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Well done!
You have completed Functional Python!
You have completed Functional Python!
Preview
No set of rules is complete without a list of anti-patterns and gotchas.
global and nonlocal let you work with variables from a higher scope. You should have a really good reason before using either of these!
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We covered a lot of
rules in the last video.
0:00
Things like keeping functions limited and
not causing side effects.
0:02
But how do we actually do those things?
0:06
Let's go to WorkSpaces and
look at some things not to do.
0:08
So to illustrate some of
the things that are bad ideas,
0:11
things we shouldn't really do when we
use Python, I've got a file here called
0:15
bad examples.py, and we're gonna walk
through what each of these things are.
0:20
So up at the top, we have this
list that's a very important list.
0:25
It needs to stay exactly that way it is.
0:30
Maybe these are the order that players
signed up, or any number of things.
0:32
So it needs to stay in the order of five,
two, three, one whenever I use it,
0:38
in different places, but
you may want to do stuff with it.
0:43
And then we have a variable
called name that's just my name.
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So we have this function
here called def mutate, and
0:50
it takes very important lists and
it sorts it.
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So let's do, right here, let's print
0:56
very_important_list, and
then let's call mutate.
1:00
And then let's again print
very_important_list.
1:07
All right, so
then we can run this with bad_example.py.
1:12
And you can see that,
since inside this function,
1:17
we called sort on the list,
it sorted the list even out here.
1:22
So ideally,
we'd get the same thing here and here.
1:28
Both of those print calls would give us 5,
2, 3, 1, but instead,
1:33
since we called mutate, we sorted
the list in memory, it's sorted for good
1:37
now as far as the program is concerned,
and we get two different outputs.
1:43
So, you don't want to call
methods on mutable types
1:47
unless you know exactly what you're
doing and why, because you get this.
1:52
It changes that list outside of the scope.
1:55
All right, so that's a bad one.
1:58
We won't do that anymore.
2:01
On our next function
here we're using global.
2:03
And so what global does, there is another
keyword similar to global called nonlocal
2:06
that I'll put in the teacher's notes and
recommend that you look up.
2:11
What global does though is it says,
hey, go out to the global scope,
2:14
go as far out as you need to go and see if
you can find a variable with this name.
2:18
And if you do, give it to me,
I'm gonna use it.
2:23
So, normally, let's ignore this line.
2:27
Let's comment out that line.
2:30
Okay, so, if we're just looking at this
function, all we're doing in here is we're
2:32
setting a name, and we're setting
it to the string James, okay?
2:36
But, when we use global and we use name it
2:41
comes out to this global scope and says oh
hey there's a variable here called name.
2:45
Let's reference that one and
then here we've set it to James.
2:49
So again let's do a similar kind of
experiment we're gonna print name and
2:52
then we're gonna call global.use.
2:57
And then we're gonna print name again.
3:00
Now ideally we would
get Kenneth both times
3:02
but We get Kenneth and then we get James.
3:05
And the reason is because we've
overridden that global name variable.
3:09
We've got back up to this top scope and
3:14
said hey,
we're gonna change that variable up there.
3:16
So don't do that.
3:19
That's not good or predictable.
3:21
There are occasionally times when
you're gonna wanna use global.
3:23
But those are very few and
very far between.
3:27
So now these next two we don't
really need to run them.
3:30
We're just gonna talk about these.
3:33
I mentioned that we want to avoid
functions that are too long, so
3:34
let's look at this.
3:37
We have this long_func here,
it imports random, it gets some random
3:38
numbers between 5 and 250, or rather
shuffles the range 5 to 250 randomly.
3:43
And then we run through, what do we have?
3:49
We have an index and a num coming out
of enumerate of all those numbers.
3:51
If the number is divisible by three,
or isn't evenly divisible by three.
3:55
So, if this comes back as a truthy value,
then we set the number to the fifth power.
4:02
If it's not evenly divisible by seven,
then we set the number to the tenth power,
4:09
otherwise I always set the number squared.
4:16
And then we total all those up, and
then we print out the total and
4:19
then we're returning the list of shuffled
and now randomly mutated numbers.
4:22
I wrote this function and
I just had to stop and read it for
4:29
a second to tell you
what was happening in it.
4:33
So we don't want functions like this,
where there's just so much stuff going on,
4:35
and you have to constantly
think about what's happening.
4:39
And now you may be saying but
Kenneth I can put in comments,
4:42
I can put in a doc string and
I can explain what's going on.
4:45
And then everybody will know and
yeah that's true you can but
4:48
if you have to explain what's happening
in a function, what, not why,
4:53
explaining the reason why the function
was written is a great thing to do.
4:57
But if you have to explain
what the function does
5:01
then you've probably written that function
wrong, you should probably simplify this.
5:05
This would be really good
if we were to say like,
5:08
maybe the function takes in the range
of numbers, the list, right?
5:12
Maybe it takes in that list and
then works on them.
5:16
Maybe it just returns
that shuffled list or
5:19
it returns, instead of returning
the shuffled list because then you
5:23
are repeating what the Python already
does, maybe it returns the mutated list.
5:25
This part.
5:30
And it doesn't print or
total or anything like that.
5:32
Because why do we need to total it?
5:34
The total seems completely useless.
5:35
So, things to think about when
you're designing functions,
5:38
when you're designing your software.
5:41
And then for the last one, lot_of_inputs.
5:43
We mentioned having functions
that take too many inputs,
5:47
they take a whole bunch of stuff.
5:50
Now in this case,
5:51
if you look through you'll see that
I've taken inputs that I'm not using.
5:53
It's kind of an idea of like, well, we
might need that some day so let's do it.
5:56
That's generally a bad idea because it
means you're usually putting way more
6:00
thought into the software than
actually needs to be there.
6:03
And that might sound like a silly thing,
but
6:08
it means that you're spending all this
time on details that don't actually
6:11
matter, instead of writing
the code that you need.
6:14
So try not to do that.
6:17
Try to do things in a smart and
6:20
simple way to where you know
exactly what the code's gonna do.
6:22
So in this one we've got
seven inputs coming in,
6:26
only four of them actually get used.
6:29
And we return this and again this
is when I would say it's too long,
6:31
it's too complicated of a function too.
6:35
Cuz inside here we make these two named
tuples which act kind of like classes
6:37
and then we return objects
that are of those classes and
6:42
it's a lot of work for one function.
6:47
So we're gonna avoid all
of these design mistakes,
6:50
all of these usage mistakes
when we write our code.
6:53
Mutable types, like lists and
6:56
dictionaries, are things
that we can deal with.
6:58
Python gives us some handy tools like
slices and some functions that we'll cover
7:00
later in this course, that make it
pretty easy to leave those things alone.
7:04
Global is also pretty simple to avoid.
7:08
Just don't use it.
7:11
The last two things,
writing long functions, or
7:12
writing functions with inflated scopes
are things you get better at not doing
7:14
the more you pay attention to your code.
7:18
You'll find,
as you get more experience and practice,
7:20
that it's second nature
to keep things tight.
7:23
In our next video, we'll get to
the tools that we're actually going to
7:25
use in the course, and
the data that we'll use those tools on.
7:28
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