A simple yet powerful tool that converts arrays of objects into clean Excel spreadsheets. It helps developers and data teams turn structured data into shareable Excel files quickly, without manual formatting or extra tooling.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project takes an array of JavaScript objects and converts it into a well-structured Excel file. It solves the common problem of exporting structured data into a spreadsheet format that’s easy to review, share, and analyze. It’s built for developers, analysts, and teams who regularly work with JSON-like data and need fast Excel output.
- Accepts arrays of objects where each object represents a row
- Automatically maps object keys to Excel columns
- Handles dynamic schemas without manual configuration
- Produces export-ready Excel files suitable for reporting
- Designed for reliability and repeatable data exports
| Feature | Description |
|---|---|
| Array-to-Excel conversion | Converts arrays of objects into structured Excel sheets automatically. |
| Dynamic column mapping | Uses object keys to generate column headers without manual setup. |
| Dataset-based export | Stores processed data in a dataset for flexible exporting. |
| Excel-ready output | Generates files compatible with standard spreadsheet tools. |
| Simple configuration | Minimal input required to produce consistent results. |
| Field Name | Field Description |
|---|---|
| sourceArray | The input array of objects to be converted into Excel rows. |
| object keys | Each key becomes a column header in the Excel file. |
| object values | Each value is written into the corresponding cell. |
[
{
"name": "John Doe",
"email": "[email protected]",
"age": 32,
"country": "USA"
},
{
"name": "Jane Smith",
"email": "[email protected]",
"age": 28,
"country": "UK"
}
]
Array to Excel/
├── src/
│ ├── index.js
│ ├── converters/
│ │ └── arrayToExcel.js
│ ├── utils/
│ │ └── fileWriter.js
│ └── config/
│ └── input.schema.json
├── data/
│ ├── input.sample.json
│ └── output.sample.xlsx
├── package.json
└── README.md
- Developers use it to export API response data, so they can share results with non-technical stakeholders.
- Data analysts use it to turn structured datasets into Excel files for quick review and filtering.
- Product teams use it to generate reports from application data, making insights easier to distribute.
- Agencies use it to automate client data exports, saving time on manual spreadsheet creation.
What input format does this project support? It supports arrays of plain objects. Each object should have consistent keys to produce clean column headers, though dynamic keys are also handled.
Can it handle large arrays? Yes, it’s designed to handle large datasets efficiently, though very large arrays may require more memory depending on the environment.
Do I need to define columns manually? No. Columns are generated automatically from the object keys in the array.
Is the Excel output compatible with common tools? Yes, the generated files work with standard spreadsheet software like Excel, LibreOffice, and Google Sheets.
Primary Metric: Converts thousands of rows into Excel format in under a few seconds for typical datasets.
Reliability Metric: Consistent output generation with a high success rate when provided valid array inputs.
Efficiency Metric: Optimized processing ensures low overhead during data transformation and file creation.
Quality Metric: Maintains full data fidelity, with accurate column mapping and complete row exports.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
|
"Exceptional results, clear communication, and flawless delivery. Syed
|