Adds dynamically interface of iterator to class
Project description
IteratorDecorator
Implementing iterator in Python is nothing complicated though what’s missing is possibility to make it even easier. This small library adds iter_attribute decorator allowing to quickly choose iterable for which iterator would be implemented.
Requirements
Python3.5+
Example
from IteratorDecorator import iter_attribute
@iter_attribute('number')
class CaseClass:
def __init__(self):
self.number = [1, 2, 3, 4]
self.attr = ['attr1', 'attr2', 'attr3']
obj = CaseClass()
for num in obj:
print(num)
Installing
You can either clone repo and create egg file manually by running make dist or add requirement to requirements.txt file with line:
-e git://github.com/stovorov/IteratorDecorator.git#egg=IteratorDecorator
pip will then clone repo and create distribution file in venv/src of your project. Then you can use code like normal library:
from IteratorDecorator import iter_attribute
Warning
When using PyCharm or MYPY you’ll probably see issues with decorated class not being recognized as Iterator. That’s an issue which I could not overcome yet, it’s probably due to the fact that interpretation of object is being done statically rather than dynamically. MYPY checks for definition of methods in class code which changes at runtime. Since __iter__ and __next__ are added dynamically MYPY cannot find those defined in objects before object of a class is created. Possible workarounds for this issue are:
Define __iter__ class like:
@iter_attribute('attr')
class Test:
def __init__(self) -> None:
self.attr = [1, 2, 3]
def __iter__(self) -> 'Test':
return self
Actually it does not have to be “real” __iter__ since it’ll be replaced by decorator implementation, but the definition is only needed for static checkers.
After creating object use cast or assert function denoting that particular instance inherits
from collections.Iterator:
assert isinstance(my_object, collections.Iterator)
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