Git and Visual Studio Code

Git and Visual Studio Code

Visual Studio Code (https://code.visualstudio.com/) has since it first public release in 2015 increased fast in popularity. Being a cross-platform editor and released as open source software, many software developers have downloaded it. The fact that Microsoft is behind Visual Studio Code means that programming languages like TypeScript, C#, and C++ are well supported.


Git has become the de facto standard for version control systems. In particular Git providers like Gitlab, Bitbucket, and Github have made it easy for software developers to set up Git repositories. Many developers are using Git directly from the command-line, but there exist also a good portion of graphical Git clients. Today, any code editor and any integrated development environment (IDE) must have some kind of Git support.

What is built-in?

Visual Studio Code has support for basic Git operations. This includes creating branches, checkout branches and pushing to and pull from remotes.

Inline diffs are useful for quickly see changes

On the status line, you can see which branch you are on. By clicking on the branch name, a list of existing branches will appear, and you can easily checkout another branch. Another option is to create a new branch.

Right to the line numbers in the editor, you can see if you have change a line: a marker is shown. If you click on the marker, the diff will be shown. The inline diff is useful when you are working together with someone else on the same branch.

Once you are ready to commit your changes, you can click on the source code icon (default: third icon from the top) or use SHIFT-CTRL-G. You will see a list of all files you have changed or created. By clicking on a file in the list, the editor will split in two. You can now see the diff of the entire file. Clicking on the +-icon will add them to the commit. Type a message, and you have created a commit.

Splitting the screen gives an overview of all the changes.

Many more Git functionality can be found in Visual Studio Code.

GitLens

GitLens (https://gitlens.amod.io) is a great extension to help you understand your code base better. It is in particular useful if you work on large code bases with many contributors. One way to explain GitLens is to say it is Git blame on steroids.


Once installed and enabled, you can see when and who change a line. Knowing who did the latest change to a line or block makes it easy to ask for help - you simply know who to ask right away. Of course, it is not the same as you will get a useful answer but that’s another story.

Git blame for every line.

GitLens gives you a simple but power explorer

GitLens also adds a new icon to the left menu. Clicking on the icon will open a Git explorer. You can now easily explore branches, tags, and stashes. Searching for old commits has never been easier.

Github issues and pull requests

It is not a bit secret - Microsoft has acquired Github. At the same time, Microsoft is the founding father of Visual Studio Code. Not surprisingly, Microsoft has developed a couple of extensions to make these two tools work better together.

First one to mention is Github Issues (https://marketplace.visualstudio.com/items?itemName=ms-vscode.github-issues-prs and https://github.com/Microsoft/vscode-github-issues-prs - yes, Microsoft has open sourced the source code!). The extension adds an issue explorer, and you find it under the file explorer. It is a personal tool in the sense it will only know Github issues assigned to you. A click on an issue, and the issue will be opened in your web browser.


Another fine extension from Microsoft is Github Pull Requests (https://marketplace.visualstudio.com/items?itemName=GitHub.vscode-pull-request-github). This extension adds an pull request explorer in the Git explorer so you can get to by SHIFT-CTRL-G. You can explore your pull requests; either the ones you have created or the ones which are assigned to you. Moreover, you can see the pull requests where you are asked for a review. Instead to doing the review in your browser, you can do it from within Visual Studio Code.

Still a console cowboy

I have recently moved to Visual Studio Code, and I am not yet a complete fanboy. But many aspects of it are good, and I keep exploring it.

After many years as a Git user, I still have the habit of doing many Git operations directly on the command-line. Simply because it has been part of my workflow for such a long time.

I have only scratch the surface by looking at a couple of extensions. If you go to Visual Studio Code market, you will be amazed by the number of Git related extensions.

How to learn WebRTC quickly

Review of WebRTC Integrator's Guide by Altanai Bisht

I picked up the book - not because I'm working on WebRTC or related stuff but simply to get an idea of what this new technology is all about. It's a lengthly book, and the author seems to know every trick of the trade. After finishing the book, I feel that I have a better understanding of what WebRTC (and SIP and PSTN) works - at least on the high level.

One thing I like about the book is that it has many diagrams. As I don't have an in-depth experience before reading the book, the diagrams help me to get a understanding fast.

From a practical standpoint I like chapter 9. It's about native clients of the most widely used platforms today (both desktop and mobile). If you read the book to years after publication, it is probably outdated, and I hope that the publisher will ask the author to update it and publish it at their web site.

Chapter 10 touches a topic which is only going to become larger: WebRTC and TV. Today, we see a shift from broadcasting services (like BBC) to streaming services (like Netflix), and a contemporary TV set (SmartTV) is more a connected computer with a monitor than a receiver of TV signals. Reading chapter 10 is like looking into the future. The book also mention WebRTC in healthcare, and I guess that most countries are discussing how to implement remote healthcare so patients can stay at home.

The book's website is http://bit.ly/1wBZ2fG.

Review of JavaScript Promises Essentials

Promises are an old pattern in concurrent programming. In the computer science literature, promises date back to the papers by Friendman and Wise from mid 1970s. Many programming languages have promise - and futures as in Java are a similar idea. A promise is a variable or an object which value is initially unknown and is the result of another task. Modern JavaScript development is highly asynchronous by design: the UI (in the web browser) is updated by calls to the backend using HTTP requests.

JavaScript (ECMAScript to be correct) will soon have promises build into the core of the runtime environment, and promises already exist in many libraries and frameworks. If you haven’t worked with promises in a JavaScript context before, now is a good time to begin. In order to ease the use of promises in JavaScript development, the Promises/A+ standard has emerged.

The book is short and divided in six chapters. The first chapter is an introduction to the state of front-end JavaScript development in general and the asynchronous model in particular. The chapter sets the scene for the rest of the book, and discuss how promises fit well into JavaScript.

The second chapter is written in a very dense format using many bullet lists. You are probably going to read the chapter more than once to get all the information. The good news is that is a lot of information. Chapters 2-4 are a presentation of how to use promises, include error handling.

Chapter 5 is devoted to WinJS - the open source library for development of Windows 8 and Windows mobile applications in  JavaScript. Personally, I don’t develop for any of the Microsoft stacks, but the chapter is still useful as it shows how a widely used library is applying the promise concepts.

The final chapter explains how to implement your own promise library. I guess that there exist many in-house JavaScript libraries. If you have such a library, you will find this chapter useful.

In general, the book is well-written. The usage of bullet list many place (and chapter 2 in particular) can make it hard to read the book. Still, any JavaScript developer should read the book and get ready to the great promise of promises. You can find more information about the book here.

Happy birthday, Grace

Happy birthday, Grace

Yesterday, Grace Hopper would have turn 107 years old. She was one of the first computer scientists. She worked on compilers but she is probably best known for her development of COBOL. COBOL is one of the first high-level programming languages (FORTRAN is the other one). Back in the 1950s, computers were used as calculators, but COBOL and Grace Hopper shown us that computers can be used for much more that simple calculations. Today, COBOL is still wildly used.

As a tribute to Grace Hopper, I have played a bit with the OpenCOBOL compiler. OpenCOBOL can translate COBOL source code to C and use a C compiler to generate a real executable program. The compiler is licensed under GNU General Public License (version 3), and the runtime is licensed under GNU Lesser General Public License (version 3). That is, OpenCOBOL is free software!

Ubuntu Linux and Linux Mint have packages for OpenCOBOL. Probably other Linux distributions and FreeBSD have packages as well but I haven't checked. The installation (using Linux Mint) is simple:

sudo apt-get install open-cobol

I haven't tried to write software in COBOL. The closest I ever came is that I worked on converting between 4th generation languages (4GL) a few years ago. 4GL programs are often converted to COBOL. But I have written a short program in COBOL:

      * Greeting to Grace Hopper

       IDENTIFICATION DIVISION.

       PROGRAM-ID.    greeting.

       DATA DIVISION.

       WORKING-STORAGE SECTION.

       01 WS-TODAY PIC X(21).

       01 WS-YEAR  PIC 9(4).

       PROCEDURE DIVISION.

       010-Greet.

           MOVE FUNCTION CURRENT-DATE TO WS-TODAY.

           MOVE WS-TODAY (1:4) TO WS-YEAR.

           

           SUBTRACT 1906 FROM WS-YEAR.

           DISPLAY "Happy birthday"

           DISPLAY WS-YEAR

           EXIT PROGRAM

           .

       STOP RUN.

Compiling the program using OpenCOBOL is easy:

cobc -x greeting.cob

and running is easy:

./greeting

I am not going to do a lot of COBOL programming in the future, but it seems to possible to replace old legacy operating systems with a modern platform like Linux.

Review: Storm - real-time processing cookbook

Review: Storm - real-time processing cookbook

Quinton Anderson has written a book on the analysis platform Storm and published it at Packt. I have worked a little with Hadoop in the last couple of years, and it is only natural to take a look at the other big data processing platform. Hadoop is a batch processing platform, and Storm is for real-time processing and analysis of data. That means the two projects are not direct competitors, and they might complement each other.

When reviewing a technical book for the general public, it is important not to review the technology but the book. You can easily write a crappy book on excellent technologies while the opposite is very difficult. This review should be read in this context.

The author starts out by explaining how to set up Storm. Storm seems to be quite a complex beast, but Mr. Anderson gets nicely through it. I would have preferred to get an introduction to some of the concept before jumping into the many tasks. But it is my personal preference, and this is a cookbook and not a text book for a university course.

The first couple of chapters is about processing real-time data. Twitter and log files are the canonical examples in this area, and the book utilizes these as well. 

One chapter are on how to use C++ and Qt in your real-time data processing. If you think that Qt is about graphical user interfaces, the book will show you that Qt is a lot more. The author is using Qt's non-GUI parts in his processing.

Another chapter is about machine learning. As part of the big data revolution, machine learning has become popular again. Machine learning is a topic that Mr. Anderson is passionate about, and he analyzes in great detail the problem before showing the recipe. 

One of the major disadvantages of the book is that the assumptions about the reader are pretty hard. The reader is assumed to know at least about:

• Java development using and Maven and Eclipse
• Some functional programming
• Ubuntu or Debian (or any UNIX) command-line
• Web development (HTML, CSS, JavaScript, JSON)
• Data modelling experience
• A little about NoSQL

This problem does not really from the author but from Storm. But the author might have chosen other examples. The book is not a university text book, and therefore I would like many more references to text book and papers.

There is a lot of source code in the cook. You should really download the examples as some of them are longer than a page. It would be great if Packt would do some kind of syntax highlighting. Most programmers find it easier to read syntax highlighted code. In particular, electronic books (I have read the book as PDF) can easily be colorized!

One of the things I really like about the book is that the author has taken time to craft understandable diagrams. A well-composed diagram is worth many words, and he often sums up the key points in a diagram. In general the author writes in a rather dry or fact based language. But on page 111, you find that the author cannot suppress his humor: "... for  automating Clojure projects without setting your hair on fire."

I'm not going to say that Storm is a crappy technology but Quinton Anderson has done the job well by writing a good cook book.

If you are serious in getting into data science and data processing, I wouldn't hesitate to recommend the book. You can find the book at http://www.packtpub.com/storm-realtime-processing-cookbook/book.

Review: Instant ExtJS Starter

Recently, Packt Publishing published a book by N. Bhava on ExtJS. It's a fairly short book, about 60 pages long. The idea is to get you started with ExtJS. If you don't know what ExtJS, it is a framework to develop the front-end of web applications. Today, users except web applications to behave must like desktop applications, and a typical web developer is much more like a GUI programmer just a few years ago. In order to get started with ExtJS, the book is an excellent introduction. By reading the book, it quickly becomes obvious that today's web developers just have a great deal of knowledge of JavaScript, object-oriented programming, HTML and CSS. JavaScript is a class-less object-oriented programming language. But ExtJS is based on the notion of classes, and they are somehow emulated by plain JavaScript. The author does not go into details - probably due to the limited length of the book. A book of less than 60 pages cannot scratch the surface no matter how great the author is. Indeed, the book is quite well written, and the flow of the book is fine. But I must be honest, I have tried ExtJS ever before, and the book is too short for my taste. I do like the cook-book like steps in how to install ExtJS. And I like the usage of the browsers' debugger to inspect code and DOM. The proof-reading of the book could be better. On page 9, the different edition of ExtJS is mentioned twice, and the example of page 35 has an extra </tpl> tag. If you have another web framework (jQuery UI, YUI, etc.), you will find the book useful. It will give you a clear idea of what ExtJS is all about in a short time. The author emphases early that the strength of ExtJS is it's components. The major components (layout, containers, data, templates, and forms) are discussed. In particular, the layout and data components are nicely explained. You can find the book here.

Review: Learning JavaScriptMVC

I haven't been developing front-end code in JavaScript for some time. Well, to be more precise: years. Most of my JavaScript code these days is unit tests for a node.js extension, I'm maintaining at work. Recently, a book on JavaScriptMVC by Wojceich Bednanski was published by Packt. I was curious to see how contemporary web applications are written so I picked up the book. It is a short book - only 124 pages. In the preface, the author sets the requirement of the reader but I think he underestimate what it takes to read the book. In my opinion, the reader is an experience software developer with a sound knowledge of JavaScript, jQuery, and HTML. If the reader hasn't read "the good parts", I would recommend her to do so before reading this book. Furthermore, the reader should not be afraid of the Linux command line. Today, most software developers are trained in object-oriented modeling and design, and the author does assume so. Through-out most of the book, the reader sees how to develop a simple TODO manager. As TODO managers generally work with dates, the book has a number of assuming dates. On page 21, one sees a task due 1st December 1012. The approach of the book is to begin by the basic elements and gradually move to more advanced components. If the book has been much longer, I believe that many readers will be lost by this approach. To be fair, a complete example is introduced in the beginning of the book but explanations are coming in later chapters, the reader is left a bit frustrated. Chapter 2 and 3 are about topics which are invisible to the user of an application: documentation and testing. I agree with the author that these topics are important but I would have preferred them later in the book. Chapter 4 is about how to organize an application. It seems strange that large portion of the example code is commented out on page 51. Moreover, some of the plugins are discussed so briefly that the reader has no clue if there are useful or when to use them. One of the toughest part of a JavaScript application is to load the required libraries - and in the right order. In my dark past as front-end developer, I wrote a small library for loading libraries. Actually, it is just an excuse to write a graph class in JavaScript. Chapter 5 shows how to do load depending library using JavaScriptMVC. Unfortunately, the author does not explain in details how it works, and the examples are so simple that they have limited value. I like that the author introduces a complex framework like JavaScriptMVC is a very short book. But I was at times a little confused: does the author only show me the simple solution or best practises? If the publisher has asked for more pages, the author might have had a chance to get deeper into the subject. You can find the book here.

Map/Reduce and GNU Parallel

Map/Reduce and GNU Parallel

This week I attended a meeting organized by DKUUG.The topic was GNU Parallel and the speaker was Ole Tange - the developer behind GNU Parallel.

To be honest, I have not used GNU Parallel before. Of course, I have heard about it as Ole always talks about the program when I meet him. His introduction to the program was great - enjoy it when DKUUG releases the video.

Simply put, GNU Parallel is able to run tasks in parallel. It can either be running locally or remotely. In order words, GNU Parallel can help you to transform your command-line into a parallel computational engine.

Lately, I have been studying Apache Hadoop. Currently, Hadoop is probably the most popular implementation of the programming paradigm Map/Reduce. GNU Parallel offers a way of specifying the Map component. It is activated by using the --pipe option. On my way home I was thinking on how to implement a simply Map/Reduce based analysis using GNU Parallel.

I have used the On Time Performance data set more than once. It is a good data set as it is highly regular and it is large (5-600,000 rows every month). The data set records every flight within USA, and you can find information about destination airport, delays, and 120 other data points. 6 months of data will result in a 1.3 GB (comma separated value) file.

A simple analysis of the data set is to generate a table of the number of time an airport is used by a flight. The three-letter airport code is unique e.g., LAX is Los Angeles International Airport. It is possible do the analysis in parallel by breaking the data file into smaller parts. This is the map task. Each task will produce a table, and the reduce task will combine the output for each map task into the final table.

In order to use GNU Parallel as driver for Map/Reduce, I have implemented the mapper and reduce in Perl. The mapper is:

#!/usr/bin/perl -w

use strict;

my %dests;
while (<>) {
    my @data = split /,/;
    my $airport = $data[14];
    $dests{$airport} = 0 if (not exists $dests{$airport});
    $dests{$airport}++
}

foreach my $airport (keys %dests) {
    printf "$airport $dests{$airport}\n";
}

The reducer is also simple:

#!/usr/bin/perl -w

use strict;

my %dests;
while (<>) {
    chomp;
    my ($airport, $count) = split / /;
    $dests{$airport} = 0 if (not exists $dests{$airport});
    $dests{$airport} += $count;
}

my $total = 0;
foreach my $airport (sort keys %dests) {
    $total += $dests{$airport};
    print "$airport $dests{$airport}\n";
}
print "Total: $total\n";

It is possible to run the Map/Reduce analysis by the command-line:

cat On_Time_Performance_1H2012.csv | parallel --pipe --blocksize 64M ./map.pl | ./reduce.pl

The input file is broken down into 64 MB chunks. GNU Parallel is line oriented so a chunk will not be exactly 64 MB but close. My laptop has four cores, and they are fully utilized.

It seems to me that GNU Parallel offers a simple approach to Map/Reduce for people living much of their life on a command-line.

GotoCon 2012

GotoCon 2012 in Århus

I attended GotoCon 2012 in Århus last week. To be more precise, I attended the Big Data track Monday. My educational background is somewhat related to supercomputing (yeah, I did my share of Fortran-77 programming as a graduate student), and I have over the years worked on various "Big Data" project: bioinformatics, credit card fraud detection, building Linux clusters, etc. Currently, I work for a small NoSQL database vendor, and our solution could fit the Big Data quite nicely. Given all this, going to Århus and spend a day listening to the open source Big Data vendors sounded like a treat.

Neo4j - Jim Webber

First speaker was Jim Webber from Neo4j. Neo4j is a graph database, and I like graph theory a lot. Jim is not just a speaker - he is an entertainer. He began his talk by looking back on the database history. As you might be aware of, relational databases were developed in 1970s, and through the 1980s, Oracle became The Database. In the last decade, a number of companies has gone "google scale" that is, they have vast amount of data. Handling big data requires different data models than relational databases.
Jim pointed out that the complexity of an application is a function of data size, connectness, and uniformity. Of course, his graph database can help you if your data is highly connected. He demonstrated a number of data sets and how to query them using Neo4j.

Couchbase - Chris Andersen

Chris noted that the database industry is changing rapidly these years. Companies are required to shrink and grow databases on demand. In particular in the mobile app world where an app can go virtal over night. As an example, he mentioned Instagram who gained about one million new users on one day when they released their Android app.
He boils down the requirements to:

• grow and shrink databases on demand
• easy cluster node deployment
• multiple masters in the cluster (for availability)
• multiple datacenters (for availability)
• auto sharding

The old-school approach to scalability of the data layer is to sharded MySQL instances and memcached. But this approach typically requires some high availability handling in the application code. With Couchbase (and probably other NoSQL databases), the applications are free of this complexity.

Couchbase has conducted a survey among NoSQL users, and the flexible schemas are reported as the most important feature.

Cassandra - Matthew Dennis

Matthew began his talk by discussing the relevance of Big Data. According to studies, companies using Big Data products and techniques seem to be out perform companies not using Big Data. Cassandra is offering a master-free cluster database, and it scales well. When data sets are larger than physical memory, it slows down gracefully. A personal note: data sets smaller than physical memory are not big data.
According to Matthew Solid State Disks (SSD) are pushing the limit as they lower the latency. Cassandra is SSD aware: it does not overwrite data but only append data. Files (probably, its blocks) are reclaimed by the database when they are not used any more. Latency is important for Matthew, and he argues that linear scalability means that latency is constant when:

• increasing throughput and increasing number of nodes
• increasing load and increasing nodes

The nodes in a Cassandra cluster are equal, and queries are proxies from node to node. This implies that Cassandra is eventually consistent.

MongoDB - Alvin Richards

Last speaker in the track was about MongoDB. Alvin talked about scaling up without spending (too much) money and that is where the NoSQL revolution fits in. In the last 40 years, we have seen a dramatic growth in computing power for example, memory has increased from 1 Kb to 4 GB, and disk space has gone from 100 MB to 3 TB.
For MongoDB, availability is some important than consistency. Together with the CAP theorem, this gives some consequences for the architectural choices for MongoDB. The asynchronous replication within a MongoDB cluster implies that MongoDB is eventually consistent.
Storing and analyzing time series is an important use case for NoSQL.

Panel discussion

The organizers has arrange a panel discussion with the major NoSQL vendors - and Martin Fowler. Martin has just published a book about NoSQL. I have read it - and I will return with a review in the near future.
Martin noted that NoSQL is still inmature. But the good news is that NoSQL brings us past "one model fits all". It is worth noticing that most NoSQL databases are released under an open source license - and backed by companies.
The panellists agreed that the CAP theorem and the application should drive which database to choose. The major issue here is that the majority of software developers only read 1 computer science book per year.

Playing with TypeScript

Taking TypeScript out for a spin

Microsoft announced a new programming language by the name TypeScript this week. The driving philosophy behind the language is to extend JavaScript. Since I have done my shared of JavaScript programming - and given talks,taught classes, and written articles and a book on the topic - I decided to take TypeScript out for a spin.
The language comes with a specification (97 pages) and a compiler. The compiler is compiling TypeScript to JavaScript. In this way, Microsoft can support virtually any platform in the world. The big trend at the moment is that JavaScript is used as a server-side programming language - node.js is popular. In my day-work, I have recently worked on an extension (in C++) for node.js for employer's database.

Open Source

One of the interesting developments of TypeScript is that Microsoft has released everything as free or open source software. According to Microsoft, they are an operating systems company and not focusing on development tools. Today, developers are used to open source software, and in order to succeed within the developer community, you are forced to released under these terms.
The TypeScript compiler has a command-line interface. Basically, it is simply a node.js application. I have tested the compiler on my laptop which is currently running Fedora 17.
As an Emacs user, I am happy to see that Microsoft has released a TypeScript mode for Emacs. It is a simple mode as it primarily does syntax highlightning and indention. I have briefly looked at the elisp source code, and it seems to pretty well organized. If TypeScript becomes popular, I do hope that we will see a more advanced mode like js2.

Classes and strongly typing

As you might know, JavaScript is an object-oriented programming language. But is does not have classes. Over the years, various techniques for encapsulating data and emulating classes have been developed. For example, you can use a function as constructor. TypeScript introduces classes, and it is possible to inherit from a class. This implies that common design patterns can probably be implemented easily in TypeScript.
JavaScript is a dynamical typed languages, and TypeScript brings strongly typing to JavaScript. You must declare variables - with associated types. It is possible for the TypeScript compiler to infer types in many cases, and an any type gives you the flexibility of weak typing.

An example

I am fond of graph theory, and I have written a simple graph class in TypeScript.I implemented typological sorting in JavaScript a few years ago as a non-trivial example for a course I was teaching.
The TypeScript example uses two classes. The MyNode class is actually just a convenient way to store collection of data items. For a C programmer, it is just a struct. The Graph class is somewhat longer. As you can see, a TypeScript class has attributes, a constructor and methods. It is different from JavaScript where you do not have classes and objects do not have methods (but properties can be anonymous functions).

class MyNode {
    id: string;
    visited: bool;
    edges: number[];
    payload: string;

    constructor(id : string, payload : string) {
        this.id = id;
        this.payload = payload;
        this.visited = false;
        this.edges = [];
    }
};
   

class Graph {
    name: string;
    nodes: MyNode[];
   
    constructor(name : string) {
        this.name = name;
        this.nodes = [];
    }

    find_node(id : string) : number {
        var i;
        var found;

        if (this.nodes.length == 0) {
            return -1;
        }

        i = 0;
        found = false;
        while (i<this.nodes.length) {
            if (this.nodes[i].id == id) {
                found = true;
            }
            if (found) {
                break;
            }
            i++;
        }
        if (found) {
            return i;
        } else {
            return -1;
        }
    }

    // add nodes - id is a unique string for identification
    add_node(id : string, payload : string) {
        if (this.find_node(id) < 0) {
            var edges = [];
            var n = new MyNode(id, payload);
            this.nodes.push(n);
        }
    }

    // add edge - work well for DAGs
    // if you don't work with DAGs, then use
    // add_edge(i, j) ; add_edge(j, i);
    add_edge(src : string, dst : string) {
        var n;
        var i = this.find_node(src);
        var j = this.find_node(dst);
        if (i>=0 && j>=0) {
            n = this.nodes[i].edges.push(j);
        }
    }

    // topological sorting - return array of IDs
    // see http://en.wikipedia.org/wiki/Topological_sort
    // (alternative algorithm)
    sort() : number[] {
        var i, j, m;
        var L = [], Lid = [];
        var that = this;

        for (i in this.nodes) {
            this.nodes[i].visited = false;
        }

        function _visit(n) {
            var j;
            if (!that.nodes[n].visited) {
                that.nodes[n].visited = true;
                for (j in that.nodes[n].edges) {
                    m = that.nodes[n].edges[j];
                    _visit(m);
                }
                L.push(n);
            }
        }
        for (i in this.nodes) {
            _visit(i);
        }

        for (i in L) {
            j = L[i];
            Lid.push(this.nodes[j].id);
        }
        return Lid;
    }
}

// Test case
var g = new Graph("Software");
g.add_node('Emacs', '23.1');
g.add_node('GTK',   '2.18.3');
g.add_node('Cairo', '1.8.8');
g.add_node('glib',  '2.22.3');
g.add_node('libc',  '2.10.1');
g.add_edge('Emacs', 'libc');
g.add_edge('Emacs', 'GTK');
g.add_edge('GTK',   'glib');
g.add_edge('GTK',   'Cairo');
g.add_edge('Cairo', 'libc');
g.add_edge('glib',  'libc');
var list = g.sort();
console.log('Topological sort: '+list.join('->'));


The TypeScript language is an interesting development as it offers (web) programmers a more mainstream approach. To be honest, when I have been teaching JavaScript for seasoned programmers, they have often been puzzled by the odd object system behind JavaScript. The scope rules of JavaScript are always regarded as being odd. I have not yet examined rules in TypeScript, but I hope to return to the topic in the near future.

Open Source Days 2012

I'm going to the Open Source Days 2012 conference this weekend. This year's program is really interesting, and I'm looking forward to spend two days listening to geeky talks. The organizers have ask me to take the role as chairman. Saturday I will chair the session of web programming, but I'm not sure about Sunday.

Actually, for me the conference began yesterday. I gave a full day course on JavaScript programming. It was really great to explains the language in details for a group of experience software developers. You can find my slides at slide share.

Morse codes and Arduino

My son Svante came home Friday and told me that he had been working on Morse codes in science class. We talked a bit on how to translate sentences to Morse code. Yesterday evening I had to construct a translator using my Arduino board, a LED and a LCD display. The program is pretty simple. It processes the message - letter by letter - and shows the current letter in capital and the Morse code on the second line. Moreover, it blinks the Morse code using the LED. You find my program below.

#include <stdio.h>
#include <stdlib.h>
#include <LiquidCrystal.h>

int LED  = 9;
LiquidCrystal lcd(10, 11, 12, 13, 14, 15, 16);
char msg[] = "super seje mig";
char m[16];
char *morse[] = {
  "*-",       // A
  "-***",     // B
  "-*-*",     // C
  "*--",      // D
  "*",        // E
  "**-*",     // F
  "--*",      // G
  "****",     // H
  "**",       // I
  "*---",     // J
  "-*-",      // K
  "*-**",     // L
  "--",       // M
  "-*",       // N
  "---",      // O
  "*--*",     // P
  "--*-",     // Q
  "*-*",      // R
  "***",      // S
  "-",        // T
  "**-",      // U
  "***-",     // V
  "*--",      // W
  "-**-",     // X
  "-*--",     // Y
  "--**"      // Z
};
void setup() {
  lcd.begin(16, 2);
  lcd.clear();
  lcd.setCursor(0, 0);
  lcd.print("Booting");
  for(int i=0; i<16; i++) {
    lcd.setCursor(i, 1);
    lcd.write('.');
    delay(100);
  }
  lcd.clear();
  lcd.setCursor(0, 0);
  lcd.print("K. Geisshirt");
  lcd.setCursor(0, 1);
  lcd.print("Copyright 2012");
  delay(1000);
  pinMode(LED, OUTPUT);
}

void loop() {
  for(int i=0; i<strlen(msg); i++) {
    for(int j=0; j<strlen(msg); j++) m[j] = msg[j];
    m[strlen(msg)] ='\0';
    if (m[i] != ' ') m[i] = m[i]+('A'-'a');
    lcd.clear();
    lcd.setCursor(0, 0);
    lcd.print(m);
    lcd.setCursor(0, 1);
    if (m[i] != ' ') {
      lcd.print(morse[m[i]-'A']);
      for(int j=0; j<strlen(morse[m[i]-'A']); j++) {
        digitalWrite(LED, HIGH);
        if (morse[m[i]-'A'][j] == '*') {
          delay(500);
        } else {
          delay(1000);
        }
        digitalWrite(LED, LOW);
        delay(250);
      }
    }
    if (m[i] != ' ') {  
      delay(1000);
    } else {
      delay(100);
    }
  }
}

If you haven't tried an Arduino board, it is highly recommended. With an electronic brick and a few components, it is much like LEGO for adults.

Edit: I have added a video.

GNOME 3

GNOME 3 - a review

After the arrivel of GNOME 3 and Unity, we have seen months of discussion on the future of the free desktops. Both GNOME 3 and Unity have been considered as a step backward. Many old-school Linux users believe that these new offerings are worse than the good well-documented desktops like GNOME 2 and XFCE.

Over the years I have used many different desktop environments and window managers. GNOME 2 (both for Debian GNU/Linux and Ubuntu Linux) has served me well. A couple of weeks ago, I decided to try out GNOME 3. And to jump to the conclusion - GNOME 3 is different!

In my test of GNOME 3, I use my four years old Dell XPS 1330M laptop. With an Intel Core2 Duo (2 GHz), 4 GB memory and Intel graphics, it is not a speed devil. But it is a small laptop, and I can carry it around (I'm usually on bike) easily. I have upgraded the battery to a 9-cell battery, and that gives me enough power to work for long period without plugging it to the wall. The operating system is Arch Linux (64 bit).

Is the difference between GNOME 2 (old-school desktop) and GNOME 3 a good thing? Yes, I like it. I like that the panel is so small - yeah, I know it's not a panel. And I the activity concept. I use the same 5 applications (browser, editor, terminal, word processor, and photo manager) so adding them to the activity panel is pretty nice. It took a couple of days to get use to the virtual desktops. In many years I have visualized my virtual desktops horisontal (and used Ctrl-Alt-Left/Right to move between them). Now, they are vertically organized (Ctrl-Alt-Down/Up). One thing I like is that the number of virtual desktops are changed dynamically as I move between them and starting and stopping applications.

The idea that you must use the Alt key together with the top-right menu is new to me. Luckily, a friend showed me after a week that I can power down my laptop as the menu changes when I press Alt. For one week I logged out and powered down. Knowing that the meta keys (Alt, Windows, etc.) is used throughout the GNOME Shell, makes me a bit more productive - or probably closer to my GNOME 2 productivity. I can only recommend that you read the user's manual to GNOME 3 and the GNOME Shell when you start using GNOME 3 for the first time.

One of the most critized parts of GNOME 3 has been that it is not possible to customize the desktop. Strangely, I have not encountered many problems with this. Maybe the default values are just right for me. Of course I have changed a few things, but I have not wished to customized an item and haven't been able to find it.

The network manager has been upgraded, and this is the place where I think it is a downgrade. The VPN dialogs do not allow to import configuration files. Typically your network administrator will send you the configuration in some sort of file (each VPN implementation has it own format). I can manually type in the information, but it was much nicer in previous versions where I could import it.

The default applications in GNOME 3 are fine with me. I have only changed two applications: Firefox as browser, and Emacs as editor. The GNOME Editor (gedit) is not powerful enough for a full time software developer like me (working in 3-4 programming languages at the same time).

GNOME 3 introduces a concept of online accounts. The idea is that you register your accounts on place and all application can use the information. Currently, only Google accounts are supported, but it is really nice that Evolution, Empathy and GNOME Shell calendar take advantage of it. I hope that Twitter, Facebook, LinkedIn and other web services soon will be supported.

For almost three weeks I have been using GNOME 3, and I must say I am impressed. The GNOME developers have really tried to rethink the free software desktop - and they have produced a cool desktop!

Free chemistry software - quantum chemistry

Free chemistry software - quantum chemistry

In the previous part of the journey into free chemistry software I wrote about molecular mechanics. The molecular mechanics view of a molecular system is a classical mechanical view i.e., the atoms move according to Newton's law.

Quantum mechanics revolutionized the view of the atomic world. The Schrödinger equation is a general model and number of parameters is limited. Solving a Schrödinger equation for an atomic or molecular system is often referred to an ab initio calculation. The word ab initio is latin and can be translated to from the beginning or  from first principles.

The Schrödinger equaiton - in particular the time-independent equation - can be used to calculate many different properties of chemical substances. Properties like enthalpy and entropy, and heat capacity can calculated as the partition function can be calculated from the solution. Moreover, it is possible to predict data for various spectra (IR, Raman, UV-VIS, etc.). The problem is that it is not possible to find an analytical solution for any non-trivial cases. The solutions to the equation are called wave functions. The Copenhagen interpretation of quantum mechanics is that the wave function represents the probably distribution (in space) of the electron.

In order to solve the (time independent) Schrödinger equation you must make two important approximations. The first approximation is that the nucleus of the atom is fixed in space, and the Schrödinger equation is reduced to only model the electrons. This approximation is called the Born-Oppenheimer approximation. The rationale behind the approximation is that the nucleus of an atom is much heavier that the electrons, and the nucleus moves much slower (this is probably a classical mechanical picture). The second approximation is that the wave function is a sum - or linear combination - of other functions. These functions form a basis set. The basis set is often atom orbitals (solution to the Schrödinger equation for a single atom), and they are often selected in much a manner that they require so few CPU cycles to process as possible. A popular family of basis set is the Slater-type orbitals.

There are many quantum chemistry packages in the world. From a license perspective, they fall in three groups. The first group is completely proprietary software. You buy the package (maybe the source code is included so you can compile it yourself) and can use it for the set of computers, you have bought a license for. It is not rare to find special pricing schemes for users in the academic world. Gaussian is a leading software vendor in this field, and a site licence (with UNIX source code) for commercial use is listed as roughly 40,000 USD. This might sound like a high price tag but you must remember that the development of a new drug can easily run in billions. Compared to that, the software is quite cheap - if you are in big pharma. Gaussian does provided must more that just a quantum chemistry calculation engine - it includes various supporting utilities. The group of free software packages is another group with a completely different licensing model. A typical example is MPQC (Massive Parallel Quantum Chemistry). Released under GNU General Public License it is a truly free software package. The motivation of the developers is to test new algorithm - in particular for the parallellization for using either compute clusters or multicore computers. Somewhere in between you find the third group. Software packages in this group are free to download (if you are in academia or using it for personal purposes) but you are allowed to redistribute the source code or binary. And often you must include a citation to a particular scientific paper if you publish any results based on the software. In this group you find packages like GAMESS (both US and UK versions). 

Gabedit
The program gabedit provides a uniform interface to many quantum chemistry packages including GAMESS-US, GAMESS-UK, Gaussian and MPQC. The program exists as a binary package for most Linux distributions including Ubuntu Linux and Debian GNU/Linux which makes the installation quite simple.

1,3,7-trimethylxanthine is a known (legal) psycho-active chemical. It is found naturally in coffee, tea, and soft drinks. The trivial (non systematic) name is cafferine. It is a small molecule with an aromatic ring structure.

Setting up a calculation in Gabedit

You can either draw your molecule or load a file. The structure of many molecules can be found at PubChem or similar services. A 3-dimensional structure of Cafferine can be found at PubChem. A 3-dimensional structure is nothing more that the coordinates of the nuclei of the atoms in the molecule. Using OpenBabel (discussed in previous blog entries), you can convert the PubChem files format to something that Gabedit can understand.

Setting up a calculation is simple but you are required to know and understand all the parameters and methods. For a causal user of quantum chemistry software, Gabedit might help you to allow to write configuration files manually, but the program is a thin wrapper only.

Monitoring a calculation

Once you have edited the calculation paramters, you are ready to go. It is possible to monitor the progress of your simulation but beware that quantum chemistry calculation might take hours. Gabedit will use the good old UNIX trick called nohup so you can come back later. Moreover, Gabedit let you perform the calculation on remote machines. This is useful for long calculations.

When the calculation has finished, Gabedit can assist you in analyzing the result. It is only a limited number of analyses offered, and if you need more advanced analysis, you will probably write small scripts and programs to help you.

Analyzing the result of a geometry optimization using Gabedit

The really good thing about Gabedit is that it provides a uniform interface to the most common quantum chemistry packages.

Other software packages exists e.g., Ghemical. Ghemical is fairly tight bound to GNOME, and tries to solve all needs for computational chemistry in one packages. The latest version of Ghemical is recent (October 2011).


MPQC
MPQC is a pure free software project which provides an ab initio package. It is designed to run in multicore or cluster environments i.e., in massive parallel environment. Ubuntu and Debian packages exists. Currently, two packages exist: the core program and supporting utilities. Even an Emacs mode can be found for editing the configuration files. The main mode of operation is that the user writes a configuration or input file and run the program from the command-line or through a batch system. The OpenBabel conversion utility supports MPQC and can write raw input files from structure file formats. This simplifies the usage a lot in the learning period.

In order to test MPQC, I have prepared an input file using Caffeine. As MPQC supports the calculation of thermodynamics properties (non-electronic enthalpy and entropy), my test input file will perform this analysis after the geometry optimization using the STO-6G basis set and a Hartree-Fock method. The Hartree-Fock method is only calculating the ground level state, and the thermodynamics will be somewhat inaccurate.

MPQC/Linux Speed-up

As MPQC is a parallel calculation program, it is worth analyzing the speed-up i.e., how well does scale as the number of core/CPUs increases. MPQC is parallellized using either MPI, SysV shared memory and Posix threads.

Running on multiple cores is simple with MPQC. You can specify the number of threads on the command-line. For a 4-thread calculation, the command-line is: mpqc -threadgrp "<PthreadThreadGrp>:(num_threads = 4) -o caffeine.out caffeine.in where caffeine.in is the input file and the output is found in caffeine.out.
As I have access to a hyperthreaded quad-core computer, I have tested the Posix thread parallellization (please remember that Linux has a highly optimized Posix thread implementation).

The result of my simple benchmark shows that hyperthreading is not a good idea in heavy computing environment - notice that the speed-up levels off at four cores. The reason is probably that the threads are competing for a limited resource: the floating-point units. A calculation of the Caffeine molecule took about 8 hours using 4 Posix threads, and this only calculated the ground state using the STO-6G basis set.

Summary
In general it is possible to carry out quantum chemistry calculation using free software if you can live without a fancy user interface. If you do many calculations, you might be happy to know that you can modify and extend the source code. For a causal computational chemist (maybe an organic chemist predicting spectras), free chemistry software might not be the solution yet.

Saved by Dropbox

Saved by Dropbox


I have installed Dropbox on my laptops and my phone. On my laptops I use it for two purposes: synchronization and backup. Initially, I used it for synchronization of my private and my work laptop (both computers are running Linux).

The laptop at work is a bit unstable. It crashes probably 3-4 times a week, and I believe it has something to do with the temperature of the processor. It happened to me the other way, and an OpenOffice document was left in a state where the file did not contain anything else that zeroes.

Luckily, Dropbox keeps track on my revisions of the files. That means that I was able to go one revision back and recover much of my file (probably lost half a page). Needless to say, I'm pretty happy with the Dropbox service now!

Emacsforum 2011

Emacsforum 2011
Peter Toft and I are in the process of preparing Emacsforum 2011 with some help by Troels Henriksen (at DIKU) and Keld Simonsen (from KLID). The program is almost ready for publication, so I will not say too much - but there will be something for scientists and developers. Even our Evil Twin will be represented.

The mini-conference takes place 12th November 2011 at DIKU. The is no conference fee - and there will be no benifits.

If you are using Emacs (and even XEmacs) and live in the Copenhagen area, Emacsforum is a good place to meet fellow users.

Free chemistry software - molecular modeling

Molecular modeling is a very large and important field of chemistry. As computers have increased in raw computing power, the usage of computers to calculate molecular properties is not a specialized fields for the few. Today, every chemist can perform calculation for even large molecules.


Roughly speaking, you can divide the calculations in two separate groups: molecular mechanics and quantum chemistry. The first is based on classical mechanics, while the second group uses quantum mechanics as a underlaying model and equations. The software list at http://en.wikipedia.org/wiki/Molecular_modeling shows a wide range of offerings. Many of them are commercial and closed-source solutions.

Molecular mechanics calculations are used when no chemistry is going to. By definition, chemistry is the rearrangement of atoms - and that involves electrons. But molecular mechanics can be used to investigate how a molecule is solvent that is, how its structure changing when it is surrounded by a solvent like water.

Gromacs is one of the oldest and most successful molecular mechanics software suites. It is covered by the GNU General Public License (version 2), and most distributions like Debian GNU/Linux have a package of it. It does not come with a fancy user interface, and the user primarily interacts with Gromacs at the command line. It is a big advantage as some of the operations can take a long time. Seldomly, you sit by your computer and work with Gromacs. The typical usage is to write small shell scripts and run them as batch jobs.

Today, most supercomputers in the chemical industry and academia are Linux clusters which are build from commodity hardware. That means that a supercomputer is a distributed system where the individual processors are loosely coupled using Ethernet (or maybe InfiniBand). The MPI  framework is used by Gromacs to utilize such a supercomputer (if you have a SMP system, MPI can still be used for parallellization). Queuing systems (SUN Grid Engine, OpenPBS/Torque, etc.) schedule which batch job to execute, and the command-line nature of Gromacs comes to its rights on such systems.

Explaining all details of Gromacs is not the scope here. But let us a quick tour on how to use some of the many utilities and programs of Gromacs. The assignment is to take the experimentally determined structure a small biological active molecule and create a solvated version of the molecule. The structure found at the Protein DataBank is for a crystal, and IGF-1 (as most other molecules in your body) is in a solution where water is the solvent (remember, 60 % of you body is water). For the tour, the Insulin-like growth factor 1 (IGF-1) is chosen. IGF-1 is a small protein (or peptide) which is involved of the growth and regeneration of your body. You can download a file with the experimental structure from Protein DataBank.

First, you must pre-process the downloaded file into files used by Gromacs. In that process you decided the force field. The force field is the parametrization of the interaction between the atoms, and all calculations in Gromacs (and any other molecular mechanical program) are based on Newton's second law. In the command-line below, two files are generated (2GF1.gro and 2GF1.top).

pdb2gmx -f 2GF1.pdb -o 2GF1.gro -p 2GF1.top -ignh -ff G53a6

Now you have to edit the output file (2GF1.gro) in order to change box size. You can do an energy minimization and generate a solvation box using the commands (some steps might take some time):

mdrun -v -deffnm 2GF1-EM-vacuum -c 2GF1-EM-vacuum.gro

editconf -f 2GF1-EM-vacuum.gro -o 2GF1-PBC.gro -bt dodecahedron -d 1.2

genbox -cp 2GF1-PBC.gro -cs spc216.gro -p 2GF1.top -o 2GF1-water.gro

The final file is 2GF1-water.gro which is the biological molecule solvated in water. It might not sound as a great deal, but the file can be used in further simulation involving the solvated molecule.

Other molecular modeling packages exists. NAMD is a highly scalable molecular dynamics program. It is aimed at large molecules (proteins) and can utilize very large parallel computers. But NAMD is not free software as defined by Free Software Foundation. You can download it and use it for any non-commercial purpose.

Free chemistry software - utilities

One of the major annoyances as chemists in front of computer is faced with is the vast number of file formats. The good news is that most file formats are text files so it is possible to reverse engineer them by looking at a number of examples. One open source project called OpenBabel tries to help chemists in converting between the formats (currently OpenBabel supports 113 file formats related to chemistry). Most Linux distributions have packages for OpenBabel, including Debian GNU/Linux (it's a version from 2009 you find in Debian stable). Converting a molecular structure of caffeine from one file format (SDF) to another (PDB) is simply done by the following command:babel -isdf caffeine.sdf -opdb caffeine.pdb

You can find many small molecules - with 3D structures, physical properties and toxicology data - at PubChem. For larger molecules (proteins mainly), you can go to the Protein Data Bank. The file for caffeine as used above can be found at PubChem.

OpenBabel project also includes a number of other utilities including a chemist's version of grep called obgrep (searching for molecules with a particular substructure within a database) and simple program to (energy) minimize a molecule called obminimize.

GNOME Chemistry Utils is a set of utilities developed for GNOME users. The set includes a calculator (for calculating the molecular mass of a molecule), the periodic table of the elements, and a spectrum viewer. The periodic table of the elements can give you the physical and chemical properties of all elements. Most chemists have a periodic table of elements close when working,

and having one on your desktop seems as a good idea.

Chemists do a lot of drawing: they draw structures of molecules. In can be regarded as a generic representation of a molecules 3-dimensional structure using a 2D paper. Understanding and drawing such chemical structures are an integral part of any chemist's education and chemists have used these drawing for more than 150 years (the discovery of the electron and the development of quantum mechanics changed the view of molecular structures). The 3-dimensional geometry is an important factor for determine the properties (reactivity, toxicology, color, etc.) of a molecule.

A drawing program for chemists is not hard to image. When it comes to free software, we are so

lucky that we have more than one. GNOME users can use the molecular drawing program from the GNOME Chem

istry Utils project. It is called GChemPaint. As GChemPaint can only load a rather small number of file formats, you really learn to use OpenBabel rather quickly. It is an easy program to work with, and it is possible to save your drawing in most used image formats (both bitmap and vector formats). You can then easily insert your drawing

in your favorite word processing software prior to publication (take publication rather broad: everything from a high-school report to a paper in Nature).

As already said, drawing programs for chemists are not hard to imagine. Other projects in this area include titles likes bkchem, chemtool, easychem, xdrawchem, jchempaint, molsKetch (probably stalled).

Free chemistry software - Introduction

The year of 2011 has been declared the International Year of Chemistry by UNESCO (United Nations Educational, Scientific and Cultural Organization) and IUPAC (International Union of Pure and Applied Chemistry). The purpose of devoting a full year to chemistry is to spread the notion that chemistry is important for our daily life.

In this series of blog post I have examine the state of free software in chemistry. This first post is an outline of the usage of computers in chemistry.

It is hard to imagine modern life without the discoveries and developments done by chemists and chemical engineers over the last two or three centuries. Plastic, gasoline, and pharmaceuticals are products from the chemical industry. And forensic scientists use many chemical analysis in order to provide evidence for police investigations all over the world. But chemistry is more that an applied science. It also give us an insight to how our world works. In the recent decade, the modern cuisine has changed. For example, the cheif Heston Blumenthal has been using chemistry to create new dishes (this branch of chemistry is called molecular gastronomy).

As you can see, chemistry is a broad science and engineering discipline. Modern chemistry is divided into a number of branches. Traditionally, an academic education of chemistry consists of courses in general, organic, inorganic, physical and even analytical chemistry. Chemistry is a wet science, and as a student you spend a lot of time in laboratories. Amongst chemists, it is still discussed whether chemistry is a descriptive science (classification of observations) or an exact science (explaining observations).

Chemistry interfaces most other sciences, including physics, mathematics, statistics and biology. Quantum chemistry applies quantum mechanics to calculate properties of chemical substances. But as you might imagine, the three-body problem is a serious show-stopper for a chemist as very few molecules have only three nucleus and electrons.

Computers are heavily used in chemistry. One example is to perform quantum chemistry calculation as finding an analytical solution for a many-body problem is impossible. A rough break-down of the usage of computers in chemistry consists of three major areas. Firstly, you have the end-user applications used by every chemist. The applications are domain-specific applications - the domain is as broad as chemistry. The second area is chemoinformatics. It is a fairly young area (a decade or two only). Chemoinformatics applies techniques from informatics to transform chemical data to knowledge and thereby improving the decision making process. The usage of specialized databases and search algorithms is an integral part of chemoinformatics. Any non-trivial chemical compound can be represented in a number of ways. Even a small molecule like styrene can be named in different ways depending on how you look at it. Chemoinformaticians have introduced a string representation for all chemical compounds called the simplified molecular input line entry specification (SMILES). The SMILES code for styrene is C=CC1=CC=CC=C1. Image to find all compounds in your database with a certain substructure. You cannot use a regular expression or an SQL query. As molecules can be regarded as graphs (atoms are connected by chemical bonds), searching in chemical databases is a variant of find subgraphs. This is the core of chemoinformatics.
The third area where computers are used in chemistry is to perform calculations and it is often refered to as computational chemistry. It is an old area - calculation and simulation of properties of chemical compounds and reaction have been carried out as long as computers have been available to scientists. The calculations either use a classical-mechanical approach or a quantum mechanical approach. In the first approach, electrons is neglected and a force-field between the atoms are applied. This is possible to simulate large molecules using this approach. But if you need to predict the energy levels, thermodynamical properties, and charge distribution of a molecule, you have to use a quantum mechanical approach. This involves solving the time-independent Schrödinger equation (or at least an approximation to the equation called the Born-Oppenheimer approximation).

It is important to understand that most chemists are not educated as programmers. On the other hand, using computational techniques can save chemical industries huge fortunes. Today, most pharmaceutical companies have specialized departments for performing chemical calculations and supporting an informatics infrastructure. These departments are small in terms of man-power compared to the company as a whole. As the market is small and the potential benefits huge (time-to-market and saving expensive laboratory time), vendors often ask for very high license-fees. Vendors like Schrödinger, Wavefunction and Gaussian, and OpenEye offer software packages for chemists. Sadly, free software is a minor player in chemistry but you can find free chemistry software for most needs.