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CSV Challenge

You got your hands on some data that was leaked from a social network and you want to help the poor people.

Luckily you know a government service to automatically block a list of credit cards.

The service is a little old school though and you have to upload a CSV file in the exact format. The upload fails if the CSV file contains invalid data.

The CSV files should have two columns, Name and Credit Card. Also, it must be named after the following pattern:


The leaked data doesn't have credit card details for every user and you need to pick only the affected users.

The data was published here:


You don't have much time to act.

What tools would you use to get the data, format it correctly and save it in the CSV file?

Do you have a crazy vim configuration that allows you to do all of this inside your editor? Are you a shell power user and write this as a one-liner? How would you solve this in your favorite programming language?

Show your solution in the comments below!

Top comments (33)

thomasrayner profile image
Thomas Rayner

PowerShell to the rescue!

$json = invoke-webrequest '' | convertfrom-json

$json | select name,creditcard | export-csv "$(get-date -format yyyyMMdd).csv" -NoTypeInformation

elcotu profile image
Daniel Coturel

Excellent, man

tobias_salzmann profile image
Tobias Salzmann • Edited


curl -s \
| ramda 'filter where name: (complement isNil), creditcard: (complement isNil)' 'map (x) -> + ", " +' -o raw > `date +%Y%m%d.csv`


import{BufferedWriter, FileOutputStream, OutputStreamWriter}
import java.text.SimpleDateFormat
import java.util.Date

import io.circe.parser._

object Data extends App {
  case class CCInfo(name: Option[String], creditcard: Option[String])

  val url = ""
  val json =

  val infos = decode[List[CCInfo]](json).toOption.get

  val lines = infos.collect{case CCInfo(Some(name), Some(creditcard)) => s"$name, $creditcard"}

  Helper.writeToFile(lines, s"${Helper.formatDate("yyyyMMdd")}.csv")

object Helper {
  def writeToFile(lines: TraversableOnce[String], fileName: String): Unit = {
    val writer = new BufferedWriter(new OutputStreamWriter(new FileOutputStream(fileName)))
    for (x <- lines) {
      writer.write(x + "\n")

  def formatDate(format: String, date: Date = new Date()) = 
    new SimpleDateFormat(format).format(new Date())
ioayman profile image
Ayman Nedjmeddine • Edited

A oneliner if you're a linuxer 😉

curl -sSLo- \
| jq -r '.[] | {name: .name, creditcard: .creditcard} | join(",")' \
> `date +%Y%m%d`.csv

However, there is something you have not mentioned in your post: Should the CSV file have the header line?

If yes, then use this:

echo 'name,creditcard' > `date +%Y%m%d`.csv && \
curl -sSLo- \
| jq -r '.[] | {name: .name, creditcard: .creditcard} | join(",")' \
>> `date +%Y%m%d`.csv
sukima profile image
Devin Weaver

This adds quotes.

"Dax Brekke II,1234-2121-1221-1211"
"Brando Stanton Jr.,1228-1221-1221-1431"
"Lacey McDermott PhD,"
"Elza Bauch,"

Maybe adding this sed command:

curl -sSLo- \
| jq '.[] | {name: .name, creditcard: .creditcard} | join(",")' \
| sed -e 's/^"//' -e 's/"$//' -e 's/\\"/"/g' \
> "$(date +%Y%m%d).csv"
rmetzler profile image
Richard Metzler

Doesn't the second solution need a >> in the last line, so the output is appended?

ioayman profile image
Ayman Nedjmeddine

Yes, it does. (Didn't copy the correct version)

Thanks ☺

mindflavor profile image
Francesco Cogno

Aaaand Rust :)

Really an overkill for this task but fun nevertheless!

extern crate chrono;
extern crate csv;
extern crate futures;
extern crate hyper;
extern crate hyper_tls;
extern crate serde;
extern crate serde_derive;
extern crate serde_json;
extern crate tokio_core;

use futures::prelude::*;
use futures::future::ok;
use tokio_core::reactor::Core;
use hyper::client::Client;
use hyper_tls::HttpsConnector;
use chrono::{DateTime, FixedOffset};
use std::collections::HashMap;
use csv::Writer;
use std::fs::File;

#[derive(Debug, Deserialize, Clone)]
struct Record {
    name: String,
    email: Option<String>,
    city: Option<String>,
    mac: String,
    timestamp: String,
    creditcard: Option<String>,

#[derive(Debug, Clone)]
struct RecordParsed {
    record: Record,
    ts: DateTime<FixedOffset>,

const FORMAT: &'static str = "%Y%m%d";

fn main() {
    let mut core = Core::new().unwrap();
    let client = Client::configure()
        .connector(HttpsConnector::new(4, &core.handle()).unwrap())

    let uri = ""

    let fut = client.get(uri).and_then(move |resp| {
        resp.body().concat2().and_then(move |body| {
            let array: Vec<Record> = serde_json::from_slice(&body as &[u8]).unwrap();
            let mut a_parsed: HashMap<String, Vec<RecordParsed>> = HashMap::new();

                .map(|item| {
                    let dt =
                        DateTime::parse_from_str(&item.timestamp, "%Y-%m-%d %H:%M:%S %z").unwrap();

                    let rp = RecordParsed {
                        record: item,
                        ts: dt,

                    let date_only = format!("{}.csv", rp.ts.format(FORMAT).to_string());

                    let ret = match a_parsed.get_mut(&date_only) {
                        Some(ar) => {
                        None => {
                            let mut ar: Vec<RecordParsed> = Vec::new();

                    if let Some(ar) = ret {
                        a_parsed.insert(date_only, ar);

                .map(|(key, array)| {
                    println!("generating file == {:?}", key);
                    let file = File::create(key).unwrap();
                    let mut wr = Writer::from_writer(file);

                        .map(|record| {
                            let creditcard = match {
                                Some(ref c) => c,
                                None => panic!("should have filtered those!"),
                            wr.write_record(&[&, creditcard]).unwrap();

tzurbaev profile image
Timur Zurbaev



$json = json_decode(file_get_contents(''), true);

$users = array_filter($json, function (array $item) {
    return !empty($item['name']) && !empty($item['creditcard']);

$file = fopen(date('Ymd').'.csv', 'w+');

foreach ($users as $user) {
    fputcsv($file, [$user['name'], $user['creditcard']]);

simplymichael profile image
Michael Orji • Edited

You beat me to the PHP implementation. And your solution is so elegant.

sukima profile image
Devin Weaver

Since the input JSON could be really large, here is a Node.JS steaming version (using stream-json package):

#!/usr/bin/env node
let fs = require('fs');
let { Transform } = require('stream');
let StreamArray = require("stream-json/utils/StreamArray");
let stream = StreamArray.make();

function escapeCSV(str) {
  if (str == null) { return ''; }
  return /[",]/.test(str) ? `"${str.replace(/"/g, '\\"')}"` : str;

class CsvStream extends Transform {
  constructor() {
    super({objectMode: true});
  _transform(chunk, enc, cb) {
    let { name, creditcard } = chunk.value;
    let line = [name, creditcard].map(escapeCSV).join(',');


  .pipe(new CsvStream())
jorinvo profile image

Nice! There is also csv-write-stream then you can save some code :)

rpalo profile image
Ryan Palo

Using the CSV module to avoid any quoting pitfalls. :)

require 'CSV'
require 'date'
require 'JSON'

data = JSON.parse(`curl #{ARGV[0]}`)
filename ='%Y%m%d') + '.csv'"#{filename}.csv", 'w') do |csv|
    .select { |item| item['name'] && item['creditcard'] }
    .map { |item| [item['name'], item['creditcard']] }
    .each { |item| csv << item }
jorinvo profile image
jorin • Edited

Ruby is still one of the most pretty languages!
Maybe you can use the open(url).read from require 'open-uri' instead of curl to allow it to run on other systems 🙂

Alernatively could look like this: "#{ '%Y%m%d'}.csv", 'w' do |csv|
  JSON.parse(open(ARGV[0]).read).each { |x| csv << x if x['creditcard'] }
rpalo profile image
Ryan Palo

Oh, I like that!

  1. I didn't know about those extra options for CSV. Awesome.
  2. I didn't know about the open-uri built-in. Also awesome.
  3. I love the short and sweet each block! It even feels a little Pythonic, which is nice. Also also awesome!
joshcheek profile image
Josh Cheek


A few things to note: cache is a program I wrote that caches command-line invocations, it's to make it cheap to iterate (e.g. so you don't have to hit the network each time)

My shell is fish ( which allows multi-line editing, and the parentheses in fish are like backticks in bash, so the > (...) is redirecting the output into a file whose name is the result of the ...

r0f1 profile image
Florian Rohrer

Nice post!

import json
from csv import DictWriter

with open("data.json", "r") as f:
    users = json.load(f)

cols = ["name", "creditcard"]
with open("20150425.csv", "w", newline='') as f:
    dw = DictWriter(f, cols)
    for u in users:
        if u["creditcard"]:
            dw.writerow({k: u[k] for k in cols})

All users share the same date. So I didn't bother and didn't write into separate files.
Another thing, I was going to write "Hey, that's not valid json you are giving us.", because I saw the objects are in a list and that list is not wrapped into an outer object. But my Python parser did not complain, so it turns out valid. You learn something new every day.

jorinvo profile image
jorin • Edited

Having arrays on the top-level of JSON documents is indeed valid although it is definitely an anti-pattern. By doing so you block yourself from adding any meta information in the future.
If you build an API, you always want to wrap an array in an object. Then you can add additional fields like possible errors or pagination later on.

  "data": [],
  "status": "not ok",
  "error": { "code": 123, "message": "..." },
  "page": 42
tobias_salzmann profile image
Tobias Salzmann

Personally, I'd prefer the array in most cases. If I call an endpoint called customers, I would expect it to return an array of customers, not something that contains such an array, might or might not have an error and so on.
If I want to stream the response, I'd also be better off with an array, because whatever streaming library I use probably supports it.

tobias_salzmann profile image
Tobias Salzmann • Edited

Seems like json can have an array at the root, even according to the first standard:, section 2

alad profile image
Al • Edited



frames <- fromJSON("")
frames <- frames[!$creditcard),]
frames <- frames[,c("name","creditcard")]

write.csv(frames, file="20171112.csv", row.names=FALSE)
niemandag profile image

I set myself a time limit of 15 minutes, with no google. I did not know how to download using python, so i used wget or powershell. The rest is straight forward.

#!/usr/bin/env python3
import json
from datetime import datetime
import os
from sys import platform

URL = ""

if platform == "linux" or platform == "linux2" or platform == "darwin":
    os.system("wget -O data.json %s" % URL)
elif platform == "win32" or platform == "win64":
    os.system("powershell Invoke-WebRequest -Uri %s -OutFile data.json" % URL)

with open('data.json', 'r') as input_file:
    input_data = json.load(input_file)

with open('%s.csv' %'%Y%m%d'), 'w') as output_file:
    for victim in input_data:
        if victim['creditcard']:
            output_file.write("%s,%s\n" % (victim['name'], victim['creditcard']))
thorstenhirsch profile image
Thorsten Hirsch • Edited

Well, at work I would use a tool called "IBM Transformation Extender", which is specialised on data transformation. It breaks the job down into 3 tasks:

  1. create the csv output format (there's a gui for that)
  2. import some example json data in order to create the input format
  3. develop the "map" by configuring 1 as output, 2 as input, and the following "mapping rule" for the transformation:
=f_record(EXTRACT(Record:json, PRESENT(creditcard:.:json)))

...and in f_record() one would simply drag'n'drop the name and the credit card fields from the input to the output.

Not the cheapest solution, obviously, but its maintainability is great if you have hundreds of these mappings.

wolpear profile image
Jakub Karczewski • Edited

Since I started learning Ruby this week my solution written in it :D

require 'open-uri'
require 'json'

url = ""
data = JSON.parse(open(url).read)
i = 0"%Y%m%d") + ".csv", "w") do |f|
    f.write("Name,\"Credit Card\"")
    data.each do |record|
        if record["creditcard"]
            name = record["name"].match(/\s/) ? "\""+ record["name"] +"\"" : record["name"]

printf("Created CSV file, %d affected accounts detected", i)

Thanks for another great challenge Jorin :)

sukima profile image
Devin Weaver

A vanilla Node.JS version:

#!/usr/bin/env node

function escapeCSV(str) {
  if (str == null) { return ''; }
  return /[",]/.test(str) ? `"${str.replace(/"/g, '\\"')}"` : str;

let data = require('./sample.json');
process.stdout.write('Name,Credit Card\n');
for (let { name, creditcard } of data) {
  let line = [name, creditcard].map(escapeCSV).join(',');
curusarn profile image
Šimon Let • Edited


curl "" 2>/dev/null | \
 jq '.[] | .name +","+ .creditcard' --raw-output > `date +"%Y%m%d.csv"`