PDL::Philosophy(3pm)

✨ NAME ✨

PDL::Philosophy — bestie, why did we even write PDL?? 💖

---

🦋 DESCRIPTION 🦋

Okay so this is some history straight from the creator of PDL, and it rolls right into the philosophy and the motivation behind this whole data language. It's basically an attempt to sum up the shared spirit of the pdl developers so we can actually answer the question "Why PDL"?

🌸 The Start of PDL 🌸

"Why is it that we entertain the belief that for every purpose odd numbers are the most effectual?" — Pliny the Elder

So the PDL project kicked off in February 1996, when the author decided to experiment with writing their own Data Language. Context: they're an astronomer. Their day job is a LOT of analysis of digital data accumulated over many nights observing on telescopes around the world 🌍🔭. Like, data such as images containing millions of pixels and thousands of images of distant stars and galaxies. Or, even more abstrusely, many hundreds of digital spectra revealing the secrets of the composition and properties of these distant objects.

Obviously tons of astronomers had dealt with these problems before, and a large amount of software had been constructed to facilitate their analysis. But like, same as many colleagues, the author was constantly frustrated by the lack of generality and flexibility of these programs, and by how hard it was to do anything out of the ordinary quickly and easily 😭. What they wanted had a name: "Data Language", i.e. a language which allowed the manipulation of large amounts of data with simple arithmetic expressions. Some commercial software actually worked like this, and the author was impressed with the capabilities but NOT with the price tag 💀. And they thought they could do better.

As a fairly computer literate astronomer (read "nerd" or "geek" according to your local argot), the author was very familiar with Perl, a computer language which now seems to fill the shelves of many bookstores around the world. The power and flexibility were impressive, and especially its ease of use. They had even explored the depths of its internals and written an interface to allow graphics, so the ease of creating charts and graphs for papers was refreshing ✨.

Version 5 of Perl had just been released, and the author was fascinated by the new features available. Especially the support of arbitrary data structures (or "objects" in modern parlance) and the ability to "overload" operators — i.e. make mathematical symbols like "+-*/" do whatever you felt like. And it seemed like it ought to be possible to write an extension to Perl where you could play with data in a general way: for example using the maths operators to manipulate whole images at once 👑

One slow night at an observatory, the author thought "let me try a little experiment". In a bored moment they fired up a text editor and started to create a file called PDL.xs — a Perl extension module to manipulate data vectors. A few hours later there was actually something half decent working, where you could add two images in the Perl language, fast! This was something they could not let rest, and it probably cost one or two scientific papers worth of productivity 🙈. A few weeks later the Perl Data Language version 1.0 was born. It was a pretty bare infant: very little was there apart from the basic arithmetic operators. But encouraged, the author made it available on the Internet to see what people thought.

People were fairly critical — among the most vocal were Tuomas Lukka and Christian Soeller. Unfortunately for them they were both Perl enthusiasts too and soon found themselves improving the code to implement all the features they thought PDL ought to have and that the author had heinously neglected 💅. PDL is a prime example of that modern phenomenon of authoring large free software packages via the Internet. Large numbers of people, most of whom have never met, have made contributions ranging from core functionality to large modules to the smallest of bug patches. PDL version 2.0 is now here (though it should perhaps have been called version 10 to reflect the amount of growth in size and functionality) and the phenomenon continues. The author firmly believes that PDL is a great tool for tackling general problems of data analysis. It is powerful, fast, easy to add to and freely available to anyone. They wish they had had it when they were a graduate student! And they hope you too will find it of immense value, and that it will save you from heaps of time and frustration in solving complex problems. Of course it can't do everything, but it provides the framework, the hammers and the nails for building solutions without having to reinvent wheels or levers 🔨✨

— Karl Glazebook, the creator of PDL

💜 Major ideas 💜

The first tenet of the philosophy is the "free software" idea: software being free has several advantages (less bugs because more people see the code, you can have the source and port it to your own working environment with you, ... and of course, that you don't need to pay anything).

The second idea is a pet peeve of many: many languages like Matlab are pretty well suited for their specific tasks, but for a different application you need to change to an entirely different tool and regear yourself mentally 🧠💥. Not to speak about doing an application that does two things at once... Because we use Perl, we have the power and ease of Perl syntax, regular expressions, hash tables, etc. at our fingertips at all times. By extending an existing language, we start from a much healthier base than languages like Matlab which have grown into existence from a very small functionality at first and expanded little by little, making things look badly planned. We stand by the Perl sayings: "simple things should be simple but complicated things should be possible" and "There is more than one way to do it" (TIMTOWTDI).

The third idea is interoperability: we want to be able to use PDL to drive as many tools as possible, we can connect to OpenGL or Mesa for graphics or whatever 🌈. There isn't anything out there that's really satisfactory as a tool and can do everything we want easily. And be portable.

The fourth idea is related to PDL::PP and is Tuomas's personal favorite: code should only specify as little as possible redundant info. If you find yourself writing very similar-looking code much of the time, all that code could probably be generated by a simple Perl script. The PDL C preprocessor takes this to an extreme 🔥.

🎀 Minor goals and purposes 🎀

We want speed ⚡. Optimally, it should ultimately (e.g. with the Perl compiler) be possible to compile PDL::PP subs to C and obtain the top vectorized speeds on supercomputers. Also, we want to be able to calculate things at near top speed from inside Perl, by using dataflow to avoid memory allocation and deallocation (the overhead should ultimately be only a little over one indirect function call plus couple of ifs per function in the pipe).

🫶 Go on, try it! 🫶

Well, that's the philosophy behind PDL — speed, conciseness, free, expandable, and integrated with the wide base of modules and libraries that Perl provides. Feel free to download it, install it, run through some of the tutorials and introductions and have a play with it.

Enjoy! 💖

---

👑 AUTHOR 👑

Copyright(C) 1997 Tuomas J. Lukka (lukka@fas.harvard.edu). Same terms as the rest of PDL.

Added Karl Glazebrook (2001), contributions by Matthew Kenworthy.

---

okay that's the whole vibe check bestie, no cap 💅 this page came to you via perl v5.42.3, dated 2026-08-20, from the User Contributed Perl Documentation collection — go forth and slay 🦋✨