If what you are doing is relating it back to the original source code ... isn't the original source code stored in 1 specific format, \r, \n or \r\n? Or do you use the models that are parsed once to map it back to different versions of the same files on different platforms? In that case you could always convert the input file into the format you want. To me however it seems like it makes most sense to keep the line + column count if you are going to keep anything yourself anyway. You do not need to rely on what petitparser knows already, you can keep this data yourself. Petitparser needs to have the char location since that's where it's parsing. The line+column is metadata that you need, not petitparser. To implement this you just again need to keep track of all the newlines you see. Everytime you see a newline you update your newline count AND keep track of the position where the newline happened. This way you actually have the column count (the actual position - the location where the last newline occurred). Another option I see is always parsing using a \r or \n file format by first converting it. Then when you show the position, you will have to check if the file is actually \r, \n or if it's rather \r\n. If it's \r or \n then you just give back the number as is. Otherwise you walk over the file to find out where all the newlines occur. From this you can build an array that tells you which position ranges have to add how many charcounts. For example [0, 10, 15, 17, 20] if the newlines occur at [0, 9, 13, 14, 16] (always subtract 1 char of the newline since we map from 1-sized newline to 2-sized newline). Now you can just translate your position by looking for the highest number lower than the position. For example if you were looking at position 15, this will map onto 14, which has index 4, so you have to do + 4 -> the real position is 19. This is just a binary search for each position in the array of newlines, so it's O(number of newlines in file * number of tokens) to translate the model to become architecture-dependent. The last option is to just store both position formats in your model directly, and figuring out which fileformat you are mapping it back onto. This is O(1) but requires double the data for position numbers (no biggy I suppose); but it does require your parser to keep track of the position info itself again. The previous option avoids that. Hope this helps to make some sort of a decision :) Toon