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[MUSIC]

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Regular expressions let us match patterns
against text.

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For example, if I had a pattern that said,

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I want to find the first time the word
ghost is used in Charles Dickens's,

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A Christmas Carol, I could do
re.search(r'ghost,christmas_carol).

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But knowing that I can do it doesn't help
you, does it?

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Before we get into

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work spaces though let's talk about the
problem we're going to solve.

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I have a text file full of names, phone
numbers, email addresses, etc.

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The problem is that it's kind of garbled
and

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some of the people don't have all of their
information.

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I'd like to get this sorted out, to where
I can turn them into classes and

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make a nice interface for looking at my
contacts.

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Regular expressions are made for

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processing text, so this should be really
doable.

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Let's get to it.

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Well I guess, first thing's first.

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We need to read the file,.

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The file we want to read is this names.txt
one.

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And let's go down here to our Python shell
and see about doing that.

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So, we can read in a file using a really
handy function that

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Python gives us called open.

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And we give it a name of the file that we
wanna open,

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just in case because this file does have
some UTF-8 characters.

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Let's actually give it an encoding of
utf-8.

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That way it knows that it is utf-8.

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So we do that and we get the file open.

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I mean that's great, but you know,

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actually I don't wanna do this in the
shell.

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I wanna do this in a, in an actual script.

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So we've used open.

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Let's just, let's get out of here and
let's do this as an actual script.

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So let's go up here and we'll make a new
file.

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Let's call this address_book.py, cuz we're
making an address book.

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Okay.

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So inside here let's go ahead and do just
what we did before.

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So names_file we're gonna open up
names.txt,

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and we're gonna say that the encoding is
utf-8 just in case.

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And so what we're doing here,

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names_file isn't the file, like the, the
contents of the file.

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Names_file is a pointer to the file on the
file system,

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which we can then do things to.

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We can read from it or close it or
whatever.

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And in fact, we're gonna do that.

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We're gonna read from it.

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So let's do names_file.read.

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So that puts all the contents of
names_file into data.

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Now I know that names.txt isn't really
that big of a file, it's fairly small.

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But if I knew it was a really big file or

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I didn't know how big it was, there's a
slightly better way of handling this.

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And I'm gonna post that in the teacher's
notes.

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I wanna do a more standard, less magical
and fancy version here in the course.

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So, now we have the file opened and

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we've read the file, we have all the
contents of it.

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We don't need that file anymore.

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So what we're gonna do now is we want to
close it so

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that we're no longer pointing to it and
it's erased out of memory.

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So that's it.

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That's opening the file, reading the file,
and then closing the file.

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I love when all of these actions are just
really simple.

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So let's print out what we have in data,
just to make sure that it's what we want.

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All right.

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So let's come down here to our console and
run this.

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Python address_book.py.

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And there we go.
We've got all of our names.

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So that's great.

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That's everything.

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All right, so now we wanna start on our
regex stuff.

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I'm gonna get rid of that print.

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And so, everything that we're gonna do
with regex,

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we need the regex library, which is called
re for regular expressions.

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So, we're gonna do a match.

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Let's try and match if we look back at
names.txt the first name here is my name.

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So let's see if we can match part of my
name.

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So let's do print re.match and love.

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And we're gonna match that against data.

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And then, you know what, let's do another
one here.

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Let's do re.match Kenneth and that's also
against data.

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Now, why do our strings in here, in our
matches have an r in front of them?

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Well, that tells Python that it's a raw
string as opposed to

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a regular string, a well done string.

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This saves us some very confusing repeated
uses of the backslash character or

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the escape character.

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We'll talk about those in a later video
if, if it comes up.

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After the r, we're just looking for the
two major parts of my name.

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Let's run this and see what we get.

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So we come down here, python
address_book.py, and

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we get back a, a match object for the
first one.

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See, we've got match object, and it
matched love.

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Cool.

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But we got none for the second one.

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Why did we get none?

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Well, if you remember I said that match,
match is from the beginning of the string.

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Our string starts with love, but it
doesn't start with Kenneth.

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Kenneth comes after love comma space.

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So the second match can't ever, doesn't
ever happen.

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But if we come back and we change this
match to search,

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then now we should be able to do it.

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And look, we've got two match objects now.

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We've got one matching Love and one
matching Kenneth.

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So if you're matching at the beginning of
a string, use match.

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If you're matching somewhere in the
string, use search.

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Now you may have all ready guessed this,
but

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if you didn't, we can do these as
variables.

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They're just strings.

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So we could say last_name equals love,
first_name equals Kenneth.

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And then here, do last_name and
first_name.

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And this would still work the same way and
we still get our two matches.

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Sometimes that's a whole lot easier than
writing them inside

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the re.match re.search areas.

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Toward the end of this course,

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we're going to look at another way of
making patterns as variables.

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For now though, I'm just gonna stick with
doing it all in one step as we,

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as we first did.

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Feel free to make the variables if you
want, though.

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All right, we can open, close, and read
files and match very exact patterns.

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It might not seem like much, but

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these are definitely the first steps on a
long path to regular expression magic.

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In our next video, we're going to look at
a more common search method and

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some more forgiving pattern options.