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Let's try a slightly harder one, slightly
weirder one perhaps.

2
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So let's actually, let's see.

3
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Let's comment these two both out, and
let's take our email address one.

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And I wanna match all the email address,
just like we did before.

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But if the email undress ends in .gov, I
want to leave that part off.

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Just pretend I have a good reason for this
cuz I, I really don't.

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So, all right, this sounds like a really
good place for us to use a negative set.

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And we can also write this out.

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I mean, this is really, there's a lot to
this.

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So, let's leave ourselves some comments,
make this a little bit easier.

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So okay, first of all, yeah.

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We can definitely use a negative set here.

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So, let's make this a multiline string.

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And we gotta end that multiline string.

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You know what, we need to make this four
spaces.

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There we go, all right.

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And we'll end our multiline string, and
then we'll do stuff as usual against data.

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All right.
So, let's take this.

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I actually don't wanna catch the part
before.

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I just wanna get the the e-mail address.

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So, let's do a \b and

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then an @, and then that part.

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And I don't care how many things are
there.

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So find a word boundary, just leaving
myself a little note here,

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an @, and then any number of characters.

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All right, then what I want to ignore is
gov, and

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I don't wanna get that tab that's in
there.

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You can't necessarily see it, but

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the space between each of these things is
a tab character.

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And I know there's a tab character right
here, and

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it just might catch it, so let's leave
that off.

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So one or more of those is fine.

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00:02:21,550 --> 00:02:29,270
And let's leave another comment here of
ignore, wow, wow.

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Ignore one or more instances of the
letters g,

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o, or v and a tab.

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All right.
And

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then we have another b here, so match
another word boundary, all right.

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And then we do data.

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Now, I've done a flag here, which is that
I've done multiple lines.

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So I need to use this VERBOSE flag.

41
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And then, since we've got gov in there,
and we've got it in lowercase.

42
00:03:04,610 --> 00:03:09,720
Just in case there was an uppercase
version, I'd want to add on the flag re.I.

43
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And we add multiple flags with the pipe
symbol in between each of the flags.

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It's a little weird.

45
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It's just something you get used to.

46
00:03:19,240 --> 00:03:20,560
You just kinda have to remember it.

47
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So, all right, let's try that out.

48
00:03:25,720 --> 00:03:26,364
And there we go,

49
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we've got @teamtreehouse.com,
@teamtreehouse.com, blah, blah, blah.

50
00:03:30,090 --> 00:03:34,500
And then we get over here, and we've got
us, this was supposed to be us.gov, and

51
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we've got just us.

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And then we were supposed to have
empire.gov, as we've got up here, and

53
00:03:39,320 --> 00:03:41,010
we've just have empire.

54
00:03:41,010 --> 00:03:43,930
And we're supposed to have spain.gov, and
we just got spain.

55
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So, that's pretty cool,

56
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we got all the email addresses, but we
left off the .gov on two of them.

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So, I think that's pretty cool, pretty
handy.

58
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Let's try another one with our VERBOSE
flag,

59
00:04:00,630 --> 00:04:03,090
just to get used to doing our VERBOSE
flag.

60
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Gonna comment this out.

61
00:04:05,170 --> 00:04:08,230
All right.

62
00:04:08,230 --> 00:04:14,730
So let's try another verbose pattern that
will match our our names.

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It'll also match our jobs, but it's still
a good practice.

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00:04:18,600 --> 00:04:23,041
So we're gonna do print(re.findall.

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And then we're gonna do a multi-line
string, cuz we're gonna use verbose.

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00:04:26,740 --> 00:04:33,770
So let's do \b -\w.

67
00:04:33,770 --> 00:04:40,998
So that would be Find a word boundary 1+

68
00:04:40,998 --> 00:04:47,220
hyphens or word characters.

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We'll just say characters.

70
00:04:49,810 --> 00:04:52,210
And a comma cuz that comma's in there.

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It has to find that comma.

72
00:04:54,030 --> 00:04:57,300
And then let's have it find, find
whitespace.

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Find 1 whitespace.

74
00:05:02,340 --> 00:05:06,036
And then let's have it find another
hyphen, a w, or

75
00:05:06,036 --> 00:05:07,731
a space as part of our set.

76
00:05:07,731 --> 00:05:10,897
We'll talk about why that's different in
just a second.

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00:05:10,897 --> 00:05:19,082
1+ hyphens and characters, and explicit
spaces.

78
00:05:21,120 --> 00:05:25,630
And then I want it to not find tabs or new
line characters.

79
00:05:25,630 --> 00:05:29,971
Ignore tabs and newlines.

80
00:05:29,971 --> 00:05:34,489
And then we wanna close this, we're gonna
run this against data, and

81
00:05:34,489 --> 00:05:36,031
we're gonna do re.x.

82
00:05:36,031 --> 00:05:36,631
All right.

83
00:05:36,631 --> 00:05:40,130
So let's talk about this one for a second
before we run it.

84
00:05:40,130 --> 00:05:43,190
So, when we do the verbose flag,

85
00:05:43,190 --> 00:05:49,100
which re.x if you didn't guess is the
short hand version of re.VERBOSE.

86
00:05:49,100 --> 00:05:54,250
When we do the verbose ones, the regular
expression engine ignores all of

87
00:05:54,250 --> 00:05:57,260
the spaces that are just out in our
pattern.

88
00:05:57,260 --> 00:06:00,087
So like, these spaces here and

89
00:06:00,087 --> 00:06:05,980
these spaces here are completely ignored,
as is this comment.

90
00:06:05,980 --> 00:06:09,880
So we have to mark those with this \s.

91
00:06:09,880 --> 00:06:12,480
That, and, and that is whitespace.

92
00:06:12,480 --> 00:06:17,080
So that matches spaces, it matches tabs,
it matches new lines.

93
00:06:17,080 --> 00:06:18,130
It matches all sorts of stuff.

94
00:06:18,130 --> 00:06:19,780
Actually, I don't remember if it matches
new lines or

95
00:06:19,780 --> 00:06:24,220
not, but it matches spaces and tabs, and
other characters like that.

96
00:06:24,220 --> 00:06:28,690
If you wanna go look up like, half tab or
letter space and

97
00:06:28,690 --> 00:06:31,950
stuff like that, there's all sorts of
these spaces that are available.

98
00:06:31,950 --> 00:06:33,410
So it matches all of those.

99
00:06:33,410 --> 00:06:36,880
But inside of a set, we can use an
explicit space and

100
00:06:36,880 --> 00:06:40,110
that will only match spaces.

101
00:06:40,110 --> 00:06:42,630
It won't match tabs or newlines or
whatever.

102
00:06:42,630 --> 00:06:46,090
And then down here we want to ignore tab
and newline.

103
00:06:46,090 --> 00:06:50,730
Now, why didn't we have to use re.i in
this one, or re.ignorecase.

104
00:06:50,730 --> 00:06:54,380
The reason's because we're not matching
any explicit characters.

105
00:06:54,380 --> 00:06:58,780
We're not matching, like, the letter t,
that may be uppercase or lowercase.

106
00:06:59,860 --> 00:07:03,590
Since we're not matching those things,
we're matching more generic stuff like

107
00:07:03,590 --> 00:07:09,100
word characters, then we can use, or we
can, we can leave off re.i.

108
00:07:09,100 --> 00:07:11,600
.
So let's run this and see what it does.

109
00:07:13,910 --> 00:07:15,840
And I forgot another character.

110
00:07:15,840 --> 00:07:18,270
We should have a plus sign there as well.

111
00:07:19,280 --> 00:07:20,250
So let's run that again.

112
00:07:21,860 --> 00:07:22,420
There we go.

113
00:07:22,420 --> 00:07:26,580
So now we've got Kenneth Love and Teacher
Treehouse, Dave MacFarlane, or

114
00:07:26,580 --> 00:07:29,100
MacFarlane, Dave, Teacher Treehouse, and
so on.

115
00:07:29,100 --> 00:07:32,650
So we got the names, and we got the where
they work.

116
00:07:34,070 --> 00:07:39,040
So, of course, if we want to get Tim in
there, we need to change this to a star.

117
00:07:40,260 --> 00:07:44,420
Run this again and we should get Tim.

118
00:07:44,420 --> 00:07:45,490
I don't see Tim actually.

119
00:07:47,220 --> 00:07:52,470
So Tim's not in there, but we will fix
that later.

120
00:07:52,470 --> 00:07:55,800
We'll select everybody before we get to
the end of this.

121
00:07:55,800 --> 00:07:59,520
As you can tell though, it really, really
helps breaking up our patterns or

122
00:07:59,520 --> 00:08:00,450
multiple lines.

123
00:08:00,450 --> 00:08:04,470
And being able to annotate each line with
a comment, so that we remember what we're

124
00:08:04,470 --> 00:08:09,890
doing, what we're looking for and how to
make things again.

125
00:08:09,890 --> 00:08:12,370
We have a ton of choices now when we write
patterns.

126
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They can be as flexible or strict as we
need.

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Our next video will cover the real meat of
what'll make our regular expressions

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capable of solving our immediate problem.