Welcome back to EDirect for
PubMed.
Today is part three, formatting
results and using Unix tools.
I'm a librarian here at NLN.
I'm here with Sara and Mike, the
director of this series.
Let's keep our team in mind,
getting PubMed data you need and
only the data you need in the
format that you need.
Last week we started the process
by getting PubMed data using
Esearch and Efetch.
In the next session we'll
restrict our output to data you
need.
Today we're going to get a data
formatted to our specifications.
Today's jeopardy is to give a
quick recap of part two,
customize separators, group
elements would block, save
results to a file and then read
from a file.
Last class Sara talked about
extract which pulls data from
XMLand arranges it to a table.
We use the pattern argument to
determine the rows for our table
and we use the element argument
to determine the columns for our
table.
When using these or any of the
extract arguments that specify
particular parts of an
XMLdocument, carefully making
sure your spelling and
capitalization are correct.
We can identify specific
elements that are in a
particular location in the
hierarchy using a parent child
construction.
We used the example of
PMIDwhich is in the Medline
citation element and we can
identify attributes using the
sign.
Before I take your questions
from the homework, I want to
remind you quickly how to find
the course materials on the data
guide site.
Okay.
So if you're at data guide, you
want to go to our classes page,
and if you expand the EDirect
for PubMed section, at the very
bottom there's a link to the
class materials.
Hopefully you've been looking at
this so far, but if you haven't,
please do.
Here you can find the handouts,
the code, the slides and the
script, and I particularly want
to point out the sample code.
So, for example, for last time
for part two, if you look
through here, you can see an
explanation of all the codes
that we reviewed with complete
annotation, and if you go down
towards the bottom, you see the
solutions to the in-class
exercises, and then at the very
bottom you see the homework
solutions fully annotated so you
get a good explanation of the
homework.
With that said, if you have
questions about the homework,
please put them in chat.
We'll do our best to answer
them.
Okay.
So Karen has a question.
PMIDcan be used along with
Medline citation.
Is there a reason why we would
use the longer one?
>> So the only reason why you
would need to use a parent-child
construction is if there are
multiple elements using that
same element name.
In the case of PMIDthere are
cases, when there's a PMIDfor
other records.
So that's why we're using the
parent-child construction so
that we don't pull up PMIDSfrom
other records.
And not every record has all of
the same data.
You may be running across
problems with some records and
not others, and as you start
extracting things you, you may
realize we have repeated
elements in places where you
didn't think we did.
So you're going to want to take
a look at your example records
when you do your tests and
hopefully, you will run across
the problems before they become
a real problem.
Okay.
Other questions about the
homework?
Please keep entering your
questions into chat.
I'll get to them, if I can,
while talking or at the end.
We now know the proper syntax
from pulling out data from XML.
Today we're going to look at how
we can pull up that data
cleanly.
Say you want to retrieve a few
PubMed records and we're going
to start with an Efetch.
You should havedown handout open
so you can copy and paste,
especially the Efetchs so you
don't have to be typing that in.
So that's what I'm going to do
here.
We start with this Efetch.
I'm going to stop for a second
and say if you are copying and
pasting code, which we expect
you to do, you're going to save
yourself much grief by using a
editor which doesn't introduce
any special characters.
As you have learned, Unix is
very particular and every
character is meaningful.
Using a program like word is
often problematic because it
adds formatting codes and
possibly other characters that
will be nonsense to Unix and
this is why, actually we've made
the handouts, which you you
should have open right now,
available in a . TXTfile.
I'm fetching three records in
XML.
He want one row per PubMed
records.
Please remember what that means.
Our extract is going to be in
the pattern PubMed article.
And then we define our elements.
So I said we wanted our PMID.
Again, we're using that Medline
citation parent because there
may be multiple PMIDs in the
record.
Okay.
So we get the output that we
wanted but it's not very pretty.
We might expect to have three
column here.
We actually do, but it's hard to
tell where each column begins
and ends.
The come he means are all
separated by tabs but so are the
multiple values in the last name
column.
We can fix this using some
special formatting arguments.
And those are tab and step.
Tab and step let you -- tab
changes what character is used
as a separator after each
column.
SEPis a separator.
Notice I phrased those two
definitions a little
differently.
The tan is the separateRafter
the SEPis between.
This distinction is going to be
important, but for now just
remember the tab separates come
he means and SEPmultiple values
in the same column.
By default both are a tab
separating which is what we've
seen in our example so far.
First we're going to start with
no tab and no SEPjust the
default.
Remember that extract creates a
new column for each different
element we specify.
So this might help you visualize
it a little better.
We have three come he means,
PMID, I SSNand last night.
Our last column has multiple
values in it.
We can see there's a tab between
each of our columns.
We assume there's a tab between
each of the values and our last
name column.
So now if we add the argument
tab and SEP, and we add them
with a back slash T, don't see
any change and that's because we
defined become our tab and our
SEPwith the back slash Dand
quotes and that's the default.
That's why we don't have a
change.
Let's start to play a little
bit.
Let's change the SEPargument
from a tab to a blank space.
So here we can see that our
columns are still separated by
tabs but the multiple values in
our last name column are now
separated by single spaces.
Let's leave, change our tab
argument to pipe.
Now our come he means are
separated by pipes instead of
tabs.
And now let' switch the SEPto
comma space.
Using the tab and SEP, as you
can see, we can cut EPLize our
output format.
Separated by pipes and last
names are separated by comma
space.
Okay.
Now playing around with these
separators can be a little
tricky.
Keep in mind two things.
First when you use a tab or a
SEP, it only effects the part of
the command that comes after it.
So in this example, even though
we set our tab to pipe right
here, separator after each
column, after the first column
is still the tab.
Sorry, first column because we
didn't change it until after.
Second you can overwrite an
earlier tab or SEPlater on in
the line.
Again, if we look at this
example, we start off with the
default tab, then change it to
pipe between the second and
third come he means and change
it again to colon between come
he means three and four.
So you can think of this as a
linear process where we are
engaging different formatting
instructions as we go.
Okay.
Please refer to your handout
because you'll want to copy and
paste the Esearch command, and
give this a shot with this
exercise.
Write an extract command that
has a new row for each PubMed
record.
You know what that means.
And that has come he means for
PMID, journal title abbreviation
and author supplied keywords.
I'd like you to separate each
column with a pipe, and I'd like
you to separate the multiple
keywords in the last column with
commas.
I'm going to give you five
minutes to do this.
Please put up a green check when
you're done and there's no shame
in checking the answers in your
handout, if you get lost.
I think Sara also is going to
give you some hints in chat as
you go to help you out.
>>> Okay.
A bunch when you have finished
or maybe given up.
Hopefully finished.
And we're going to go through
the solutions.
So let's take a look at this.
Sorry.
Bear with me a sec.
Okay.
So hopefully you copied and
pasted your Efetch.
We have these four records we're
look at in XML.
For many of these examples we
with are having one PubMed
record per line, so that's
pattern PubMed article.
So each row is going to be from
a different record.
Okay.
And then here is where we're
going to add our tab and our
SEP.
So we ask for pipe between come
he means and a comma within come
he means between the data within
one column.
And then our elements are --
again we're using this a lot so
that we can check our data with
one PMID per row and then we
used ISo, upper aviation and
then the author keywords are in
keyword, singular, sorry about
that.
That was my fault.
So that's how you would do that.
And here are your results.
You got your PMID.
And you have your Medline title
abbreviation.
Those are separated with pipes,
and then your last column with
your author keywords separated
with commas.
Questions about that?
Okay.
Even if you're still thinking
about that, I'm going to ask you
to stop thinking about that
because we're going to move on
and I need you with me.
Let's say we want to pull all of
the authors for each citation.
We want one row per record and
we're going to put the PMID in
there too.
We'll copy this in fetch.
We've got a few records in
there.
And we're going to do an
extract.
Again PubMed article.
And we're going to want PMID.
Okay.
And them we want the last name
of the author and the initial.
Okay.
So take a look at what I have
here.
What happened?
Extract the date from the last
name element and them pulled all
of the date from the initials
element.
If you look at what I typed in,
that's what we asked it to do,
just not what we intended.
What we want to do is retain a
relationship between the last
name and corresponding initials
Mike's got a beautiful visual
here to explain how this is
working.
All right.
Take a look at this slide.
On the left we have some dummy
XMLfrom which we are
extracting.
On the right is going to be the
output of our command.
On the bottom is our code.
In this case that PubMed
article.
Great.
Then exact looks for all
instances for the element or
elements identified and outputs
them.
So first going to look for
Medline citation PMID of which
there should be a single
occurrence, there it is, and
then it's going to look for last
name.
And then rather than giving us
the initials, it gives us the
next and here it is.
And then it keeps going to the
next last name and next last
name until it can't find another
match for that pattern because
all it's doing is scanning
through the XML, finding the
string that identifies the
element that we're looking for
and identifies the contents of
that element.
Here it's done and now it's
finished.
Only then did it look for the
next element we asked for,
initials.
It gives each one in the pattern
until it can't find another one.
Okay.
So hopefully you're following
what happened with that example.
There's a way to fix this.
We can fix this using the block
argument.
Block is one of our series of
extract arguments known as
exploration arguments which help
us identify and group the
elements we want to output.
This is what we want to group
each related pair of last name
and initials.
A block associates multiple
child elements of the same
parent element and the results.
Let's try it.
Here start with the same code
and we want the PMID in there.
But now what we want to do is
block those authors.
So block author and then we're
choosing the elements from
within that block, within the
author element.
Last name and initials.
So it's asking for the last name
and initials in this block
before it moves to the next
block, and there we go.
It worked.
Why did it work?
Let me show you.
Okay.
Again, just like before I'm
showing you some dummy XML, and
the output is going to be on the
right for the command that's at
the bottom of the screen.
Just like before, first instance
in the XMLof our pattern PubMed
article.
Then extract looks for all
instances of the element or
elements identified and output
stuff.
This time it's looking for PMID
and it outputs that.
Then extract finds the first
instance of the element
identified in the block
argument, author.
Extract that looks within that
first author element and outputs
the element or elements
identified in the element
argument.
So should be one last name,
there you go, and one initials
MP.
When it's done with the elements
within that block, only then
does it move to the next block.
And here exactly looks within
the second author element,
outputs the last name and then
initials.
Done with that block, goes to
the next block and then last
NATO, initials and extract keeps
repeating these steps until
there are no more author
elements in the pattern.
There we go.
If there isn't another author
element in the pattern,
extracting moves on.
It's reached the end of the line
so it goes back to the beginning
to find the element identified
in the pattern.
Okay.
So I'm looking at questions.
I don't see any questions about
how block works.
You can think P what other
elements exist in PubMed data in
the relationship with the child
elements and parent are
important to keep when you're
exporting that data and consider
whether block is something you
want to use.
Sticking with this particular
example, you know, this is good.
We've got the PMID and then we
have the last name and initials
for the same authors and
together.
We pulled them next to each
other by blocking them by their
parent element.
We've got all of the authors on
a single line.
But the thing is everything is
separated by tabs.
Wouldn't it be nice if we could
actually group the last name and
initials together in our output
in our relationships.
Well, we can.
Here's what we know so far.
From the beginning of the class,
we begin by creating pattern to
create rows.
Each of our columns have had
data from a single element or
attribute in them.
If you look at the three come he
means of this output table, you
can see that happening.
The first column is data from
the PMID element.
The second column has data from
the ISNNelement and a third
column has multiple values, but
each of these values is from
different occurrences of the
same element, the last name
element.
With what we know about tab and
set, we can now specify
different characters to separate
between come he means versus in
the same column.
With our author last NATO
initials examples.
We want to outcome values from
two different elements in the
same column and use our
SEPseparator to separate them.
And we can do this with a comma.
Instead of separating the
multiple elements with a space,
we use a comma instead.
That sort of puts them in the
same column.
We're excelling extract not to
consider these separate come he
means because the data is in the
separate column.
Then when we combine this with
block, we still have our come he
means separated by taps but our
last name and initials are
grouped together in the same
column with the face separated
by the two values which makes
our information a lot easier to
read.
A little aside that may reduce
some confusion if you're
building your commands.
Whenever you have a block
argument in your command it
resets your defall.
Looking at this example, we
define our tab as pipe and our
first two come he means are
separated by the pipe.
Once we start creating new come
he means for each of these aller
blocks, our tab gets reset.
The block argument is resetting
our tab.
So our SEPstill works in this
particular example because, as
you see, we defined it after our
block.
So if we want all of our calm
separated by pipes, we need to
go in and had another argument.
Are you ready?
I'm ready.
Okay.
Exercise two.
Time for another hands on
exercise.
This is a nice challenge where
you're going to combine tab,
SEP, lock and comma all
together.
What I'd like you to do is write
in extract command that has a
new row for each PubMed record,
has a column for PMID and lists
all of the mesh headings
separated by a pipe.
If the heading has sub headings,
separate the heading in each of
the sub headings with a slash.
Okay.
If I just blew your mind and
you're a little overwhelmed,
take a moment and just listen to
a suggestion of how you might
get started on this.
Because it is a little bit
complicated to try to take all
that in at once.
So let's work through this
logically.
Start by pulling up at least one
of these records in PubMed and
XML.
Identify the elements you want
to extract.
Write them down, tape them up,
copy them, paste them.
Just identify the elements
first.
Then think about what elements
have parent elements that you
want to use to group them using
block.
After you've done that, then
consider what elements you might
like combined into the same
column using comma.
And then finally consider what
characters you'd like to use to
separate the come he means using
tab, and then the data within a
column using SEP.
This might require some
experimentation.
So try some things here and see
how you do.
Whether you did it yourself or
copied from the handout, that's
fine.
When you're done, give me a
green check so that we can move
in.
We're going to give you a little
extra time with this one, about
seven minutes, unless everybody
has a grown check right away, in
which case we'll move on.
Again, Sara's going to put some
hints in chat as you go.
Good luck.
Some of you have it.
Some of you not quite yet.
That's okay.
This is not a simple thing to
figure out in a short time
period.
But let's take a look at it so
you can ask any questions you
might have about how to involve
this.
And show you a solution.
Okay.
So the way that you would
construct this in real life is
probably something like what I
just suggested before, and first
start by identifying elements
that contain the data that we
want.
So hear you can see that we're
pulling the PMID from the
Medline citations wrapper and we
found the element's descriptor
name and qualifier name.
The next part to determine where
we're going to use block
requires us to understand that
descriptors and qualifiers are
different elements but they are
wrapped in a mesh heading
element, similar to the way last
name and initials are wrapped in
that author element.
So we want to use block to keep
the relationship between each
descriptor and its qualifiers.
Then we want to display the
qualifiers with their associated
scripters in the same column by
using that comma between them to
force them into the same column.
Finally we clean it all up by
using pipe between the come he
means, and here we started out
using the tab argument up here
before PMID, but then we have to
repeat it again because remember
block is going to start our
formatting over from scratch, so
we have to put the tab back in
and then our SEP, which is our
forward slash between the
descriptor name and qualifier
name.
Okay.
I guess I'll just rip that.
And either if you figure this
out on your own or if you copied
and pasted the code, you should
see something like this.
Now if you figured that block
out on that one, you are doing
great.
If you figured out the block and
the comma, you are doing really
great.
If you figured out the block,
the comma and the tab in the
sets, I would say you're an
impressive human being or you've
done this before.
If you didn't figure out any of
that on your own and you looked
at the answer and sorta kinda
get what we're doing, that's
what I hoped for at this point
because this is a short class,
but using this stuff takes
practice.
If you're still having trouble,
take a breath, you're going to
need your review and practice,
and if you're like me, probably
sleep on this a few times and
let your brain work through it.
Okay.
I'm going to clear your and
we're going to switch gears a
little bit.
So, if you're still working on
that, I would ask you to pull
your brain away from it and
attend to what I'm doing now.
Oh, there's a question.
So Kate asks what if you wanted
to have a subject heading that
has several sub headings to be
repeated.
I'm not sure I understand that
question.
Oh, it has multiple sub headings
applied to the same descriptor.
Do we have any examples in this?
Yeah, we do.
So if you take a look at the
example, it's kind of towards
the end.
On my screen it's the fourth
line up on the right.
You see how it handles the
multiple, the settings apply to
the same descriptor.
Oh, you want to repeat that.
I don't think I'm going to come
up with an explanation on the
fly for that or a solution for
that.
I'm going to have to think for
that.
Can I come back to you?
Sorry about that.
I'm not sure I can resolve that
right now.
But now I understand what you're
asking.
So right now I'm going to change
gears a little bit and talk
about Unix.
We often had some unfortunate
line wrapping, otherwise some
somewhat unwielding results.
There's only so much data
manipulation we want to do here
in EDirect.
One of our goals here is to
extract our data as cleanly and
as neatly and as well-organized
as we can to import some excel
or a text editor or some other
environment where we can play
with it.
You can copy and paste but it
may not be an option.
Saving your output to a file is
very simple.
You just take the same set of
commands as we were using, add a
greater than symbol, a space and
file name.
Let me give you an example of
that.
Okay.
So here I'm fetching three
PMIDs and to put that into a
file, I use greater than symbol,
I live the file a name.
I'm going to make it a text
file.
So that's all you have to do,
greater than sign, file name.
When we execute this, it doesn't
look like anything happened but
it did save the file to my
current directly, and to prove
that to you, we use another Unix
command, LSor list.
List lists all the files in your
current directly.
It created this next file.
I listed my files.
There it is.
It worked.
But where is that?
Where is this file?
Well, if this class is the first
time you've used the Unix
terminal on your machine, you
may be wondering where this
mystical folder we're viewing
is.
One thing you can do is try the
PWDcommand.
That's PWDfor print the working
directory.
It displays on the screen the
name of the directory you're
currently working in.
You can try that, PWD.
It tells me that I'm in a folder
which is my user name and home.
Great.
But where's that?
Well, depending on how your
software is set up, this folder
is most likely on your hard
drive.
I'm pretty sure I use a defall
setup.
So I can show you where this is
on my machine.
Okay.
So here's my windows.
I went to my local disc C.
I have a folder here.
This is my folder and here's
where that PWDcomes in handy.
I'm looking for a folder called
home.
There's a folder called home.
Check it out.
And then I'm looking for a
folder.
If I go in there it, here it is.
So among other stuff that I
don't care about, and by the
way, the EDirect installation is
that text file that I generated
from EDirect, and I can even
show this to you.
Here are the three PMIDs that
I exported to this file.
So, yes, all is right with the
world.
There it is.
You can save in whatever file
format you want.
I can do an Esearch and then an
Efetch to get a list of PMIDs.
I could use Efetch to download
full XMLand save the outpout to
an XML file.
I'll do that for you.
Clear my screen so you can see
what I'm doing here.
Here I'm fetching these three
PMIDs in XMLformat.
I'm putting them in a file.
I'm not going to see anything
but but if I list using that
LScommand, I can see that file
has appeared in my folder.
And I can look at it in Unix and
I can look at it in my native
environment, if I like.
Now for SIGWYNusers like me,
your working directory is a sub
folder of the folder where you
installed.
For Mac users, try looking in
your users folder.
So user slash your user name.
Hopefully you can find your
files.
If you're having trouble,
another trick is to use a
distinctive file name so that
you can search your computer for
it using your operating system.
Let's all create a new file
which we're going to use in a
minute.
Copy this from the handout.
Show you what it looks like.
So we're going to fetch these
fours records just so you IDfor
them and put them in a file
called special name.
This is going to create a file
and you can use this special
name file if you'd like to use
your search feature on your
computer to find it.
Just go ahead and do that.
Again, I could verify that this
file is created properly making
sure that it's there and there
it is.
Okay.
After you've done that, I have
another quick exercise.
Similar idea but I want you to
this time do a search of PubMed
and export that XMLinto an
XMLfile.
So get the full XMLof all
articles about the relationship
to Zika virus in Brazil and this
might take a while because it is
a large search result.
And again give me the green
check when you're done.
This one shouldn't take too
long.
Okay.
A couple of you had some
problems with that.
It's almost always a typo.
I'll show you how I did this.
So we're doing an Esearch,
PubMed.
I did query Zika virus, Brazil,
should be in quotes.
Efetch in XML and then greater
than sign, a file name dot XML.
So we have -- if it didn't work
for you, you probably have maybe
a misplaced character, some kind
of typo in there.
If you're still having trouble
finding your file or with that
last exercise, we can try to get
to some of those questions at
the end of the we're going to go
ahead and move on, so I'm going
to ask you to stop working on
that for now and ask you to
clear your statuses.
Hopefully you can come back to
this.
If you have questions, please
put them in the chat.
Okay.
So Unix has a lot of tools
designed just for manipulating
files.
We're not going to get into them
much but there's one exception.
Sorry.
So those are those flee I put in
earlier.
Here's just a stripping of
characters.
Take a look at this other file,
another string of characters.
That's all that's in the file.
Like I said, it is kind of an
easy way to pull two files
together.
What you do is put in one tile
name.
And then the next file name.
And it will apenned file two to
file one.
There you go.
And if I wanted to save that as
another file, I can use that
greater than sign and call it
file three.
As you can see, kind of a handy
way to look at files and play
with them right near Unix
system.
So list that, can see that I
created file three there.
Okay.
How does this help us?
What do we do with it.
I'm going to ask you not to
follow along with me.
Let's say you have a long search
string that you want to use in
Esearch.
So, for example, sorry.
Hang on.
>> It's an effort to capture all
intramural research.
Lovingly known as NAAID.
But it has a lot of different
names, labs, sub components or
divisions.
Any one of these could be listed
in a paper's affiliation.
Additionally there are over 100
researchers who work at NIAID.
So in order to have a search
strategy that captures the work
of this institute, it takes a
long-term strategy as one that's
going to change over time.
We may need to add knew authors,
new need for sub components,
whatever, so you don't want a
big search stripping like this
to be part of your command.
However, what you can do is to
have your search string in a
separate file and use cat to
pull the contents of this file
into your search string.
Now again you don't have this
search string file on your
computer.
So just watch this for now and
don't do this at home.
Clear my screen.
You would start your Esearch
normally specifying your data
base, PubMed, are and then what
we want to do is have a query
where we take it's dollar sign
and open parenthesis, cat and
that file that has my search
string in it, close parenthesis,
close quotes.
So the dollar sign parenthesis
gives us the value of what's
inside the parenthesis.
So the value of cat search
string . TXT, is the output of
reading search stringTXTto the
screen.
So you could use that to pull in
a really long crazy search
string and do a search with it
in EDirect.
And you can do something like
this in Efetch too.
Say you had a list of PMIDs in a
filing and you want to fetch
them all.
It's useful if you maintain a
list you want to retrieve
instead of just retrieving the
search results.
You could do the exact same
thing.
But let's say you have a file
with one PMID in each line.
If you do it this way, you're
going to get an error.
For this we want to use another
EDirect command we haven't yet
talked about.
Before we do that, I want to
take a step back and look at
something we talked about a lot
which is the pipe.
So let me pull up my slides
here.
Okay.
So when we introduce the pipe
earlier this the class, we were
talking about Esearch and Essex
fetch.
We said we were piping the
results of one command and using
them for the basis of another.
Remember when we do an Esearch,
we aren't actually getting out a
list of PMIDs.
What we're getting is this
XMLsnippet with a number of
search Pmids that mitt our
search criteria.
History server is what keeps
track of your previous searchers
and it's just like what you see
on the advanced search page in
PubMed.
It tracks your session to
specify your specific history
and not some of the history.
What the pipe is actually doing
is piping the web PNBand query
key from Esearch to Efetch.
It's saving them on the history
server.
The web EMDtell Efetch which
results to pull down from the
history server.
Again, most of the time you can
think of the pipe as piping
MP*EUD commands from one to
another.
The fact that this works this
way allows you some interesting
and powerful options because
Esearch isn't the only thing
that can put Mmudslides on the
history server.
The EDirect command Epost can be
used to up load a series of
PMIDs to the history server.
Piping the results of Epost to
Efetch works exactly the same
way as Esearch.
All right.
So quick demo.
Here we can run Epost by itself.
And we get, as you can see,
query key.
And we need to be sure to
specify the data base when we do
this because Essex direct can be
used to access other data bases.
We can pipe that in Efetch just
like we would have an Esearch.
Efetch and we'll do abstract
format.
But this actually as you can see
doesn't get us anything that
Efetch doesn't.
But when we use cat to open the
file, then pipe the contents of
the file into Epost, let me show
you, sorry, hang on.
Lost my KR-P.
Should see this on your handout.
Remember that special name file
we created?
When we use cat to open the
file.
Type the contents of the file
into Epost, types to Epost which
uploads them to the history
server and then pipe
environmental query key to
Efetch to download the full XML.
All right.
Okay.
So here you go.
You can pipe this from one to
the other.
All right.
Now until recently this was the
best way to get a list of Pmids
into a Efetch pipe line but
recently in September EMIadded
a new argument.
It's called an input argument
which let you skip the cat part.
Let me show you that.
Okay.
So here you see Epost using the
input argument for that same
file and them we can fetch the
records that way.
Okay.
I think I missed some questions.
Let me take a look.
All right.
Before I go back to earlier
questions, does anybody have a
question about using Epost or
using this input argument, other
ways to pull data into your
Edirect.
Am I missing any questions?
Was there a space.
Oh.
Yes, I put in a space because I
needed the space or they would
have mushed together.
So if I -- you can't see it but
there was a space -- I think I
put the space after the Sthere
so it wouldn't be merged with
the next word.
If you're trying to follow
along, there was a space.
Wrapping up I think.
Okay.
All right.
So that was the content that I
have for today.
Next time we're going to
continue our discussion of
extract and talk about some more
advanced arguments, conditional
arguments, which are really fun
to limit our output to the exact
data that wee need and we're
going to cover some ways to
intergrade all of this into
practical solution to see real
world problems which brings me
to in the meantime between now
and then in addition to doing
your homework, if you could
please send us your case
studies, if you have some ideas
on things you might want to do,
even if it's just an inkling,
send it along and we'll take a
look at it.
We've gotten a couple so far,
but we want to see some more.
As always, please we encourage
you to visit our website for
more information and
documentation as well as I
showed you the script, the
slides are recording.
As soon as we can put it up and
remember to sign up for that
Eutilities mailing list, if you
haven't already.
There's a contact us button on
your website to reach us.
If you have any questions before
Thursday, please send us those
questions.
If you have questions right now,
please put them in.