通过CSV文件进行解析以转换为JSON格式的文件

Question

I am given the following CSV file which I extracted from an excel spreadsheet. Just to give some background information which could be of assistance, it discusses AGI Numbers (think of it as protein identifiers), unmodified peptide sequences for those protein identifiers, and then modified peptide sequences with modifications made on the unmodified sequences, the index/indeces of those modifications, and then the combined spectral count for repeated peptides. The text file is called MASP.GlycoModReader.txt and the information is in the following format below:

AGI,UnMd Peptide (M) = x,Mod Peptide (oM) = Ox,Index/Indeces of Modification,counts,Combined 
Spectral count for repeated Peptides

AT1G56070.1,NMSVIAHVDHGKSTLTDSLVAAAGIIAQEVAGDVR,NoMSVIAHVDHGKSTLTDSLVAAAGIIAQEVAGDVR,2,17
AT1G56070.1,LYMEARPMEEGLAEAIDDGR,LYoMEARPoMEEGLAEAIDDGR,"3, 9",1
AT1G56070.1,EAMTPLSEFEDKL,EAoMTPLSEFEDKL,3,7
AT1G56070.1,LYMEARPMEEGLAEAIDDGR,LYoMEARPoMEEGLAEAIDDGR,"3, 9",2
AT1G56070.1,EGPLAEENMR,EGPLAEENoMR,9,2
AT1G56070.1,DLQDDFMGGAEIIK,DLQDDFoMGGAEIIK,7,1

The output file that needs to result after extracting the above is in the following format below:

AT1G56070.1,{"peptides": [{"sequence": "NMSVIAHVDHGKSTLTDSLVAAAGIIAQEVAGDVR", "mod_sequence":    
"NoMSVIAHVDHGKSTLTDSLVAAAGIIAQEVAGDVR" , "mod_indeces": 2, "spectral_count": 17}, {"sequence": 
"LYMEARPMEEGLAEAIDDGR" , "mod_sequence": "LYoMEARPoMEEGLAEAIDDGR", "mod_indeces": [3, 9], 
"spectral_count": 3}, {"sequence": "EAMTPLSEFEDKL" , "mod_sequence": "EAoMTPLSEFEDKL", 
"mod_indeces": [3,9], "spectral_count": 7}, {"sequence": "EGPLAEENMR", "mod_sequence": 
"EGPLAEENoMR", "mod_indeces": 9, "spectral_count": 2}, {"sequence": "DLQDDFMGGAEIIK", 
"mod_sequence": "DLQDDFoMGGAEIIK", "mod_indeces": [7], "spectral_count": 1}]}

I have provided my solution below: If anyone has a better solution in another language or can possibly analyze mine and let me know if there are more efficient methods of coming about this, then please comment below. Thank you.

    #!/usr/bin/env node

    var fs = require('fs');
    var csv = require('csv');
    var data ="proteins.csv";

    /* Uses csv nodejs module to parse the proteins.csv file.
    * Parses the csv file row by row and updates the peptide_arr.
    * For new entries creates a peptide object, for similar entries it updates the
    * counts in the peptide object with the same AGI#.
    * Uses a peptide object to store protein ID AGI#, and the associated data.
    * Writes all formatted peptide objects to a txt file - output.txt.
    */

    // Tracks current row
    var x = 0;
    // An array of peptide objects stores the information from the csv file
    var peptide_arr = [];

    // csv module reads row by row from data 
    csv()
    .from(data)
    .to('debug.csv')
    .transform(function(row, index) {
        // For the first entry push a new peptide object with the AGI# (row[0]) 
        if(x == 0) {
        // cur is the current peptide read into row by csv module
        Peptide cur = new Peptide( row[0] );

        // Add the assoicated data from row (1-5) to cur
        cur.data.peptides.push({
            "sequence" : row[1];
            "mod_sequence" : row[2];
            if(row[5]){
            "mod_indeces" : "[" + row[3] + ", " + row[4] + "]";
            "spectral_count" : row[5];  
            } else {
            "mod_indeces" : row[3];
            "spectral_count" : row[4];  
            }
        });

        // Add the current peptide to the array
        peptide_arr.push(cur);
        }

        // Move to the next row
        x++;
    });

    // Loop through peptide_arr and append output with each peptide's AGI# and its data
    String output = "";
    for(var peptide in peptide_arr) 
    {
        output = output + peptide.toString()
    }
    // Write the output to output.txt
    fs.writeFile("output.txt", output);

    /* Peptide Object :
     *  - id:AGI#
     *  - data: JSON Array associated
     */
    function Peptide(id) // this is the actual function that does the ID retrieving and data 
                        // storage
{
    this.id = id;
    this.data = {
        peptides: []
    };
}

/* Peptide methods :
 *  - toJson : Returns the properly formatted string
 */
Peptide.prototype = {
    toString: function(){
        return this.id + "," + JSON.stringify(this.data, null, " ") + "/n"
    }
};

Edited note: It seems when I run this solution I posted, I am getting a memory leak error; it is infinitely running while not producing any substantial, readable output. If anyone could be willing to assist in assessing why this is occurring, that would be great.

Answer 1

Does your version work? It looks like you only ever create one Peptide object. Also, what is the "if(row[5])" statement doing? In your example data there are always 5 elements. Also, mod_indeces is always supposed to be a list, correct? Because in your example output file mod_indeces isn't a list in the first peptide. Anyway, here is what I came up with in python:

import csv
import json
data = {}
with open('proteins.csv','rb') as f:
    reader = csv.reader(f)
    for row in reader:
        name = row[0]
        sequence = row[1]
        mod_sequence = row[2]
        mod_indeces = map(int,row[3].split(', '))
        spectral_count = int(row[4])
        peptide = {'sequence':sequence,'mod_sequence':mod_sequence,
                   'mod_indeces':mod_indeces,'spectral_count':spectral_count}
        if name in data:
            data[name]['peptides'].append(peptide)
        else:
            data[name] = {'peptides':[peptide]}
    f.close()

f = open('output.txt','wb')
for protein in data:
    f.write(protein)
    f.write(',')
    f.write(json.dumps(data[protein]))
    f.write('\n')
f.close()

If you are on windows and want to view the file as plain text, you may want to replace '\\n' with '\\r\\n' or os.linesep.

If you want to skip some rows (if there is a header or something), you can do something like this:

import csv
import json
data = {}
rows_to_skip = 1
rows_read = 0
with open('proteins.csv','rb') as f:
    reader = csv.reader(f)
    for row in reader:
        if rows_read >= rows_to_skip:
            name = row[0]
            sequence = row[1]
            mod_sequence = row[2]
            mod_indeces = map(int,row[3].split(', '))
            spectral_count = int(row[4])
            peptide = {'sequence':sequence,'mod_sequence':mod_sequence,
                       'mod_indeces':mod_indeces,'spectral_count':spectral_count}
            if name in data:
                data[name]['peptides'].append(peptide)
            else:
                data[name] = {'peptides':[peptide]}
        rows_read += 1
    f.close()

f = open('output.txt','wb')
for protein in data:
    f.write(protein)
    f.write(',')
    f.write(json.dumps(data[protein]))
    f.write('\n')
f.close()

If you want the keys of the dictionary to be in a particular order, you can use an orderedDict instead of the default dict. Just replace the peptide line with the following:

peptide = OrderedDict([('sequence',sequence),
                       ('mod_sequence',mod_sequence),
                       ('mod_indeces',mod_indeces),
                       ('spectral_count',spectral_count)])

Now the order is preserved. That is, sequence is followed by mod_sequence followed by mod_indeces followed by spectral_count . To change the order, just change the order of elements in the OrderedDict.

Note that you will also have to add from collections import OrderedDict in order to be able to use OrderedDict.