.NET AYUDA

C# Parallel Foreach (Cómo Funciona para Desarrolladores)

Q: ¿Cómo puedo convertir varios archivos HTML a PDFs simultáneamente en C#?

Puedes usar IronPDF con el método Parallel.ForEach para convertir varios archivos HTML a PDFs simultáneamente. Este enfoque aprovecha el procesamiento concurrente para mejorar el rendimiento al reducir el tiempo total de ejecución.

Curtis Chau

Actualizado:junio 22, 2025

What is Parallel.ForEach in C#?

Parallel.ForEach is a method in C# that allows you to perform parallel iterations over a collection or data source. Instead of processing each item in the collection sequentially, a parallel loop enables concurrent execution, which can significantly improve performance by reducing the overall execution time. Parallel processing works by dividing the work across multiple core processors, allowing tasks to run simultaneously. This is particularly useful when processing tasks that are independent of each other.

In contrast to a normal foreach loop, which processes items sequentially, the parallel approach can handle large datasets much faster by utilizing multiple threads in parallel.

Why Use Parallel Processing with IronPDF?

IronPDF is a powerful library for handling PDFs in .NET, capable of converting HTML to PDF, extracting text from PDFs, merging and splitting documents, and more. When dealing with large volumes of PDF tasks, using parallel processing with Parallel.ForEach can significantly reduce execution time. Whether you're generating hundreds of PDFs or extracting data from multiple files at once, leveraging data parallelism with IronPDF ensures that tasks are completed faster and more efficiently.

This guide is intended for .NET developers who want to optimize their PDF processing tasks using IronPDF and Parallel.ForEach. Basic knowledge of C# and familiarity with the IronPDF library is recommended. By the end of this guide, you will be able to implement parallel processing to handle multiple PDF tasks concurrently, improving both performance and scalability.

Getting Started

Installing IronPDF

To use IronPDF in your project, you need to install the library via NuGet.

NuGet Package Installation

To install IronPDF, follow these steps:

Open your project in Visual Studio.
Go to Tools → NuGet Package Manager → Manage NuGet Packages for Solution.
Search for IronPDF in the NuGet package manager.

C# Parallel Foreach (How it Works for Developers): Figure 1

Click Install to add the IronPDF library to your project.

C# Parallel Foreach (How it Works for Developers): Figure 2

Alternatively, you can install it via the NuGet Package Manager Console:

Install-Package IronPdf

Once IronPDF is installed, you're ready to start using it for PDF generation and manipulation tasks.

Basic Concepts of Parallel.ForEach in C#

Parallel.ForEach is part of the System.Threading.Tasks namespace and provides a simple and effective way to execute iterations concurrently. The syntax for Parallel.ForEach is as follows:

Parallel.ForEach(collection, item =>
{
    // Code to process each item
});

Parallel.ForEach(collection, item =>
{
    // Code to process each item
});

Parallel.ForEach(collection, Sub(item)
	' Code to process each item
End Sub)

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Each item in the collection is processed in parallel, and the system decides how to distribute the workload across available threads. You can also specify options to control the degree of parallelism, such as the maximum number of threads used.

In comparison, a traditional foreach loop processes each item one after the other, whereas the parallel loop can process multiple items concurrently, improving performance when handling large collections.

Step-by-Step Implementation

Setting Up the Project

First, make sure IronPDF is installed as described in the Getting Started section. After that, you can start writing your parallel PDF processing logic.

Writing the Parallel Processing Logic

Code Snippet: Using Parallel.ForEach for HTML to PDF Conversion

string[] htmlFiles = { "page1.html", "page2.html", "page3.html" };
Parallel.ForEach(htmlFiles, htmlFile =>
{
    // Load the HTML content into IronPDF and convert it to PDF
    ChromePdfRenderer renderer = new ChromePdfRenderer();
    PdfDocument pdf = renderer.RenderHtmlAsPdf(htmlFile);
    // Save the generated PDF to the output folder
    pdf.SaveAs($"output_{htmlFile}.pdf");
});

string[] htmlFiles = { "page1.html", "page2.html", "page3.html" };
Parallel.ForEach(htmlFiles, htmlFile =>
{
    // Load the HTML content into IronPDF and convert it to PDF
    ChromePdfRenderer renderer = new ChromePdfRenderer();
    PdfDocument pdf = renderer.RenderHtmlAsPdf(htmlFile);
    // Save the generated PDF to the output folder
    pdf.SaveAs($"output_{htmlFile}.pdf");
});

Dim htmlFiles() As String = { "page1.html", "page2.html", "page3.html" }
Parallel.ForEach(htmlFiles, Sub(htmlFile)
	' Load the HTML content into IronPDF and convert it to PDF
	Dim renderer As New ChromePdfRenderer()
	Dim pdf As PdfDocument = renderer.RenderHtmlAsPdf(htmlFile)
	' Save the generated PDF to the output folder
	pdf.SaveAs($"output_{htmlFile}.pdf")
End Sub)

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This code demonstrates how to convert multiple HTML pages to PDFs in parallel.

Handling Parallel Processing Errors

When dealing with parallel tasks, error handling is crucial. Use try-catch blocks inside the Parallel.ForEach loop to manage any exceptions.

Code Snippet: Error Handling in Parallel PDF Tasks

Parallel.ForEach(pdfFiles, pdfFile =>
{
    try
    {
        var pdf = IronPdf.PdfDocument.FromFile(pdfFile);
        string text = pdf.ExtractAllText();
        System.IO.File.WriteAllText($"extracted_{pdfFile}.txt", text);
    }
    catch (Exception ex)
    {
        Console.WriteLine($"Error processing {pdfFile}: {ex.Message}");
    }
});

Parallel.ForEach(pdfFiles, pdfFile =>
{
    try
    {
        var pdf = IronPdf.PdfDocument.FromFile(pdfFile);
        string text = pdf.ExtractAllText();
        System.IO.File.WriteAllText($"extracted_{pdfFile}.txt", text);
    }
    catch (Exception ex)
    {
        Console.WriteLine($"Error processing {pdfFile}: {ex.Message}");
    }
});

Parallel.ForEach(pdfFiles, Sub(pdfFile)
	Try
		Dim pdf = IronPdf.PdfDocument.FromFile(pdfFile)
		Dim text As String = pdf.ExtractAllText()
		System.IO.File.WriteAllText($"extracted_{pdfFile}.txt", text)
	Catch ex As Exception
		Console.WriteLine($"Error processing {pdfFile}: {ex.Message}")
	End Try
End Sub)

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Practical Use Cases with Full Code Examples

Extracting Text from Multiple PDFs Simultaneously

Another use case for parallel processing is extracting text from a batch of PDFs. When dealing with multiple PDF files, performing text extraction concurrently can save a lot of time. The following example demonstrates how this can be done.

Example: Parallel Text Extraction from Multiple Documents

using IronPdf;
using System.Linq;
using System.Threading.Tasks;

class Program
{
    static void Main(string[] args)
    {
        string[] pdfFiles = { "doc1.pdf", "doc2.pdf", "doc3.pdf" };
        Parallel.ForEach(pdfFiles, pdfFile =>
        {
            var pdf = IronPdf.PdfDocument.FromFile(pdfFile);
            string text = pdf.ExtractText();
            System.IO.File.WriteAllText($"extracted_{pdfFile}.txt", text);
        });
    }
}

using IronPdf;
using System.Linq;
using System.Threading.Tasks;

class Program
{
    static void Main(string[] args)
    {
        string[] pdfFiles = { "doc1.pdf", "doc2.pdf", "doc3.pdf" };
        Parallel.ForEach(pdfFiles, pdfFile =>
        {
            var pdf = IronPdf.PdfDocument.FromFile(pdfFile);
            string text = pdf.ExtractText();
            System.IO.File.WriteAllText($"extracted_{pdfFile}.txt", text);
        });
    }
}

Imports IronPdf
Imports System.Linq
Imports System.Threading.Tasks

Friend Class Program
	Shared Sub Main(ByVal args() As String)
		Dim pdfFiles() As String = { "doc1.pdf", "doc2.pdf", "doc3.pdf" }
		Parallel.ForEach(pdfFiles, Sub(pdfFile)
			Dim pdf = IronPdf.PdfDocument.FromFile(pdfFile)
			Dim text As String = pdf.ExtractText()
			System.IO.File.WriteAllText($"extracted_{pdfFile}.txt", text)
		End Sub)
	End Sub
End Class

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Output Documents

C# Parallel Foreach (How it Works for Developers): Figure 3

In this code, each PDF file is processed in parallel to extract text, and the extracted text is saved in separate text files.

Example: Batch PDF Generation from HTML Files in Parallel

In this example, we will generate multiple PDFs from a list of HTML files in parallel, which could be a typical scenario when you need to convert several dynamic HTML pages to PDF documents.

Code

using IronPdf;
using System;
using System.Threading.Tasks;

class Program
{
    static void Main(string[] args)
    {
        string[] htmlFiles = { "example.html", "example_1.html", "example_2.html" };
        Parallel.ForEach(htmlFiles, htmlFile =>
        {
            try
            {
                // Load the HTML content into IronPDF and convert it to PDF
                ChromePdfRenderer renderer = new ChromePdfRenderer();
                PdfDocument pdf = renderer.RenderHtmlFileAsPdf(htmlFile);
                // Save the generated PDF to the output folder
                pdf.SaveAs($"output_{htmlFile}.pdf");
                Console.WriteLine($"PDF created for {htmlFile}");
            }
            catch (Exception ex)
            {
                Console.WriteLine($"Error processing {htmlFile}: {ex.Message}");
            }
        });
    }
}

using IronPdf;
using System;
using System.Threading.Tasks;

class Program
{
    static void Main(string[] args)
    {
        string[] htmlFiles = { "example.html", "example_1.html", "example_2.html" };
        Parallel.ForEach(htmlFiles, htmlFile =>
        {
            try
            {
                // Load the HTML content into IronPDF and convert it to PDF
                ChromePdfRenderer renderer = new ChromePdfRenderer();
                PdfDocument pdf = renderer.RenderHtmlFileAsPdf(htmlFile);
                // Save the generated PDF to the output folder
                pdf.SaveAs($"output_{htmlFile}.pdf");
                Console.WriteLine($"PDF created for {htmlFile}");
            }
            catch (Exception ex)
            {
                Console.WriteLine($"Error processing {htmlFile}: {ex.Message}");
            }
        });
    }
}

Imports IronPdf
Imports System
Imports System.Threading.Tasks

Friend Class Program
	Shared Sub Main(ByVal args() As String)
		Dim htmlFiles() As String = { "example.html", "example_1.html", "example_2.html" }
		Parallel.ForEach(htmlFiles, Sub(htmlFile)
			Try
				' Load the HTML content into IronPDF and convert it to PDF
				Dim renderer As New ChromePdfRenderer()
				Dim pdf As PdfDocument = renderer.RenderHtmlFileAsPdf(htmlFile)
				' Save the generated PDF to the output folder
				pdf.SaveAs($"output_{htmlFile}.pdf")
				Console.WriteLine($"PDF created for {htmlFile}")
			Catch ex As Exception
				Console.WriteLine($"Error processing {htmlFile}: {ex.Message}")
			End Try
		End Sub)
	End Sub
End Class

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Console Output

C# Parallel Foreach (How it Works for Developers): Figure 4

PDF Output

C# Parallel Foreach (How it Works for Developers): Figure 5

Explanation

HTML Files: The array htmlFiles contains paths to multiple HTML files that you want to convert into PDFs.
Parallel Processing:
- Parallel.ForEach(htmlFiles, htmlFile => {...}) processes each HTML file concurrently, which speeds up the operation when dealing with multiple files.
- For each file in the htmlFiles array, the code converts it to a PDF using renderer.RenderHtmlFileAsPdf(htmlFile);.
Saving the PDF: After generating the PDF, it is saved using the pdf.SaveAs method, appending the output file name with the original HTML file's name.
Error Handling: If any error occurs (e.g., the HTML file doesn't exist or there's an issue during the conversion), it's caught by the try-catch block, and an error message is printed for the specific file.

Performance Tips and Best Practices

Avoiding Thread Safety Issues with IronPDF

IronPDF is thread-safe for most operations. However, some operations like writing to the same file in parallel may cause issues. Always ensure that each parallel task operates on a separate output file or resource.

Optimizing Parallel Processing for Large Datasets

To optimize performance, consider controlling the degree of parallelism. For large datasets, you may want to limit the number of concurrent threads to prevent system overload.

var options = new ExecutionDataflowBlockOptions
{
    MaxDegreeOfParallelism = 4
};

var options = new ExecutionDataflowBlockOptions
{
    MaxDegreeOfParallelism = 4
};

Dim options = New ExecutionDataflowBlockOptions With {.MaxDegreeOfParallelism = 4}

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Memory Management in Parallel PDF Operations

When processing a large number of PDFs, be mindful of memory usage. Try to release resources like PdfDocument objects as soon as they are no longer needed.

Using Extension Methods

An extension method is a special kind of static method that allows you to add new functionality to an existing type without modifying its source code. This can be useful when working with libraries like IronPDF, where you might want to add custom processing methods or extend its functionality to make working with PDFs more convenient, especially in parallel processing scenarios.

Benefits of Using Extension Methods in Parallel Processing

By using extension methods, you can create concise, reusable code that simplifies the logic in parallel loops. This approach not only reduces duplication but also helps you maintain a clean codebase, especially when dealing with complex PDF workflows and data parallelism.

Conclusion

Using parallel loops like Parallel.ForEach with IronPDF provides significant performance gains when processing large volumes of PDFs. Whether you're converting HTML to PDFs, extracting text, or manipulating documents, data parallelism enables faster execution by running tasks concurrently. The parallel approach ensures that operations can be executed across multiple core processors, which reduces the overall execution time and improves performance for batch processing tasks.

While parallel processing speeds up tasks, be mindful of thread safety and resource management. IronPDF is thread-safe for most operations, but it’s important to handle potential conflicts when accessing shared resources. Consider error handling and memory management to ensure stability, especially as your application scales.

If you're ready to dive deeper into IronPDF and explore advanced features, the official documentation provides extensive information. Additionally, you can take advantage of their trial license, allowing you to test the library in your own projects before committing to a purchase.

Preguntas Frecuentes

¿Cómo puedo convertir varios archivos HTML a PDFs simultáneamente en C#?

Puedes usar IronPDF con el método Parallel.ForEach para convertir varios archivos HTML a PDFs simultáneamente. Este enfoque aprovecha el procesamiento concurrente para mejorar el rendimiento al reducir el tiempo total de ejecución.

¿Cuáles son los beneficios de usar Parallel.ForEach con el procesamiento de PDFs en C#?

Usar Parallel.ForEach con IronPDF permite la ejecución concurrente de tareas de PDF, mejorando significativamente el rendimiento, especialmente cuando se manejan grandes volúmenes de archivos. Este método aprovecha múltiples núcleos para manejar tareas como la conversión de HTML a PDF y la extracción de texto de manera más eficiente.

¿Cómo instalo una biblioteca PDF de .NET para tareas de procesamiento paralelo?

Para instalar IronPDF para tu proyecto .NET, abre Visual Studio y navega a Herramientas → Administrador de paquetes NuGet → Administrar paquetes NuGet para la solución. Busca IronPDF y haz clic en Instalar. Alternativamente, usa la Consola del Administrador de paquetes NuGet con el comando: Install-Package IronPdf.

¿Cuáles son las mejores prácticas para el manejo de errores en el procesamiento paralelo de PDFs?

En el procesamiento paralelo de PDFs con IronPDF, usa bloques try-catch dentro del bucle Parallel.ForEach para manejar excepciones. Esto asegura una gestión de errores robusta y previene que fallas en tareas individuales afecten el proceso general.

¿Puede IronPDF manejar la extracción de texto de varios PDFs al mismo tiempo?

Sí, IronPDF puede extraer texto simultáneamente de varios PDFs utilizando el método Parallel.ForEach, lo que permite un procesamiento concurrente para manejar grandes conjuntos de datos de manera eficiente.

¿Es IronPDF seguro para hilos en operaciones concurrentes de PDF?

IronPDF está diseñado para ser seguro para hilos en la mayoría de las operaciones. Sin embargo, es importante asegurarse de que cada tarea paralela opere en recursos separados, como diferentes archivos, para evitar conflictos y asegurar la integridad de los datos.

¿Cómo puedo mejorar la gestión de memoria durante operaciones paralelas de PDF en C#?

Para optimizar la gestión de memoria, libera recursos como objetos PdfDocument de inmediato después de usarlos, especialmente al procesar un gran número de PDFs. Esto ayuda a mantener un uso óptimo de la memoria y el rendimiento del sistema.

¿Qué papel juegan los métodos de extensión en el procesamiento paralelo de PDFs con C#?

Los métodos de extensión te permiten agregar funcionalidad a tipos existentes sin modificar su código fuente. Son útiles en el procesamiento paralelo de PDFs con IronPDF para crear código reutilizable y conciso, simplificando operaciones dentro de bucles paralelos.

¿Cómo puedo controlar el grado de paralelismo en C# para tareas de PDF?

En C#, puedes controlar el grado de paralelismo para tareas de PDF usando opciones como ExecutionDataflowBlockOptions para limitar el número de hilos concurrentes. Esto ayuda a gestionar los recursos del sistema efectivamente y prevenir sobrecargas.

Curtis Chau

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Escritor Técnico

Curtis Chau tiene una licenciatura en Ciencias de la Computación (Carleton University) y se especializa en el desarrollo front-end con experiencia en Node.js, TypeScript, JavaScript y React. Apasionado por crear interfaces de usuario intuitivas y estéticamente agradables, disfruta trabajando con frameworks modernos y creando manuales bien ...