tracktracker/back/data/sources/tam.js

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JavaScript
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const unzip = require('unzip-stream');
const csv = require('csv-parse');
const axios = require('axios');
/**
* Process a CSV stream to extract passings.
*
* @private
* @param csvStream Stream containing CSV data.
* @param callback See fetchRealtime for a description of the callback.
*/
const processTamPassingStream = (csvStream, callback) =>
{
const parser = csv({
delimiter: ';',
});
const rowStream = csvStream.pipe(parser);
rowStream.on('readable', () =>
{
let row;
while ((row = rowStream.read()))
{
if (row.length === 0 || row[0] === 'course')
{
// Ignore les lignes invalides et len-tête
continue;
}
callback(null, {
course: row[0],
stopCode: row[1],
stopId: row[2],
stopName: row[3],
routeShortName: row[4],
tripHeadsign: row[5],
directionId: row[6],
departureTime: row[7],
isTheorical: row[8],
delaySec: row[9],
destArCode: row[10],
});
}
});
rowStream.on('end', () => callback(null, null));
rowStream.on('error', err => callback(err));
};
const tamRealtimeEndpoint = 'http://data.montpellier3m.fr/node/10732/download';
/**
* Fetch realtime passings across the network.
*
* The callback always receives two arguments. If an error occurs, the first
* argument will contain an object with information about the error. Otherwise,
* it will be null and the second argument will be the payload.
*
* The first call will provide metadata, specifically the time at which
* the data that follows was last updated (`lastUpdate`) and the time at
* which it will be updated next (`nextUpdate`).
*
* Following calls will provide each passing of the dataset individually,
* and will be closed with a call where both arguments are null.
*
* @param callback Called for each passing during parsing.
*/
const fetchRealtime = callback =>
{
axios.get(tamRealtimeEndpoint, {
responseType: 'stream'
}).then(res =>
{
const lastUpdate = new Date(res.headers['last-modified']).getTime();
// Data is advertised as being updated every minute. Add a small
// margin to account for potential delays
const nextUpdate = lastUpdate + 65 * 1000;
callback(null, {lastUpdate, nextUpdate});
processTamPassingStream(res.data, callback);
}).catch(err => callback(err));
};
exports.fetchRealtime = fetchRealtime;
const tamTheoreticalEndpoint =
'http://data.montpellier3m.fr/node/10731/download';
const tamTheoreticalFileName = 'offre_du_jour.csv';
/**
* Fetch theoretical passings for the current day across the network.
*
* @param callback Called for each passing during parsing. First argument will
* be non-null only if an error occurred. Second argument will contain passings
* or be null if the end was reached.
*/
const fetchTheoretical = callback =>
{
axios.get(tamTheoreticalEndpoint, {
responseType: 'stream'
}).then(res =>
{
const fileStream = res.data.pipe(unzip.Parse());
fileStream.on('entry', entry =>
{
if (entry.type !== 'File' || entry.path !== tamTheoreticalFileName)
{
entry.autodrain();
return;
}
processTamPassingStream(entry, callback);
});
fileStream.on('error', err => callback(err));
});
};
exports.fetchTheoretical = fetchTheoretical;