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CSV Challenge

jorinvo profile image jorin ・1 min read

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:

YYYYMMDD.csv.

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:

data.json

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!

Posted on by:

Discussion

markdown guide
 

PowerShell to the rescue!

$json = invoke-webrequest 'gist.githubusercontent.com/jorinvo...' | convertfrom-json

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

 
 

ramda-cli:

curl -s https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json \
| ramda 'filter where name: (complement isNil), creditcard: (complement isNil)' 'map (x) -> x.name + ", " + x.creditcard' -o raw > `date +%Y%m%d.csv`

scala:

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

import io.circe.generic.auto._
import io.circe.parser._

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

  val url = "https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json"
  val json = scala.io.Source.fromURL(url).mkString

  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")
    }
    writer.close()
  }

  def formatDate(format: String, date: Date = new Date()) = 
    new SimpleDateFormat(format).format(new Date())
} 
 

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;
#[macro_use]
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())
        .build(&core.handle());

    let uri = "https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json"
        .parse()
        .unwrap();

    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();

            array
                .into_iter()
                .filter(|item| item.creditcard.is_some())
                .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) => {
                            ar.push(rp);
                            None
                        }
                        None => {
                            let mut ar: Vec<RecordParsed> = Vec::new();
                            ar.push(rp);
                            Some(ar)
                        }
                    };

                    if let Some(ar) = ret {
                        a_parsed.insert(date_only, ar);
                    }
                })
                .collect::<()>();

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

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

            ok(())
        })
    });

    core.run(fut).unwrap();
}
 

A oneliner if you're a linuxer 😉

curl -sSLo- https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json \
| 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- https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json \
| jq -r '.[] | {name: .name, creditcard: .creditcard} | join(",")' \
>> `date +%Y%m%d`.csv
 

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- https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json \
| jq '.[] | {name: .name, creditcard: .creditcard} | join(",")' \
| sed -e 's/^"//' -e 's/"$//' -e 's/\\"/"/g' \
> "$(date +%Y%m%d).csv"
 

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

 

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

Thanks ☺

 

PHP:

<?php

$json = json_decode(file_get_contents('https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json'), 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']]);
}

fclose($file);
 

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

 

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(',');
    this.push(`${line}\n`);
    cb();
  }
}

process.stdin
  .pipe(stream.input);

stream.output
  .pipe(new CsvStream())
  .pipe(process.stdout);
 

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

 

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

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

data = JSON.parse(`curl #{ARGV[0]}`)
filename = Date.today.strftime('%Y%m%d') + '.csv'

CSV.open("#{filename}.csv", 'w') do |csv|
  data
    .select { |item| item['name'] && item['creditcard'] }
    .map { |item| [item['name'], item['creditcard']] }
    .sort
    .each { |item| csv << item }
end
 

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:

CSV.open "#{Date.today.strftime '%Y%m%d'}.csv", 'w' do |csv|
  JSON.parse(open(ARGV[0]).read).each { |x| csv << x if x['creditcard'] }
end
 

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!
 

solution

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) github.com/JoshCheek/dotfiles/blob...

My shell is fish (fishshell.com) 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 ...

 

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)
    dw.writeheader()
    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.

 

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.
e.g.

{
  "data": [],
  "status": "not ok",
  "error": { "code": 123, "message": "..." },
  "page": 42
}
 

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.

 

Seems like json can have an array at the root, even according to the first standard: tools.ietf.org/html/rfc4627, section 2

 

Here is my take in this challenge in PHP.

<?php
    // Getting Data.json contents
    $inMemoryData = file_get_contents("https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json");
    $convertToArray = json_decode($inMemoryData);
    echo "Whole Data Count ".count($convertToArray).PHP_EOL;
    // Filtering th data using array_filter method
    // $filteredData = array_filter($convertToArray, function ($arr){
    //     return !empty($arr->creditcard) ? 1 : 0;
    // });
    // Create a file to save data
    $fileHandle = fopen(date("Ymd").".csv", "w");
    // Save Array of to CSV
    fputcsv($fileHandle, ["Name", "Credit Card"]);
    // Filtering data
    foreach ($convertToArray as $data) {
        if (!empty($data->creditcard)) {
            fputcsv($fileHandle, [
                $data->name,
                $data->creditcard
            ]);
        }
    }
    echo "Completed. ".PHP_EOL;
?>
 

R

library("jsonlite")

frames <- fromJSON("https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json")
frames <- frames[!is.na(frames$creditcard),]
frames <- frames[,c("name","creditcard")]

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

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 = "https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json"

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' % datetime.today().strftime('%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']))
 

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.

 

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

require 'open-uri'
require 'json'

url = "https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json"
data = JSON.parse(open(url).read)
i = 0

File.open(DateTime.now.strftime("%Y%m%d") + ".csv", "w") do |f|
    f.write("Name,\"Credit Card\"")
    data.each do |record|
        if record["creditcard"]
            i+=1
            name = record["name"].match(/\s/) ? "\""+ record["name"] +"\"" : record["name"]
            f.write("\n"+name+","+record["creditcard"])
        end    
    end 
end

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

Thanks for another great challenge Jorin :)

 

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(',');
  process.stdout.write(`${line}\n`);
}
 

Oneliner:

curl "https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json" 2>/dev/null | \
 jq '.[] | .name +","+ .creditcard' --raw-output > `date +"%Y%m%d.csv"`
 
require "json"
require "open-uri"
url = "https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json"
data = JSON.parse(open(url).read)

filtered_data = data.select { |line| not line["creditcard"].nil? }
file = File.open(DateTime.now.strftime("%Y%m%d") + ".csv", 'w')
file.write "Name,Creditcart\n"
filtered_data.each do |line|
    file.write [line["name"], line["creditcard"]].join(',')
    file.write("\n")
end

Or if you guys line nasty oneliners (requre statements don't count)

require "json"
require "open-uri"
File.open(DateTime.now.strftime("%Y%m%d") + ".csv", 'w') { |file| file.write "Name,Creditcard\n"; JSON.parse(open("https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json").read).select { |line| not line["creditcard"].nil? }.each { |line| file.write "#{line['name']},#{line['creditcard']}\n" } }

I'm trying to do it in Elixir now :D

 

Perl 6? :

use JSON::Fast;

my $json = 'data.json'.IO.slurp;

my $d = Date.today;
my $out-filename = sprintf "%04i%02i%02i.csv", $d.year, $d.month, $d.day;

my $out = $out-filename.IO.open(:w);

for from-json($json).list -> %row {
    if %row<creditcard> {
        $out.say: %row<name>, ',', %row<creditcard>;
    }
}
$out.close;

Of course in reality you'd probably want to use Text::CSV to properly format the CSV output in order to handle quoting and escaping properly.

 

Almost all (except 2 at this time) submission writes csv by hand, not using library. The output will not be valid if a value contains , or "

 

True. I have not thought of that.
I open the csv in LibreOffice, to make sure it comes out fine, but with really big files, it might not be possible.

 

awk:

awk '
    BEGIN {FS=",";OFS=","}
    /creditcard/ {
        split($1,namearr,":")
        name = namearr[2]; gsub(/"/,"",name)
        split($5,dtarr,":")
        dt = dtarr[2]; gsub(/"| .+|-/,"",dt)
        split($6,ccarr,":")
        cc = ccarr[2]; gsub(/"|}/,"",cc)
        fname=dt ".csv"
        print name, cc >> fname
    }
' data.json
 
import csv
import requests

LEAK_URL = 'https://gist.githubusercontent.com/jorinvo/7f19ce95a9a842956358/raw/e319340c2f6691f9cc8d8cc57ed532b5093e3619/data.json'

with open('20171112.csv', 'w') as csv_file:
    writer = csv.DictWriter(csv_file, ['Name', 'Credit Card'])
    writer.writeheader()
    writer.writerows(
        {'Name':x['name'],'Credit Card':x['creditcard']} for x in requests.get(LEAK_URL).json() if x['creditcard']
    )
 

Just leaving a note here for everyone that would like see more tools and solutions. Checkout the original CSV Challenge.