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For 2023 - we are now fully retired from IT training.
We have made many, many friends over 25 years of teaching about Python, Tcl, Perl, PHP, Lua, Java, C and C++ - and MySQL, Linux and Solaris/SunOS too. Our training notes are now very much out of date, but due to upward compatability most of our examples remain operational and even relevant ad you are welcome to make us if them "as seen" and at your own risk.

Lisa and I (Graham) now live in what was our training centre in Melksham - happy to meet with former delegates here - but do check ahead before coming round. We are far from inactive - rather, enjoying the times that we are retired but still healthy enough in mind and body to be active!

I am also active in many other area and still look after a lot of web sites - you can find an index ((here))
Practical Extraction and Reporting

The week just gone, I gave a Perl course in Edinburgh to a dozen very bright scientists, working in the bionformatics field, where they're concerned with analysing a veritable flood of data. A great deal of that analysis is fairly standard and so will be done using standard tools - some written in C for sheer speed of operations, some as Perl modules, and some using R - [link]. But there's also strong layers of experimental data extraction - producing tables of filtered information from incoming flows, and gluewhere work where those are a variety of flows. Inputs can be plain file, SQL feeds, web pages, and files saved from a spreadhseet such as Excel.

As a computer scientist, I can flip between different data sets easily, shrugging off the differences with "it's just data" - but the newcomer needs to learn to apply the same principle very widely. So I used a varierty of data sets during the course. Where can you find them?

http://www.wellho.net/data/access_log.xyz - Web server access log records
http://www.wellho.net/data/requests.xyz - Staff and skills data
http://www.wellho.net/data/cpg.xyz - Bioinformatic data
http://www.wellho.net/data/refflat.xyz - Bioinformatic data
http://www.wellho.net/data/railstats.xyz - Railway station location and use

Some of these have space characters between the fields, others have tabs. Some of them then have other data within a single field that is split by commas. Provided yoou can work out what the data means (and that's wehre you may need a reference manual for the data, and a knowledge of the what the data's about and what is a sensible thing to try), you're then in a good position to engineer it into variables in your perl program for analysis.

Reading from a file this week I used open and <>. Reading from a database, I used DBI -> connect then prepare, execute and a loop of fetchrows. Reading from a website, I used LWP::Simple and get. Just examples of how it can be done, of course, as with Perl "There's more than one way to do it". And once the "top bit" of the code has been written to get the data, the source type becomes irellavant and we can go on to processing the data ...

Many typical programs in this data flow / processing world involve sucking the data in - it can be done all at once for a small data set, or "drip, drip" - line by line - if the incoming set is huge. If the program takes the form of a filter, then information / results can be output as the data is being read in, but if the data is to be output sorted in some way, then it needs to be retained. You'll use collection variables in Perl to do this - either lists (which start with an @ symbol and have numbered positions) or hashes (which start with a % symbol and have named positions). Once you've read all the data, you can sort your lists prior to output. You cannot sort hashes ... but you can (and often do) sort a list of the keys.

And when you're done ... you can output to the screen. Or to a file. Or to a(nother) database. If you're runing on a web server, you can send the output to your user's browser too. We looked very briefly at CGI this week, but there are other ways too.

Let's see a short example - and this is a general one, using data which most people should be able to identify with. I have a data file containing a list of all my staff members- one per line. And after each of their names, on the same line, is a list of the subjects they would like to learn. So:
  ivan Ruby Java Perl Tcl/Tk MySQL
  nigel PHP Python Java Perl
  jenny XML Perl Ruby ASP
  kerry Perl Tcl/Tk Ruby MySQL

And I want to produce a list of subject, and against each subject a list of the people who's top (first) choice it is for them to learn - thus:
  Java - graham rupert ulsyees venus xena
  MySQL - ethel fred olivia orpheus uva zachary
  PHP - harry hazel john leane nigel peter rita xavier

and so on.

The Perl code turns out to be short ... I can read the data in with the following:

  open FH,"requests.xyz" or die "Input data file not available\n";
  while ($line = <FH>) {
    @flds = split(/\s+/,$line);
    push @{$skill{$flds[1]}},$flds[0];

And I can produce my output like this:

  @skilllist = sort keys(%skill);
  oreach $sk (@skilllist) {
    @ordered_names = sort(@{$skill{$sk}});
    print "$sk - @ordered_names\n";

With code that's this short, a skilled Perl programmer can work very quickly indeed - hidden within the terse instructions are a lot of cleverness, and hidden within Perl are further levels of celverness which leave the language to do all the hard work internal to sorting the answers, and to allowing the program to work and have enough memory available no matter how many staff are involved. My sample data file had 52 people and about 10 skills in it. But it would work with 500,000 people and 100,000 skills just as well.

But quick to code doesn't necessarily mean quick and easy to learn and indeed there's something of a tradeoff. Other languages (and other styles of Perl coding, come to that) may be easier to learn, but will from then onwards be somewhat slower in code development. So this is why our Perl Courses are a little longer than our other programming courses, and yet the Perl language continues to be so very popular.

Illustration - travelling to work in Edinburgh
(written 2011-06-26)

Associated topics are indexed as below, or enter http://melksh.am/nnnn for individual articles
P669 - Perl - Data Munging
  [597] Storing a regular expression in a perl variable - (2006-02-09)
  [1316] Filtering and altering Perl lists with grep and map - (2007-08-23)
  [1509] Extracting information from a file of records - (2008-01-16)
  [1947] Perl substitute - the e modifier - (2008-12-16)
  [2129] Nothing beats Perl to solve a data manipulation requirement quickly - (2009-04-14)
  [2702] First and last match with Regular Expressions - (2010-04-02)
  [3707] Converting codons via Amino Acids to Proteins in Perl - (2012-04-25)
  [3764] Shell, Awk, Perl of Python? - (2012-06-14)
  [4620] Perl 6 - a Practical Extraction and Reporting example! - (2016-01-11)

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Horse's mouth home
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Efficient travel - from Melsksham to Edinburgh by Sleeper Train
Some other Articles
Simplest ever proxy configuration?
Return trip - Dogs Trust, Newbury
Home Grown Pigs, near Melksham Station
Efficient travel - from Melsksham to Edinburgh by Sleeper Train
Practical Extraction and Reporting
A lesson from the sporran market?
Honesty and a friendly welcome goes a long way
DNA to Amino Acid - a sample Perl script
Comparing Alloa and Melksham - stations and services
A lot of exercise this week
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This is a page archived from The Horse's Mouth at http://www.wellho.net/horse/ - the diary and writings of Graham Ellis. Every attempt was made to provide current information at the time the page was written, but things do move forward in our business - new software releases, price changes, new techniques. Please check back via our main site for current courses, prices, versions, etc - any mention of a price in "The Horse's Mouth" cannot be taken as an offer to supply at that price.

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