

def some_ip   <- ipaddress.ip_address "151.101.193.140"
def my_server <- MyServer(some_ip)

def message <- "Hello World!"
my_server.send message handle
    err: ServerErr => print "Error while sending message: \"{message}\": {err}"

if my_server isa ConnectedMyServer then my_server.disconnect

In the above script, we will always print the error since we forgot to actually connect to the server. Here we showcase how we try to handle errors on-site instead of in a (large) try block. This means that we don't need a finally block: We aim to deal with the error where it happens and then continue executing the remaining code. This also prevents us from wrapping large code blocks in a try, where it might not be clear what statement or expression might throw what error.

handle can also be combined with an assign. In that case, we must either always return (halting execution or exiting the function), or evaluate to a value. This is shown below:

def a <- function_may_throw_err() handle
    err : MyErr => 
        print "We have a problem: {err.message}."
        # we return, halting execution
        return
    err : MyOtherErr => 
        print "We have another problem: {err.message}."
        # or if we don't return, return a default value
        0
        
print "a has value {a}."

If we don't want to use a handle, we can simply use raises after a statement or exception to show that its execution might result in an exception, but we don't want to handle that here. See the sections above for examples where we don't handle errors and simply pass them on using raises.

πŸ’» Using the Command Line Interface

Usage

mamba [OPTIONS]

Options

-i, --input <INPUT>      Input file or directory.
                         If file, file taken as input.
                         If directory, recursively search all sub-directories for *.mamba files.
                         If no input given, current directory used as input directory.
-o, --output <OUTPUT>    Output directory to store mamba files.
                         Output directory structure reflects input directory structure.
                         If no output given, 'target' directory created in current directory and is used as ouput.

You can type mamba -help for a message containing roughly the above information.

πŸ‘₯ Contributing

Before submitting your first issue or pull request, please take the time to read both our contribution guidelines and our code of conduct.

πŸ”¨ Tooling

Several tools are used to help maintain the quality of the codebase. These tools are used by the continuous integration tools to statically check submitted code. Therefore, to save time, it is a good idea to install these tools locally and run them before pushing your changes.

Rustfmt

Rustfmt formats Rust code and ensures the formatting is consistent across the codebase.

  • To install rustup component add rustfmt --toolchain nightly
  • To run cargo +nightly fmt

The configuration of Rustfmt can be found in .rustfmt.toml.

Note The nightly build of cargo must be used (rustup install nightly).

Clippy

Clippy catches common mistakes made in Rust.

  • To install rustup component add clippy
  • To run cargo clippy

The configuration of Clippy can be found in .clippy.toml.

Note The stable build of cargo must be used (rustup install stable).

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