Question

I need to create a lexer/parser which deals with input data of variable length and structure.

Say I have a list of reserved keywords:

keyWordList = ['command1', 'command2', 'command3']

and a user input string:

userInput = 'The quick brown command1 fox jumped over command2 the lazy dog command 3'
userInputList = userInput.split()

How would I go about writing this function:

INPUT:

tokenize(userInputList, keyWordList)

OUTPUT:
[['The', 'quick', 'brown'], 'command1', ['fox', 'jumped', 'over'], 'command 2', ['the', 'lazy', 'dog'], 'command3']

I’ve written a tokenizer that can identify keywords, but have been unable to figure out an efficent way to embed groups of non-keywords into lists that are a level deeper.

RE solutions are welcome, but I would really like to see the underlying algorithm as I am probably going to extend the application to lists of other objects and not just strings.

Answer 1

Try this:

keyWordList = ['command1', 'command2', 'command3']
userInput = 'The quick brown command1 fox jumped over command2 the lazy dog command3'
inputList = userInput.split()

def tokenize(userInputList, keyWordList):
    keywords = set(keyWordList)
    tokens, acc = [], []
    for e in userInputList:
        if e in keywords:
            tokens.append(acc)
            tokens.append(e)
            acc = []
        else:
            acc.append(e)
    if acc:
        tokens.append(acc)
    return tokens

tokenize(inputList, keyWordList)
> [['The', 'quick', 'brown'], 'command1', ['fox', 'jumped', 'over'], 'command2', ['the', 'lazy', 'dog'], 'command3']