In this article, I'll explain why implementing numbers with just algebraic datatypes is desirable. I'll then talk about common implementations of FFT (Fast Fourier Transform) and why they hide inherent inefficiencies. I'll then show how to implement integers and complex numbers with just algebraic datatypes, in a way that is extremely simple and elegant. I'll conclude by deriving a pure functional implementation of complex FFT with just datatypes, no floats.
Putting cryptographic primitives together is a lot like putting a jigsaw puzzle together, where all the pieces are cut exactly the same way, but there is only one correct solution. Thankfully, there are some projects out there that are working hard to make sure developers are getting it right.
The following advice comes from years of research from leading security researchers, developers, and cryptographers. This Gist was [forked from Thomas Ptacek's Gist][1] to be more readable. Additions have been added from
| -- Decoding | |
| SELECT CONVERT_FROM(DECODE(field, 'BASE64'), 'UTF-8') FROM table; | |
| -- Encoding | |
| SELECT ENCODE(CONVERT_TO(field, 'UTF-8'), 'base64') FROM table; |
CSS class names quickly get out of hand. Repos end up with unorganized CSS files all over the place making it difficult to name things and find them in the code.
The scoped components pattern addresses this by grouping classes into "component" scopes.
<div data-component="news-menu">
<h1 class="title">...</h1>
<ul class="items">
<li class="item">...</li>