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[MUSIC PLAYING]

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SPEAKER: Well, hello
one and all, and welcome

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to our short on the random module.

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Now the random module
is a module you can

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use to add an element of randomness
or chance to your programs.

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And we'll see here, I have
a program called cards.py,

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which I've created by typing
code cards.py, and adding

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in these lines of code on
lines 1, 3, 4, and 7 down here.

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So the goal of cards.py is to simulate
kind of dealing from this deck of cards

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that I have here in the
form of this list, one

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called cards with three
cards, jack, queen, and king.

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But if I want to deal cards, I could
think of this element of randomness,

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shuffling the cards, and dealing
them, and seeing what cards I get.

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And to get somewhat of randomness,
we'll need to use the random module.

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So I can import it up top using import.

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Import random, just like this.

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And then down below,
I can see a few ways

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to use the random module with a few
functions that are built into it.

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Now one we've seen is the choice
function, which I can get access to

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by calling random.choice.

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And .choice here, this function, takes
as input some list and returns to me

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some random element from that list.

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So I think I could give as input here
cards, my list, my deck of cards here,

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and have it choose for me one card
randomly from this deck of three.

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I could then print the
result just like this.

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If I go down below and
type Python of cards.py,

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we'll see I got back
queen from random.choice.

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Just to prove this is a bit random
here, I'll do Python of cards.py,

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and I get queen again by chance.

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But let's keep trying.

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I'll get queen again.

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I'll do Python of
cards.py, and there we go.

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Now we have a new card again, each
one being chosen randomly by chance.

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So what else is built
into the random module?

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Well, one that can be
useful to you, one function,

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is not just choice, but choices, plural.

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And choices, true to its name, lets you
choose not just one item from a list,

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but multiple if you wanted to.

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So let's try that out.

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I'll go down below and
I'll type random.choices.

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And it turns out, if I
read the documentation,

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I'll find out that
choices, this function,

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takes as input its first argument the
same list of options to choose from.

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And the second argument
is one called k, which

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stands in for number of items I want
to randomly choose from this list.

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So here, let's try choosing
two cards instead of just one.

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I'll set k equal to 2.

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And now if I go down below
and run Python of cards.py,

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let's see what we get.

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I'll get queen and king.

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So it seems like it randomly
chose two cards from this deck

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and got back queen and king.

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Let's keep trying this again.

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I'll do python of cards.py,
I'll get queen and jack.

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Python of cards.py, king and jack.

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And we can keep going here, but--

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so here, I seem to have
gotten queen and queen, which

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might not be what you'd expect.

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Now it turns out that
random.choices is doing what's

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called sampling with replacement.

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It's akin to me having a deck of three,
shuffling it, taking one card out,

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writing down that card, putting
it back in, shuffling again,

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and choosing another random card
from that same deck of three.

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So every time I choose
a new card in this case,

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I'm choosing from this set of three.

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When I choose a card,
that doesn't eliminate it

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from future choosing of my random
choosing in this particular case.

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So this is sampling without--

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or sampling with replacement.

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Adding the card, let's
say, back into the deck.

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Now if we don't want
that, we want to sample,

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let's say, without replacement,
I could use a different function,

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one called random.sample.

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Random.sample.

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And this one has the same arguments,
the first one being the list of cards

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to choose from, or really any
list to choose anything from,

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and then k being the number of items
we hope to select from this list.

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Now, like I said, random.sample
will select without replacement.

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It will be akin to me
having a deck of three,

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shuffling it, taking one card
out, shuffling the remaining two,

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and choosing one more card.

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So let's see what happens here.

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I'll run Python of
cards.py, and I'll get back

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queen and king, two distinct cards.

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I'll again do Python of
cards.py, jack and king.

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And again, queen and king.

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So you can see here I'm getting a
random set of choices from this deck,

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but because I only
have one card for each,

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in this case, jack, queen,
and king, I'll always get,

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at the end, unique choices from my deck.

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I'm here sampling without replacement.

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Now what if I wanted to maybe weight
the odds a little more in my favor

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and make some things more
likely to happen than others?

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Well, I can actually use, if we go back
to random.choices, another argument

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to this choices function,
one called weights.

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Weights.

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And weights takes as input this
argument here, a list of values, numbers

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to be sure, the same length as the
list that I'm selecting elements from.

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So let's say I wanted to currently
make it more likely a user will

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choose the jack card.

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Well, I could do that by
adjusting the weights here.

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Currently, if I didn't
set weights at all,

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it would be equally likely that a user
would choose jack, queen, or king.

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But I could weight things
more, let's say, in my favor,

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and maybe make it so that the user
100% of the time will choose jack.

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And I can do so like this.

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Here, 100, indicating 100%,
means that the user will always

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choose the jack card and 0
here, meaning kind of 0%,

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will be they'll never choose,
in this case, queen or king.

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So let's run this.

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I'll do Python of cards.py.

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And here, well, unsurprisingly,
we get jack and jack.

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And we'll run this again,
we get jack and jack,

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and again, we get jack and jack.

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So it seems like I've weighted
things more towards this jack card.

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But what else could I try?

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Maybe I could make it only
a little bit more likely

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that a user chooses the jack card.

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And I'll then make it
a little more likely

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they choose the queen card and
king, let's put at about 5%.

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So to be sure these
weights add up to 100%--

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of course, we're always going to select
at least one card from the options here.

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But it seems like 75% of the time,
we'll get back a jack, 20% of the time,

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we'll get back a queen, and 5% of
the time, we'll get back a king.

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So let's try this out.

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I'll run Python of cards.py.

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Again, get Jack and Jack.

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Python of cards.py,
again, get jack and jack.

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And if we keep going, odds are we'll
eventually, as we have down below,

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end up with a queen.

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But again, this is much less
likely than it was before

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without having applied these weights.

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Now randomness is
really fun, really cool,

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but it's not so fun and not so cool when
you're trying to debug your programs.

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In fact, randomness can get in the
way of debugging because really, you

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want to think of debugging as thinking
of defined inputs and defined outputs.

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And if everything happens randomly,
it's hard to debug your program.

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So thankfully, there are ways to have
your programs work with randomness,

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but to guarantee certain outcomes when
you want to do something like debugging.

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Now in the random module, there is,
in this case, a function called seed.

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And a seed is something that goes into
this thing called a pseudorandom number

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generator.

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It actually underlies
the random choices that

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go into functions like choices, and
sample, and choice that we've seen here.

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Now it turns out when you initialize
a Python program like this one,

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or call a function like
random.choices, you

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are using that pseudorandom
number generator.

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And it takes as input
something like a seed that

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might change on different runs of
your program, like your system time.

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But if we give a seed that is a specific
number that always stays the same,

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well, we'll always get the
same choices from, let's say,

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a function like random.choices,
or sample, or choice.

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Let's take a look at it here.

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I'll go down and I will say random.seed,
and I'll give it here some number.

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Let's just say 0 for simplicity.

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Now normally, the seed would be set
by something like my system time.

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It changes on each run of the program.

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But here, I want to define it explicitly
as 0 every time I run this program.

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Well, I could go ahead and
run Python of cards.py,

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and we'll see we get back
king and king by chance.

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But now if I run Python of cards.py,
I'll get back king and king again,

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and maybe again here, I'll
get back king and king.

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So it seems like setting
the seed has given me

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a random choice,
certainly from this deck,

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but one that will
always stay consistent.

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And I could try this again.

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I could do, maybe, a seed of 1, and
see if that might change anything here.

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Python of cards.py.

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I'll get jack and king here.

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And I claim that as long as my seed
is 1, I'll get back jack and king.

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So setting the seed here
is a really good way

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to help you debug your programs.

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Your programs can involve
randomness, but you can actually

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be sure of the outcome when you
set something like a random seed.

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So this was our short on random.

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Feel free to use it to add an element of
chance or randomness to your programs,

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or whenever you want to
set the odds in your favor.

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This was our short on random.

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We'll see you next time.

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