Bython (aka Python w/ Braces)

Regardless of the braces syntax you use, Bython has your back! Check out the following that have been tested and should work flawlessly!

def example(value: T) -> T
{
    return value;
}

for value in [] {
    return value;
}

while True {
}

if True {} else {}

To run a Bython file, you can do one of the following:

• drag the bython file onto the command file
• run bython "path_to_bython_file/filename.txt" in a command line

More configurations can be found by running bython -h

Other Major Additions

• This is bython, not python. This doesn't require indentations but you will have to use braces ({, }) and semicolons (;)
• Increment and Decrement operators have been added such as:
  • ++x->(x:=x+1)
  • x++->((x:=x+1)-1)
  • --x->(x:=x-1)
  • x--->((x:=x-1)+1)
• Increment and Decrement operators also work with values such as:
  • ++1->1+1
  • 2++->2
  • --3->3-1
  • 4--->4
• until loops have been added and function as a while not loop
• do-while loops have been added and can be used as:

  x=0;
  do {
      print(x);
      x++;
  } while x < 5;
  

• for-loop standard styling from languages such as C++ has been added and can be used as:

  for (i=0; i < 5; i+=2) {
      print(i);
  }
  

• Unique for-loop behavior has been implemented to make prefix and postfix operators influence the order of incrementation and loop checks making for(i=0;i<5;i++) have the values [0, 1, 2, 3, 4] while for(i=0;i<5;++i) has the values [1, 2, 3, 4, 5]
• The interface class declaration has also been added for classes you don't want instantiated
• Along with the and, or, raise, except, and elif keywords, &&, ||, throw, catch, and else if have also been implemented respectively
• Comments can now be declared with // for single line comments and /* to open multiline comments and */ to close them

What is the utils package?

The utils package contains small utilities to make Python, and by extension Bython, more user-friendly. The package adds in "hidden" types that Python has but hides from the user along with faster, more useful and user friendly, or completely new functions that work in standard Python!

• The copy function has been reworked to now copy entire classes, functions, and multi-dimensional lists and dictionaries
• The set data container has been completely remade to now be a blend of the best parts of lists and dictionaries while sporting an all new look without losing any of its original functionality making visualisations of data such as set(1,2,a=4) be represented as {0:1,1:2,a:4}
• The flatten function has been added to take a multi-dimensional list and make it into a one-dimensional list
• The builtin type function has been reworked to now be much more useful by giving deeper type descriptions such as type({'a':[1,2]}) returning dict[str,list[int]]
• The builtin isinstance function has also bee reworked to remove that pesky isinstance(True,int) from returning True while also now checking deeper typing such as isinstance([1,"a"],list[int|str])
• The builtin vars function finally has something useful to do! The function now returns a dict of all variables used within the function it is used on such as def func(x:int)->int:pass returning {'x':{'type':int},'return':{'type':int}}
• The annotate wrapper (used with functions and methods) has been added to enforce deep-typing annotations on the arguments of functions
• The init wrapper (used with classes) has been added to build those annoying init methods of classes using simple annotations and default values
• The factory class has been added to make using the init wrapper even more user-friendly by allowing unique instantiations of data containers by using the new copy function
• The constants wrapper (used with classes) has been added for when you want some members of a class to be constants
• The dicts wrapper (used with classes) unifies the attributes and indeces of a class allowing both instance["value"] and instance.value to function identically
• The private wrapper (used with methods) allows Private Members to be declared in Python by using stack checking

What is the overloads package?

• The overloads package contains a new utility that utilizes the utils package. The package adds the ability to overload class instance methods with the new typing utilities from utils with complete type depth!
• A quick example can be seen below. Depending on the type of the arguments passed in, a different method will be called!
• For an in-depth explaination of how this all works, check out mCoding's video here!

class Test(metaclass=OverloadMeta):
        @overload
        def test(self, x: int):
            print("Passed an integer")
        @overload
        def test(self, x: str):
            print("Passed a string")
        @overload
        def test(self, x: list[int]):
            print("Passed a list of integers")
        @overload
        def test(self, x: list[str]):
            print("Passed a list of strings")
        @overload
        def test(self, x: duck):
            print("Passed other")
        @overload
        def test(self, *x: int):
            print("Passed integers")
        @overload
        def test(self, *x: duck):
            print("Passed others")

Small Changes/Additions To Keep In Mind

• Use parentheses ((, )) around lambda functions
• Use parentheses ((, )) around until loop conditions
• Single-element dictionaries and sets must have a comma after the lone element (similar to the declaration of a single-element tuple) - this is to allow for easy pass blocks without using the keyword such as: else: pass now being written as else {}
• Comments are immediately removed by the compiler and can be declared with #, //, or a multiline comment starting with /* and closing with */
• Comments CANNOT use string characters that are not escaped with \ such as \' and \"

Minor Bugs

• Type annotations, in general, can cause issues, so use them with caution. Hopefully, many should work
• As with annotations, f-strings can also cause issues