Open xmnlab opened 1 month ago
just an idea for the get_struct
and __str__
methods:
def __str__(self) -> str:
"""Return a string representation of the lambda expression."""
params_str = ", ".join(arg.name for arg in self.params.args)
return f"lambda {params_str}: {self.body}"
def get_struct(self, simplified: bool = False) -> ReprStruct:
"""Return the AST structure of the lambda expression."""
key = "LambdaExpr"
value: ReprStruct = {
"params": self.params.get_struct(simplified),
"body": self.body.get_struct(simplified),
}
return self._prepare_struct(key, value, simplified)
Suggestion for the graphical/ascii representation:
[LambdaExpr]
| |
params body
| |
[Arguments (1)] [Expr]
|
[Argument(myargname)]
PS1: the final result could be different because it depends on the implementation.
PS2: the values inside []
are ASTx nodes/classes
Examples of output for the python transpiler:
lambda v: v
lambda: 1
lambda a, b: (a+b)
lambda a, b, c: ((a+b) + c)
from gpt:
1. Update
ASTKind
Enum inastx/base.py
Add the following line to your
ASTKind
enumeration to include the newLambdaExprKind
:2. Define
LambdaExpr
inastx/expressions.py
Add the following class definition to represent lambda expressions:
Notes:
Arguments
from wherever it's defined, typically used in function definitions.params
: AnArguments
instance representing the parameters of the lambda.body
: AnExpr
representing the body of the lambda function.LambdaExpr
with parameters and body, setting the appropriateASTKind
.3. Usage Example (Optional)
If you need to see how it might be used: