Python syntax question. "mylist(csv_location: str): -> list:" [duplicate]
It's a function annotation.
In more detail, Python 2.x has docstrings, which allow you to attach a metadata string to various types of object. This is amazingly handy, so Python 3 extends the feature by allowing you to attach metadata to functions describing their parameters and return values.
There's no preconceived use case, but the PEP suggests several. One very handy one is to allow you to annotate parameters with their expected types; it would then be easy to write a decorator that verifies the annotations or coerces the arguments to the right type. Another is to allow parameter-specific documentation instead of encoding it into the docstring.
These are function annotations covered in PEP 3107. Specifically, the ->
marks the return function annotation.
Examples:
def kinetic_energy(m:'in KG', v:'in M/S')->'Joules':
return 1/2*m*v**2
>>> kinetic_energy.__annotations__
{'return': 'Joules', 'v': 'in M/S', 'm': 'in KG'}
Annotations are dictionaries, so you can do this:
>>> '{:,} {}'.format(kinetic_energy(12,30),
kinetic_energy.__annotations__['return'])
'5,400.0 Joules'
You can also have a python data structure rather than just a string:
rd={'type':float,'units':'Joules',
'docstring':'Given mass and velocity returns kinetic energy in Joules'}
def f()->rd:
pass
>>> f.__annotations__['return']['type']
<class 'float'>
>>> f.__annotations__['return']['units']
'Joules'
>>> f.__annotations__['return']['docstring']
'Given mass and velocity returns kinetic energy in Joules'
Or, you can use function attributes to validate called values:
def validate(func, locals):
for var, test in func.__annotations__.items():
value = locals[var]
try:
pr=test.__name__+': '+test.__docstring__
except AttributeError:
pr=test.__name__
msg = '{}=={}; Test: {}'.format(var, value, pr)
assert test(value), msg
def between(lo, hi):
def _between(x):
return lo <= x <= hi
_between.__docstring__='must be between {} and {}'.format(lo,hi)
return _between
def f(x: between(3,10), y:lambda _y: isinstance(_y,int)):
validate(f, locals())
print(x,y)
Prints
>>> f(2,2)
AssertionError: x==2; Test: _between: must be between 3 and 10
>>> f(3,2.1)
AssertionError: y==2.1; Test: <lambda>
In the following code:
def f(x) -> int:
return int(x)
the -> int
just tells that f()
returns an integer (but it doesn't force the function to return an integer). It is called a return annotation, and can be accessed as f.__annotations__['return']
.
Python also supports parameter annotations:
def f(x: float) -> int:
return int(x)
: float
tells people who read the program (and some third-party libraries/programs, e. g. pylint) that x
should be a float
. It is accessed as f.__annotations__['x']
, and doesn't have any meaning by itself. See the documentation for more information:
https://docs.python.org/3/reference/compound_stmts.html#function-definitions https://www.python.org/dev/peps/pep-3107/
As other answers have stated, the ->
symbol is used as part of function annotations. In more recent versions of Python >= 3.5
, though, it has a defined meaning.
PEP 3107 -- Function Annotations described the specification, defining the grammar changes, the existence of func.__annotations__
in which they are stored and, the fact that it's use case is still open.
In Python 3.5
though, PEP 484 -- Type Hints attaches a single meaning to this: ->
is used to indicate the type that the function returns. It also seems like this will be enforced in future versions as described in What about existing uses of annotations:
The fastest conceivable scheme would introduce silent deprecation of non-type-hint annotations in 3.6, full deprecation in 3.7, and declare type hints as the only allowed use of annotations in Python 3.8.
(Emphasis mine)
This hasn't been actually implemented as of 3.6
as far as I can tell so it might get bumped to future versions.
According to this, the example you've supplied:
def f(x) -> 123:
return x
will be forbidden in the future (and in current versions will be confusing), it would need to be changed to:
def f(x) -> int:
return x
for it to effectively describe that function f
returns an object of type int
.
The annotations are not used in any way by Python itself, it pretty much populates and ignores them. It's up to 3rd party libraries to work with them.
This means the type of result the function returns, but it can be None
.
It is widespread in modern libraries oriented on Python 3.x.
For example, it there is in code of library pandas-profiling in many places for example:
def get_description(self) -> dict:
def get_rejected_variables(self, threshold: float = 0.9) -> list:
def to_file(self, output_file: Path or str, silent: bool = True) -> None:
"""Write the report to a file.