Importing a CSV file in C# with ASP.NET Core means reading a file stream, parsing delimited rows, and mapping each record to a typed object -- all before you can do anything useful with the data. IronXL handles every step through a single API that works equally well for CSV, XLSX, and TSV files, so you spend time on your application logic rather than string-splitting edge cases.
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Before writing any parsing code, add IronXL to your project. Open the Package Manager Console in Visual Studio or a terminal in your project directory and run one of the following commands:
The package targets .NET 10, .NET 6+, .NET Framework 4.6.2+, and .NET Standard 2.0, so it fits any modern project type. No Microsoft Office installation is required on the server. After the package restores, add using IronXL; at the top of any file that calls the library.
For detailed setup options, including global tool installation and CI/CD pipeline configuration, visit the IronXL installation guide.
Importing a CSV file in ASP.NET Core requires reading the file stream from the server, parsing each row, and mapping values to a model class. While some developers reach for manual StreamReader implementations or third-party packages, IronXL provides a single method that handles CSV files alongside Excel formats without additional configuration.
The following code shows how to load a CSV file using IronXL's WorkBook.LoadCSV method:
using IronXL;
// Load the CSV file directly using the full file path
var csv = WorkBook.LoadCSV("products.csv");
WorkSheet worksheet = csv.DefaultWorkSheet;
// Access CSV data by iterating through rows
foreach (var row in worksheet.Rows)
{
string productName = row.Columns[1].StringValue;
decimal price = row.Columns[2].DecimalValue;
Console.WriteLine($"Product: {productName}, Price: {price}");
}Imports IronXL
' Load the CSV file directly using the full file path
Dim csv = WorkBook.LoadCSV("products.csv")
Dim worksheet As WorkSheet = csv.DefaultWorkSheet
' Access CSV data by iterating through rows
For Each row In worksheet.Rows
Dim productName As String = row.Columns(1).StringValue
Dim price As Decimal = row.Columns(2).DecimalValue
Console.WriteLine($"Product: {productName}, Price: {price}")
NextThe WorkBook.LoadCSV method reads the CSV file and creates a worksheet where each line becomes a row and each delimited value becomes a cell. IronXL automatically detects the delimiter (comma, semicolon, or tab) and handles quoted fields that contain commas within the value. You do not need to configure a delimiter manually for standard CSV files.
Cell value accessors like StringValue, DecimalValue, IntValue, and DateTimeValue handle type conversion so you avoid manual parsing with int.TryParse or decimal.Parse. When a cell is empty or contains an unrecognized value, these accessors return the type's default rather than throwing an exception, which prevents unhandled errors during bulk import operations.
This approach eliminates the error-prone manual string parsing that custom implementations require, particularly for edge cases like escaped quotes, Windows-style line endings, and multi-line cell values. For more details on supported formats and delimiter options, see the IronXL CSV documentation.
Mapping CSV data to strongly-typed objects requires a model class that mirrors the file structure. You convert raw string data into specific types like integers, decimals, and DateTime values. For product inventory data, create a class with properties matching each CSV column:
public class Product
{
public int Id { get; set; }
public string Name { get; set; } = string.Empty;
public decimal Price { get; set; }
public int Quantity { get; set; }
}Public Class Product
Public Property Id As Integer
Public Property Name As String = String.Empty
Public Property Price As Decimal
Public Property Quantity As Integer
End ClassWith the model class defined, you can parse CSV records into a typed collection. The following example skips the header row using a loop index and maps each subsequent row to a Product object:
using IronXL;
WorkBook workbook = WorkBook.LoadCSV("inventory.csv");
WorkSheet ws = workbook.DefaultWorkSheet;
var records = new List<Product>();
// Skip header row (index 0), iterate through data rows
for (int i = 1; i < ws.Rows.Count(); i++)
{
var row = ws.Rows[i];
var product = new Product
{
Id = row.Columns[0].IntValue,
Name = row.Columns[1].StringValue,
Price = row.Columns[2].DecimalValue,
Quantity = row.Columns[3].IntValue
};
records.Add(product);
}
Console.WriteLine($"Loaded {records.Count} products.");Imports IronXL
Dim workbook As WorkBook = WorkBook.LoadCSV("inventory.csv")
Dim ws As WorkSheet = workbook.DefaultWorkSheet
Dim records As New List(Of Product)()
' Skip header row (index 0), iterate through data rows
For i As Integer = 1 To ws.Rows.Count() - 1
Dim row = ws.Rows(i)
Dim product As New Product With {
.Id = row.Columns(0).IntValue,
.Name = row.Columns(1).StringValue,
.Price = row.Columns(2).DecimalValue,
.Quantity = row.Columns(3).IntValue
}
records.Add(product)
Next
Console.WriteLine($"Loaded {records.Count} products.")The records collection now contains typed Product objects ready for database operations, JSON serialization, or further business logic. IronXL's cell value accessors handle type conversion automatically, including null handling for optional fields.
Real-world CSV files often contain empty cells or optional columns. IronXL's value accessors return default values rather than exceptions when a cell is blank. For nullable types, you can use a conditional check:
// Reading an optional DateTime field
DateTime? lastUpdated = string.IsNullOrEmpty(row.Columns[4].StringValue)
? null
: row.Columns[4].DateTimeValue;' Reading an optional DateTime field
Dim lastUpdated As DateTime? = If(String.IsNullOrEmpty(row.Columns(4).StringValue), Nothing, row.Columns(4).DateTimeValue)This pattern keeps your import code defensive without wrapping every cell access in a try-catch block. For guidance on handling complex data types and large files, visit the IronXL WorkSheet documentation.
Building an API endpoint that accepts CSV file uploads from a browser requires combining ASP.NET Core's IFormFile with IronXL's parsing capabilities. The following code demonstrates a complete controller implementation that parses the uploaded file and returns a JSON response:
using IronXL;
using Microsoft.AspNetCore.Mvc;
[Route("api/[controller]")]
[ApiController]
public class CsvController : ControllerBase
{
[HttpPost("upload")]
public async Task<IActionResult> UploadCsv(IFormFile file)
{
if (file == null || file.Length == 0)
return BadRequest("Please upload a valid CSV file.");
try
{
using var stream = new MemoryStream();
await file.CopyToAsync(stream);
stream.Position = 0;
WorkBook workbook = WorkBook.Load(stream, "csv");
WorkSheet ws = workbook.DefaultWorkSheet;
var records = new List<Product>();
// Skip header row, iterate through data rows
for (int i = 1; i < ws.Rows.Count(); i++)
{
var row = ws.Rows[i];
records.Add(new Product
{
Id = row.Columns[0].IntValue,
Name = row.Columns[1].StringValue,
Price = row.Columns[2].DecimalValue,
Quantity = row.Columns[3].IntValue
});
}
return Ok(new
{
message = "Import successful",
count = records.Count,
data = records
});
}
catch (Exception ex)
{
return BadRequest($"Error processing file: {ex.Message}");
}
}
}Imports IronXL
Imports Microsoft.AspNetCore.Mvc
Imports System.IO
Imports System.Threading.Tasks
<Route("api/[controller]")>
<ApiController>
Public Class CsvController
Inherits ControllerBase
<HttpPost("upload")>
Public Async Function UploadCsv(file As IFormFile) As Task(Of IActionResult)
If file Is Nothing OrElse file.Length = 0 Then
Return BadRequest("Please upload a valid CSV file.")
End If
Try
Using stream As New MemoryStream()
Await file.CopyToAsync(stream)
stream.Position = 0
Dim workbook As WorkBook = WorkBook.Load(stream, "csv")
Dim ws As WorkSheet = workbook.DefaultWorkSheet
Dim records As New List(Of Product)()
' Skip header row, iterate through data rows
For i As Integer = 1 To ws.Rows.Count() - 1
Dim row = ws.Rows(i)
records.Add(New Product With {
.Id = row.Columns(0).IntValue,
.Name = row.Columns(1).StringValue,
.Price = row.Columns(2).DecimalValue,
.Quantity = row.Columns(3).IntValue
})
Next
Return Ok(New With {
.message = "Import successful",
.count = records.Count,
.data = records
})
End Using
Catch ex As Exception
Return BadRequest($"Error processing file: {ex.Message}")
End Try
End Function
End ClassFor the [HttpPost("upload")] action to accept file uploads, the project must support multipart form data. In Program.cs for a minimal API setup, ensure you have called builder.Services.AddControllers() and app.MapControllers(). The endpoint becomes accessible at /api/csv/upload.
When testing from a browser form, set the form's enctype attribute to multipart/form-data and use a file input element. For API clients like Postman, select "form-data" in the request body, add a key named file, and attach the CSV file. The controller returns a JSON object containing the record count and the parsed data array, which client-side JavaScript can consume immediately.
Before passing the stream to IronXL, validate the file extension to reject non-CSV uploads:
var extension = Path.GetExtension(file.FileName).ToLowerInvariant();
if (extension != ".csv" && extension != ".txt")
return BadRequest("Only CSV files are accepted.");Dim extension As String = Path.GetExtension(file.FileName).ToLowerInvariant()
If extension <> ".csv" AndAlso extension <> ".txt" Then
Return BadRequest("Only CSV files are accepted.")
End IfThis check prevents malformed binary data from reaching the parser and provides a clear error message to API consumers. You can extend this validation to check MIME type using file.ContentType for stricter enforcement.
After parsing CSV files into typed objects, you typically persist the records to a database. The following example extends the service layer pattern by using Entity Framework Core's AddRangeAsync for bulk inserts:
using IronXL;
public class CsvImportService
{
private readonly AppDbContext _context;
public CsvImportService(AppDbContext context)
{
_context = context;
}
public async Task<int> ImportProductsAsync(Stream csvStream)
{
WorkBook workbook = WorkBook.LoadCSV(csvStream);
WorkSheet ws = workbook.DefaultWorkSheet;
var products = new List<Product>();
foreach (var row in ws.Rows.Skip(1))
{
products.Add(new Product
{
Id = row.Columns[0].IntValue,
Name = row.Columns[1].StringValue,
Price = row.Columns[2].DecimalValue,
Quantity = row.Columns[3].IntValue
});
}
await _context.Products.AddRangeAsync(products);
return await _context.SaveChangesAsync();
}
}Imports IronXL
Public Class CsvImportService
Private ReadOnly _context As AppDbContext
Public Sub New(context As AppDbContext)
_context = context
End Sub
Public Async Function ImportProductsAsync(csvStream As Stream) As Task(Of Integer)
Dim workbook As WorkBook = WorkBook.LoadCSV(csvStream)
Dim ws As WorkSheet = workbook.DefaultWorkSheet
Dim products As New List(Of Product)()
For Each row In ws.Rows.Skip(1)
products.Add(New Product With {
.Id = row.Columns(0).IntValue,
.Name = row.Columns(1).StringValue,
.Price = row.Columns(2).DecimalValue,
.Quantity = row.Columns(3).IntValue
})
Next
Await _context.Products.AddRangeAsync(products)
Return Await _context.SaveChangesAsync()
End Function
End ClassRegister CsvImportService in Program.cs so the controller can request it through constructor injection:
builder.Services.AddScoped<CsvImportService>();netThen update the controller constructor to accept the service and call ImportProductsAsync instead of building the list inline. This separation keeps controller actions thin and moves data-access logic into a testable service class. Entity Framework Core batches the AddRangeAsync call into a single INSERT statement per batch, which performs well for CSV files containing thousands of rows.
For very large imports (tens of thousands of rows), consider using EF Core's Bulk Extensions or a raw SQL BULK INSERT statement to reduce round-trips to the database.
IronXL is not limited to reading CSV files -- it also writes them. The SaveAsCsv method exports any worksheet to a CSV file, which is useful for generating reports or sending data to downstream systems:
using IronXL;
WorkBook workbook = WorkBook.Create(ExcelFileFormat.XLS);
WorkSheet ws = workbook.DefaultWorkSheet;
// Write headers
ws["A1"].Value = "Id";
ws["B1"].Value = "Name";
ws["C1"].Value = "Price";
// Write data rows
ws["A2"].Value = 1;
ws["B2"].Value = "Widget A";
ws["C2"].Value = 9.99;
ws["A3"].Value = 2;
ws["B3"].Value = "Widget B";
ws["C3"].Value = 14.49;
// Save as CSV
workbook.SaveAsCsv("export.csv");
Console.WriteLine("CSV export complete.");Imports IronXL
Dim workbook As WorkBook = WorkBook.Create(ExcelFileFormat.XLS)
Dim ws As WorkSheet = workbook.DefaultWorkSheet
' Write headers
ws("A1").Value = "Id"
ws("B1").Value = "Name"
ws("C1").Value = "Price"
' Write data rows
ws("A2").Value = 1
ws("B2").Value = "Widget A"
ws("C2").Value = 9.99
ws("A3").Value = 2
ws("B3").Value = "Widget B"
ws("C3").Value = 14.49
' Save as CSV
workbook.SaveAsCsv("export.csv")
Console.WriteLine("CSV export complete.")The exported file uses comma delimiters by default. For semicolon-delimited files common in European locales, call SaveAsCsv("export.csv", ";") with an explicit delimiter argument. You can also save to a MemoryStream and return the result as a file download from an API endpoint using File(stream, "text/csv", "export.csv").
For a full reference on export options, visit the IronXL save and export documentation.
Manual CSV parsing looks straightforward until you encounter edge cases: values that contain commas wrapped in quotes, newlines embedded in a cell, escaped quotation marks, and byte-order marks at the start of UTF-8 files. Handling all of these correctly in a custom StreamReader loop requires significant testing and ongoing maintenance.
IronXL addresses all of these cases internally. Comparing the two approaches shows clear advantages:
| Capability | IronXL | Manual StreamReader |
|---|---|---|
| Automatic delimiter detection | Yes | No -- must configure manually |
| Quoted field handling | Built-in | Requires custom logic |
| Type conversion (int, decimal, DateTime) | Built-in accessors | Requires Parse/TryParse calls |
| Multi-line cell values | Handled automatically | Difficult to implement correctly |
| BOM handling | Automatic | Requires StreamReader configuration |
| Excel format support (XLSX, XLS) | Same API | Requires separate library |
| Export to CSV | SaveAsCsv method | Requires separate write logic |
One of IronXL's practical advantages is that the same WorkBook.Load and worksheet iteration pattern works for XLSX, XLS, ODS, and CSV files. If your application needs to accept multiple spreadsheet formats from users, you can switch between formats without changing the parsing logic. Pass the file stream to WorkBook.Load and IronXL detects the format automatically based on the file signature.
This cross-format API means you write and test one code path instead of maintaining separate implementations for CSV and Excel. For a full list of supported formats, see the IronXL supported file formats page.
For CSV files under 100 MB, IronXL performs well without any tuning. For larger files, consider these strategies:
MemoryStream to reduce memory allocation.ws.Rows.Skip(1) with LINQ to avoid materializing the header row as a Product object.The IronXL performance guide covers additional optimizations for high-volume import scenarios including parallel processing and streaming modes.
You now have a working pattern for every stage of CSV import in ASP.NET Core: installing the library, loading files from disk or uploaded streams, mapping rows to typed model objects, persisting records to a database with Entity Framework Core, and exporting data back to CSV when needed.
To build on this foundation, explore these resources:
With IronXL in your project, adding support for XLSX uploads alongside CSV requires no additional code changes -- the same WorkBook.Load call handles both. That consistency means you can expand the feature set of your import endpoint incrementally as your application requirements grow.
Curtis Chau holds a Bachelor’s degree in Computer Science (Carleton University) and specializes in front-end development with expertise in Node.js, TypeScript, JavaScript, and React. Passionate about crafting intuitive and aesthetically pleasing user interfaces, Curtis enjoys working with modern frameworks and creating well-structured, visually appealing manuals.
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