ArtArchive/Class11/MARC_Disaster/index.js

255 lines
7.8 KiB
JavaScript

/*
MARC List Example
Jer Thorp
3/11/19
- npm install
- npm run download-data
- npm start
NOTE: You will need to have the URLs you'd like the download script to get listed in data/urls.txt
NOTE: If the download-data command doesn't work you probably need to install wget:
OSX: brew install wget
Windows: http://gnuwin32.sourceforge.net/packages/wget.htm
This example runs through the Visual Materials and makes a data file recording how many items were
published in each given year.
This tactic could be used to get distribution data for any MARC field - and could be filtered by
title keyword (see CleanMARC example)
*/
//We're using the xml2object package, which takes XML loaded as text and parses it into a javascript object
const xml2object = require('xml2object');
//The filesystem package is used to load the .gz files from the local directory
const fs = require('fs');
//The zlib package is used to unzip the .gz files
const zlib = require('zlib');
//I like to use this package which provides a clean way to reference to root directory of a node project
const appRoot = require('app-root-path');
//Natural is a nice NLP package for node: https://www.npmjs.com/package/natural
const natural = require('natural');
//Where is the data?
var dataPath = appRoot + "/data";
//Which subset of the MARC files were we looking for?
const filePrefix = "Maps";
//How many of them are there?
const fileMap = [];
fileMap["BooksAll"] = 41;
fileMap["Computer.Files"] = 1;
fileMap["Maps"] = 1;
fileMap["Music"] = 1;
fileMap["Names"] = 37;
fileMap["Serials"] = 11;
fileMap["Subjects"] = 2;
fileMap["Visual.Materials"] = 1;
//Total number of files to load
const fileCount = fileMap[filePrefix];
//Number of files we've already loaded
//We start at 1 because the MARC files are 1-indexed
var fileCounter = 1;
//Counter to keep track of years
var outCounter = {};
//Array to hold CSV outs
var rows = [];
//Search word
var search = "fire";
//The xml2object package needs us to build a parser object - that will ingest the XML and then
//trigger functions when the parse is complete.
const parser = new xml2object([ 'record' ]);
//XML PARSER ---------------------------------------------------------------------------!!
//When we construct the parser with an array of which xml elements to look for. In our case, we're
//interested in the record objects. We also can pass in a reference to the file name.
function makeParser() {
//The parser's on method handles events. Here, we'll define what happens when it finishes parsing an object
parser.on('object', function(name, obj) {
//Get the Year of the object from subfield 260
var marcDict = {};
marcDict["245"] = {"*" :"Title"};
marcDict["260"] = {"c" :"Year"};
marcDict["752"] = {"*" : "Location"};
marcDict["650"] = {"a" : "Subject"};
var record = parseRecord(obj, marcDict);
var year = record.Year;
if (record.Year) {
var cy;
try {
cy = record.Year[0].replace(/-/g, "5");
cy = cy.replace(/[.,\/#!$%\^&\*\[\];:{}=\-_`~()]/g,"");
var yearRegex = /(\d{4})/;///(\d{4}|\d{4}\-\d{4})$/g;
///(17|18|19|20)\d{2}/
var y = cy.match(yearRegex)[0];
if (y) year = y;
} catch (error) {
//console.log("failed year extract" + record.Year);
//console.log(cy);
}
}
if (record.Location && record.Title) {
var chk1 = checkForMatches(record.Title.join(" ").toLowerCase(), ["hazard","fire","flood","storm","tornado","earthquake"]).chk;
var chk2;
if (record.Subject) {
chk2 = checkForMatches(record.Subject.join(" ").toLowerCase(), ["hazard","fire","flood","storm","tornado","earthquake"]).chk
}
if (chk1 || chk2) {
rows.push([record.Title.join(" ") + " " + year + " " + record.Location. join(" ")]);
console.log(record);
}
}
});
//And what happens when it finishes parsing all of the records.
parser.on('end', function() {
onParseFinished();
});
}
//------------------CHECK FOR MATCHES FUNCTION ---------------------------------------------------------------------------!!
//This function checks any string (input) against any list of candidate strings (candidates)
//Uses NLP to split the sentence into words and also to stem
var tokenizer = new natural.TreebankWordTokenizer();
//Used to singularize the words so that frogs matches frog. Wether or not you have to do this will depend on what data you're trying to match.
//For example if it's something *already* standardized (ie. Subjects) you won't have to.
//This function is SLOW if there are a lot of words to check against
var nounInflector = new natural.NounInflector();
function checkForMatches(input, candidates) {
//Tokenize the record (break it into words)
var words = [tokenizer.tokenize(input)][0];
//Set up our return object, this is the state that is returned with no matches
var chk = {chk:false, words:[]};
for (var i = 0; i < candidates.length; i++) {
var cand = nounInflector.singularize(candidates[i].toLowerCase());
for (var j = 0; j < words.length; j++) {
if (nounInflector.singularize(words[j].toLowerCase()) == cand) {
chk.chk = true;
chk.words.push(candidates[i]);
}
}
}
//Returns an object with a boolean and a list of words (if any)
//ie {chk:true, words:["frog","monkey"]}
return(chk);
}
//MARC PARSE FUNCTION ---------------------------------------------------------------------------!!
//This function expects an object from xml2obj, and a dictionary object which links
//the mark tags and subfields to a property name.
//
//For example, you could do this:
// marcDict["260"] = {"c" :"Year"};
//
//Which asks the parser to link records with a tag of 260 and a subfield of c to the property Year.
//
//You can also use * to say you want ALL subfields of a tag to be stored in a property:
//
// marcDict["245"] = {"*" :"Title"};
function parseRecord(obj, marcDict) {
record = {};
for (var i = 0; i < obj.datafield.length; i++) {
var df = obj.datafield[i];
//Get the numeric tag
var tag = df.tag;
//If we have the tag in our dictionary, write to the JSON object
//Based on the code (doesn't work for all cases?)
if (marcDict[tag] && df.subfield) {
var isAll = marcDict[tag]['*'];
for (var j = 0; j < df.subfield.length; j++) {
var code = isAll ? "*":df.subfield[j].code;
var disp = df.subfield[j]['$t'];
if (marcDict[tag][code] || isAll) {
if (!record[marcDict[tag][code]]) {
record[marcDict[tag][code]] = [];
}
record[marcDict[tag][code]].push(disp);
}
}
}
}
return(record);
}
//FILE LOADING CASCADE ---------------------------------------------------------------------------!!
//These two functions sequence through the list of MARC records one by one and process them with our
//xml2object parser
function loadNextFile() {
if (fileCounter <= fileCount) {
//Put a zero in file names under 10
var n = (fileCounter < 10 ? "0":"") + fileCounter;
//Construct the URL
var url = dataPath + "/" + filePrefix + ".2014.part" + n + ".xml.gz";
//Open up a read stream and unzip it
var rstream = fs.createReadStream(url);
var gunzip = zlib.createGunzip();
rstream // reads from the url we've constructed
.pipe(gunzip) // uncompresses
.pipe(parser.saxStream); //Parses into record objects
fileCounter ++;
console.log("LOADING FILE : " + url);
}
}
function onParseFinished() {
//Write every time - useful in very long processes
writeFile(rows);
try {
loadNextFile();
} catch(err) {
console.log("ERROR LOADING NEXT FILE: " + fileCounter);
}
}
//File WRITER ---------------------------------------------------------------------------!!
function writeFile(rows) {
var text = rows.join("\n");
//Write
//File prefix is defined on line 26
fs.writeFile(appRoot + "/out/" + search + ".tsv", text, 'utf8', function() {
console.log("Saved JSON.");
});
}
//PULL THE TRIGGER.
makeParser();
loadNextFile();