Elaboration on some categories of errors thrown by Pyre.
Pyre Error : Incompatible Variable Type
Pyre will error when assigning incompatible types to local variables and parameters that were explicitly annotated.
That is, the following will error:
def f(x: int) -> None: x = "" # Incompatible variable type error y: int = 1 y = "" # Incompatible variable type error
The rationale here is that it's surprising for an explicitly annotated variable to have an incompatible type later on in the same function.
If you intended to change the type of the variable, you can explicitly annotate it with the new type:
def f(x: int) -> None: x: str = "" # No errors! y: int = 1 y: str = "" # No errors!
Pyre Errors [14/15]: Behavioral Subtyping
Method overrides should follow Liskov's substitution principle. In short, parameter types can't be more restrictive and return types can't be more permissive in overridden methods. To see why, consider the following example:
def width(image: Image) -> float: return image.width()
Say we now have different implementations of our
Image class, one of which
violates the substitution principle:
class Image: def width() -> float: pass class JpegImage(Image): def width() -> int: return 10 # this is fine class ComplexImage(Image): def width() -> complex: return 1j
width function above breaks when used with a
The case for parameters follows analogously.
Pyre Errors : Missing Attributes
Your code is most likely trying to access an attribute that Pyre does not know about. Pyre has various ways of inferring what is an attribute of an object:
class Derp: attribute: int = 1 @property def property(self) -> int: ...
class Derp: def __init__(self): self.attribute: int = 1
Pyre does one level of inlining to infer implicit parameters We suggest you do not heavily rely on this feature as it is not sound and makes our code brittle. Support for this is temporary.
Pyre Errors [18/21]: Undefined Name, Undefined Import
Error 18 ("Undefined name") is raised when your code tries to access a variable or function that Pyre could not resolve. This is usually caused by failing to import the proper module.
# 'import some_module' is missing some_module.some_func()
Pyre will raise error 21 instead ("Undefined import") when the import statement is present, but the module to be imported could not be found in the search path.
If the module provides stub files, please provide their location via the
--search-path commandline parameter.
List and Dictionary Mismatches With Subclassing
Pyre will error when, for instance, a
List[int] is passed in when a
List[float] is expected, as in the following example:
def to_seconds(milliseconds: List[float]) -> List[int]: return [int(x/1000.0) for x in milliseconds] my_list: List[int] =  my_list = to_seconds(my_list) # Pyre errors here!
This code is fine at runtime, so it might be surprising that Pyre errors here. However, consider the following code:
def halve_first_element(list: List[float]) -> None: list /= 2 my_list: List[int] =  halve_first_element(my_list) function_taking_int(my_list) # Oh no, my_list is 0.5!
If we allowed passing in
my_list to the
halve_first_element function here, the above code would type check. It's perfectly valid from the perspective of the callee to modify the list's element to be a float, as it was annotated as taking a list of floats, but because this list escapes the scope of the callee, we can't allow this in the type checker.
To work around this, we can signal to the type checker that the parameter can't be modified. Here's how you can tell the type checker that you won't change the container in your function:
# I can't modify milliseconds here, so it's safe to pass a Iterable[int]. def to_seconds(milliseconds: Iterable[float]) -> List[int]: return [int(x/1000.0) for x in milliseconds] my_list: List[int] =  my_list = to_seconds(my_list) # Type checks!
typing.Iterable is an immutable variant for lists that allows accessing the list without modifying it. Most commonly used generic containers have immutable variants, and I would encourage you to use them for function parameters whenever you don't need to modify a container in your function.
Here are some immutable variants for commonly used containers:
typing.List → typing.Iterable typing.Dict → typing.Mapping typing.Set → typing.AbstractSet
Invariance, combined with type inference, comes with a few gotchas. When you write an expression, Pyre infers the most precise type possible. For instance, Pyre infers the
List[int] type for
[1, 2], even though
List[float] would be a perfectly valid type here. This can cause issues, as in the following example:
def zeroes(number_of_elements: int) -> List[float]: a =  * number_of_elements return a # Pyre errors here!
What happened above is that Pyre inferred a type of
List[int] for a, and invariance kicked in. You can work around this by adding an explicit annotation when declaring a:
def zeroes(number_of_elements: int) -> List[float]: a: List[float] =  * number_of_elements return a # Type checks!