lets-make-csvs

0.0.10 • Public • Published

lets-make-csvs

Let's make CSV's from row objects

What

I wanted to create an iterative CSV, one row at a time. But I also want ot add properties.

This module will make a CSV one row at a time. It will also modify the CSV header as it goes. Because it uses Node pipes and buffers, it can handle super large files.

Usage

npm install lets-make-csvs

Use a github token, because this module is probably private

example

const async = require('async')
let lmcsv = require("lets-make-csvs")
 
let csv = new lmcsv("test.csv")
 
 
let myobj = [{
  "id": 1,
  "first_name": "Hartley",
  "last_name": "Mulvenna",
  "email": "hmulvenna0@delicious.com",
  "gender": "Male",
  "ip_address": "6.25.240.135",
  "hobbies": ["fishing", "camping", "hiking"]
}, {
  "id": 2,
  "first_name": "Antonio",
  "last_name": "Pigne",
  "email": "apigne1@feedburner.com",
  "gender": "Male",
  "ip_address": "102.234.210.24",
  "hobbies": ["bowling", "music"],
  "farm animals":{
    "pigs":3,
    "cows":{
      "male":2,
      "female":1
    },
    "horses":1
  }
}, {
  "id": 3,
  "first_name": "Gamaliel",
  "last_name": "Graser",
  "email": "ggraser2@nymag.com",
  "SAT score": 1420
}, {
  "id": 4,
  "first_name": "Celestyna",
  "last_name": "Pawels",
  "email": "cpawels3@home.pl",
  "gender": "Female",
  "ip_address": "18.17.253.197",
  "age": 22
}, {
  "id": 5,
  "first_name": "Mommy",
  "last_name": "Caitlin",
  "email": "mcaitlin4@smh.com.au",
  "gender": "Female",
  "ip_address": "213.145.160.242"
}, {
  "id": 6,
  "first_name": "Nettle",
  "last_name": "Mordey",
  "email": "nmordey5@ox.ac.uk",
  "gender": "Female",
  "ip_address": "178.58.2.233",
  "occupation":"Engineer"
}]
 
async.eachSeries(myobj, function eachRow(row, cb) {
  csv.writeRow(row, function(err) {
    if (err) return cb(err)
    return cb(null)
  })
}, function endEachRow(err) {
  if (err) throw err
  console.log("done")
})
 

output:

"id","first_name","last_name","email","gender","ip_address","hobbies","activites","crimes","age"
"1","Hartley","Mulvenna","hmulvenna0@delicious.com","Male","6.25.240.135","["fishing","camping","hiking"]
"2","Antonio","Pigne","apigne1@feedburner.com","Male","102.234.210.24"," ","["bowling","crime"]
"3","Gamaliel","Graser","ggraser2@nymag.com","Male","32.18.140.241"," "," ","{"theft":"misdemeanor","treason":"felony","attempted murder":"misdemeanor"}
"4","Celestyna","Pawels","cpawels3@home.pl","Female","18.17.253.197"," "," "," ","22"
"5","Mommy","Caitlin","mcaitlin4@smh.com.au","Female","213.145.160.242"," "," "," "," "
"6","Nettle","Mordey","nmordey5@ox.ac.uk","Female","178.58.2.233"," "," "," "," "

CSV result:

Open the result in your Excel or Google Sheets and you should see something like this:

id first_name last_name email gender ip_address hobbies farm animals SAT score age occupation
1 Hartley Mulvenna hmulvenna0@delicious.com Male 6.25.240.135 ["fishing","camping","hiking"]
2 Antonio Pigne apigne1@feedburner.com Male 102.234.210.24 ["bowling","music"] {"pigs":3,"cows":{"male":2,"female":1},"horses":1}
3 Gamaliel Graser ggraser2@nymag.com 1420
4 Celestyna Pawels cpawels3@home.pl Female 18.17.253.197 22
5 Mommy Caitlin mcaitlin4@smh.com.au Female 213.145.160.242
6 Nettle Mordey nmordey5@ox.ac.uk Female 178.58.2.233 Engineer

Todo:

  • Array method

Readme

Keywords

none

Package Sidebar

Install

npm i lets-make-csvs

Weekly Downloads

1

Version

0.0.10

License

ISC

Unpacked Size

11.2 kB

Total Files

7

Last publish

Collaborators

  • drj
  • jtruant