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Readme
Object-Flatify
Transforms nested objects and arrays into a single-level structure with dot notation keys, including array indices. This simplifies hierarchical data for tabular formats like CSV or Excel, aiding data manipulation, analysis, and export for reporting or visualization.
Table of Contents
Installation
npm install object-flatifyUsage
TypeScript:
import * as objectFlatify from "object-flatify";
import { ObjectFlattener } from "object-flatify";JavaScript:
const objectFlatify = require("object-flatify");
const { ObjectFlattener } = require("object-flatify");ObjectFlattener.toDotNotation(input)
Flattens a nested object into a single-level object with dot notation keys.
Parameters
input:Object- A valid JavaScript object (e.g.,
{ a: { b: { c: 1 } } }).
- A valid JavaScript object (e.g.,
Returns
Object- A single-level object (e.g.,
{ 'a.b.c': 1 }).
- A single-level object (e.g.,
ObjectFlattener.toDataTableFromObject(input, [options])
Flattens a nested object into an array of single-level objects for tabular data.
Parameters
input:Object- A valid JavaScript object.
options:Object(Optional)batchSize:number- Processes data in chunks for memory optimization.keysAsColumn:boolean- Generates columns from object keys.
Returns
Array of Object- Array of single-level objects with dot notation keys.
ObjectFlattener.toDataTableFromListAsStream(input, [options])
Flattens a list of nested objects into a stream of single-level objects.
Parameters
input:Object[]- Array of valid JavaScript objects.
options:Object(Optional)batchSize:number- Processes data in chunks.keysAsColumn:boolean- Generates columns from object keys.
Returns
Readable Stream- Emits events with:
data: Array of single-level objects.dataSetLength: Total dataset length.dataProcessed: Count of processed items.completed: Boolean indicating completion.
- Emits events with:
ObjectFlattener.toDataTableFromFile(input, [options])
Flattens a JSON file (local or remote URL) into a stream of single-level objects.
Parameters
input:string- Path or URL to a JSON file (e.g.,
./file.jsonorhttps://example.com/file.json).
- Path or URL to a JSON file (e.g.,
options:Object(Optional)batchSize:number- Processes data in chunks.keysAsColumn:boolean- Generates columns from object keys.
Returns
Readable Stream- Same event structure as
toDataTableFromListAsStream.
- Same event structure as
Examples
Dot Notation Conversion
const { ObjectFlattener } = require("object-flatify");
const DOCUMENT = {
company: {
name: "Tech Innovators Inc.",
departments: [
{
name: "R&D",
teams: [
{
name: "AI Team",
projects: [
{
projectId: "P001",
tasks: [{ taskId: "T1001", description: "Develop module" }],
},
],
},
],
},
],
},
};
const flattened = ObjectFlattener.toDotNotation(DOCUMENT);
console.log(flattened);
/*
{
'company.name': 'Tech Innovators Inc.',
'company.departments[0].name': 'R&D',
'company.departments[0].teams[0].name': 'AI Team',
'company.departments[0].teams[0].projects[0].projectId': 'P001',
'company.departments[0].teams[0].projects[0].tasks[0].taskId': 'T1001',
'company.departments[0].teams[0].projects[0].tasks[0].description': 'Develop module'
}
*/Data Table Conversion
const flattened = ObjectFlattener.toDataTableFromObject(DOCUMENT, {
keysAsColumn: true,
});
console.log(flattened);
/*
{
keysAsColumn: Set(['company.name', 'company.departments.name', ...]),
data: [{
'company.name': 'Tech Innovators Inc.',
'company.departments.name': 'R&D',
'company.departments.teams.name': 'AI Team',
'company.departments.teams.projects.projectId': 'P001',
'company.departments.teams.projects.tasks.taskId': 'T1001',
'company.departments.teams.projects.tasks.description': 'Develop module'
}],
dataProcessed: 1,
dataSetLength: 1,
completed: true,
isError: false
}
*/Stream-Based Processing (List)
const { Readable } = require("stream");
const flattened$ = ObjectFlattener.toDataTableFromListAsStream(
[DOCUMENT, DOCUMENT],
{ keysAsColumn: true, batchSize: 1 }
);
flattened$.on("data", (data) => console.log("Chunk:", data));
flattened$.on("end", (data) => console.log("Completed:", data));
/*
Chunk: {
data: [{
'company.name': 'Tech Innovators Inc.',
'company.departments.name': 'R&D',
...
}],
keysAsColumn: Set([...]),
dataProcessed: 1,
dataSetLength: 2,
completed: false,
isError: false
}
Completed: {
keysAsColumn: Set([...]),
dataProcessed: 2,
dataSetLength: 2,
completed: true,
isError: false
}
*/File-Based Processing (Local or Remote)
const { Readable } = require("stream");
const { ObjectFlattener } = require("object-flatify");
// Local File
const localStream = ObjectFlattener.toDataTableFromFile(
"./dist/mock/file.json",
{ keysAsColumn: true }
);
localStream.on("data", (data) => console.log("Local Chunk:", data));
localStream.on("end", (data) => console.log("Local Completed:", data));
// Remote File
const remoteStream = ObjectFlattener.toDataTableFromFile(
"https://examples/file.json",
{ keysAsColumn: true }
);
remoteStream.on("data", (data) => console.log("Remote Chunk:", data));
remoteStream.on("end", (data) => console.log("Remote Completed:", data));
/*
Local Chunk: {
data: [
{ 'sepal.length': 7.4, 'sepal.width': 2.8, 'petal.length': 6.1, 'petal.width': 1.9, variety: 'Virginica' },
...
],
keysAsColumn: Set(['sepal.length', 'sepal.width', 'petal.length', 'petal.width', 'variety']),
dataProcessed: 10,
dataSetLength: 150,
completed: false,
isError: false
}
Local Completed: {
keysAsColumn: Set(['sepal.length', 'sepal.width', 'petal.length', 'petal.width', 'variety']),
dataProcessed: 150,
dataSetLength: 150,
completed: true,
isError: false
}
Remote Chunk: {
data: [
{ 'sepal.length': 7.4, 'sepal.width': 2.8, 'petal.length': 6.1, 'petal.width': 1.9, variety: 'Virginica' },
...
],
keysAsColumn: Set(['sepal.length', 'sepal.width', 'petal.length', 'petal.width', 'variety']),
dataProcessed: 10,
dataSetLength: 150,
completed: false,
isError: false
}
Remote Completed: {
keysAsColumn: Set(['sepal.length', 'sepal.width', 'petal.length', 'petal.width', 'variety']),
dataProcessed: 150,
dataSetLength: 150,
completed: true,
isError: false
}
*/Contributing
Contribute via GitHub:
- Report Issues: Open an issue at github.com/MakeAnIque/object-flattener/issues.
- Submit Pull Requests:
git clone https://github.com/MakeAnIque/object-flattener
License
MIT License. See LICENSE file.
Author
Created by Amitabh Anand.