The most obvious solution is to define a dictionary with individual characters as keys and their corresponding digits as values, and do dictionary lookups on each character. This is what we have in soundex/stage1/soundex1c.py (the current best result so far):

charToSoundex = {"A": "9",
                 "B": "1",
                 "C": "2",
                 "D": "3",
                 "E": "9",
                 "F": "1",
                 "G": "2",
                 "H": "9",
                 "I": "9",
                 "J": "2",
                 "K": "2",
                 "L": "4",
                 "M": "5",
                 "N": "5",
                 "O": "9",
                 "P": "1",
                 "Q": "2",
                 "R": "6",
                 "S": "2",
                 "T": "3",
                 "U": "9",
                 "V": "1",
                 "W": "9",
                 "X": "2",
                 "Y": "9",
                 "Z": "2"}

def soundex(source):
    # ... input check omitted for brevity ...
    source = source[0].upper() + source[1:]
    digits = source[0]
    for s in source[1:]:
        s = s.upper()
        digits += charToSoundex[s]

You timed soundex1c.py already; this is how it performs:

C:\samples\soundex\stage1>python soundex1c.py
Woo             W000 14.5341678901
Pilgrim         P426 19.2650071448
Flingjingwaller F452 30.1003563302

This code is straightforward, but is it the best solution? Calling upper() on each individual character seems inefficient; it would probably be better to call upper() once on the entire string.

Then there's the matter of incrementally building the digits string. Incrementally building strings like this is horribly inefficient; internally, the Python interpreter needs to create a new string each time through the loop, then discard the old one.

Python is good at lists, though. It can treat a string as a list of characters automatically. And lists are easy to combine into strings again, using the string method join().

Here is soundex/stage2/soundex2a.py, which converts letters to digits by using ↦ and lambda:

def soundex(source):
    # ...
    source = source.upper()
    digits = source[0] + "".join(map(lambda c: charToSoundex[c], source[1:]))

Surprisingly, soundex2a.py is not faster:

C:\samples\soundex\stage2>python soundex2a.py
Woo             W000 15.0097526362
Pilgrim         P426 19.254806407
Flingjingwaller F452 29.3790847719

The overhead of the anonymous lambda function kills any performance you gain by dealing with the string as a list of characters.

soundex/stage2/soundex2b.py uses a list comprehension instead of ↦ and lambda:

    source = source.upper()
    digits = source[0] + "".join([charToSoundex[c] for c in source[1:]])

Using a list comprehension in soundex2b.py is faster than using ↦ and lambda in soundex2a.py, but still not faster than the original code (incrementally building a string in soundex1c.py):

C:\samples\soundex\stage2>python soundex2b.py
Woo             W000 13.4221324219
Pilgrim         P426 16.4901234654
Flingjingwaller F452 25.8186157738

It's time for a radically different approach. Dictionary lookups are a general purpose tool. Dictionary keys can be any length string (or many other data types), but in this case we are only dealing with single-character keys and single-character values. It turns out that Python has a specialized function for handling exactly this situation: the string.maketrans function.

This is soundex/stage2/soundex2c.py:

allChar = string.uppercase + string.lowercase
charToSoundex = string.maketrans(allChar, "91239129922455912623919292" * 2)
def soundex(source):
    # ...
    digits = source[0].upper() + source[1:].translate(charToSoundex)

What the heck is going on here? string.maketrans creates a translation matrix between two strings: the first argument and the second argument. In this case, the first argument is the string ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz, and the second argument is the string 9123912992245591262391929291239129922455912623919292. See the pattern? It's the same conversion pattern we were setting up longhand with a dictionary. A maps to 9, B maps to 1, C maps to 2, and so forth. But it's not a dictionary; it's a specialized data structure that you can access using the string method translate, which translates each character into the corresponding digit, according to the matrix defined by string.maketrans.

timeit shows that soundex2c.py is significantly faster than defining a dictionary and looping through the input and building the output incrementally:

C:\samples\soundex\stage2>python soundex2c.py
Woo             W000 11.437645008
Pilgrim         P426 13.2825062962
Flingjingwaller F452 18.5570110168

You're not going to get much better than that. Python has a specialized function that does exactly what you want to do; use it and move on.

import string, re

allChar = string.uppercase + string.lowercase
charToSoundex = string.maketrans(allChar, "91239129922455912623919292" * 2)
isOnlyChars = re.compile('^[A-Za-z]+$').search

def soundex(source):
    if not isOnlyChars(source):
        return "0000"
    digits = source[0].upper() + source[1:].translate(charToSoundex)
    digits2 = digits[0]
    for d in digits[1:]:
        if digits2[-1] != d:
            digits2 += d
    digits3 = re.sub('9', '', digits2)
    while len(digits3) < 4:
        digits3 += "0"
    return digits3[:4]

if __name__ == '__main__':
    from timeit import Timer
    names = ('Woo', 'Pilgrim', 'Flingjingwaller')
    for name in names:
        statement = "soundex('%s')" % name
        t = Timer(statement, "from __main__ import soundex")
        print name.ljust(15), soundex(name), min(t.repeat())