Many business applications today need the ability to scan barcodes and QR codes in ASP.NET environments. From ticket validation and payment processing to inventory management, an ASP.NET QR code scanner or barcode reading feature can greatly improve efficiency and accuracy for both web and enterprise systems.

This tutorial demonstrates how to build a complete solution to scan barcodes in ASP.NET with C# code using Spire.Barcode for .NET. We’ll create an ASP.NET Core web application that can read both QR codes and various barcode formats from uploaded images, delivering high recognition accuracy and easy integration into existing projects.

Guide Overview

• 1. Project Setup
• 2. Implementing QR Code and Barcode Scanning Feature with C# in ASP.NET
• 3. Testing and Troubleshooting
• 4. Extending to Other .NET Applications
• 5. Conclusion

1. Project Setup

Step 1: Create the Project

Create a new ASP.NET Core Razor Pages project, which will serve as the foundation for the scanning feature. Use the following command to create a new project or manually configure it in Visual Studio:

dotnet new webapp -n QrBarcodeScanner
cd QrBarcodeScanner

Step 2: Install Spire.Barcode for .NET

Install the Spire.Barcode for .NET NuGet package, which supports decoding a wide range of barcode types with a straightforward API. Search for the package in the NuGet Package Manager or use the command below to install it:

dotnet add package Spire.Barcode

Spire.Barcode for .NET offers built-in support for both QR codes and multiple barcode formats such as Code128, EAN-13, and Code39, making it suitable for ASP.NET Core integration without requiring additional image processing libraries. To find out all the supported barcode types, refer to the BarcodeType API reference.

You can also use Free Spire.Barcode for .NET for smaller projects.

2. Implementing QR Code and Barcode Scanning Feature with C# in ASP.NET

A reliable scanning feature involves two main parts:

1. Backend logic that processes and decodes uploaded images.
2. A simple web interface that lets users upload files for scanning.

We will first focus on the backend implementation to ensure the scanning process works correctly, then connect it to a minimal Razor Page frontend.

Backend: QR & Barcode Scanning Logic with Spire.Barcode

The backend code reads the uploaded file into memory and processes it with Spire.Barcode, using either a memory stream or a file path. The scanned result is then returned. This implementation supports QR codes and other barcode types without requiring format-specific logic.

Index.cshtml.cs

using Microsoft.AspNetCore.Mvc;
using Microsoft.AspNetCore.Mvc.RazorPages;
using Spire.Barcode;

public class IndexModel : PageModel
{
    [BindProperty]
    public IFormFile Upload { get; set; }  // Uploaded file

    public string Result { get; set; }     // Scanning result
    public string UploadedImageBase64 { get; set; } // Base64 string for preview

    public void OnPost()
    {
        if (Upload != null && Upload.Length > 0)
        {
            using (var ms = new MemoryStream())
            {
                // Read the uploaded file into memory
                Upload.CopyTo(ms);

                // Convert the image to Base64 for displaying in HTML <img>
                UploadedImageBase64 = "data:" + Upload.ContentType + ";base64," +
                                      Convert.ToBase64String(ms.ToArray());

                // Reset the stream position before scanning
                ms.Position = 0;

                // Scan the barcode or QR code from the stream
                try
                {
                    string[] scanned = BarcodeScanner.Scan(ms);
                    // Return the scanned result
                    Result = scanned != null && scanned.Length > 0
                        ? string.Join(", ", scanned)
                        : "No code detected.";
                }
                catch (Exception ex)
                {
                    Result = "Error while scanning: " + ex.Message;
                }
            }
        }
    }
}

Explanation of Key Classes and Methods

• BarcodeScanner: A static class in Spire.Barcode that decodes images containing QR codes or barcodes.
• BarcodeScanner.Scan(Stream imageStream): Scans an uploaded image directly from a memory stream and returns an array of decoded strings. This method scans all barcodes in the given image.
• Supplementary methods (optional):
  • BarcodeScanner.Scan(string imagePath): Scans an image from a file path.
  • BarcodeScanner.ScanInfo(string imagePath): Scans an image from a file path and returns additional barcode information such as type, location, and data.

These methods can be used in different ways, depending on the application requirements.

Frontend: QR & Barcode Upload & Scanning Result Interface

The following page design provides a simple upload form where users can submit an image containing a QR code or barcode. Once uploaded, the image is displayed along with the recognized result, which can be copied with a single click. The layout is intentionally kept minimal for fast testing, yet styled for a clear and polished presentation.

Index.cshtml

@page
@model IndexModel
@{
    ViewData["Title"] = "QR & Barcode Scanner";
}

<div style="max-width:420px;margin:40px auto;padding:20px;border:1px solid #ccc;border-radius:8px;background:#f9f9f9;">
    <h2>QR & Barcode Scanner</h2>
    <form method="post" enctype="multipart/form-data" id="uploadForm">
        <input type="file" name="upload" accept="image/*" required onchange="this.form.submit()" style="margin:10px 0;" />
    </form>

    @if (!string.IsNullOrEmpty(Model.UploadedImageBase64))
    {
        <div style="margin-top:15px;text-align:center;">
            <img src="/@Model.UploadedImageBase64" style="width:300px;height:300px;object-fit:contain;border:1px solid #ddd;background:#fff;" />
        </div>
    }

    @if (!string.IsNullOrEmpty(Model.Result))
    {
        <div style="margin-top:15px;padding:10px;background:#e8f5e9;border-radius:6px;">
            <b>Scan Result:</b>
            <p id="scanText">@Model.Result</p>
            <button type="button" onclick="navigator.clipboard.writeText(scanText.innerText)" style="background:#28a745;color:#fff;padding:6px 10px;border:none;border-radius:4px;">Copy</button>
        </div>
    }
</div>

Below is a screenshot showing the scan page after successfully recognizing both a QR code and a Code128 barcode, with the results displayed and a one-click copy button available.

This ASP.NET Core application can scan QR codes and other barcodes from uploaded images. If you're looking to generate QR codes or barcodes, check out How to Generate QR Codes in ASP.NET Core.

3. Testing and Troubleshooting

After running the application, test the scanning feature with:

• A QR code image containing a URL or plain text.
• A barcode image such as Code128 or EAN-13.

If recognition fails:

• Ensure the image has good contrast and minimal distortion.
• Use images of reasonable resolution (not excessively large or pixelated).
• Test with different file formats such as JPG, PNG, or BMP.
• Avoid images with reflections, glare, or low lighting.
• When scanning multiple barcodes in one image, ensure each code is clearly separated to improve recognition accuracy.

A good practice is to maintain a small library of sample QR codes and barcodes to test regularly after making code changes.

4. Extending to Other .NET Applications

The barcode scanning logic in this tutorial works the same way across different .NET application types — only the way you supply the image file changes. This makes it easy to reuse the core decoding method, BarcodeScanner.Scan(), in various environments such as:

• ASP.NET Core MVC controllers or Web API endpoints
• Desktop applications like WinForms or WPF
• Console utilities for batch processing

Example: Minimal ASP.NET Core Web API Endpoint — receives an image file via HTTP POST and returns decoded results as JSON:

[ApiController]
[Route("api/[controller]")]
public class ScanController : ControllerBase
{
    [HttpPost]
    public IActionResult Scan(IFormFile file)
    {
        if (file == null) return BadRequest("No file uploaded");
        using var ms = new MemoryStream();
        file.CopyTo(ms);
        ms.Position = 0;
        string[] results = BarcodeScanner.Scan(ms);
        return Ok(results);
    }
}

Example: Console application — scans a local image file and prints the decoded text:

string[] result = BarcodeScanner.Scan(@"C:\path\to\image.png");
Console.WriteLine(string.Join(", ", result));

This flexibility makes it simple for developers to quickly add QR code and barcode scanning to new projects or extend existing .NET applications.

5. Conclusion

This tutorial has shown how to implement a complete QR code and barcode scanning solution in ASP.NET Core using Spire.Barcode for .NET. From receiving uploaded images to decoding and displaying the results, the process is straightforward and adaptable to a variety of application types. With this approach, developers can quickly integrate reliable scanning functionality into e-commerce platforms, ticketing systems, document verification tools, and other business-critical web applications.

For more advanced scenarios, Spire.Barcode for .NET provides additional features such as customizing the recognition process, handling multiple image formats and barcode types, and more. Apply for a free trial license to unlock all the advanced features.

Download Spire.Barcode for .NET today and start building your own ASP.NET barcode scanning solution.

Optical Character Recognition (OCR) technology has become essential for developers working with scanned documents and image-based PDFs. In this tutorial, you learn how to perform OCR on PDFs in C# to extract text from scanned documents or images within a PDF using the Spire.PDF for .NET and Spire.OCR for .NET libraries. By transferring scanned PDFs into editable and searchable formats, you can significantly improve your document management processes.

Table of Contents :

• Why OCR is Needed for Scanned PDFs?
• Setting Up: Installing Required Libraries
• Performing OCR on Scanned PDFs
• Extracting Text from Images within PDFs
• Wrapping Up
• FAQs

Why OCR is Needed for Scanned PDFs?

Scanned PDFs are essentially image files —they contain pictures of text rather than actual selectable and searchable text content. When you scan a paper document or receive an image-based PDF, the text exists only as pixels , making it impossible to edit, search, or extract. This creates significant limitations for businesses and individuals who need to work with these documents digitally.

OCR technology solves this problem by analyzing the shapes of letters and numbers in scanned images and converting them into machine-readable text. This process transforms static PDFs into usable, searchable, and editable documents—enabling text extraction, keyword searches, and seamless integration with databases and workflow automation tools.

In fields such as legal, healthcare, and education, where large volumes of scanned documents are common, OCR plays a crucial role in document digitization, making important data easily accessible and actionable.

Setting Up: Installing Required Libraries

Before we dive into the code, let's first set up our development environment with the necessary components: Spire.PDF and Spire.OCR . Spire.PDF handles PDF operations, while Spire.OCR performs the actual text recognition.

Step 1. Install Spire.PDF and Spire.OCR via NuGet

To begin, open the NuGet Package Manager in Visual Studio, and search for "Spire.PDF" and "Spire.OCR" to install them in your project. Alternatively, you can use the Package Manager Console :

Install-Package Spire.PDF
Install-Package Spire.OCR

Step 2. Download OCR Models:

Spire.OCR requires pre-trained language models for text recognition. Download the appropriate model files for your operating system (Windows, Linux, or MacOS) and extract them to a directory (e.g., D:\win-x64).

• Windows x64
• Linux x64
• MacOS 10.15 and later

Important Note : Ensure your project targets x64 platform (Project Properties > Build > Platform target) as Spire.OCR only supports 64-bit systems.

Performing OCR on Scanned PDFs in C#

With the necessary libraries installed, we can now perform OCR on scanned PDFs. Below is a sample code snippet demonstrating this process.

using Spire.OCR;
using Spire.Pdf;
using Spire.Pdf.Graphics;
using System.Drawing;

namespace OCRPDF
{
    class Program
    {
        static void Main(string[] args)
        {
            // Create an instance of the OcrScanner class
            OcrScanner scanner = new OcrScanner();

            // Configure the scanner
            ConfigureOptions configureOptions = new ConfigureOptions
            {
                ModelPath = @"D:\win-x64", // Set model path
                Language = "English"        // Set language
            };

            // Apply the configuration options
            scanner.ConfigureDependencies(configureOptions);

            // Load a PDF document
            PdfDocument doc = new PdfDocument();
            doc.LoadFromFile(@"C:\Users\Administrator\Desktop\Input5.pdf");

            // Iterate through all pages
            for (int i = 0; i < doc.Pages.Count; i++)
            {
                // Convert page to image
                Image image = doc.SaveAsImage(i, PdfImageType.Bitmap);

                // Convert the image to a MemoryStream
                using (MemoryStream stream = new MemoryStream())
                {
                    image.Save(stream, System.Drawing.Imaging.ImageFormat.Png);
                    stream.Position = 0; // Reset the stream position

                    // Perform OCR on the image stream
                    scanner.Scan(stream, OCRImageFormat.Png);
                    string pageText = scanner.Text.ToString();

                    // Save extracted text to a separate file
                    string outputTxtPath = Path.Combine(@"C:\Users\Administrator\Desktop\Output", $"Page-{i + 1}.txt");
                    File.WriteAllText(outputTxtPath, pageText);
                }
            }

            // Close the document
            doc.Close();
        }
    }
}

Key Components Explained :

1. OcrScanner Class : This class is crucial for performing OCR. It provides methods to configure and execute the scanning operation.
2. ConfigureOptions Class : This class is used to set up the OCR scanner's configurations. The ModelPath property specifies the path to the OCR model files, and the Language property allows you to specify the language for text recognition.
3. PdfDocument Class : This class represents the PDF document. The LoadFromFile method loads the PDF file that you want to process.
4. Image Conversion : Each PDF page is converted to an image using the SaveAsImage method. This is essential because OCR works on image files.
5. MemoryStream : The image is saved into a MemoryStream , allowing us to perform OCR without saving the image to disk.
6. OCR Processing : The Scan method performs OCR on the image stream. The recognized text can be accessed using the Text property of the OcrScanner instance.
7. Output : The extracted text is saved to a text file for each page.

Output :

To extract text from searchable PDFs, refer to this guide: Automate PDF Text Extraction Using C#

Extracting Text from Images within PDFs in C#

In addition to processing entire PDF pages, you can also extract text from images embedded within PDFs. Here’s how:

using Spire.OCR;
using Spire.Pdf;
using Spire.Pdf.Graphics;
using System.Drawing;

namespace OCRPDF
{
    class Program
    {
        static void Main(string[] args)
        {
            // Create an instance of the OcrScanner class
            OcrScanner scanner = new OcrScanner();

            // Configure the scanner
            ConfigureOptions configureOptions = new ConfigureOptions
            {
                ModelPath = @"D:\win-x64", // Set model path
                Language = "English"        // Set language
            };

            // Apply the configuration options
            scanner.ConfigureDependencies(configureOptions);

            // Load a PDF document
            PdfDocument doc = new PdfDocument();
            doc.LoadFromFile(@"C:\Users\Administrator\Desktop\Input5.pdf");

            // Iterate through all pages
            for (int i = 0; i < doc.Pages.Count; i++)
            {
                // Convert page to image
                Image image = doc.SaveAsImage(i, PdfImageType.Bitmap);

                // Convert the image to a MemoryStream
                using (MemoryStream stream = new MemoryStream())
                {
                    image.Save(stream, System.Drawing.Imaging.ImageFormat.Png);
                    stream.Position = 0; // Reset the stream position

                    // Perform OCR on the image stream
                    scanner.Scan(stream, OCRImageFormat.Png);
                    string pageText = scanner.Text.ToString();

                    // Save extracted text to a separate file
                    string outputTxtPath = Path.Combine(@"C:\Users\Administrator\Desktop\Output", $"Page-{i + 1}.txt");
                    File.WriteAllText(outputTxtPath, pageText);
                }
            }

            // Close the document
            doc.Close();
        }
    }
}

Key Components Explained :

1. PdfImageHelper Class : This class is essential for extracting images from a PDF page. It provides methods to retrieve image information such as GetImagesInfo , which returns an array of PdfImageInfo objects.
2. PdfImageInfo Class : Each PdfImageInfo object contains properties related to an image, including the actual Image object that can be processed further.
3. Image Processing : Similar to the previous example, each image is saved to a MemoryStream for OCR processing.
4. Output : The extracted text from each image is saved to a separate text file.

Output:

Wrapping Up

By combining Spire.PDF with Spire.OCR , you can seamlessly transform scanned PDFs and image-based documents into fully searchable and editable text. Whether you need to process entire pages or extract text from specific embedded images, the approach is straightforward and flexible.

This OCR integration not only streamlines document digitization but also enhances productivity by enabling search, copy, and automated data extraction. In industries where large volumes of scanned documents are the norm, implementing OCR with C# can significantly improve accessibility, compliance, and information retrieval speed.

FAQs

Q1. Can I perform OCR on non-English PDFs?

Yes, Spire.OCR supports multiple languages. You can set the Language property in ConfigureOptions to the desired language.

Q2. What should I do if the output is garbled or incorrect?

Check the quality of the input PDF images. If the images are blurry or have low contrast, OCR may struggle to recognize text accurately. Consider enhancing the image quality before processing.

Q3. Can I extract text from images embedded within a PDF?

Yes, you can. Use a helper class to extract images from each page and then apply OCR to recognize text.

Q4. Can Spire.OCR handle handwritten text in PDFs?

Spire.OCR is primarily optimized for printed text. Handwriting recognition typically has lower accuracy.

Q5. Do I need to install additional language models for OCR?

Yes, Spire.OCR requires pre-trained language model files. Download and configure the appropriate models for your target language before performing OCR.

Get a Free License

To fully experience the capabilities of Spire.PDF for .NET and Spire.OCR for .NET without any evaluation limitations, you can request a free 30-day trial license.

Converting between Excel and JSON formats is a valuable skill for developers dealing with data exchange, API integration, and modern web applications.

Excel files (.xls, .xlsx) are excellent for organizing and analyzing tabular data, while JSON (JavaScript Object Notation) is lightweight, human-readable, and ideal for transmitting data across platforms.

In this step-by-step tutorial, you’ll learn how to seamlessly convert Excel to JSON and JSON to Excel in C# using the Spire.XLS for .NET library. Whether you’re exporting Excel data for frontend apps, feeding structured datasets into APIs, or importing JSON into spreadsheets, this guide provides clear explanations, complete code samples, and tips to help you get started quickly.

What You Will Learn

• Why Convert Between Excel and JSON Formats
• Prerequisites
• Installing Required Packages
• How to Convert Excel to JSON in C# .NET (Step-by-Step)
• How to Convert JSON to Excel in C# .NET (Step-by-Step)
• Tips and Best Practices
• Conclusion
• Further Reading
• FAQs

Why Convert Between Excel and JSON Formats?

Converting between Excel and JSON can be beneficial for several reasons:

• Data Exchange: JSON is a standard format for data interchange in web applications, making it easier to share data across platforms.
• Integration with APIs: Many web APIs require data in JSON format, necessitating conversion from Excel for seamless integration.
• Lightweight and Compact: JSON files are generally smaller in size compared to Excel files, leading to faster data transfer and reduced storage needs.
• Readability: JSON is human-readable and easier to understand, which can simplify data analysis and troubleshooting.
• Compatibility with NoSQL Databases: JSON format is commonly used in NoSQL databases, facilitating easy data migration and storage.

Prerequisites

Before we start, ensure you have the following:

• Visual Studio or any C# development IDE installed.
• .NET Framework or .NET Core installed.
• Spire.XLS package installed for handling Excel files.
• Newtonsoft.Json package installed for handling JSON serialization and deserialization.

Installing Required Packages

You can install the required packages using NuGet Package Manager in Visual Studio:

Install-Package Spire.XLS
Install-Package Newtonsoft.Json

How to Convert Excel to JSON in C# .NET (Step-by-Step)

Exporting Excel files to JSON format in C# involves extracting data from Excel spreadsheets and transforming it into a structured JSON string. This process is particularly useful for applications that require data interchange between web services or databases. Below are detailed steps to guide you through the conversion process.

Steps to Export Excel to JSON

1. Load the Excel File:
   • Begin by creating a Workbook object that will hold the Excel file's content using the Spire.XLS library. Load the Excel file into this object.
2. Access the Desired Worksheet:
   • Identify and access the specific worksheet from which you want to extract data. This is done by referencing the appropriate index of the Worksheets collection.
3. Export to DataTable:
   • Utilize the ExportDataTable() method to convert the worksheet's content into a DataTable. This provides a structured representation of the data, making it easier to manipulate.
4. Serialize to JSON:
   • Use the Newtonsoft.Json library to serialize the DataTable into a JSON string. This step involves converting the structured data into a JSON format, which is human-readable and suitable for web applications.
5. Save the JSON to a File:
   • Finally, write the generated JSON string to a file. This allows for easy access and reuse of the data in future applications or processes.

Complete Code Example: Excel to JSON

Here’s a complete code example demonstrating the process:

using Newtonsoft.Json;
using Spire.Xls;
using System.Data;
using System.IO;

namespace ConvertExcelToJSON
{
    class Program
    {        
        static void Main(string[] args)
        {
            // Path to the Excel file
            string excelFilePath = @"Sample.xlsx";

            // Create a new Workbook instance
            Workbook workbook = new Workbook();

            // Load the Excel file
            workbook.LoadFromFile(excelFilePath);

            // Get the first worksheet
            Worksheet worksheet = workbook.Worksheets[0];

            // Export the worksheet content to a DataTable
            DataTable dataTable = worksheet.ExportDataTable();

            // Convert the DataTable to a JSON string
            string jsonResult = JsonConvert.SerializeObject(dataTable, Formatting.Indented);

            // Save JSON string to a text file
            File.WriteAllText("output.txt", jsonResult);
        }
    }
}

How to Convert JSON to Excel in C# .NET (Step-by-Step)

Importing JSON data into an Excel file is a valuable process, especially when you need to analyze or present data in a more user-friendly format. JSON is easy for humans to read and write, and easy for machines to parse and generate. However, for many users, Excel remains the preferred tool for data analysis, reporting, and visualization.

In the following steps, we will outline the process of importing JSON into Excel, enabling you to effectively utilize your JSON data within Excel for further analysis and reporting.

Steps to Import JSON into Excel

1. Read the JSON String:
   • Start by reading the JSON data from a file or other sources. This could include API responses, local files, or even hardcoded strings for testing purposes.
2. Deserialize to DataTable:
   • Use the Newtonsoft.Json library to deserialize the JSON string into a DataTable. This structured format makes it easy to manipulate data before inserting it into Excel.
3. Create a New Excel Workbook:
   • Initialize a new Workbook instance using the Spire.XLS library. This workbook will serve as the container for your Excel data.
4. Insert the DataTable into the Worksheet:
   • Use the InsertDataTable() method to transfer the contents of the DataTable into the first worksheet of the workbook. This method allows you to include column headers and organize the data neatly.
5. Apply Optional Formatting:
   • Enhance the visual appeal of your Excel file by applying formatting to headers and data cells. This step involves defining styles for fonts, background colors, and borders, making the data easier to read.
6. Save the Workbook:
   • Finally, save the populated workbook as an Excel file. Choose an appropriate file format (e.g., .xlsx) to ensure compatibility with modern Excel versions.

Complete Code Example: JSON to Excel

Here’s a complete code snippet demonstrating the conversion process:

using Newtonsoft.Json;
using Spire.Xls;
using System.Data;
using System.Drawing;

namespace ConvertJSONToExcel
{
    class Program
    {        
        static void Main(string[] args)
        {
            // Sample JSON data
            string json = @"
        [
            {""Name"":""John Smith"",""Age"":30,""Department"":""Sales"",""StartDate"":""2020-05-12"",""FullTime"":true},
            {""Name"":""Jane Doe"",""Age"":25,""Department"":""Marketing"",""StartDate"":""2021-09-01"",""FullTime"":false},
            {""Name"":""Michael Lee"",""Age"":40,""Department"":""IT"",""StartDate"":""2018-03-15"",""FullTime"":true},
            {""Name"":""Emily Davis"",""Age"":35,""Department"":""Finance"",""StartDate"":""2019-07-20"",""FullTime"":true}
        ]";

            // Deserialize JSON into DataTable
            DataTable dataTable = JsonConvert.DeserializeObject<DataTable>(json);

            // Create a new Excel workbook
            Workbook workbook = new Workbook();

            // Get the first worksheet
            Worksheet worksheet = workbook.Worksheets[0];

            // Insert DataTable into worksheet with column headers
            worksheet.InsertDataTable(dataTable, true, 1, 1);

            // (Optional) Applying formatting to Excel data
            // Set style for heading row
            CellStyle headerStyle = workbook.Styles.Add("HeaderStyle");
            headerStyle.Font.IsBold = true;
            headerStyle.Font.Size = 12;
            headerStyle.Font.Color = Color.White;
            headerStyle.HorizontalAlignment = HorizontalAlignType.Center;
            headerStyle.VerticalAlignment = VerticalAlignType.Center;
            headerStyle.Color = Color.DarkBlue;

            int colCount = dataTable.Columns.Count;
            for (int c = 1; c <= colCount; c++)
            {
                worksheet.Range[1, c].CellStyleName = "HeaderStyle";
            }

            // Set style for data cells
            CellStyle dataStyle = workbook.Styles.Add("DataStyle");
            dataStyle.HorizontalAlignment = HorizontalAlignType.Center;
            dataStyle.VerticalAlignment = VerticalAlignType.Center;
            dataStyle.Borders[BordersLineType.EdgeLeft].LineStyle = LineStyleType.Thin;
            dataStyle.Borders[BordersLineType.EdgeRight].LineStyle = LineStyleType.Thin;
            dataStyle.Borders[BordersLineType.EdgeTop].LineStyle = LineStyleType.Thin;
            dataStyle.Borders[BordersLineType.EdgeBottom].LineStyle = LineStyleType.Thin;

            int rowCount = dataTable.Rows.Count;
            worksheet.Range[2, 1, rowCount + 1, colCount].CellStyleName = "DataStyle";

            // Auto-fit column widths
            worksheet.AllocatedRange.AutoFitColumns();

            // Save Excel file
            workbook.SaveToFile("output.xlsx", ExcelVersion.Version2013);
            // Release resources
            workbook.Dispose();
        }
    }
}

Tips and Best Practices

When converting between Excel and JSON, following best practices can help ensure data integrity and usability. Here are some key tips to keep in mind:

• Validate Data Types: Ensure that data types (e.g., dates, numbers) are correctly formatted to avoid issues during conversion.
• Handle Empty Cells: Decide how to treat empty cells (e.g., convert to null or omit) to maintain data integrity.
• Use Consistent Naming Conventions: Standardize column names in Excel for clear and consistent JSON keys.
• Test Thoroughly: Always test the conversion processes to ensure valid JSON output and accurate Excel representation.
• Include Headers: When converting JSON to Excel, always insert headers for improved readability and usability.

Conclusion

Converting Excel to JSON and JSON to Excel is a common but critical operation in modern C# development, especially for applications involving data exchange and API integration. Using Spire.XLS together with Newtonsoft.Json simplifies this process with intuitive APIs and robust functionality.

This guide has walked you through every step—from installing necessary packages to implementing complete converters—with clear explanations and sample code. With these tools and knowledge, you can confidently integrate Excel-JSON conversion into your applications, improving flexibility and interoperability.

Further Reading

• Spire.XLS for .NET Documentation
• Newtonsoft.Json Official Documentation

FAQs

Q1: How to convert multiple worksheets to JSON at once?

You can iterate through the Workbook.Worksheets collection and export each worksheet’s data individually, supporting batch Excel to JSON conversion.

Q2: How to customize JSON output formatting?

JsonConvert.SerializeObject allows you to set indentation, camelCase naming, or ignore null values. You can also use custom converters for more control.

Q3: How to improve readability when converting JSON to Excel?

Keep column headers, set alignment, apply borders and styles to generate a clear and easy-to-read Excel report.

Q4: Is this method compatible with .NET Core?

Yes, it is fully compatible. Both Spire.XLS and Newtonsoft.Json support .NET Core and .NET Framework, making it usable in various C# projects.