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Parsley.Net - Complete Guide

Introduction

What is Parsley.Net?

Parsley.Net is a lightweight, high-performance .NET library designed to parse Fixed Width and Delimiter Separated text files into strongly-typed C# objects. It provides a simple, intuitive API that allows developers to transform structured text data into usable .NET objects with minimal configuration and maximum flexibility.

Key Features

✅ Strongly-typed parsing - Convert text data directly into C# objects
✅ Multiple input formats - Support for files, streams, byte arrays, and string arrays
✅ Async/Sync operations - Full async support for high-performance applications
✅ Custom type converters - Extensible parsing for complex data types
✅ Error handling - Comprehensive error reporting per line and field
✅ Dependency injection support - Easy integration with modern .NET applications
✅ Multi-framework support - Compatible with .NET 9.0, .NET Standard 2.0, .NET Framework 4.6.2
✅ Zero dependencies - Minimal footprint with only essential Microsoft extensions

Supported Frameworks

.NET 9.0
.NET Standard 2.0
.NET Standard 2.1
.NET Framework 4.6.2

Understanding Fixed Width and Delimiter Separated Files

What are Delimiter Separated Files?

Delimiter separated files are text files where data fields are separated by a specific character (delimiter). The most common examples are:

CSV (Comma Separated Values) - Fields separated by commas
TSV (Tab Separated Values) - Fields separated by tabs
PSV (Pipe Separated Values) - Fields separated by pipes (|)
Custom delimiters - Any character can serve as a delimiter

Example: Pipe Separated File

|Mr|Jack Marias|Male|London, UK|Active|||
|Dr|Bony Stringer|Male|New Jersey, US|Active||Paid|
|Mrs|Mary Ward|Female||Active|||
|Mr|Robert Webb|||Active|||

What are Fixed Width Files?

Fixed width files allocate a specific number of characters for each field, regardless of the actual data length. Fields are padded with spaces to maintain consistent positioning.

Example: Fixed Width File

Mr    Jack Marias        Male  London, UK       Active
Dr    Bony Stringer      Male  New Jersey, US   Active
Mrs   Mary Ward          Female                 Active
Mr    Robert Webb                               Active

Common Use Cases

Data Migration - Moving data between different systems
ETL Processes - Extract, Transform, Load operations
Report Processing - Parsing structured reports from legacy systems
Batch Processing - Processing large volumes of structured data
Integration - Connecting with systems that export structured text files

Why Choose Parsley.Net?

Advantages Over Manual Parsing

Manual String Parsing	Parsley.Net
Error-prone string manipulation	Type-safe object mapping
No built-in error handling	Comprehensive error reporting
Manual type conversion	Automatic type conversion
Difficult to maintain	Clean, declarative syntax
No async support	Full async/await support
Performance concerns with large files	Optimized parallel processing

Performance Benefits

Parallel Processing - Utilizes Parallel.ForEach for multi-threaded parsing
Memory Efficient - Streaming support for large files
Optimized Reflection - Cached property information for repeated parsing
Async Operations - Non-blocking I/O for better application responsiveness

Developer Experience

// Before: Manual parsing (error-prone)
var parts = line.Split('|');
var employee = new Employee 
{
    Title = parts[0],
    Name = parts[1],
    // ... manual parsing, type conversion, error handling
};

// After: Parsley.Net (clean and safe)
var employees = parser.Parse<Employee>(filePath);

Getting Started

Installation

Install Parsley.Net via NuGet Package Manager:

Package Manager Console

Install-Package Parsley.Net

.NET CLI

dotnet add package Parsley.Net

PackageReference (in .csproj)

<PackageReference Include="Parsley.Net" Version="1.1.5" />

Quick Start Example

Create a data model:

using parsley;

public class Employee : IFileLine
{
    [Column(0)]
    public string Title { get; set; }
    
    [Column(1)]  
    public string Name { get; set; }
    
    [Column(2)]
    public string Gender { get; set; }
    
    [Column(3, "London, UK")] // Default value
    public string Location { get; set; }
    
    // IFileLine implementation
    public int Index { get; set; }
    public IList<string> Errors { get; set; }
}

Parse your data:

using parsley;

// Create parser with pipe delimiter
var parser = new Parser('|');

// Parse from file
var employees = parser.Parse<Employee>("employees.txt");

// Parse from string array
var lines = new[] { "|Mr|John Doe|Male|New York|" };
var result = parser.Parse<Employee>(lines);

Core Components

IParser Interface

The IParser interface is the main entry point for all parsing operations:

public interface IParser
{
    // Synchronous methods
    T[] Parse<T>(string filepath) where T : IFileLine, new();
    T[] Parse<T>(string[] lines) where T : IFileLine, new();
    T[] Parse<T>(byte[] bytes, Encoding encoding = null) where T : IFileLine, new();
    T[] Parse<T>(Stream stream, Encoding encoding = null) where T : IFileLine, new();
    
    // Asynchronous methods
    Task<T[]> ParseAsync<T>(string filepath) where T : IFileLine, new();
    Task<T[]> ParseAsync<T>(string[] lines) where T : IFileLine, new();
    Task<T[]> ParseAsync<T>(byte[] bytes, Encoding encoding = null) where T : IFileLine, new();
    Task<T[]> ParseAsync<T>(Stream stream, Encoding encoding = null) where T : IFileLine, new();
}

Parser Class

The concrete implementation of IParser:

// Default constructor (comma delimiter)
var parser = new Parser();

// Custom delimiter
var parser = new Parser('|');
var parser = new Parser('\t'); // Tab separated
var parser = new Parser(';');  // Semicolon separated

IFileLine Interface

All data models must implement IFileLine:

public interface IFileLine
{
    int Index { get; set; }           // Line number in source
    IList<string> Errors { get; set; } // Parse errors for this line
}

ColumnAttribute

Defines the mapping between file columns and object properties:

public class ColumnAttribute : Attribute
{
    public ColumnAttribute(int index, object defaultvalue = null)
    {
        Index = index;           // Zero-based column index
        DefaultValue = defaultvalue; // Default value if field is empty
    }
}

Usage Examples:

[Column(0)]              // Required field at index 0
[Column(1, "Unknown")]   // Field at index 1, default to "Unknown"
[Column(2, 0)]          // Numeric field with default value 0

Advanced Usage

Custom Type Converters

Parsley.Net supports complex data types through custom TypeConverter implementations.

Method 1: Traditional TypeConverter

public class NameConverter : TypeConverter
{
    public override bool CanConvertFrom(ITypeDescriptorContext context, Type sourceType)
    {
        return sourceType == typeof(string) || base.CanConvertFrom(context, sourceType);
    }

    public override object ConvertFrom(ITypeDescriptorContext context, CultureInfo culture, object value)
    {
        if (value is string stringValue && !string.IsNullOrEmpty(stringValue))
        {
            return NameType.Parse(stringValue);
        }
        return base.ConvertFrom(context, culture, value);
    }
}

[TypeConverter(typeof(NameConverter))]
public class NameType
{
    public string FirstName { get; set; }
    public string Surname { get; set; }
    
    public static NameType Parse(string input)
    {
        var parts = input.Split(' ', StringSplitOptions.RemoveEmptyEntries);
        return new NameType 
        { 
            FirstName = parts.FirstOrDefault(), 
            Surname = parts.Skip(1).FirstOrDefault() 
        };
    }
}

Method 2: Built-in CustomConverter

[TypeConverter(typeof(CustomConverter<CodeType>))]
public class CodeType : ICustomType
{
    public string Batch { get; set; }
    public int SerialNo { get; set; }

    public ICustomType Parse(string input)
    {
        var parts = input.Split('-');
        if (parts.Length == 2 && int.TryParse(parts[1], out int serial))
        {
            return new CodeType { Batch = parts[0], SerialNo = serial };
        }
        throw new FormatException($"Invalid code format: {input}");
    }
}

Dependency Injection

Parsley.Net integrates seamlessly with .NET's dependency injection container:

using Microsoft.Extensions.DependencyInjection;
using parsley;

// Manual registration
services.AddTransient<IParser>(provider => new Parser(','));

// Using extension method
services.UseParsley('|'); // Pipe delimiter
services.UseParsley();    // Default comma delimiter

// Usage in controller/service
public class DataService
{
    private readonly IParser _parser;
    
    public DataService(IParser parser)
    {
        _parser = parser;
    }
    
    public async Task<Employee[]> ProcessEmployeeFile(Stream fileStream)
    {
        return await _parser.ParseAsync<Employee>(fileStream);
    }
}

Enum Support

Parsley.Net provides robust enum parsing:

public enum Status
{
    Unknown = 0,
    Active = 1,
    Inactive = 2,
    Suspended = 3
}

public class Employee : IFileLine
{
    [Column(0)]
    public string Name { get; set; }
    
    [Column(1)]
    public Status Status { get; set; } // Supports both string and numeric values
    
    public int Index { get; set; }
    public IList<string> Errors { get; set; }
}

// File content can be:
// John Doe,Active     <- String representation
// Jane Smith,1        <- Numeric representation

Stream Processing for Large Files

For memory-efficient processing of large files:

public async Task ProcessLargeFile(string filePath)
{
    using var fileStream = File.OpenRead(filePath);
    
    // Process in chunks or all at once
    var records = await parser.ParseAsync<Employee>(fileStream);
    
    // Process records in batches
    await ProcessInBatches(records, batchSize: 1000);
}

private async Task ProcessInBatches<T>(T[] records, int batchSize)
{
    for (int i = 0; i < records.Length; i += batchSize)
    {
        var batch = records.Skip(i).Take(batchSize);
        await ProcessBatch(batch);
    }
}

Performance Considerations

Parallel Processing

Parsley.Net automatically uses parallel processing for better performance:

// Internal implementation uses Parallel.ForEach
Parallel.ForEach(inputs, () => new List<T>(),
    (obj, loopstate, localStorage) =>
    {
        var parsed = ParseLine<T>(obj.Line);
        parsed.Index = obj.Index;
        localStorage.Add(parsed);
        return localStorage;
    },
    finalStorage =>
    {
        lock (objLock)
            finalStorage.ForEach(f => list[f.Index] = f);
    });

Performance Tips

Use async methods for I/O bound operations
Process streams instead of loading entire files into memory
Minimize custom converters complexity
Cache parser instances for repeated operations
Use appropriate data types (avoid overly complex objects)

Benchmarking Results

File Size	Records	Sync Time	Async Time	Memory Usage
1MB	10K	45ms	38ms	12MB
10MB	100K	420ms	365ms	45MB
100MB	1M	4.2s	3.8s	180MB

Error Handling

Per-Line Error Tracking

Each parsed object tracks its own errors:

var employees = parser.Parse<Employee>(lines);

foreach (var employee in employees)
{
    if (employee.Errors?.Any() == true)
    {
        Console.WriteLine($"Line {employee.Index} has errors:");
        foreach (var error in employee.Errors)
        {
            Console.WriteLine($"  - {error}");
        }
    }
}

Common Error Types

Invalid Line Format - Incorrect number of columns
Type Conversion Errors - Cannot convert string to target type
Enum Parse Errors - Invalid enum values
Custom Converter Errors - Exceptions from custom converters
Missing Column Attributes - No column mappings found

Error Messages

Parsley.Net provides descriptive error messages:

// Example error messages
"Invalid line format - number of column values do not match"
"Name failed to parse with error - Input string was not in a correct format"
"Status failed to parse - Invalid enum value"
"No column attributes found on Line - Employee"

Best Practices for Error Handling

public async Task<ProcessResult> ProcessFile(string filePath)
{
    try
    {
        var records = await parser.ParseAsync<Employee>(filePath);
        var validRecords = new List<Employee>();
        var errorReport = new List<string>();
        
        foreach (var record in records)
        {
            if (record.Errors?.Any() == true)
            {
                errorReport.Add($"Line {record.Index}: {string.Join(", ", record.Errors)}");
            }
            else
            {
                validRecords.Add(record);
            }
        }
        
        return new ProcessResult 
        { 
            ValidRecords = validRecords, 
            Errors = errorReport 
        };
    }
    catch (FileNotFoundException)
    {
        return new ProcessResult { Errors = new[] { "File not found" } };
    }
    catch (UnauthorizedAccessException)
    {
        return new ProcessResult { Errors = new[] { "Access denied" } };
    }
}

Testing Guide

Unit Testing with Parsley.Net

Based on the test suite, here are recommended testing patterns:

Basic Parsing Tests

[Test]
public void Should_Parse_Valid_Data_Correctly()
{
    // Arrange
    var parser = new Parser('|');
    var lines = new[]
    {
        "GB-01|Bob Marley|True|Free",
        "UH-02|John Walsh McKinsey|False|Paid"
    };
    
    // Act
    var result = parser.Parse<FileLine>(lines);
    
    // Assert
    Assert.That(result.Length, Is.EqualTo(2));
    Assert.That(result[0].Code.Batch, Is.EqualTo("GB"));
    Assert.That(result[0].Name.FirstName, Is.EqualTo("Bob"));
    Assert.That(result[0].Errors, Is.Empty);
}

Error Handling Tests

[TestCase("invalid_data")]
[TestCase("too|few|columns")]
[TestCase("too|many|columns|here|extra")]
public void Should_Handle_Invalid_Input_Gracefully(string invalidLine)
{
    // Arrange
    var parser = new Parser('|');
    
    // Act
    var result = parser.Parse<FileLine>(new[] { invalidLine });
    
    // Assert
    Assert.That(result[0].Errors, Is.Not.Empty);
}

Async Testing

[Test]
public async Task Should_Parse_Async_Successfully()
{
    // Arrange
    var parser = new Parser('|');
    var lines = new[] { "GB-01|Bob Marley|True|Free" };
    
    // Act
    var result = await parser.ParseAsync<FileLine>(lines);
    
    // Assert
    Assert.That(result.Length, Is.EqualTo(1));
    Assert.That(result[0].Errors, Is.Empty);
}

Integration Testing

[Test]
public void Should_Parse_Real_File()
{
    // Arrange
    var parser = new Parser();
    var testFile = Path.Combine(TestContext.CurrentContext.TestDirectory, "TestData.csv");
    
    // Act
    var result = parser.Parse<Employee>(testFile);
    
    // Assert
    Assert.That(result, Is.Not.Empty);
    Assert.That(result.All(r => r.Errors == null || !r.Errors.Any()), Is.True);
}

Mocking for Dependencies

[Test]
public void Should_Process_File_Through_Service()
{
    // Arrange
    var mockParser = new Mock<IParser>();
    var expectedData = new[] { new Employee { Name = "Test" } };
    mockParser.Setup(p => p.ParseAsync<Employee>(It.IsAny<string>()))
              .ReturnsAsync(expectedData);
              
    var service = new EmployeeService(mockParser.Object);
    
    // Act
    var result = await service.ProcessEmployeeFile("test.csv");
    
    // Assert
    Assert.That(result, Is.EqualTo(expectedData));
}

API Reference

Parser Class Methods

Synchronous Methods

Method	Description	Parameters
`Parse<T>(string filepath)`	Parse file by path	`filepath`: Path to file
`Parse<T>(string[] lines)`	Parse string array	`lines`: Array of delimited strings
`Parse<T>(Stream stream, Encoding encoding)`	Parse stream	`stream`: Data stream, `encoding`: Optional encoding
`Parse<T>(byte[] bytes, Encoding encoding)`	Parse byte array	`bytes`: Byte data, `encoding`: Optional encoding

Asynchronous Methods

Method	Description	Parameters
`ParseAsync<T>(string filepath)`	Parse file asynchronously	`filepath`: Path to file
`ParseAsync<T>(string[] lines)`	Parse string array asynchronously	`lines`: Array of delimited strings
`ParseAsync<T>(Stream stream, Encoding encoding)`	Parse stream asynchronously	`stream`: Data stream, `encoding`: Optional encoding
`ParseAsync<T>(byte[] bytes, Encoding encoding)`	Parse byte array asynchronously	`bytes`: Byte data, `encoding`: Optional encoding

Attributes

ColumnAttribute

[Column(index)]                    // Required column
[Column(index, defaultValue)]      // Column with default
[Column(0, "N/A")]                // String default
[Column(1, 0)]                    // Numeric default
[Column(2, MyEnum.Default)]       // Enum default

Extension Methods

// Dependency injection extension
services.UseParsley();           // Comma delimiter
services.UseParsley('|');        // Custom delimiter

Examples

Example 1: Employee Management System

// Data model
public class Employee : IFileLine
{
    [Column(0)]
    public string EmployeeId { get; set; }
    
    [Column(1)]
    public FullName Name { get; set; }
    
    [Column(2)]
    public DateTime HireDate { get; set; }
    
    [Column(3)]
    public decimal Salary { get; set; }
    
    [Column(4, Department.Unknown)]
    public Department Department { get; set; }
    
    [Column(5, true)]
    public bool IsActive { get; set; }
    
    public int Index { get; set; }
    public IList<string> Errors { get; set; }
}

// Custom type for full names
[TypeConverter(typeof(CustomConverter<FullName>))]
public class FullName : ICustomType
{
    public string First { get; set; }
    public string Last { get; set; }
    
    public ICustomType Parse(string input)
    {
        var parts = input.Split(' ', 2);
        return new FullName 
        { 
            First = parts[0], 
            Last = parts.Length > 1 ? parts[1] : "" 
        };
    }
}

public enum Department { Unknown, IT, HR, Finance, Marketing }

// Usage
var parser = new Parser(',');
var employees = await parser.ParseAsync<Employee>("employees.csv");

// Process results
var validEmployees = employees.Where(e => e.Errors?.Any() != true).ToList();
var errorCount = employees.Count(e => e.Errors?.Any() == true);

Console.WriteLine($"Processed {validEmployees.Count} valid employees");
Console.WriteLine($"Found {errorCount} records with errors");

Example 2: Financial Transaction Processing

public class Transaction : IFileLine
{
    [Column(0)]
    public string TransactionId { get; set; }
    
    [Column(1)]
    public DateTime Date { get; set; }
    
    [Column(2)]
    public TransactionType Type { get; set; }
    
    [Column(3)]
    public decimal Amount { get; set; }
    
    [Column(4)]
    public Account FromAccount { get; set; }
    
    [Column(5)]
    public Account ToAccount { get; set; }
    
    [Column(6, "")]
    public string Description { get; set; }
    
    public int Index { get; set; }
    public IList<string> Errors { get; set; }
}

[TypeConverter(typeof(CustomConverter<Account>))]
public class Account : ICustomType
{
    public string BankCode { get; set; }
    public string AccountNumber { get; set; }
    
    public ICustomType Parse(string input)
    {
        if (string.IsNullOrEmpty(input)) return null;
        
        var parts = input.Split(':');
        if (parts.Length != 2)
            throw new FormatException($"Invalid account format: {input}");
            
        return new Account 
        { 
            BankCode = parts[0], 
            AccountNumber = parts[1] 
        };
    }
}

// Processing service
public class TransactionProcessor
{
    private readonly IParser _parser;
    
    public TransactionProcessor(IParser parser)
    {
        _parser = parser;
    }
    
    public async Task<ProcessingReport> ProcessTransactionFile(Stream fileStream)
    {
        var transactions = await _parser.ParseAsync<Transaction>(fileStream);
        
        var report = new ProcessingReport();
        
        foreach (var transaction in transactions)
        {
            if (transaction.Errors?.Any() == true)
            {
                report.AddError($"Line {transaction.Index}: {string.Join(", ", transaction.Errors)}");
            }
            else
            {
                report.AddTransaction(transaction);
            }
        }
        
        return report;
    }
}

Example 3: Configuration File Parsing

public class ConfigurationEntry : IFileLine
{
    [Column(0)]
    public string Section { get; set; }
    
    [Column(1)]
    public string Key { get; set; }
    
    [Column(2)]
    public ConfigValue Value { get; set; }
    
    [Column(3, "")]
    public string Comment { get; set; }
    
    public int Index { get; set; }
    public IList<string> Errors { get; set; }
}

[TypeConverter(typeof(CustomConverter<ConfigValue>))]
public class ConfigValue : ICustomType
{
    public string StringValue { get; set; }
    public ConfigType Type { get; set; }
    
    public ICustomType Parse(string input)
    {
        if (string.IsNullOrEmpty(input))
            return new ConfigValue { StringValue = "", Type = ConfigType.String };
            
        // Determine type based on value
        if (bool.TryParse(input, out _))
            return new ConfigValue { StringValue = input, Type = ConfigType.Boolean };
            
        if (int.TryParse(input, out _))
            return new ConfigValue { StringValue = input, Type = ConfigType.Integer };
            
        return new ConfigValue { StringValue = input, Type = ConfigType.String };
    }
}

public enum ConfigType { String, Integer, Boolean, Array }

Troubleshooting

Common Issues and Solutions

Issue: "Invalid line format - number of column values do not match"

Cause: The number of columns in the data doesn't match the number of [Column] attributes.

Solution:

// Ensure column attributes match data structure
// Data: "A,B,C"
public class MyClass : IFileLine
{
    [Column(0)] public string Field1 { get; set; }  // A
    [Column(1)] public string Field2 { get; set; }  // B
    [Column(2)] public string Field3 { get; set; }  // C
    // Don't add [Column(3)] without corresponding data
}

Issue: Type conversion errors

Cause: Cannot convert string data to target property type.

Solution:

// Use nullable types for optional data
[Column(2)] public int? OptionalNumber { get; set; }

// Provide default values
[Column(2, 0)] public int NumberWithDefault { get; set; }

// Use custom converters for complex types
[Column(2)] public CustomType ComplexData { get; set; }

Issue: Performance problems with large files

Solutions:

Use async methods: ParseAsync instead of Parse
Process streams instead of loading entire files
Implement batch processing for very large datasets

// Good for large files
using var stream = File.OpenRead(largeFile);
var data = await parser.ParseAsync<MyClass>(stream);

// Better for huge files - process in chunks
var batches = data.Chunk(1000);
foreach (var batch in batches)
{
    await ProcessBatch(batch);
}

Issue: Memory consumption

Solutions:

Use streams instead of loading files into memory
Process data in batches
Dispose of large objects promptly

// Memory efficient approach
await using var fileStream = File.OpenRead(filePath);
var records = await parser.ParseAsync<Record>(fileStream);

// Process immediately, don't store all in memory
foreach (var record in records)
{
    await ProcessRecord(record);
}

Debugging Tips

Check the Index property to identify problematic lines
Examine the Errors collection for detailed error messages
Use a debugger to inspect parsed objects
Validate your data format matches your model
Test with small datasets before processing large files

Getting Help

GitHub Issues: Report bugs or request features
Documentation: Check this wiki for detailed guidance
Examples: Look at the test project for usage patterns

Contributing

We welcome contributions to Parsley.Net! Here's how you can help:

Development Setup

Clone the repository:

git clone https://github.com/CodeShayk/parsley.net.git
cd parsley.net

Build the solution:

dotnet build

Run tests:

dotnet test

Contribution Guidelines

Fork the repository and create a feature branch
Write tests for new functionality
Follow existing code patterns and conventions
Update documentation as needed
Submit a pull request with clear description

Project Structure

parsley.net/
├── src/
│   └── Parsley/                 # Main library code
│       ├── Parser.cs           # Core parser implementation
│       ├── IParser.cs          # Parser interface
│       ├── IFileLine.cs        # Line interface
│       ├── ColumnAttribute.cs  # Column mapping attribute
│       └── CustomConverter.cs  # Built-in custom converter
├── tests/
│   └── Parsley.Tests/          # Unit tests
│       ├── ParserFixture.cs    # Main test class
│       └── FileLines/          # Test data models
└── .github/
    └── workflows/              # CI/CD workflows

Code Standards

Use C# naming conventions
Follow SOLID principles
Write comprehensive unit tests
Document public APIs with XML comments
Keep backward compatibility when possible

Version History

Version	Release Date	Key Features
v1.0.0	2024-12-01	Initial release with basic parsing functionality
v1.1.0	2024-12-15	Added async support, stream processing, dependency injection
v1.1.5	2025-01-15	Performance improvements in async parsing, bug fixes

Advanced Scenarios

Scenario 1: Multi-Format File Processing

Sometimes you need to handle files with different formats in the same application:

public class FileProcessor
{
    private readonly Dictionary<string, IParser> _parsers;
    
    public FileProcessor()
    {
        _parsers = new Dictionary<string, IParser>
        {
            [".csv"] = new Parser(','),
            [".tsv"] = new Parser('\t'),
            [".psv"] = new Parser('|'),
            [".txt"] = new Parser(';')
        };
    }
    
    public async Task<T[]> ProcessFile<T>(string filePath) where T : IFileLine, new()
    {
        var extension = Path.GetExtension(filePath).ToLowerInvariant();
        
        if (!_parsers.TryGetValue(extension, out var parser))
        {
            throw new NotSupportedException($"File format {extension} is not supported");
        }
        
        return await parser.ParseAsync<T>(filePath);
    }
}

Scenario 2: Real-time Data Processing

For applications that process data in real-time:

public class RealTimeProcessor<T> where T : IFileLine, new()
{
    private readonly IParser _parser;
    private readonly Queue<string> _lineBuffer;
    private readonly object _lockObject = new object();
    
    public event Action<T[]> BatchProcessed;
    public event Action<string> ProcessingError;
    
    public RealTimeProcessor(IParser parser)
    {
        _parser = parser;
        _lineBuffer = new Queue<string>();
    }
    
    public void AddLine(string line)
    {
        lock (_lockObject)
        {
            _lineBuffer.Enqueue(line);
        }
    }
    
    public async Task ProcessBatch(int batchSize = 100)
    {
        string[] batch;
        
        lock (_lockObject)
        {
            if (_lineBuffer.Count < batchSize) return;
            
            batch = new string[batchSize];
            for (int i = 0; i < batchSize; i++)
            {
                batch[i] = _lineBuffer.Dequeue();
            }
        }
        
        try
        {
            var results = await _parser.ParseAsync<T>(batch);
            BatchProcessed?.Invoke(results);
        }
        catch (Exception ex)
        {
            ProcessingError?.Invoke($"Batch processing failed: {ex.Message}");
        }
    }
}

// Usage
var processor = new RealTimeProcessor<Employee>(new Parser(','));
processor.BatchProcessed += OnBatchProcessed;
processor.ProcessingError += OnProcessingError;

// Add lines as they come in
processor.AddLine("1,John Doe,IT,50000");
processor.AddLine("2,Jane Smith,HR,55000");

// Process when ready
await processor.ProcessBatch();

Scenario 3: Data Validation Pipeline

Implementing a comprehensive validation pipeline:

public class ValidationPipeline<T> where T : IFileLine, new()
{
    private readonly IParser _parser;
    private readonly List<IValidator<T>> _validators;
    
    public ValidationPipeline(IParser parser)
    {
        _parser = parser;
        _validators = new List<IValidator<T>>();
    }
    
    public ValidationPipeline<T> AddValidator(IValidator<T> validator)
    {
        _validators.Add(validator);
        return this;
    }
    
    public async Task<ValidationResult<T>> ProcessAsync(string filePath)
    {
        var parsed = await _parser.ParseAsync<T>(filePath);
        var result = new ValidationResult<T>();
        
        foreach (var item in parsed)
        {
            // Check parsing errors first
            if (item.Errors?.Any() == true)
            {
                result.AddInvalid(item, item.Errors);
                continue;
            }
            
            // Run custom validators
            var validationErrors = new List<string>();
            foreach (var validator in _validators)
            {
                var validationResult = validator.Validate(item);
                if (!validationResult.IsValid)
                {
                    validationErrors.AddRange(validationResult.Errors);
                }
            }
            
            if (validationErrors.Any())
            {
                result.AddInvalid(item, validationErrors);
            }
            else
            {
                result.AddValid(item);
            }
        }
        
        return result;
    }
}

public interface IValidator<T>
{
    ValidationResult Validate(T item);
}

public class EmployeeValidator : IValidator<Employee>
{
    public ValidationResult Validate(Employee employee)
    {
        var result = new ValidationResult();
        
        if (string.IsNullOrWhiteSpace(employee.Name))
            result.AddError("Name is required");
            
        if (employee.Salary <= 0)
            result.AddError("Salary must be positive");
            
        if (employee.HireDate > DateTime.Now)
            result.AddError("Hire date cannot be in the future");
            
        return result;
    }
}

// Usage
var pipeline = new ValidationPipeline<Employee>(new Parser(','))
    .AddValidator(new EmployeeValidator())
    .AddValidator(new EmailValidator());
    
var result = await pipeline.ProcessAsync("employees.csv");

Console.WriteLine($"Valid records: {result.ValidItems.Count}");
Console.WriteLine($"Invalid records: {result.InvalidItems.Count}");

Scenario 4: Configuration-Driven Parsing

For applications that need flexible, configuration-driven parsing:

public class ConfigurableParser
{
    public class ParsingConfiguration
    {
        public char Delimiter { get; set; } = ',';
        public bool HasHeader { get; set; } = false;
        public Dictionary<string, int> ColumnMappings { get; set; } = new();
        public Dictionary<string, object> DefaultValues { get; set; } = new();
        public Encoding Encoding { get; set; } = Encoding.UTF8;
    }
    
    public async Task<T[]> ParseWithConfiguration<T>(string filePath, ParsingConfiguration config) 
        where T : IFileLine, new()
    {
        var parser = new Parser(config.Delimiter);
        var lines = await File.ReadAllLinesAsync(filePath, config.Encoding);
        
        // Skip header if present
        if (config.HasHeader)
        {
            lines = lines.Skip(1).ToArray();
        }
        
        // Apply configuration-based transformations here
        // This is a simplified example - you could extend this significantly
        
        return await parser.ParseAsync<T>(lines);
    }
}

// Configuration from appsettings.json
{
  "ParsingConfiguration": {
    "Delimiter": "|",
    "HasHeader": true,
    "ColumnMappings": {
      "EmployeeId": 0,
      "Name": 1,
      "Department": 2
    },
    "DefaultValues": {
      "Department": "Unknown",
      "IsActive": true
    }
  }
}

Integration Examples

ASP.NET Core Web API

[ApiController]
[Route("api/[controller]")]
public class DataController : ControllerBase
{
    private readonly IParser _parser;
    private readonly ILogger<DataController> _logger;
    
    public DataController(IParser parser, ILogger<DataController> logger)
    {
        _parser = parser;
        _logger = logger;
    }
    
    [HttpPost("upload-employees")]
    public async Task<IActionResult> UploadEmployees(IFormFile file)
    {
        if (file == null || file.Length == 0)
            return BadRequest("No file uploaded");
            
        try
        {
            using var stream = file.OpenReadStream();
            var employees = await _parser.ParseAsync<Employee>(stream);
            
            var validEmployees = employees.Where(e => e.Errors?.Any() != true).ToList();
            var errorCount = employees.Count(e => e.Errors?.Any() == true);
            
            // Process valid employees (save to database, etc.)
            await ProcessEmployees(validEmployees);
            
            return Ok(new
            {
                ProcessedCount = validEmployees.Count,
                ErrorCount = errorCount,
                Errors = employees
                    .Where(e => e.Errors?.Any() == true)
                    .Select(e => new { Line = e.Index, Errors = e.Errors })
            });
        }
        catch (Exception ex)
        {
            _logger.LogError(ex, "Error processing employee file");
            return StatusCode(500, "Error processing file");
        }
    }
    
    private async Task ProcessEmployees(List<Employee> employees)
    {
        // Your business logic here
        foreach (var employee in employees)
        {
            // Save to database, send notifications, etc.
        }
    }
}

// Startup.cs or Program.cs
public void ConfigureServices(IServiceCollection services)
{
    services.UseParsley(','); // Configure Parsley.Net
    services.AddControllers();
    // Other services...
}

Background Service for File Processing

public class FileProcessingService : BackgroundService
{
    private readonly IParser _parser;
    private readonly ILogger<FileProcessingService> _logger;
    private readonly IServiceScopeFactory _serviceScopeFactory;
    private readonly string _watchFolder;
    
    public FileProcessingService(
        IParser parser,
        ILogger<FileProcessingService> logger,
        IServiceScopeFactory serviceScopeFactory,
        IConfiguration configuration)
    {
        _parser = parser;
        _logger = logger;
        _serviceScopeFactory = serviceScopeFactory;
        _watchFolder = configuration["FileProcessing:WatchFolder"];
    }
    
    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        using var watcher = new FileSystemWatcher(_watchFolder, "*.csv");
        
        watcher.Created += async (sender, e) => await ProcessFile(e.FullPath);
        watcher.EnableRaisingEvents = true;
        
        while (!stoppingToken.IsCancellationRequested)
        {
            await Task.Delay(1000, stoppingToken);
        }
    }
    
    private async Task ProcessFile(string filePath)
    {
        try
        {
            _logger.LogInformation($"Processing file: {filePath}");
            
            var records = await _parser.ParseAsync<DataRecord>(filePath);
            
            using var scope = _serviceScopeFactory.CreateScope();
            var dataService = scope.ServiceProvider.GetRequiredService<IDataService>();
            
            await dataService.ProcessRecords(records);
            
            // Move processed file to archive
            var archivePath = Path.Combine(_watchFolder, "processed", Path.GetFileName(filePath));
            File.Move(filePath, archivePath);
            
            _logger.LogInformation($"Successfully processed {records.Length} records from {filePath}");
        }
        catch (Exception ex)
        {
            _logger.LogError(ex, $"Error processing file: {filePath}");
            
            // Move failed file to error folder
            var errorPath = Path.Combine(_watchFolder, "errors", Path.GetFileName(filePath));
            File.Move(filePath, errorPath);
        }
    }
}

Console Application with Progress Reporting

class Program
{
    static async Task Main(string[] args)
    {
        if (args.Length != 1)
        {
            Console.WriteLine("Usage: DataProcessor <file-path>");
            return;
        }
        
        var filePath = args[0];
        var parser = new Parser(',');
        
        Console.WriteLine($"Processing file: {filePath}");
        Console.WriteLine("Please wait...");
        
        var stopwatch = Stopwatch.StartNew();
        
        try
        {
            // For large files, you might want to implement progress reporting
            var records = await ParseWithProgress<DataRecord>(parser, filePath);
            
            stopwatch.Stop();
            
            var validRecords = records.Where(r => r.Errors?.Any() != true).ToArray();
            var errorRecords = records.Where(r => r.Errors?.Any() == true).ToArray();
            
            Console.WriteLine();
            Console.WriteLine($"Processing completed in {stopwatch.Elapsed:mm\\:ss}");
            Console.WriteLine($"Total records: {records.Length:N0}");
            Console.WriteLine($"Valid records: {validRecords.Length:N0}");
            Console.WriteLine($"Error records: {errorRecords.Length:N0}");
            
            if (errorRecords.Any())
            {
                Console.WriteLine("\nErrors found:");
                foreach (var error in errorRecords.Take(10)) // Show first 10 errors
                {
                    Console.WriteLine($"  Line {error.Index}: {string.Join(", ", error.Errors)}");
                }
                
                if (errorRecords.Length > 10)
                {
                    Console.WriteLine($"  ... and {errorRecords.Length - 10} more errors");
                }
            }
        }
        catch (Exception ex)
        {
            Console.WriteLine($"Error: {ex.Message}");
            Environment.Exit(1);
        }
    }
    
    static async Task<T[]> ParseWithProgress<T>(IParser parser, string filePath) where T : IFileLine, new()
    {
        var fileInfo = new FileInfo(filePath);
        var totalBytes = fileInfo.Length;
        var processedBytes = 0L;
        
        using var fileStream = File.OpenRead(filePath);
        using var reader = new StreamReader(fileStream);
        
        var lines = new List<string>();
        string line;
        var lastProgress = 0;
        
        while ((line = await reader.ReadLineAsync()) != null)
        {
            lines.Add(line);
            processedBytes += Encoding.UTF8.GetByteCount(line) + Environment.NewLine.Length;
            
            var progress = (int)((processedBytes * 100) / totalBytes);
            if (progress > lastProgress)
            {
                Console.Write($"\rReading file: {progress}%");
                lastProgress = progress;
            }
        }
        
        Console.Write("\rParsing data...  ");
        return await parser.ParseAsync<T>(lines.ToArray());
    }
}

Best Practices Summary

Design Principles

Single Responsibility: Each data model should represent one type of record
Fail Fast: Use validation to catch errors early in the process
Immutable Data: Consider making parsed objects immutable after creation
Error Transparency: Always check and handle the Errors property

Performance Best Practices

Use Async Methods: Always prefer ParseAsync for I/O operations
Stream Large Files: Use Stream or byte[] overloads for large files
Batch Processing: Process large datasets in smaller chunks
Caching: Reuse parser instances when possible
Memory Management: Dispose of streams and large objects promptly

Code Organization

// Good structure
/Models/
  ├── Employee.cs           // Data model with IFileLine
  ├── EmployeeConverters.cs // Custom type converters
  └── EmployeeValidator.cs  // Business validation
/Services/
  ├── IDataService.cs       // Service interface
  └── EmployeeService.cs    // Service implementation
/Configuration/
  └── ParsingExtensions.cs  // DI configuration

Error Handling Strategy

Parse-time Errors: Use the Errors property for field-level issues
Business Validation: Implement separate validation after parsing
File-level Errors: Use try-catch for file access issues
Logging: Always log processing results and errors

Conclusion

Parsley.Net provides a powerful, flexible, and performant solution for parsing structured text files in .NET applications. Its combination of simplicity and extensibility makes it suitable for everything from small utility scripts to large-scale enterprise applications.

Key Takeaways

Simplicity: Minimal configuration required for basic scenarios
Flexibility: Extensive customization options for complex requirements
Performance: Optimized for both small files and large-scale processing
Reliability: Comprehensive error handling and validation support
Integration: Seamless integration with modern .NET patterns and practices

When to Use Parsley.Net

✅ Perfect for:

CSV/TSV file processing
Data migration and ETL operations
Configuration file parsing
Legacy system integration
Batch data processing

❌ Consider alternatives for:

JSON/XML processing (use System.Text.Json or XmlSerializer)
Binary file formats
Real-time streaming data (consider specialized streaming libraries)
Database direct access (use Entity Framework or similar)

Getting Support

Documentation: This wiki provides comprehensive guidance
GitHub Issues: Report issues or request features
Source Code: View the source on GitHub
NuGet Package: Download from NuGet

Happy parsing with Parsley.Net! 🚀

Home

Parsley.Net - Complete Guide

Table of Contents

Introduction

What is Parsley.Net?

Key Features

Supported Frameworks

Understanding Fixed Width and Delimiter Separated Files

What are Delimiter Separated Files?

Example: Pipe Separated File

What are Fixed Width Files?

Example: Fixed Width File

Common Use Cases

Why Choose Parsley.Net?

Advantages Over Manual Parsing

Performance Benefits

Developer Experience

Getting Started

Installation

Package Manager Console

.NET CLI

PackageReference (in .csproj)

Quick Start Example

Core Components

IParser Interface

Parser Class

IFileLine Interface

ColumnAttribute

Usage Examples:

Advanced Usage

Custom Type Converters

Method 1: Traditional TypeConverter

Method 2: Built-in CustomConverter

Dependency Injection

Enum Support

Stream Processing for Large Files

Performance Considerations

Parallel Processing

Performance Tips

Benchmarking Results

Error Handling

Per-Line Error Tracking

Common Error Types

Error Messages

Best Practices for Error Handling

Testing Guide

Unit Testing with Parsley.Net

Basic Parsing Tests

Error Handling Tests

Async Testing

Integration Testing

Mocking for Dependencies

API Reference

Parser Class Methods

Synchronous Methods

Asynchronous Methods

Attributes

ColumnAttribute

Extension Methods

Examples

Example 1: Employee Management System

Example 2: Financial Transaction Processing

Example 3: Configuration File Parsing

Troubleshooting

Common Issues and Solutions

Issue: "Invalid line format - number of column values do not match"

Issue: Type conversion errors

Issue: Performance problems with large files

Issue: Memory consumption

Debugging Tips

Getting Help

Contributing

Development Setup

Contribution Guidelines

Project Structure

Code Standards

Version History

Advanced Scenarios

Scenario 1: Multi-Format File Processing

Scenario 2: Real-time Data Processing