>> PARLANTE: All right, hey there. Hey, good morning. Welcome to the PyQuick Basic Python
Class. My name is Nick Parlante and I work in Google's engEDU group which deals with
sort of technical training in engineering. And also I have a job at Stanford where I
work as a lecturer. So, the Python today is--or rather, it's actually a 2-day class. So this
class is about just the basic useful normal Python. And Python is sort of--you know, it's
a nice friendly learn--and you can actually learn a lot of Python in two days. So, that's
the good news. This is the class where the prerequisite is not--you don't need to be
like super-expert engineer to come in here and learn Python. What we want is just that
you have some experience in some language. So, like, yeah, you have some idea what a
variable is or something like that. And then, and Python's going to meet you halfway on
this. Python, like I was saying before, you know, it's a nicely designed language. It--a
lot of things work pretty easily and so you can learn a lot of Python pretty quickly.
So, this is a 2-day class. And what's going to happen is it'll be a mix of lecture and
coding sections. I'll kind of alternate between the two. The good news or I guess the bad
news or whatever; the news is that the class moves pretty quickly. So, I'll show few things
in lecture and, you know, kind of demonstrate couple of things. And I want to get pretty
quickly to you trying that in coding because, really, when you code it up, you know, that's
when you're going to learn it. So, as I lecture through stuff, don't feel like--I don't want
you to have the idea like, "Oh,"--where you're memorizing or writing down everything that
I say. So, [INDISTINCT] few here for a second, so there's a--for the PyQuick class, we have
a whole set of written materials and here's the PyQuick page, it links all of them. And
particular today, there's this one PyQuick Basics. And that's pretty much what we're
going to talk about today. It's pretty long and it talks about strings and lists and modules
and a bunch of things that I'm going to lecture about. So, my goal is in the lecture sections,
just kind of pick up the basic idea of what I'm showing you. But don't feel like you need
to memorize every detail of it. And then later, when we're in the lab section, yeah, you can
go to the [INDISTINCT] packing it. You can go, "Oh, rightly, he said something about
strings," you can sort of orient yourself a little bit and figure it out how this stuff
works. So, there's also--I had, sort of--I printed some copies of this Basics thing but
then I didn't make quite enough before class started, so I'll go get those when we're at
the next break so I'll also give you a printed dead-tree version of this document for you
to get started. Alrighty, so, let's just get started. So, Python is a--actually kind of
an old language. It was created by a guy name Guido van Rossum, who actually works at Google,
and it was created in 1990. So, I think about it as, like, a little bit old by, you know,
hip language standards. However, in the most recent years, Python seems to have gotten
a lot of momentums. It's becoming pretty popular. And I think it stems from--I get it, it's
basically a pretty good language. I think of Python as being sort of a quick and light
language. So, if I have some little tasks, some little automation, I just want to just
dance, encode and be done. Python seems to work very well, like it's very, sort of, frictionless.
It's just--quick little things just happen very nicely. I think you would categorize
Python as a scripting language. So, it's similar to maybe Pearl or Bash or Ruby or maybe JavaScript,
the whole sort of space of languages that don't have a real heavy type system. So, Python
is certainly a nice example in there. Python as a--I'll show you as we start mess around
with Python. Python is good at, sort of, quick turnaround. So, you could--if you have an
idea, a little experiment you want to run, you just type it in and you could just try
it immediately. There's not a big compile stuff or anything, sort of, slow. So, we're
going to--I'm going to encourage you to have a development style where you have a, sort
of, quick turnaround between editing and running and I'll demo that in a minute. So Python
is certainly very appropriate for small projects, with little bits of animation. Within Google,
Python gets used for all sorts of little things like that. There is debate about whether or
not Python is also good for huge projects, since it lacks a big type system--and I'm
not going to settle that debate today. But, you know, there's certainly advocates for
both sides. But, certainly, as you know, Python is a wonderful language to learn for solving
small encoding problems. Ah, all right. So, let me show you--a little bit of Python code
here. Let's see. So, Python is an interpretive language. So, there's this program called
Python. And later on, we're going to write Python programs, the Python--this is called
the Python interpreter. It's actually going to, kind of, do the running for us. So, one
of the nice qualities of Python is that you can just run the interpreter, so I just type
"python" in here. And then, I can just type little snippets of codes, just add it and
it'll, sort of, compile and run them just as we go. And so, this is a marvelous way
to sort of see what's going on. So, I can just show you some basic Python here. So,
I'll assign a variable "a," I'll say, you know, "a is 6." And so, what the interpreter
does here is what's called the read eval print loop. So, I type a little bit of code to it.
When I hit return, it's going to evaluate it and its going to come back with a prompt.
It'll say, "Okay, I know you--now what do you want to do?" So if I type "a," just a
value, what it does is it evaluates it. In some sense, it kind of prints like, "Well,
here's, sort of, the ASCII form of that," and then it comes back with a prompt. This
is a very standard interpreter sort of thing. So, a couple of notes; please notice there.
Notice I didn't have to declare that I was going to have a variable "a" or that it was
going to be an "int," no. Python, it's all about quick light. We're just like, get right
to it. So, just by assigning to "a" that it cause us to exist. Later on, I could say,
"Oh, let's have 'a' be the string 'hello,'" Well, okay. We're fine. So, there's not a
compiled time type that associated with "a." Instead, "a" just points to whatever it points
to. So right now--so I have to hit "a" here. So, yeah, so now it's a string, earlier it
wasn't it. Though, with the jolly a little bit aligned, the way you can think about in
Python is that a value, you know, "a" in this case, it points to something and in or a string.
And whatever it points to knows what type it is. That's stored at runtime. And so, then,
as the code runs, it just uses the types of the objects as they are at runtime. And we'll
certainly see that theme in a lot of the cases. Okay, I'll show you just syntax, at least.
So, there's a built-in function called Len. And so, if I wanted to take the, you know,
find the length of that string, I could say, "Len of a," and okay, it turns out, that's
"5." Also, Python is case sensitive. So, if I type an upper case "A" I'm going to get
this error. So it says, "nah, blah-blah." This bottom part, I think it's almost English,
"Name error: name "A" is not defined." Okay, well, that's telling you something. So, in
Python, if it comes across a variable or some other symbol which has not previously been
given some value, then that's an error. Then there's a little bit in contrast to some languages
where if it's undefined, it's like, "Well, you know, let's just use the empty string."
Or, you know, "Let's just kind of blunder ahead." Python is not that way. So, this will
also come up like when you go out and bounce an array or do some other thing where it's
a little bit like it doesn't seem to match up, Python will halt. And I think giving you
an experience, the Python language is just--since the greatest source of delays in your code-working
is bugs. And so, it's bad, or if it's been found, it's bad if a bug is, sort of, sitting
in there, hidden. Really, if there's an error, you want to know. And so, Python reflects,
or reflects that style. So, let me show--so, what's going to happen is we're going to do
all sorts of Python. And the interpreter is a great source of doing little experiments.
So, for example, what's going to happen is someone's going to ask me some questions about
Python and I'm just not going to know the answer. I mean, of course. And--but rather
than admit that, what I'm going to say is, "Oh, that's an excellent question. Hey, let's
try it in the interpreter and see." And in that way, I'm never at risk of being wrong,
or whatever, it's just going to do whatever it is going to do. So, for example, you might
wonder, "Oh, well, what if I want to have a string and an int together?" So, I'll say,
"'Hello' + 6." Now, what does that do? Okay, it turns out that doesn't work. I was mentioning
the solution, so you're already at "+"--in Java that works and some of the--in Python
though, "+" between a string and it does not automatically convert then it fix it. Oh,
in the interpreter, by the way, the "Up arrow" works. So it's, sort of, like in Bash, I can,
like, flip the previous lines. So it just happens, if I call, there's an "str" function.
So, if I do "str" on it then "str" on kind of anything. Then that makes, or tries to
make a string out of it and then the code works. I'll talk more about strings and stuff
later on. But you can do that yourself, right? You can be the interpreter and if you have
some questions about, "Oh, what if I do to--do the--where?" It's just so quick like, well,
just, you know, fire up the interpreter and try it out. And so, Python does work. I guess
it's in an interactive style. And I'm being a little repetitious about this because coming
from a Java or C++ background, this feature isn't very foreign. So, it's not something
you would necessary have an instinct to do. But in Python, it works very well. So I will
certainly encourage you to go that way. Oh, all right. So let me get out this. I'll show
you how quit the interpreter; the way I do it. What I do is I type the word, "quit,"
and it doesn't work. But in the error message, it says--"Oh, right, right, Control D." Okay,
good. And so then I type 'control'--Oops. So, here we go. So, in our in--you know, later
on, oh, you don't have to do it now, but later on we'll have this PyQuick directory. It's
going to have a bunch of exercises for you to do. And I'll analyze my selling here. And
in particular, I've got this "hello.py" file. And so, I'm going to use that as kind of a--just
real basic example to start things up. So, one of the required, you know, in order to
do this class, what you want to do is you're going to have a way of editing and running,
and switching between those two very quickly. And there's a separate handout that talks
about that. So, I won't repeat that in lecture. In this case, I'm going to have these two
windows. So up here, I've got this like, you know, whatever, primitive EmEx editor but
while I can do editing in that screen and then in this screen, I can do running. So,
what I'd like to do is, you know, right here is a very basic Python program. I'd like to
just talk about the parts of this thing. So, up here at the very top, you've have this
standard user bin, Python, you know, sort of, or, you know, number sign--bang! Just
talking about what interpreter is going to use this. We're going to--today, we're going
to use Python 2.4. It's a perfectly modern version and this is also the official modern
version used here in Google. There's also a 2.5 and a 2.6. But those differences are
like not real big, so I wouldn't worry about those. I would not use Python 2.2 because
that at--is actually different. So, 2.4. Go with that. Python 3 actually just came out
and it does have some real differences; although, it's not in wide use yet. Here and there--mostly,
we're doing just totally straight-ahead normal standard Python. And so, that's not very different
in Python 3000--in Python 3. But in a couple of places, I may point out things that are
going to be over little different in Python 3. But for the most part, the stuff we're
going to do, we'll all come through fine. The "-tt" thing, I'll talk about in a second.
Okay, let's get rid with this import system. There. So, what this says, this is a "def
main: print 'Hello.'" That defines a function. So, you say, "def" and space and then the
name of the thing. Yeah, question? >> [INDISTINCT]
>> PARLANTE: Oh, I'm sorry. It's coming off a bit. Oh, thank you. There we go, all right.
So, this is just a simple function definition. In this case, I can get whatever name I want.
But it's very conventional in Python that whatever is going to be, kind of, like the
main thing you do, you'll call lower case m, "main." In this case, it turns out Python
has a print operator. And so, you can say "print" and then there's a series of things
and separate them with commas and it prints them. So, in this case, it just prints out,
"Hello." This thing at the bottom is a little unfortunate but I'm going to--it's boilerplate
syntax. And that is the boilerplate syntax to run the "main," that we find above. And
I will mention very briefly why this is here. But then, you should think of this as just
something that's just mechanically you just put at the bottom of the file and then don't
think about too much. The way this works is that a Python program can be--in this case,
"Hello.py," you can run it like [INDISTINCT] like I want to invoke this program. And in
that case, that if statement will be true, the way the interpreter sets things up. And
so, since it's true then here what does is it's calling the main function. So, actually,
I can just demonstrate that. So, if I go down here to my--same directory, so, the way you
run this thing--well, there's two ways, you could type "python," the name of the interpreter,
and then give it "hello.py," say, "Hey, please run that." And then, you could see here it
prints, "Hello." So, there's my marvelous program functioning. In the Unix way, the
more modern thing is that you would--you have the XQ bit set--I'll have talk about this
a little bit, and so then, you can just say, that's the, you know, whatever. "hello.py"
and it just runs it. So, either of those techniques will work okay. All right. So, in that example,
I'm running it and so that then this if statement is trying out to be true and so then it runs
"main." There is this other way that you can load a Python program. Where one Python module
wants to load another one and use it essentially like a library--which I, actually, am going
to demonstrate, I think, tomorrow. And in that case, I want to load the Python module,
it's sort of synonymous with [INDISTINCT] file in Python. I want to load it but I don't
want to run it. I just want to have its definitions available and so, in that case, this if statement
will be false if I load it. And so then, it will bring the module in but it won't run
its main. So, that's what the if statement is for. But for today, we're just always going
to run it just like hello.py so you don't need to worry about this too much. Okay, so
let me show you--I want to, you know, I going to add a few features to this thing; and so
just to, kind of, show you some things. So first thing I'm going to do is, I want to
print out the command-line arguments from my main here. It's just a very common thing
to want to do. And it turns out, there's a module called "sys." And the sys module, there's
a Python--standard Python thing, it includes a lot of, sort of, operating system interface-type
stuff. So, you could access command-line arguments or you could exit the whole program or whatever.
I'll show you how to bring up the documentation in a second. In Python, the way that you refer
to some external module of stuff you'd like to pull in is you have an import statement.
You say, "import sys" or import--I'll show you a bunch of different ones over the next
few days. And then, down here, to refer to something inside of the module, you say module
name, so "sys" and then dot and then and you'll just need to know the name. In this case,
it's, "sys.argv," is the name of the command-line arguments in that module. So, I'm going to
save that and then down here, I'll run, "hello," and I'll just say like "aaa bbb ccc," right?
So, those are command-line arguments. So now, when I run it, see it prints these out. So
that is a Python list. It has four--so Python lists have square brackets around them. And
we'll mess with this a lot more later on. In this case, this list has four elements
in it, which is, kind of, the old Unix standard way of doing command-line arguments. The first
argument, it points to the script itself, so that's "./hello.py." And then, the subsequently
three elements--these guys here, that's just--Oops! These guys then just correspond to the arguments
here of that I passed at. So, what I want to show you--so, I'm going back to my source
code here. So, so far, this part doesn't really do anything very useful. But I do want to
show you just the idea of a module like, yeah, there's--we're going to use modules a lot
today. So, that's how we're going to pull stuff, you know, you use codec way to write
by code of my program. Now, a very reasonable question is like, "Oh, 'sys,' like, how am
I supposed to know that?" like, "Where did that come from?" So, I want to show you two
ways that you can, kind of, research what a module is and what it has in it. And I'm
going to show you two. There's the hi-tech way and there's the easy way. And they both
work fine. So, you could use either of these ways. First of all, I'll show you the hi-tech
way. All right, so I'm going to fire up the Python interpreter, and actually in the Python
interpreter, I can say "import sys." I mean, it really kind of looks like a program. It's
just that I get to type stuff interactively. So then, inside of--there are two functions
in here. One is "dir," so I can do a "dir" on sys. And what that does is to just, kind
of, shows me all the symbols that are defined in there. So, it's sort of an homage to dash,
I always think of dir. And so, you can see, you know, if you didn't know about "argv,"
or whatever, you'd say like, "Oh, exit." "Oh, that's probably the exit function," and--where's
"argv?" Oh, all right. Check it out. There's "argv." So this--some of these are data, some
of them are codes but you can at least get a feel for what's inside of there. So, dir,
that's the first one; then there's a companion called help. And what help does is it kind
of pulls up sort of a JavaDoc, sort of a man page documents about like, oh, what is going
on with this module? And so, with dir and help, you can kind of poke around a little
bit and orient yourself. And what's nice--if you look at my list here, for example, there's--this
is my example, there's exit. So, that's sys dot exit that's a function. I can actually
say help of sys dot exit, and then it pulls up just help about that function. So, just
in Python and in lecture or whatever, I will say, "Oh, use the Ebola ABC Module," and I'll
kind of mention a couple of functions that you need to use but I won't give you further
direction than that. And so then, what you know, which is a very realistic position to
be in. And what will happen is that in Python, you can use dir and help to kind of dig around
and get better docs, or you know, using--using this technique. I'll do another example. Remember
I talked about the len function earlier? So, I could say help of len and that like, gives
you like, okay--not pretty scant description but a little bit of description about that.
One thing I'll point out about this first of all, usual--notice why, when I type help
len, I'm just typing len without a set of parentheses after it? And that's a kind of
subtle syntactic distinction. When I say len paren hello like that, I'm calling the len
function. But when I just say len with no parens like that, I'm just referring to the
len function. I'm pointing to say, well, here is some code. Don't run it, I just want to
talk about this code. So, here when I call help, notice it's just len and it's just unadorned,
all righty? So, let me show you--so that's the high-tech way of doing dir and help, certainly
very useful. Now, I'll show you the easy way. The easy way is you go to your browser and
you just go to Google and you just type Python--like what did we just do? I'll say Python sys exit
and then whatever; Google searches, for whatever reason, just work really well with Python.
So, like the first couple hits, like yeah, it just is the docs for the Python sys exit
function or I've been doing a Python--I'll show you strings in a second. So, if I say
Python string, type that out, oh yeah, first hit here. So, Python.org is the official--so,
Python, I should mention, is you know open-source and all, like good minor stuff. Python.org
is sort of the official Python home and so if you see a link that's docs.Python.org a
lot--you know that--Python.org has excellent documentation and tutorials and all sorts
of stuff like that. And so, if you get a Google search that just kind of points into that
a lot of times, so that's going to be nice authoritative answer. So, just doing Google
actually works amazing alone. I was feel like I'm being kind of powerful and hip if I use
like, dir and help to dig around, but I must admit that in fact, just doing a Google search
that, like, any six-year old could do, like, in fact, works great. And so, you know, both
those techniques are available, you have to use whichever one you like, all righty. So,
let me show you--let me go back to my--get out of here. So, I want to build up the Python
code inside of a--inside of this function bit, show you couple of things. One thing,
I'm going to show you a very common error, real quick. So, I'm going to comment out the
import sys. So, incidentally the number sign is the comment character, so like, and that
just goes to the end of the line. So, this is a very typical way I would write this code.
I'm using sys.argv, but I've forgotten to do the import. So, I want to show you what
that looks like. So, if I say hello, I get an error. So, this is a Python error trace.
So, the most interesting part here is maybe at the bottom, says, "Global name sys is not
defined." Now, the error is not very specific here but it's kind of--it doesn't quite know
if I wanted to have a variable name sys or module, it doesn't know. It just looks like
S-Y-S to it, but it is that error like, while I came across the symbol and it was not previously
defined. So, you could see that that is one of the basic rules of Python that if you--if
you're going to use a symbol, it previously needs to have been given a value. So, when
you see something like that and it refers to a module that you're trying to use, then
what that means is--oh, right, I forgot to do the import. So, I go back here, I'll put
the import back. So, essentially what the import does is it takes the symbol S-Y-S and
it binds it to point to something so that then down stream, when you say sys dot whatever,
it's able to see if it'll actually work. So, let's try that much and now work again. Okay
good, now we're back to just pitching the arguments. All right, so I'd like to do--well,
I'll show you how to build a real program out of this. So, I'm going to define a hello
function that does something. So, I'll say hello and then let's say this will take in
a string. So, I'm doing a second def here and let's say--let's say this is a name, actually.
I'll say prints, "hello" and then the print--you can actually separate things with commas.
So, if I say "hello" name--and you can have multiple comments, multiple things in it;
it sort of prints those out and puts them on a line. So, what I'll do down here actually
and when I'm all set, let's have--let's put a bunch of exclamation marks after the name.
So, that's my little "hello" function that has two lines in it and I'll talk about the
plus and--you know, I'm glossing over some details there, but you can sort of see what
it does. And then down here, I'll call my "hello" function and what I'm going to do
is I'm going to pass in the first command line argument. So that was sys.argv and that
turns out the zeroth element refers to the script itself which is--that's just an ancient
convention. So, the element that I really care about is sys.argv one there. So, I'm
going to save that and I'll see if this works, so I'll say, "Hello Alice," and so there,
check it out. All right, so now it prints "Hello Alice," you can sort of see the results
there. All right, so let me talk a little bit. I just want to use this as a vehicle
to kind of talk about what's going on syntactically with Python. So, I'll sort of o through this
top to bottom. So, I give this thing an argument called name. Notice just like--just as with
the variables, I didn't have to declare that this was a string or an ant or anything like
that. I just say well, whatever; it's just called name and it just points to whatever
it points to. So, arguments and variables are similar, they're both just names that
point to some value. Then, in Python when you want set off a block of code, it very
often uses the colon, as you see here. So, I'm going to say define this function and
there's a colon. Now, I'm going to go to the next line and I'm going to have, you know,
how are many lines of code I want to have. Now, this brings us to Python's most sort
of famous syntactic feature which is that Python does not have any sort--any left curly
brace, right curly brace notion to enclose a block of code, instead, Python uses indentation.
So, notice under the def here--so the Google standard is to indent by two spaces, and so
that's a fine thing to do for today. So under the def, this first line is indented by two
and this next line is indented by two. So, that's what's putting them inside of that
function and there just isn't a left curly brace or right curly brace I typed to put
those in there. So, this is--it's a little bit controversial. I'll just give you my take
on it. I think the idea is that if we were writing this in Java--I'll disturb all the
real Python people here, you know. I don't know. Suppose it looked like this ... sounds
really funny, all right. Suppose we had that, right? We're blocking out the code that makes
this function and what we would've indented--like we would've had one set of brain cells that
was managing the curly bracers and putting them in right. But then, we also would've
indented correctly, right? And we were raised right and it looks terrible. So, of course,
we would've indented correctly as well; that would've been a second set of brain cells,
those. So, we would've maintaining these two things kind of in parallel. But if you start
to think about it, those two bits of syntax would've been reflecting the same piece of
information; they always would've moved in tandem. And so, the Python idea is like you
know, having two bits of syntax that represent the same thing and then we're just trying
to keep them in sync is dumb. Like, we want to just do the quickest, most minimal, clean
thing and that's kind what Python looks like, and so it's like, you know what? Let's just
get rid of the curly braces. If the--if we want to look right--so I'll put the colon
back there--let's just have the indentation define how the blocks of code go. I'll fill
this--this function have to be little longer so you'd get a better feel for what indentation
looks like. My advice about this is that it seems extremely foreign, weird and slightly
wrong for about the first 11 minutes that you use it. And then, it's just fine. I mean,
it's just basically very logical and reason why--it's kind of visual and so, it very quickly
just seems normal. So I encourage you just not worry about it. All right, so let me--I
want to make this function a little longer; then allow me to demonstrate the indentation
a little more. Yeah, question? >> It has space between hello and Alice [INDISTINCT].
>> PARLANTE: Oh, so yeah, the question is, where does the space come? That's a quality
of print that when you separate things with a comma, it puts a single space between them.
If I wanted to bunch those together, I could've done a plus. The plus in string space just
crams them together, so that would've done it. All right, so, let me show you--so, I
want to make this a little fancier here. I'm going to put in an If statement. So, let's
see. I'll say if--let's say, if name and I know I'll just end up showing you how Boolean
this stuff work. If name is, let's say, Alice, then we'll say--I'm just going to--this won't
be very meaningful. Here, we'll add some question marks on there. So the--I'll just start at
the top here. So, this is what an If statement looks like. You say if and then you have the
test and then there's a colon and then it has whatever--block of statements underneath
it. Now, just to get with this idea of indentation, if I wanted to also do multiple things, I
could say you know, you know, I'd consider, you know, "Alert: Alice Mode" here or something.
The fact that those two lines, the print alert and these two lines are underneath the If,
that's what's putting them, you know, under the control of that if statement. And then
here, when this line is indented back to Alt that--that's what putting me outside the If
statement. So, this is what it means to say that the indentation is significant, right?
Where something is placed left-right does control what the code means and so that's
the foreign part. All right, so let's start about this If statement. Here, I'm using "= =." "= =" does
sort of an intuitive deep comparison. In some languages, you kind of have to worry, well,
is this a point of comparison or whatever? In Python, you do not to have that worry.
"= =" does what I have described as a kind of a real comparison. It takes the thing on
the left, the thing in the right and it really fleshes them out and compares them. So, it
works for integers, it works for strings; later on, I'll show you it works for entire
lists. So, you could have relatively big data structures and just compare them with "= =" and
you'd still get a reasonable result. In C++ or Java, you always got to have the parentheses
around the test. In Python, the parentheses are not required. And then, so it's regarded
as the best Python style to not put them in. It's a little bit like--it's like speaking
with your sort of vulgar accent. Like if you put the parens in, then everyone's like, "Oh,
I see. One of you is, you know, C++ refugees." So, you could sort of show off your modernity
by, like, not putting in it. If you want to have a logical connective, this is a little
bit strange. The logical connectives are spelled out with letters. So, or is O-R and is A-N-D
and not is--it's a little hard to say in English--not isn't the thing above the one on the keyboard,
its N-O-T. So, I'll say, you know, if name is, you know, Nick. So, finally, I'll put
a--I'll put an else in here just to show off. So I'll say else colon--what do we do in the
else case? I'll print "Else." Okay. So, now you that--you could sort of see the indentation
and you're really working here and we've got this kind of modest Python program. All those
mentioned, you know, all the regular Boolean stuff. You know, there's less than and equal
equal and, you know, all the kind of regular Boolean stuff works in Python as it does in
other languages. There are Boolean true and false values, although those aren't used very
often. The rule in Python is that if you have appointed (ph) or something, there's a few
kind of null values that count as false. So, if a number is zero that counts as false.
If a string is the empty string that counts as false and any other value or, you know,
and the--or if the string is not empty or if a number is not zero, then those count
as true. So, that's similar to how other languages do it. All right, so let me just try running
this a little bit. So, I guess if I run this and I say "Hello Alice," then my If statement
kicks in, so I get all those question marks and then the line below kicks in and I go--oh,
it's pretty doofy, pretty doofy looking out, but hey, at least it works. So, I'm going
to show you--I'm going to make a very sweeping claim about how Python works. Python does
everything at the last possible second. So, in C++ or Java, it takes your code and it
compiles and it checks it in a million different ways and you might get a lot of different
compile errors, and then only after all that compile checking, then it runs it. That's
not how Python works. When you feed your Python code like my hello.py in the Python, it just
looks at it in the most superficial way, it checks pretty much nothing; it just starts
running it. And each line it gets to, it evaluates at that line kind of in the moment. So, in
the moment, it looks at what those variables point to and oh, he's got a string and an
ant here and it just tries to do it just at the last possible second. And only at that
second does it notice if there's an error, maybe a variable is not defined or you're
calling a function that doesn't exist or you know, dividing by zero--I mean, we're always,
you know, aware of bugs. So, to highlight that, I want to try calling a function here.
I'm going to call a function called DoesNotExist. Here, I'll pass in a name. Now, there is no
such function. I haven't defined it, there's not a built in code DoesNotExist, it's just
wrong, all right? That else is just incorrect. This does demonstrate a deep quality of Python.
Now, if I call hello.py and pass Alice, you know what? It's going to work fine. All right,
this is what I mean. What happens is Python only checks a line when it runs that line,
all right? And so, because it just kind of never hit this else, whatever, it just kind
of never knows that that was wrong. Now, in the great, you know--as we understand the
universe, you don't get something for nothing. Well, in Python it means there's not a big
barrier between you and just, like, your code running. And that can be a real virtue in
a lot of cases. But also, you're giving up a certain amount of checking that some languages
might have done. This also means that in a more industrial sense, because Python doesn't
really check a lot at a compel time, for industrial code, it's more important for it have to have
good units test coverage. Like you actually need to have run all the lines to see that
they're correct. Now, for our two days, we're going to work on things that are just kind
of medium sized little utilities where, you know, if they're incorrect, you can see pretty
clearly and so for that kind of problem Python is really a good match. All righty. So, let
me show you--I think I'm going to go back to the Python interpreter here. And I've showed
you--I've sort of used strings and lists and a few things informally, but I never really
explained them, so I want to kind of slowdown a little bit here and actually talk about
how some of these things work. So, the Python string-type is enclosed in quotes. So, there's
like this string "hello" I've been done. You can also actually put the string in double
quotes or--here I'll do a different one. Isn't--oops--that works the same. There's not a deep semantic
difference you could--it's just your choice, you can either use single quotes or double
quotes. The one difference is that inside of a double quoted string, as I have here,
you can put a single quote like isn't there and it just, just works. And, likewise, if
I'd use single quotes, on the outside, I could put a double quote inside. There's not a real
strong preference. You can kind of use which the one you prefer. I tend to use the single
quote one. It's just, it looks a little Python to me. Yeah, question.
>> What kind string that you want include single and double quotes?
>> PARLANTE: Ah, in fairness to your question, so if want to--so let's say I'll do a double
quoted one and I want to put a double quote inside of it. So say like--I--what would you
say, I'd say like--I--what you do is you put a back quote, a back taken from it. So I'd
say, "I love this exercise," yeah, that's fine. Well, alternately, I could have done
it, and set some quotes. All right. So, I should you--let's see what's a--isn't. So
I showed you the "len." Oops. The "len" function earlier. So strings also––as I think I've
already done, they--the plus works. So if I'd say "a + you know yay" then that puts
it together, you know, plus put strings together to make a bigger string. Strings in Python
are what is called immutable and that means that once the string is created it never changes.
It's like a little read only thing. That's a pretty modern style that turns out to be
pretty popular in a lot of languages. So for an example when I did that little plus there,
if I look at the original "a" it's unchanged. All right, the--so whenever anything you do
with strings, lowercase, uppercase, I'm gonna show you a few things. It's always creating
new strings to sort of show you the result, but the original string it's always left unchanged.
So, well, maybe I'll do is I'll set "a" to let's say uppercase "hello." Now it turns
out there are a bunch of built-in string what are called methods and I'll show you one now.
So for example there's one called "lower" and what that does is it makes the lowercase
version of a string. Now the reason this is called a method and this is basic object oriented
programming just as a--you know there's some--a few things that are very easy and that's we're
going to work on for the next couple of days. "A" this is, it points to the string, all
right, I could think of a string object and with this syntax where I say pointer to a
thing dot and them the name of the method I want to run. What that means is run that
method on that object. So if I had "b" is equal to like "yay," so if I say "b.lower"
okay, well, it runs on that string. Whereas when I'd say "a.lower" then it ran on "a,"
so that's basic, it's, it's, it doesn't, it's a different syntax for running a piece of
code called the method on an object and that's you know hopefully pretty--that's done pretty
intuitively. So, what I was saying before is that strings are immutable, they are never
changed. So for example, if I look at the original--so here, I'll do it again. If I
say "a.lower" that's not changing "a" that's returning to me a new string that's the lowercase
version I wanted. d if I look at the original "a, it's unchanged. Now Python has--there
are many built-in string methods. I showed you lower. I can show you--there's like a
find, just for example. So if I say "a.find of "e" and what that does is it searches in
the string for the first occurrence of that and then returns to me in the index. Now in
reality, there are probably dozens of built-in string methods and I'm not gonna demo them
all in lecture. I just want you to know that there are a lot of built-in ones and either
you could look at the Python (ph) where it talks about some of the common ones, or you
could type, you know, in Google, type, Python string, or maybe Python string method and
go to the page where it list them all. One of the theme--you know one of the reasons
that software is a lot more productive than it was say 15 years ago is that we've gotten
better at having what I think sort of built-in codes. Like a code you didn't write that,
but that you can call and it just solves basic problems for you, sort of code reuse, and
Python like any modern language actually has a lot of code already done for you. And so
one of the basic skills--I think it's kind of living higher on the food chain is when
you're solving a problem, you don't necessarily like, "Oh, now I'm gonna manually ride a loop
to solve that." Very often your first instinct is to find the module and dig around a little
bit to find some code that somebody else already wrote, it's already done and you're going
to build your solution on top of that. That is, that's a sort of good modern technique
and it's an excellent Python technique. Python has a lot of built-in stuff and you know over
the cost of few days, I will certainly point you where a lot of that code list. All right.
So, I haven't talked about how to look inside of a string. It turns out you can use a square
brackets to look inside of a string. So if I'd say, "a [0]" that's the left most character
in "a [1]" that's the "e" and so on. If I go out of bounds here then that's an error,
so I really need to adjust you know keep within the bounds of the actual thing. So one last--some
text--I'll show you for this--this is a little less--so you can use the plus to put together.
You know if I wanted to have a string and whatever, I could use the plus to put together.
There's another form that uses seized print-up syntax where I could say like "hi % s" and
the "% s" is a place holder where I'd like a string to go and I could say like, "I have"
you know "% d donuts" and so that's, that's called a format string and it a sort of--it's
a good way of mixing in. You have this outer skeleton and you want to sort of substitute
in a few things and so then you use the "%" sign and then you combine it with what you want.
So here I'll say, "Alice and 42." And so using this sort of "%" construct, you can have a
string in sort of substitute values into it into make a bigger string. Does not it really
ever required, you could always have gotten that result using plus to kind of put the
string together but, it's fairly common to use this so I'll just, I'll just mention it.
The last thing I'll say about strings is that, the strings that I'm showing you right here
these are Unicode strings. Python's Unicode treatment has been like a little uneven and
particular in Python 3 it changed a little bit, it got better. So for here I just want
you to realize like, yeah, these are not Python strings. These are not Unicode strings but--and
in the handout talks about there's a slightly difference route by which you create Unicode
string. But once you've got a Unicode string then all the things I showed you still work.
The square brackets, the "len", the ".lower," all that kind of stuff, it's the same interface
is just you created or so in a different way. And so, I will--but for our purposes this
will work. These strings essentially are just serious and bites, it's just a (buck) of bites.
All right. So that's almost--I'm going to show there. So, I want to, I want to show
you this one--how are we do on time? Oh, excellent. I want to show this last string feature and
I want to block out time for our first exercise. So, in order to show you this, I'm going to
go to the py quick basics document. I want to--very high tech here. I'm going to attempt
to--here we go. It's just possible. I'm going to try and show the interpreter in a little
bit of art that I put in there to end up. Okay, oh, perfect. All right. So here, I'll
say, "a = hello," so I've got the same string. So, in that little piece of art, all I've
done is I've drawn in the index numbers, so like all the languages in Python, the things
are--if I want a number and when your sequence of things, they are numbered from zero, starting
at the left. So, if I'd say--if I refer to "a [0]" that's the "h"--this is how I should
have done it for or "a [1]" that's the "e." Or if I say, "What's the len of this thing?"
that's "5," so that just sort of conventional indexing into something. Now Python has a
syntax for referring to not just a single element in a string like this but a kind of
subpart of it, and this syntax is gonna use the colon. So the way this is going to work
is if I say "a" and I'll put the square bracket but I'm going to put a colon in the middle
here, and I'm going to refer--I'm going to indicate both the start and the end. So, for
example, if I'd say, "What, what?" I want you to start at one; so that's the first index
number and then the second number--yeah, it's going to say, it's going to go up to but not
including that one. In Python, this is called a slice. So if I'd say "a [1:3]" that's the
subpart of the string starting at the one and going up to but not including the three.
This is called--it's only entitled called the slice. There's a--the word Pythonic is
not a word I just made up, it's a real one, in the nerdoroty (ph), and this is a very
Pythonic feature. Python likes having syntaxes which are sort of very short but crisp but
then again you know it express something that a common thing that you might want to do.
So, if I wanted to--if I wanted to say, "Hello," I guess, I could say, what is it, a one--oops,
"a [1:5]." That's a little weird. The five is kind of one out of bounds there but, actually,
what you could do in the slice syntax is if you omit the second, the thing after the colon,
it just goes all the way through the end of the string. And, if you omit the first one,
it starts at the beginning. So actually it is a truism that if I'd just say square bracket,
colon square bracket, well, I just get the whole of whatever it was. So this is a very
heavy syntax. For say, for example, if I want to, you know, remove the first level--level--letter.
I could just say one colon (ph) so like instead of starting at zero, start at one and then
just go through the end. So that's, so far that's like pretty neat. But now, just a little
bit of scrolling, I'd show you the slightly other crazy thing it does. So, thus far, I've
just used the positive numbers, but in Python, they also added a second set of numbers that
also index into the strings. So it's just using the negative numbers and the negative
numbers instead of starting at the left, they start at the right. So minus one refers to
the rightmost character and minus two refers to the next one and the minus three and so
on. You can think of essentially as there's an implicit len there that--the minus one
essentially saying len minus one, right. So len in this case is five. Len minus one is
four. I'll check it out for you. So do you have written a code in a zero based system
but it means that referring to things that happen to be at the left is very convenient
because like zero, one, two, you always know where you are. But then referring to things
at the right is like a pain because you always have to add len and subtract something. So
the negative numbers scheme just also makes it convenient to refer to things on the right
hand side, and they work in slices too. So, for example, how about I say that I want to
omit--first, I'll just do my earlier example. So I could say what is it? "[-4:-2]"--oops.
I'll put the "a" there. That's exactly equivalent to the one where earlier it was a one colon
three, right. The minus four is just another way of saying that. I'm going to get a more
realistic example. Say for example, I wanted to omit the last three characters of the string.
I didn't know how long it was. I could just write that as colon minus three. All right,
that it's going to go up to but not included. I know minus three is the third in. So like
I could "he" or I could do a getaway. What if I only want the last three characters of
a string? I guess right that is minus three colon. So, it just--I think, syntactically,
this is maybe it looks a little bit weird but I found--the slice syntax, I find it--it's
just useful in a lot of situations. So I would encourage you to go ahead and actually learn
this one and we're going to have all these exercises and stuff in a little bit. Certainly,
I have hidden inside of their little opportunities for you to end up going to use the slice syntax.
So that is a nice one to get the stuff going. Okay, so that actually concludes the first
lecture section. So what I would like you to do is pull up the exercises and so if you
go to the py quick page--just do it here--it points to this page, py quick exercises, here
you go. And then that explains how you copy and I--if you could raise your hand, I'm happy
to kind of walk on. How you can copy--this is--said directory, direct, directories. It's
going to look like this and let me--now, let me show what I want you to do. So inside here,
there's like day one, day two, and some other stuff. Today, we're doing day one. So go in
the day one directory, and the first thing I want you to look at is there's this, there's
a file there called--oops, no, not that one. There's a file there called "string1.py" and
I'm just going to look inside of there. A so what this thing has--is in the comments--sorry,
I'll make this a little bigger. There are some little exercises in here that just use
the stuff in lecture that we've done so far. So, for example, here's, you know, exercise
"A: Dr. Evil" and just in English, there's a little description of like what it is I
want you to do and it gives a little example but then the code it just not done. And so
your job is fill in the code there to actually compute what it's suppose to compute; there's
a few of these things. And then at the bottom, I have filled in little bits of test code.
And so you see that you don't have to touch that, that's already done. They're just going
to call the functions above and just kind of check that they were trying the right thing.
So it's kind of a primitive form of unit testing. So if I run this thing right now, what it
does is they all fail, because yeah, there is no code and so what's gonna happen is as
you fill those bits of function in then somebody's pass--this discussion start passing. You can
just run it each time to just very quickly just get feedback about how it's going. So
that is string one, I'd like everyone to do string one. If you are just so fast, you get
a little bored, there's also a string two. In string two, it just contains more. And
so, optionally, if we you have more time to kill, I'd be happy for you to go ahead and
do that. The last thing I need to point out here--let's see, I'll just look at string
one here. There's a thing I mentioned earlier that I never explained. This "-tt" flag. What
that refers to is in a Python file, what I would recommend is you just always indent
with spaces and that that is the Google standard, just always indent with spaces and you're
okay. But, in your editor, maybe by habit or whatever you might accidentally hit the
tab key, and if you have a Python file that has a mixture where it uses and spaces in
some places, in tabs and other places that is deeply confusing, because visually where
the codes appears to vertically appears to a line may not correspond to how it really
aligns as far as Python is concerned. So what the "-tt" flag does is if it ever finds a
mixture of spaces and tabs, it just immediately halts, which is for--when you're on your first
day of Python programming that's absolutely what you want. So this will help you find
the case where you want to do is the [INDISTINCT] I've talked about. You want to set your editor
so that if you ever hit the tab key, it understands to just put in spaces. So put the "-tt" flag
will protect you if, if you end up with--make a mistake with that. Oh, all right so here's
what I'd like to do, it's now, it's about 10:50, so I'm going to imagine; I want you
to work on this with me maybe about half hour for that, so that's--what I'd like you to
do is then go have lunch. So what I'd like you to do is be back in here--I'll have do
all the math here. Back in here at 1:15 and so I'm going to leave you some time for doing
Python coding and then some time for having for having lunch. You, it allows you to bounce
something and of course, you know, I'm in here to answer questions or whatever during
that whole time. All right. So, so please go ahead and get started with that.