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    <p>The <code>show</code>/<code>read</code> approach will work fine, I use it as well, but only for small values. On larger, more complex values <code>read</code> will be very slow.</p> <p>This contrived example demonstrates the bad performance of <code>read</code>:</p> <pre><code>data RevList a = (RevList a) :&lt; a | Nil deriving (Show, Read) ghci&gt; read "(((((((((((((((Nil)))))))))))))))" :: RevList Int </code></pre> <p>Also, <code>read</code> won't be able to read some valid Haskell expressions, especially ones that use infix constructors (like the <code>:&lt;</code> in my example). The reason for this is that <code>read</code> is unaware of the fixity of operators. This is also why <code>show $ Nil :&lt; 1 :&lt; 2 :&lt; 3</code> will generate a lot of seemingly redundant parentheses. </p> <p>If you want to have serialization for bigger values, I'd suggest to use some other library like <a href="http://code.haskell.org/binary/" rel="noreferrer">Data.Binary</a>. This will be somewhat more complex than a simple <code>show</code>, mainly because of the lack of <code>deriving Binary</code>. However, there are various generic programming solutions to give you <code>deriving</code>-like surrogates.</p> <p><strong>Conclusion:</strong> I'd say, use the <code>show</code>/<code>read</code> solution until you reach its limits (probably once you start building actual applications), then start looking at something more scalable (but also more complex) like Data.Binary.</p> <hr> <p>Side note: To those interested in parsers and more advanced Haskell stuff; The examples I gave came from the paper: <a href="http://www.cs.uu.nl/wiki/pub/Center/TTTAS/paper-read.pdf" rel="noreferrer">Haskel Do You Read Me?</a>, on an alternative, <em>fast</em> <code>read</code>-like function.</p>
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    1. COFor deriving Binary, http://repetae.net/computer/haskell/DrIFT/ comes to mind. That being said, it is certainly possible write smarter Read and Show instances for RevList in this simple case, and I agree that OP should stick to simple until scalability becomes an issue.
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