This article is part of the article series "Vim Plugins You Should Know About."
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Vim Plugins, surround.vimThis is the seventh post in the article series "Vim Plugins You Should Know About". This time I am going to introduce you to a plugin called "ragtag.vim". A month ago it was still known as "allml.vim" but now it has been renamed to ragtag.vim.

The best parts of RagTag are mappings for editing HTML tags. It has a mapping for quickly closing open HTML tags, a mapping for quickly turning the typed word into a pair of open/close HTML tags, several mappings for inserting HTML doctype, linking to CSS stylesheets, loading JavaScript <script src="...">...</script> and it includes mappings for wrapping the typed text in a pair of <?php ... ?> tags for PHP, or <% ... %> for ASP or eRuby, and {% .. %} for Django.

RagTag is written by Tim Pope. He's the master of Vim plugin programming. I have already written about two of his plugins - surround.vim and repeat.vim and more articles about his plugins are coming!

Previous articles in the series.

Here are examples of using the RagTag plugin.

Quickly closing an open HTML tag.

Suppose you have typed <div> and you want to close it without typing the whole closing tag </div> yourself.

The quick way to do it with RagTag is to press CTRL+X /. This mapping automatically closes the last open HTML tag.

Extra tip: If you didn't have this plugin you could quickly close the tag by typing </ and pressing CTRL+X CTRL+O. The default Vim mapping CTRL+X CTRL+O guesses the item that may come after the cursor. In case of an open HTML tag it's the close tag.

Creating a pair of open/close HTML tags from a word.

Suppose you want to quickly create a pair of <div></div> and place the cursor between the two tags.

The quick way to do it with RagTag is to type div and press CTRL+X SPACE. This mapping takes the typed word and creates a pair of HTML tags, one closing tag and one open tag on the same line.

However, if you wish to create open/close tag pair separated by a newline, type CTRL+X ENTER.

Here is an example, if you just typed div and then press CTRL+X ENTER it will produce the following output:

<div>
|
</div>

| indicates the position of cursor.

Insert HTML doctype.

If you type CTRL+X ! RagTag will display a list of HTML doctypes to choose from. Defaults to HTML 4.01 Strict.

This mapping is not that useful, given that I already introduced snipmate.vim plugin for creating snippets. Using snipmate.vim you can create a snippet "h" that would insert the whole HTML structure, including doctype, html, body, title, meta tags, etc.

Link to a CSS stylesheet.

Typing CTRL+X @ inserts the snippet for linking to a CSS stylesheet.

<link rel="stylesheet" type="text/css" href="/stylesheets/|.css">

This is again not that useful, given that we have snipmate.vim.

The mapping is easy to remember because @ is used for importing in CSS.

Insert meta content-type tag.

Typing CTRL+X # inserts the HTML meta tag for document's content type and encoding.

<meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1">

The charset depends on document's charset. If it's utf-8, the mapping will set the charset to utf-8 in the meta tag.

Load JavaScript document.

Typing CTRL+X $ links to a JavaScript file.

<script type="text/javascript" src="/javascripts/|.js">

The mapping is easy to remember because $ is a valid char in identifiers in many languages.

Wrap the typed text in PHP, Django, eRuby template tags.

There are several different mappings for wrapping text in template tags. It's best to summarize them in the following table. The table assumes you had just typed "foo" and you are editing an eRuby document:

Mapping    Result
---------  -----------
CTRL+X =   foo<%= | %>
CTRL+X +   <%= foo| %>
CTRL+X -   foo<% | %>
CTRL+X _   <% foo| %>
CTRL+X '   foo<%# | %>
CTRL+X "   <%# foo| %>

What this table shows us is, for example, that if you have typed "foo" and press CTRL+X _, the plugin will wrap "foo" in <% %> tags and place the cursor after "foo".

Summary of all the RagTag mappings.

CTRL+X /       Close the last open HTML tag
CTRL+X SPACE   Create open/close HTML tags from the typed word
CTRL+X CR      The same as CTRL+X SPACE but puts a newspace in between
CTRL+X !       Insert HTML doctype
CTRL+X @       Insert CSS stylesheet
CTRL+X #       Insert meta content-type meta tag
CTRL+X $       Load JavaScript document

For the following mappings, suppose that
you have typed "foo".

Mapping        Result
---------      -----------
CTRL+X =       foo<%= | %>
CTRL+X +       <%= foo| %>
CTRL+X -       foo<% | %>
CTRL+X _       <% foo| %>
CTRL+X '       foo<%# | %>
CTRL+X "       <%# foo| %>

How to install ragtag.vim?

To get the latest version:

  • 1. Download ragtag.zip.
  • 2. Extract ragtag.zip to ~/.vim (on Unix/Linux) or ~\vimfiles (on Windows).
  • 3. Run :helptags ~/.vim/doc (on Unix/Linux) or :helptags ~\vimfiles\doc (on Windows) to rebuild the tags file (so that you can read help :help ragtag.)
  • 4. Restart Vim or source ragtag.vim by typing :so ~/.vim/plugin/ragtag.vim (on Unix/Linux) or :so ~\vimfiles\plugin\ragtag.vim

Have Fun!

Have fun closing those HTML tags and until next time!

I was reading Knuth's "Selected Papers on Computer Science" and in chapter 13 "The IBM 650: An Appreciation from the Field" he had included a photo of a young himself from 1958 at his first computer.

Young Donald Knuth from 1958 at an IBM 650 Computer
Young Donald Knuth, age 20, at his first IBM 650 computer in 1958.

Don Knuth's first computer, as the chapter's title suggests, was the IBM 650. At that time Knuth had a part-time job helping the statisticians at Case Institute of Technology to draw graphs and do keypunching. Soon a strange new machine was installed across the hall, that the student newspaper called a "giant brain". It was actually an IBM 650.

One afternoon someone at the institute explained some of the machine's internal code to a bunch of freshmen, including Knuth. It all sounded mysterious to him, but it seemed to make a bit of sense, so he got ahold of some manuals. His first chance to try the machine came a few weeks later, when one of the upperclassmen at the fraternity needed to know the five roots of a particular fifth degree equation. Knuth decided to compute the roots using the 650. This was his first program on the 650.

Later Knuth realized how lucky he was to have had such a good first encounter with computers. The polynomial problem was well matched to his mathematical knowledge and interests, and he had a chance for hands-on experience, pushing buttons on the machine and seeing it punch the cards containing the answers.

Knuth's first large program was a tic-tac-toe that learned to play by remembering the relative desirability or undesirability of each position that it had ever encountered. The hardest part, as Knuth writes, was figuring out how to keep one digit of memory for each possible configuration of the board. The machine had just 2000 words of memory, each 10 digits long, plus a sign bit.

Next Knuth proceeded to writing a program that would find prime factors. The idea was that a person could set up any 10-digit number in the console switched and start his program, which would punch the corresponding prime factors on a card and stop. Knuth spent several weeks on this problem, rewriting his program several times. The final program took 11 minutes to determine that the number 9999999967 was prime.

The next major Knuth's program was the improvement of SOAP (Symbolic Optimal Assembly Program) and SOAP II assembly languages. He wrote SOAP III and learned about "creeping featurism," where each of his friends would suggest different things they wanted in an assembler. The program used all 2000 words of memory. Knuth doesn't think he could have gotten by with only 1999 words, because he had spent considerable time finding every last bit of space by using terrible tricks, such as using a single instruction on a specific address that would cause 4 side effects.

Along the way Knuth wrote a lot fun programs. One of the competitions between the students was to do as much as possible with programs that would fit on a single punch card - which had room for only eight instructions. One of the unsolved problems was to take the 10-digit number on the console and to reverse its digits from left to right, then display the answer and stop; nobody could figure out how to do this on a signle card. But one day Knuth proudly marched up to the machine and made a demonstration: he read in a card, then dialled the number 0123456789 on the console, and started the machine. Sure enough, it stopped, displaying the number 9876543210. Everybody applauded. He didn't explain until later that his card would display the number 9876543210 regardless of what number appeared on the console switches. :)

But there is more to the story. One day the IBM 650 machine got an extra set of console switches, that were called register 8004 (top row of switches in the picture). It turned out that nine instructions on an extended 650 were sufficient to reverse the digits of a number, and the ninth instruction could be put into the switches. Therefore he was able to solve the problem without cheating.

Knuth was very close with IBM 650. One night he missed a date with his wife-to-be, because he was so engrossed in debugging that he had forgotten all about the time.

The 650 provided Knuth with solid instruction in the art of programming. It was directly related to the topics of the first two technical articles he ever submitted for publication. Therefore it's not surprising at all that he decided to dedicate The Art of Computer Programming books to the IBM 650 computer. "This series of books is affectionately dedicated to the Type 650 computer once installed at Case Institute of Technology, in remembrance of many pleasant evenings."

The End.

If you liked this story, you may want to get Knuth's book "Selected Papers on Computer Science". The collection focuses on Knuth's publications that are addressed primarily to a general audience than to specialists.

This article is part of the article series "MIT Linear Algebra."
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MIT Introduction to Linear AlgebraThis is the sixth post in an article series about MIT's course "Linear Algebra". In this post I will review lecture six on column spaces and null spaces of matrices. The lecture first reviews vector spaces and subspaces and then looks at the result of intersect and union of vector subspaces, and finds out when Ax=b and Ax=0 can be solved.

Here is a list of the previous posts in this article series:

Lecture 6: Column Space and Null Space

Lecture six starts with a reminder of what the vector space requirements are. If vectors v and w are in the space, then the result of adding them and multiplying them by a number stays in the space. In other words, all linear combinations of v and w stay in the space.

For example, the 3-dimensional space R3 is a vector space. You can take any two vectors in it, add them, and multiply them by a number and they will still be in the same R3 space.

Next, the lecture reminds subspaces. A subspace of some space is a set of vectors (including the 0 vector) that satisfies the same two requirements. If vectors v and w are in the subspace, then all linear combinations of v and w are in the subspace.

For example, some subspaces of R3 are:

  • Any plane P through the origin (0, 0, 0).
  • Any line L through the origin (0, 0, 0).

See the previous, lecture 5, on more examples of spaces on subspaces.

Now suppose we have two subspaces of R3 - plane P and line L. Is the union P∪L a subspace? No. Because if we take some vector in P and some vector in L and add them together, we go outside of P and L and that does not satisfy the requirements of a subspace.

What about intersection P∩L? Is P∩L a subspace? Yes. Because it's either the zero vector or L.

In general, given two subspaces S and T, union S∪T is a not a subspace and intersection S∩T is a subspace.

The lecture now turns to column spaces of matrices. The notation for a column space of a matrix A is C(A).

For example, given this matrix,

Matrix A

The column space C(A) is all the linear combination of the first (1, 2, 3, 4), the second (1, 1, 1, 1) and the third column (2, 3, 4, 5). That is, C(A) = { a·(1, 2, 3, 4) + b·(1, 1, 1, 1) + c·(2, 3, 4, 5) }. In general, the column space C(A) contains all the linear combinations of columns of A.

A thing to note here is that C(A) is a subspace of R4 because the vectors contain 4 components.

Now the key question, does C(A) fill the whole R4? No. Because there are only three columns (to fill the whole R4 we would need exactly 4 columns) and also because the third column (2, 3, 4, 5) is a sum of first column (1, 2, 3, 4) and second column (1, 1, 1, 1).

From this question follows another question, the most important question in the lecture - Does Ax=b have a solution for every right-hand side vector b? No. Because the columns are not linearly independent (the third can be expressed as first+second)! Therefore the column space C(A) is actually a two-dimensional subspace of R4.

Another important question arises - For which right-hand sides b can this system be solved? The answer is: Ax=b can be solved if and only if b is in the column space C(A)! It's because Ax is a combination of columns of A. If b is not in this combination, then there is simply no way we can express it as a combination.

That's why we are interested in column spaces of matrices. They show when can systems of equation Ax=b be solved.

Now the lecture turns to null spaces of matrices. The notation for a null space of a matrix A is N(A).

Let's keep the same matrix A:

Matrix A

The null space N(A) contains something completely different than C(N). N(A) contains all solutions x's that solve Ax=0. In this example, N(A) is a subspace of R3.

Let's find the null space of A. We need to find all x's that solve Ax=0. The first one, obviously, is x = (0, 0, 0). Another one is x = (1, 1, -1). In general all x's (c, c, -c) solve Ax=0. The vector (c, c, -c) can be rewritten as c·(1, 1, -1).

Note that the null space c·(1, 1, -1) is a line in R3.

The lecture ends with a proof that solutions x to Ax=0 always give a subspace. The first thing to show in the proof is that if x is a solution and x' is a solution, then their sum x + x' is a solution:

We need to show that if Ax=0 and Ax' = 0 then A(x + x') = 0. This is very simple. Matrix multiplication allows to separate A(x + x') into Ax + Ax' = 0. But Ax=0 and Ax'=0. Therefore 0 + 0 = 0.

The second thing to show is that if x is a solution, then c·x is a solution:

We need to show that if Ax=0 then A(c·x)=0. This is again very simple. Matrix multiplication allows to bring c from A(c·x) outside c·A(x) = c·0 = 0.

That's it. We have proven that solutions x to Ax=0 always form a subspace.

Here is the video of the sixth lecture:

Topics covered in lecture six:

  • [01:00] Vector space requirements.
  • [02:10] Example of spaces R3.
  • [02:40] Subspaces of spaces.
  • [03:00] A plane P is a subspace of R3.
  • [03:50] A line L is a subspace of R3.
  • [04:40] Union of P and L.
  • [07:30] Intersection of P and L.
  • [09:00] Intersection of two subspaces S and T.
  • [11:50] The column space C(A) of a matrix A.
  • [16:20] Does Ax=b have a solution for every b?
  • [19:45] Which b's allow Ax=b to be solved?
  • [23:50] Can solve Ax=b exactly when b is in C(A).
  • [28:50] The null space N(A) of a matrix A.
  • [37:00] Why is the null space a vector space?
  • [37:30] A proof that the null space is always a vector space.
  • [41:50] Do the solutions to Ax=b form a subspace?

Here are my notes of lecture six:

MIT Linear Algebra, Lecture 6: Column Space and Null Space
My notes of linear algebra lecture 6 on column space and null space.

Have fun with this lecture! The next post is going to be about general theory of solving equations Ax=0, pivot variables and special solutions.

PS. This course is taught from Introduction to Linear Algebra textbook. Get it here:

Y-CombinatorIn this post I'll derive the Y-combinator and explain all the steps taken. The key to understanding the Y-combinator is knowing precisely what it does. I am sure many people never understand Y-combinator because of this very reason, or because the introduction is too lengthy to comprehend. Therefore I'll give the shortest possible explanation of Y-combinator before I derive it so that you know what the end result should be.

The Y-combinator allows an anonymous function to call itself, that is, it allows anonymous function recursion. Since anonymous functions don't have names, they can't refer to themselves easily. The Y-combinator is a clever construct helps them to refer to themselves. That's it. That's all the Y-combinator does. Remember that.

I'll use the Scheme programming language to derive the Y-combinator. My derivation is based on the one in "The Little Schemer" book. I took the examples from the book, filled in the missing steps and explained the steps in more details.

Here it is.

Suppose we want to write the length function, which, given a list, returns the number of elements in it. It's really easy if we can give the function a name:

(define length
  (lambda (list)
    (cond
      ((null? list) 0)
      (else
        (add1 (length (cdr list)))))))

But now suppose that we can't give names - we can only use anonymous functions:

(lambda (list)
  (cond
    ((null? list) 0)
    (else
      (add1 (??? (cdr list)))))))

Suddenly there is no way this anonymous function can refer to itself. What do we put in ???? We can't refer to the name length anymore because it's an anonymous function, which doesn't have any name. One thing we can try is to put the function itself in the place of ???:

(lambda (list)
  (cond
    ((null? list) 0)
    (else
      (add1 (
             
  (lambda (list)                   ; the
    (cond                          ; 
      ((null? list) 0)             ; function
      (else                        ;
       (add1 (??? (cdr list))))))  ; itself
  
  (cdr list))))))

This is not much better, we are still left with ???. But there is a bright side to it, this function can determine lengths of lists with one element and no elements. Let's try inserting the same anonymous function in place of ??? again:

(lambda (list)
  (cond
    ((null? list) 0)
    (else
      (add1 (
  (lambda (list) 
    (cond 
      ((null? list) 0) 
      (else 
       (add1 (
    (lambda (list)
      (cond
        ((null? list) 0)
        (else
         (add1 (??? (cdr list))))))
    (cdr list))))))  
  (cdr list))))))

Now this function can determine lengths of lists with 0, 1 and 2 elements. If we continue this way, we can construct the length function for lists with a certain number of elements. But this is not what we want, we the real length function that works for lists with any number of elements.

As we all know, repeating code is not a good thing. Let's try to factor out the repetitions and rewrite the original anonymous function slightly. Instead of leaving ??? in the code, let's pass it to an anonymous function via an argument called length.

((lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list)))))))
 ???)

Notice that this code invokes the first lambda (length) function and passes it ??? as the length argument. This function in turn returns the original anonymous function:

(lambda (list)
  (cond
    ((null? list) 0)
    (else
     (add1 (??? (cdr list))))))

Now let's try constructing the previous two length functions that work for lists with a maximum of one and two elements. First the function for lists with a maximum of one element:

((lambda (f)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (f (cdr list)))))))
 ((lambda (g)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (g (cdr list)))))))
 ???))

Here ??? first gets passed to lambda (g), which returns the original anonymous function, which then gets passed to lambda (f), which in turn returns the function that works for lists with one element:

(lambda (list)
  (cond
    ((null? list) 0)
    (else
      (add1 (
  (lambda (list)
    (cond
      ((null? list) 0)
      (else
       (add1 (??? (cdr list))))))
  (cdr list))))))

Similarly, the following code returns a function that works for lists with a maximum of two elements:

((lambda (f)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (f (cdr list)))))))
 ((lambda (g)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (g (cdr list)))))))
 ((lambda (h)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (h (cdr list)))))))
 ???)))

Since the argument names f, g,h in (lambda (f) ...), (lambda (g) ...), (lambda (h) ...) are independent, we can rename all of them to length, to make it look more similar to the length function:

((lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list)))))))
 ((lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list)))))))
 ((lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list)))))))
 ???)))

We are still repeating code. The obvious thing we can do about it is create an anonymous function called mk-length (make length) that creates this code for us:

((lambda (mk-length)
   (mk-length ???))
 (lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list))))))))

This is pretty tricky. Observe how (lambda (mk-length) ...) gets the (lambda (length) ...) function passed as the mk-length argument, which in turn accepts ??? as an argument and returns our original anonymous function:

(lambda (list)
  (cond
    ((null? list) 0)
    (else
     (add1 (??? (cdr list))))))

Now let's try constructing length functions for lists of length one and two. For the list of length one, we just need to apply mk-length on itself:

((lambda (mk-length)
   (mk-length
     (mk-length ???)))
 (lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list))))))))

Let's go through this code. First (lambda (length) ...) gets passed to the lambda (mk-length) function as the mk-length argument. Then it applies the result of (mk-length ???) (which is the original anonymous function) to the mk-length. This produces our well known function that works on lists with one or none elements:

(lambda (list)
  (cond
    ((null? list) 0)
    (else
      (add1 (
  (lambda (list)
    (cond
      ((null? list) 0)
      (else
       (add1 (??? (cdr list))))))
  (cdr list))))))

Similarly, by adding another call to mk-length, we get the function that works for lists with two or less elements:

((lambda (mk-length)
   (mk-length
     (mk-length
       (mk-length ???)))
 (lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list))))))))

Now, since we don't know what ??? is, let's just call it mk-length and see what happens:

((lambda (mk-length)
   (mk-length mk-length))
 (lambda (length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (length (cdr list))))))))

Nothing bad actually happens, we still get the same original anonymous function, except in place of ??? we have the function:

(lambda (length)
  (lambda (list)
    (cond
      ((null? list) 0)
      (else
       (add1 (length (cdr list)))))))

Notice also that argument names mk-length and length in lambda (mk-length) and lambda (length) are independent. Therefore we can rename length to mk-length to remind that the first argument to mk-length is mk-length:

((lambda (mk-length)
   (mk-length mk-length))
 (lambda (mk-length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 (mk-length (cdr list))))))))

And now comes the key trick. We replace mk-length with a self-application (mk-length mk-length):

((lambda (mk-length)
   (mk-length mk-length))
 (lambda (mk-length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 ((mk-length mk-length) (cdr list))))))))

If you try this code out, you'll see that it returns the length of a list for any list. Here is an example of applying it to a list of 10 elements:

(((lambda (mk-length)
   (mk-length mk-length))
 (lambda (mk-length)
   (lambda (list)
     (cond
       ((null? list) 0)
       (else
        (add1 ((mk-length mk-length) (cdr list))))))))
 '(a b c d e f g h i j))

The function works because it keeps adding recursive uses by passing mk-length to itself, just as it is about to expire. This is not yet the Y-combinator, but we have successfully managed to recursively call an anonymous function. Now we need to massage the code a bit to separate the anonymous function from the self-applicative code.

The first step is to move the self-applicative code out as much as possible:

((lambda (mk-length)
   (mk-length mk-length))
 (lambda (mk-length)
   ((lambda (length)
      (lambda (list)
        (cond
          ((null? list) 0)
          (else
           (add1 (length (cdr list)))))))
   (lambda (x)
     ((mk-length mk-length) x)))))

Now the code in bold looks very much like the length function we need! Let's move it outside as well:

((lambda (le)
   ((lambda (mk-length)
      (mk-length mk-length))
    (lambda (mk-length)
      (le (lambda (x)
            ((mk-length mk-length) x))))))
 (lambda (length)
    (lambda (list)
      (cond
        ((null? list) 0)
        (else
         (add1 (length (cdr list))))))))

There we have it! The anonymous length function has been separated from the self-applicative call. The code in bold is the length function, and the code not-in-bold is the Y-combinator!

Now let's rename mk-length to f and join the lines to make it more compact:

((lambda (le)
   ((lambda (f) (f f))
    (lambda (f)
      (le (lambda (x) ((f f) x))))))
 (lambda (length)
   (lambda (list)
      (cond
        ((null? list) 0)
        (else
         (add1 (length (cdr list))))))))

And we are done. We can now write down the definition of Y-combinator:

(define Y
  (lambda (le)
    ((lambda (f) (f f))
     (lambda (f)
       (le (lambda (x) ((f f) x)))))))

And we can apply it to our anonymous length function:

((Y (lambda (length)
     (lambda (list)
       (cond
         ((null? list) 0)
         (else
          (add1 (length (cdr list))))))))
 '(a b c d e f g h i j))

; ==> 10

This is one of many derivations of the applicative-order Y-combinator. See the publication "The Why of Y" for another derivation.

Windows 95 LogoI am not just a Linux enthusiast, I also happen to use Windows quite often. In fact, Windows is my primary desktop from which I connect to all the other boxes and do my work on. During the years of Windows usage, I have accumulated a list of must-have Windows programs that I wouldn't be able to work without. Some of them are commercial, some are freeware, but that doesn't matter. What matters is how productive you are with your setup. If you're really productive on Linux with your own set of tools, it's perfectly fine and you have done a great job of finding the best tools of trade.

1. Total Commander.

I can't imagine working on a computer without Total Commander. Absolutely must-have software. Total Commander is what separates boys from men. Total Commander is probably the #1 reason why I don't use other operating system on my desktop. Tabs, a great GUI interface and customize-everything-configuration make it superior to all the other file managers. If I switch the desktop OS, I'll have to write my own clone of Total Commander or I wouldn't be able to work with the computer. Total commander is shareware.

2. TrueCrypt.

Because you don't want anyone to know what you store on your disks. TrueCrypt the best disk encryption software for Windows. TrueCrypt is freeware.

3. SecureCRT and Putty.

SecureCRT is the SSH client to use. Again, the primary reason I use it is because it has tab support. Putty comes second as it doesn't have tabs. SecureCRT is shareware. Putty is freeware.

4. WinSCP.

Forget all your FTP clients. FTP is dead and unsecure. I use WinSCP to send all my files over a secure connection. WinSCP is freeware.

5. Cygwin.

Since Windows has never had a usable shell, the only way to get one is to run a local ssh server via Cygwin and connect to localhost via SecureCRT. This way you get the best possible shell. Cygwin is freeware.

6. VMWare Workstation.

I have been using VMWare Workstation since 2004 and have never had a single problem. It's the best virtualization software ever written and nothing comes close. VMWare Workstation is shareware.

7. Synergy.

Synergy allows you to share your mouse and keyboard via network with other computers (no need for a KVM switch). It just works. Synergy is freeware.

8. Beyond compare.

The greatest visual diff tool ever written. Period. Beyond compare is shareware.

9. Tclock2.

Tclock2 is freeware that allows you to customize the windows clock in the systray. I set it to dddd\nyyyy.mm.dd\nhh:nn:ss.

10. Auto Hotkeys.

With Auto Hotkeys you can remap your keyboard and script shortcuts. For one, the first thing to do is to remap ESC to CAPS LOCK so that you could work in Vim. Auto Hotkeys is freeware.

11. Locate32.

Locate32 is to Windows what locate is to Linux. It helps you find all your files in an instant. Locate32 is freeware.

12. allSnap.

allSnap snaps your windows one next to each other, i.e., it aligns them nicely. allSnap is freeware.

13. Fineprint.

Fineprint is the best printer proxy ever. Allows you to print multiple pages per sheet even much more smartly than your printer does. Plus it has a real print preview. Fineprint is shareware.

14. Launchy.

I can't imagine working without Launchy. It's QuickSilver for Windows. It allows to quickly launch programs by pressing Alt+Space and typing in the first few chars of the program's name. Launchy is freeware.

15. ClipX.

ClipX maintains a paste buffer. Use Winkey+V to paste from it. If you haven't used it, it will change the way you work with your computer. ClipX is freeware.

16. DU Meter.

Du Meter measures your network usage and shows nice plots of it. I like it. Du Meter is shareware.

17. Taskbar Shuffle.

Taskbar Shuffle allows you to rearrange taskbar tabs and systray icons. Must-have. Taskbar Shuffle is freeware.

18. UltraMon.

If you're on a multi-screen setup, like me, UltraMon adds taskbars to your other screens. It's productivity super-booster. UltraMon is shareware.

19. Sumatra PDF.

Adobe Reader got bloated and died 5 years ago. Foxit Reader got bloated died 2 years ago. I hope Sumatra PDF reader doesn't die. Sumatra PDF is freeware.

20. KeePass.

KeePass is a secure password manager. I probably have 10 thousand passwords in it secured by one master password. Keepass is freeware.

21. RoboForm.

While KeePass keeps your passwords secure in a file, RoboForm allows you to dynamically submit them to various website forms. It also stores them under the master password. RoboForm is shareware.

22. WinRAR.

WinRAR is the best archivator for Windows. I have been using it since I was born. 7-Zip doesn't come close. WinRAR is shareware.

23. Inkscape.

Inkscape is a descent vector graphics editor. It's free.

24. FFDShow.

FFDShow is a codec library. If you wish to watch all kinds of videos on your computer, it's a must-have. FFDShow is freeware.

25. Media Player Classic.

MPC is the best video player for windows. It doesn't have skins or any other useless bullshit. MPC is freeware.

26. Real Alternative.

Real Alternative will use Media Player Classic to play RealMedia files. Real Alternative is freeware.

27. Quicktime Alternative.

Quicktime Alternative is to QuickTime files what Real Alternative is to RealMedia files. Freeware.

28. AviSynth.

AviSynth is a video processing programming language. If you wish to speed your videos up, it's a must-have. AviSynth is freeware.

29. FFMpeg.

FFMpeg is a must-have for converting videos and working with AviSynth scripts. FFMpeg is freeware.

30. VirtualDub.

VirtualDub is another must-have software for editing videos on Windows. VirtualDub is freeware.

31. Dependency Walker.

Sometimes programs don't work because of DLL hell. Dependency Walker helps you to diagnose and solve these problems. Dependency Walker is freeware.

32. Most of the Sysinternals tools.

Autoruns, regmon, procmon, procexp, tcpview, to name a few from Sysinternals are just must-have. They are all freeware.

33. File & Folder Unlocker.

UFFunlock is used when you get the nasty "Access denied" errors and you know that no process should be using the resource. FFunlock is freeware.

34. Hijackthis.

Hijackthis is necessary just to make sure you don't have nasty programs on your computer. Hijackthis is freeware.

35. ImgBurn.

ImgBurn is the new Nero. It burns your CDs and DVDs. ImgBurn is freeware.

36. IsoBuster.

IsoBuster knows all the CD/DVD image formats. IsoBuster is shareware.

37. Virtual CloneDrive.

Virtual CloneDrive allows you to mount ISOs right as windows drives. Virtual CloneDrive is freeware.

38. SQLyog.

As crappy as SQLyog is, it's somehow the most usable MySQL front-end. 10 years ago I used mysql-gui-console but the project got discontinued and no one has written a usable MySQL front-end ever since. If I'm ever in a mood, I'll write one that doesn't suck. SQLyog is shareware but I wouldn't pay a cent for it.

39. pgAdmin.

I applaud to pgAdmin dev team for making the best GUI front-end for PostgreSQL. Folks who write MySQL front-ends should learn from these guys. They know what a GUI tool should do. pgAdmin is freeware.

40. XML Notepad.

A notepad.exe for XML files. Allows you to edit XML smartly without destroying its structure accidentally. XML Notepad is freeware.

41. Hex Workshop.

Hex Workshop is a really great and easy to use Hex editor. It's shareware.

42. Vim.

For everything else.

What tools do you use?

This was a list of tools that I can't live without. What tools did I miss?