Function attributes and decorators
We will take the code below as an example.
def count(f):
"""Count how many times the recursive function runs"""
def counted(n):
counted.call_count += 1
return f(n)
counted.call_count = 0
return counted
@count
def fib(n):
if n == 0 or n == 1:
return n
else:
return fib(n-2) + fib(n-1)
Function attributes
This is not special for python. Given that python is object-oriented programming, it’s kin of easy to understand that function, which is also an object, can have attributes.
We can check what attributes and methods fib has through dir. There are so many things in the list, two important things are __dict__ and call_count. The appearence of call_count means we already add a new attribute to this function fib.
As for __dict__, in PEP232,this proposal adds a new dictionary to function objects, called func_dict(a.k.a. __dict__).
This dictionary can be set and get using ordinary attribute set and get syntax.
- Deleting a function’s
__dict__, or setting it to anything other than a concrete dictionary object results in a TypeError.- If no function attributes have ever been set, the function’s
__dict__will be empty.
>>> dir(fib)
['__annotations__', '__call__', '__class__', '__closure__', '__code__', '__defaults__', '__delattr__', '__dict__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__get__', '__getattribute__', '__globals__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__kwdefaults__', '__le__', '__lt__', '__module__', '__name__', '__ne__', '__new__', '__qualname__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', 'call_count']
>>> hasattr(fib, 'call_count')
True
>>> fib.__dict__
{'call_count': 3}
>>> count.__dict__
{}
Because we assign a default value 0 to this cal_count attribute in the decorator, the value of fib.__dict__['call_count'] would be 0 when fib hasn’t been called.
Decorators
A decorator is a design pattern in Python that allows a user to add new functionality to an existing object without modifying its structure.
The @count we put just above the target function we want to extend is a shorthand for fib = count(fib). These two syntaxes both create a new version of fib that can count the number of recursion.
Given the purpose, we need to ensure the return of decorator is the new version of function we want when design the decorator. Here, counted in decorator is exactly the new version of fib we want. You can see that we create a new attribute for function counted, which means our new version of fib will have this attribute.
List operations
Slice assignment
slice assignment replaces a slice with new values. If the length of the slice is shorter than the length of the values. extra values will be added and then the length of original list will be larger. Slice assignment can also remove elements from a list by assigning [] to a slice.
>>> x = [1,2]
>>> x[0:0]
[]
>>> x[0:0] = [5]
>>> x
[5, 1, 2]
>>> x[1:1] = [0]
>>> x
[5, 0, 1, 2]
>>> x[1:2] = [9]
>>> x
[5, 9, 1, 2]
Copy of lists
The only two ways that you can get a copy of a list are: list(t) and t[:].
In the example below, [t] doesn’t a list of a copy of t, so if t changes, [t] also changes.
>>> t = [1,2,3]
>>> t[1:3] = [t]
>>> t
[1, [...]]
>>> t.extend(t)
>>> t
[1, [...], 1, [...]]