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  • >> 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.

>> PARLANTE: All right, hey there. Hey, good morning. Welcome to the PyQuick Basic Python

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A2 初級

Google Pythonの授業1日目 前編 (Google Python Class Day 1 Part 1)

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    mike に公開 2021 年 01 月 14 日
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