© Pradeep Mishra, Licensed under the MIT-LICENSE
var csvjson = require('csvjson');
/*
sample.csv
sr,name,age,gender
1,rocky,33,male
2,jacky,22,male
3,suzy,21,female
*/
/*
schema_sample.csv
created,contact.name,contact.age+,contact.number+,address[],address[],contact.hobbies[],contact.hobbies[],-id
2014-11-12,Pradeep,25,4352436,MG Road,Mumbai,pc games,guitar,5
2014-10-06,Arnav,16,7364537,KB Road,Mumbai,pc games,traveling,7
*/
/*
schema_sample2.csv
name,age,contacts[0].name,contacts[0].phone,contacts[1].name,contacts[1].phone,musician,instruments.past,instruments.current[],instruments.current[]
Mark,33,Jim Palmer,8888888888,Marcus Aurelius,7309899877,Yes,Guitar,Drums,Bass Guitar
Jeff,27,John Doe,8009008000,Michael Corleone,2121001000,Yes,Drums,Flute,Trumpet
*/
/*
jsoncsv.json
{
"book": {
"person": [
{
"firstName": "Jane",
"lastName": "Doe",
"age": "25",
"address": {
"streetAddress": "21 2nd Street",
"city": "Las Vegas",
"state": "NV",
"postalCode": "10021-3100"
},
"hobbies" : ["gaming", "volleyball"]
},
{
"firstName": "Agatha",
"lastName": "Doe",
"age": "25",
"address": {
"streetAddress": "21 2nd Street",
"city": "Las Vegas",
"state": "NV",
"postalCode": "10021-3100"
},
"hobbies" : ["dancing", "politics"]
}
]
}
}
*/
var data = fs.readFileSync(path.join(__dirname, 'schema_sample2.csv'), { encoding : 'utf8'});
/*
{
delimiter : <String> optional default is ","
quote : <String|Boolean> default is null
}
*/
var options = {
delimiter : ',', // optional
quote : '"' // optional
};
// for multiple delimiter you can use regex pattern like this /[,|;]+/
/*
for importing headers from different source you can use headers property in options
var options = {
headers : "sr,name,age,gender"
};
*/
csvjson.toObject(data, options);
/*
returns
[
{
sr : 1,
name : "rocky",
age : 33,
gender : "male"
},
{
sr : 2,
name : "jacky",
age : 22,
gender : "male"
},
{
sr : 3,
name : "suzy",
age : 21,
gender : "female"
}
]
*/
/*
for creating schema of json object following key can be used in header of csv file:
. for defining nested json object
[] for defining data as array (suffix)
-- can add delimiter in the array (i.e. [;] for delimiter of ;)
-- can nest objects in the array, index must be listed (i.e. [1] for index 1)
+ for defining data as integer (suffix)
- for omitting data from result output (prefix)
*/
/*
schema_sample.csv
created,contact.name,contact.age+,contact.number+,address[],address[],contact.hobbies[;],-id,friends[0].name,friends[0].phone,friends[1].name,friends[1].phone
2014-11-12,Pradeep,25,4352436,MG Road,Mumbai,pc games; guitar,5,Jeff,8761234567,Mike,1234567890
2014-10-06,Arnav,16,7364537,KB Road,Mumbai,pc games; traveling,7,Steve,555555555,Pradeep,4352436
*/
var data = fs.readFileSync(path.join(__dirname, 'schema_sample.csv'), { encoding : 'utf8'});
/*
{
delimiter : <String> optional default is ","
quote : <String|Boolean> default is null
}
*/
var options = {
delimiter : ',', // optional
quote : '"' // optional
};
// for multiple delimiter you can use regex pattern like this /[,|;]+/
/*
for importing headers from different source you can use headers property in options
var options = {
headers : "created,contact.name,contact.age+,contact.number+,address[],address[],contact.hobbies[;],-id,friends[0].name,friends[0].phone,friends[1].name,friends[1].phone"
};
*/
csvjson.toSchemaObject(data, options)
/*
returns
[
{
"created":"2014-11-12",
"contact":{
"name":"Pradeep","
age":25,
"number":4352436,
"hobbies":["pc games","guitar"]
},
"address":["MG Road","Mumbai"],
"friends":[
{
"name": "Jeff",
"phone": "8761234567"
},
{
"name": "Mike",
"phone": "1234567890"
}
]
},
{
"created":"2014-10-06",
"contact":{"
name":"Arnav",
"age":16,
"number":7364537,
"hobbies":["pc games","traveling"]
},
"address":["KB Road","Mumbai"],
"friends":[
{
"name": "Steve",
"phone": "5555555555"
},
{
"name": "Pradeep",
"phone": "4352436"
}
]
}
]
*/
var data = fs.readFileSync(path.join(__dirname, 'sample.csv'), { encoding : 'utf8'});
/*
{
delimiter : <String> optional default is ","
quote : <String|Boolean> default is null
}
*/
var options = {
delimiter : ',', // optional
quote : '"' // optional
};
// for multiple delimiter you can use regex pattern like this /[,|;]+/
csvjson.toArray(data, options);
/*
returns
[
["sr","name","age","gender"],
["1","rocky","33","male"],
["2","jacky","22","male"],
["3","suzy","21","female"]
]
*/
var data = fs.readFileSync(path.join(__dirname, 'sample.csv'), { encoding : 'utf8'});
/*
{
delimiter : <String> optional default is ","
quote : <String|Boolean> default is null
}
*/
var options = {
delimiter : ',', // optional
quote : '"' // optional
};
// for multiple delimiter you can use regex pattern like this /[,|;]+/
/*
for importing headers from different source you can use headers property in options
var options = {
headers : "sr,name,age,gender"
};
*/
csvjson.toColumnArray(data, options);
/*
returns
{
sr: [ '1', '2', '3' ],
name: [ 'rocky', 'jacky', 'suzy' ],
age: [ '33', '22', '21' ],
gender: [ 'male', 'male', 'female' ]
}
*/
var data = fs.readFileSync(path.join(__dirname, 'jsoncsv.json'), { encoding : 'utf8'});
var options = {
delimiter : ",",
wrap : false
}
/* supported options
delimiter = <String> optional default value is ","
wrap = <String|Boolean> optional default value is false
headers = <String> optional supported values are "full", "none", "relative", "key"
objectDenote = <String> optional default value is "."
arrayDenote = <String> optional default value is "[]"
*/
csvjson.toCSV(data, options);
/*
returns
book.person[].firstName,book.person[].lastName,book.person[].age,book.person[].address.streetAddress,book.person[].address.city,book.person[].address.state,book.person[].address.postalCode,book.person[].hobbies[]
Jane,Doe,25,21 2nd Street,Las Vegas,NV,10021-3100,gaming;volleyball
Agatha,Doe,25,21 2nd Street,Las Vegas,NV,10021-3100,dancing;politics
*/
var read = fs.createReadStream(path.join(__dirname, 'sample.csv'));
var write = fs.createWriteStream(path.join(__dirname, 'sample.json'));
var toObject = csvjson.stream.toObject();
var stringify = csvjson.stream.stringify();
read.pipe(toObject).pipe(stringify).pipe(write);
/*
following functions available for stream transformation
csvjson.stream.toObject()
csvjson.stream.toArray()
csvjson.stream.toColumnArray()
csvjson.stream.toSchemaObject()
*/
/*
csvjson.stream.stringify([space<number>])
stringify function accepts optional space parameter to format output
*/
npm install csvjson --save
FAQs
convert csv to json and json to csv
The npm package csvjson receives a total of 52,476 weekly downloads. As such, csvjson popularity was classified as popular.
We found that csvjson demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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