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    <p>For best efficiency, you generally want to process more than a single bit at a time. You can use a simple method to get a fixed width binary representation. eg.</p> <pre><code>def _bin(x, width): return ''.join(str((x&gt;&gt;i)&amp;1) for i in xrange(width-1,-1,-1)) </code></pre> <p>_bin(x, 8) will now give a zero padded representation of x's lower 8 bits. This can be used to build a lookup table, allowing your converter to process 8 bits at a time (or more if you want to devote the memory to it).</p> <pre><code>_conv_table = [_bin(x,8) for x in range(256)] </code></pre> <p>Then you can use this in your real function, stripping off leading zeroes when returning it. I've also added handling for signed numbers, as without it you will get an infinite loop (Negative integers conceptually have an infinite number of set sign bits.)</p> <pre><code>def bin(x): if x == 0: return '0' #Special case: Don't strip leading zero if no other digits elif x &lt; 0: sign='-' x*=-1 else: sign = '' l=[] while x: l.append(_conv_table[x &amp; 0xff]) x &gt;&gt;= 8 return sign + ''.join(reversed(l)).lstrip("0") </code></pre> <p>[Edit] Changed code to handle signed integers.<br> [Edit2] Here are some timing figures of the various solutions. bin is the function above, constantin_bin is from <a href="https://stackoverflow.com/questions/187273/base-2-binary-representation-using-python#189579">Constantin's answer</a> and num_bin is the original version. Out of curiosity, I also tried a 16 bit lookup table variant of the above (bin16 below), and tried out Python3's builtin bin() function. All timings were for 100000 runs using an 01010101 bit pattern.</p> <pre><code>Num Bits: 8 16 32 64 128 256 --------------------------------------------------------------------- bin 0.544 0.586 0.744 1.942 1.854 3.357 bin16 0.542 0.494 0.592 0.773 1.150 1.886 constantin_bin 2.238 3.803 7.794 17.869 34.636 94.799 num_bin 3.712 5.693 12.086 32.566 67.523 128.565 Python3's bin 0.079 0.045 0.062 0.069 0.212 0.201 </code></pre> <p>As you can see, when processing long values using large chunks really pays off, but nothing beats the low-level C code of python3's builtin (which bizarrely seems consistently faster at 256 bits than 128!). Using a 16 bit lookup table improves things, but probably isn't worth it unless you really need it, as it uses up a large chunk of memory, and can introduce a small but noticalbe startup delay to precompute the table.</p>
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    1. COThanks for the more or less complete answer, which is use 2.6 or 3.0 bin() function :)
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