Parsing an XML file in C without parsing libraries

Question

I am trying to access all of the < spectrum > tags in an XML file that have "ms level" value equal to 1. Then, produce a .txt file that contains strings of data within the tag including bits, whether or not the data is compressed, and the raw binary string. It should then go further and do the same for any other tags in the file. This is for a project where I am not allowed to use parsing libraries.

I am unsure how to access tags in an XML file without using external libraries and then pull out data within the tags. I understand the high level plan on how to complete the task but do not know what tools I should be using.

EDIT: It occurred to me to mention that there is more to the file before the first < spectrum > tag occurs. When creating the first mzmlFileBuffer, it is only getting the first line of the entire file "< ?xml version="1.0" encoding="ISO-8859-1"? >" and I'm not sure why. It will not access anything with tags in the entirety of the file which is what I would like to figure out how to do.

This is an example of the file:

<spectrum index="0" id="controllerType=0 controllerNumber=1 scan=1" defaultArrayLength="1625">
  <cvParam cvRef="MS" accession="MS:1000511" name="ms level" value="1"/>
  <cvParam cvRef="MS" accession="MS:1000130" name="positive scan" value=""/>
  <cvParam cvRef="MS" accession="MS:1000580" name="MSn spectrum" value=""/>
  <cvParam cvRef="MS" accession="MS:1000127" name="centroid spectrum" value=""/>
  <cvParam cvRef="MS" accession="MS:1000528" name="lowest observed m/z" value="451.17056274414062"/>
  <cvParam cvRef="MS" accession="MS:1000527" name="highest observed m/z" value="1199.9544677734375"/>
  <cvParam cvRef="MS" accession="MS:1000504" name="base peak m/z" value="786.59503173828125"/>
  <cvParam cvRef="MS" accession="MS:1000505" name="base peak intensity" value="6488257.5"/>
  <cvParam cvRef="MS" accession="MS:1000285" name="total ion current" value="114753896"/>
  <scanList count="1">
    <cvParam cvRef="MS" accession="MS:1000795" name="no combination" value=""/>
    <scan instrumentConfigurationRef="IC1">
      <cvParam cvRef="MS" accession="MS:1000616" name="preset scan configuration" value="1"/>
      <cvParam cvRef="MS" accession="MS:1000498" name="full scan" value=""/>
      <cvParam cvRef="MS" accession="MS:1000016" name="scan start time" value="0.259" unitCvRef="UO" unitAccession="UO:0000010" unitName="second"/>
    </scan>
  </scanList>
  <binaryDataArrayList count="2">
    <binaryDataArray encodedLength="6748">
      <cvParam cvRef="MS" accession="MS:1000523" name="64-bit float" value=""/>
      <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
      <cvParam cvRef="MS" accession="MS:1000514" name="m/z array" value="" unitCvRef="MS" unitAccession="MS:1000040" unitName="m/z"/>
       <binary>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</binary>
    </binaryDataArray>
    <binaryDataArray encodedLength="7872">
      <cvParam cvRef="MS" accession="MS:1000521" name="32-bit float" value=""/>
      <cvParam cvRef="MS" accession="MS:1000574" name="zlib compression" value=""/>
      <cvParam cvRef="MS" accession="MS:1000515" name="intensity array" value="" unitCvRef="MS" unitAccession="MS:1000131" unitName="number of counts"/>
       <binary>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</binary>
    </binaryDataArray>
  </binaryDataArrayList>
</spectrum>

This is as far as I've gotten with my code, where my next step would be to use strstr to look through the spectrumString for the appropriate data I want to pull out:

#include <stdio.h>
#include <string.h>
#include <stdlib.h>

int main(void) {
    char mzmlFileBuffer[23000];
    char *spectrumPtr;
    char *spectrumEndPtr;
    int indexStart;
    int indexEnd;
    char spectrumString[18000];

    FILE *fp;
    fp = fopen("32_64_compressed.mzML", "r");

    if (fp == NULL) {
        printf("File failed to open...");
        exit(EXIT_FAILURE);
    }

    while (fgets(mzmlFileBuffer, 23000, fp) != NULL) {

        //FIND FIRST OCCURRENCE OF <SPECTRUM
        spectrumPtr = strstr(mzmlFileBuffer, "<spectrum ");
        indexStart = spectrumPtr - mzmlFileBuffer;

        //FIND END OF SPRECTRUM
        spectrumEndPtr = strstr(mzmlFileBuffer, "</spectrum>");
        indexEnd = spectrumEndPtr - mzmlFileBuffer;

        //CREATE NEW STRING BETWEEN INDICES
        strncpy(spectrumString, spectrumPtr, indexEnd - indexStart);

        //IF SPECTRUM IS MS LEVEL 1
        //if (strstr(spectrumString, "name=\"ms level\" value=\"1\"") != NULL) {
        // 
        //}
    }
}

Answer 1

Writing a fully conformant xml parser is a vast and complex project. Your approach will work if the actual format used for the file is simple and regular, but any change in the presentation will break your simplistic parser.

You should add consistency checks everywhere you can to detect such departures from the expected format.

Note also that strncpy does not do what you think it does. You should NEVER use this function . It is not the right tool for the job. To extract a fragment from a string, use memcpy and add a final '\\0' by hand. Incidentally, strncpy will not null terminate the destination if the size argument is less than the length of the source string.

Depending on how large your xml file may be, it may be simpler to read the whole file into a buffer and parse it from this buffer. Reading one line at a time requires you to implement some form of state machine to keep track of the pseudo-parsing stage.

Can you share with us what reasons prevent you from using an xml parsing library? There might be ways to include the parsing code in your project and stay within your constraints and those of the package licence.

EDIT : since you are in a basic C course and not supposed to use external libraries, this assignment is quite surprising. They are probably expecting you to write a quick and dirty solution that searches for tag strings and " string quotes, extracts fragments, possibly converting binary encodings such as base64. It is difficult to make this work in the general case, but for a specific given file, you should be able to produce a working solution.