Free Node.js Library to Open & Read Excel Files

Getting Started with read-excel-file

To install read-excel-file, you can use npm, the package manager for JavaScript. Please use the following commands for a successful installation.

npm install read-excel-file --save

Read Large Excel Files in Node.js Apps

Software developers often need to integrate Excel file reading capabilities into their applications. The open source read-excel-file library makes it easy for software developers to load and read small as well as large Excel files inside Node.js applications with just a couple of lines of code. It supports various file formats, including .xls and .xlsx, making it compatible with a wide range of Excel versions. Additionally, it handles parsing and formatting of data, ensuring that developers can easily access and manipulate the extracted information. The following basic example demonstrates how to read an Excel file in a Node.js environment using JavaScript commands.

const readXlsxFile = require('read-excel-file/node');

// Path to your Excel file
const filePath = 'path/to/your/excel-file.xlsx';

readXlsxFile(filePath).then((rows) => {
  // rows is an array of arrays representing the rows and columns of the Excel file
  console.log(rows);
}).catch((error) => {
  console.error('Error reading Excel file:', error);
});

Flexible Data Parsing in Node.js

The open source read-excel-file library has included complete support for flexible data parsing, enabling software developers to define custom schemas to interpret the data. This feature is particularly useful when dealing with complex Excel files that contain various data types and structures. By defining a schema, you can ensure that the data is parsed correctly and consistently. For more advanced scenarios, you can define a schema to map the Excel columns to specific data types and structures. The following example shows how software developers can define a custom schema to validate the structure and content of Excel files inside Node.js applications.

const schema = {
  'Column 1': {
    prop: 'column1',
    type: String,
    required: true
  },
  'Column 2': {
    prop: 'column2',
    type: Number
  }
};

readXlsxFile(filePath, { schema }).then(({ rows, errors }) => {
  if (errors.length > 0) {
    console.error('Validation errors:', errors);
  } else {
    console.log(rows);
  }
});

Custom Types and Date Parsing in Node.js

The read-excel-file library provides robust support for custom types and date parsing, which is especially useful when dealing with complex data structures in Excel files. This is a very useful feature and allows software developers to define how different data types, including dates, should be parsed, ensuring data integrity and consistency. To define a custom schema, you create an object where the keys are the column names from the Excel file, and the values describe the properties, types, and validation rules for those columns. In the below example the 'Event Date' column values are parsed into Date objects, and the toISOString method is used to format the dates as ISO strings.

const readXlsxFile = require('read-excel-file/node');

// Schema with date parsing
const schema = {
  'Event Date': {
    prop: 'eventDate',
    type: Date,
    required: true
  }
};

// Read and parse the Excel file with date parsing
readXlsxFile('path/to/file.xlsx', { schema }).then(({ rows, errors }) => {
  if (errors.length > 0) {
    console.error('Validation errors:', errors);
  } else {
    rows.forEach(row => {
      console.log(`Event Date: ${row.eventDate.toISOString()}`);
    });
  }
}).catch((error) => {
  console.error('Error reading Excel file:', error);
});

Better Error Handling Support

Robust error handling features are incorporated in the open-source read-excel-file package. Validation issues that arise while parsing are recorded and can be addressed or logged appropriately. To guarantee the integrity of the data being read, the library includes validation rules and offers clear error signals. This makes it easier for developers to find and fix problems with the data or the Excel file itself more rapidly.