Python progression path – From apprentice to guru is a popular StackOverflow post. To categorize whether a person should take his beginner/intermediate course, one of the commentors posted this question:
I can better answer this question after reading Fluent Python. Example 1 and Example 2 deal with immutable and mutable data types – respectively. Let’s address each example individually.
Example 1
The id built in method returns the object’s memory address. We’ll use this to inspect the memory address for x and ythroughout the examples.
x and y point to the same memory address when they are first assigned.
>>> x = 42 >>> y = x >>> id(x) 4298172632 >>> id(y) 4298172632
Because the value of x is immutable (e.g INT) and cannot be modified, by definition, a new memory address is allocated when x is modified. But, y‘s memory remains unmodified:
>>> x = x + 1 >>> id(x) 4298172608 >>> id(y) 4298172632 >>>
Example 2
Like Example 1, the memory address starts off the same:
>>> x = [1,2,3] >>> y = x >>> id(x) 4299948256 >>> id(y) 4299948256
Now that we are dealing with mutable data types, x can be modified in place and the memory address does not change:
>>> id(x) 4299948256 >>> id(y) 4299948256
Mutable default arguments
This quiz seems trivial but it isn’t. Understanding this will prevent a novice mistake of using mutable default arguments.
>>> def update(x, y=[]): ... y.append(x) ... return y ... >>> list1 = ['a', 'b', 'c'] >>> list2 = [1, 2, 3] >>> update('d', list1) ['a', 'b', 'c', 'd'] >>> update(4, list2) [1, 2, 3, 4] >>> list1 ['a', 'b', 'c', 'd'] >>> list2 [1, 2, 3, 4] >>> update('a') ['a'] >>> list3 = update('b') >>> list3 ['a', 'b'] >>> list4 = update('hello') >>> list4 ['a', 'b', 'hello']
That’s it. You can integrate this with your Pager Duty account or just have it send directly to an e-mail address.
Last night, I presented (
I’ve always been scared of open sourcing, despite wanting to get involved for a long time? Why?