Cinchoo ETL – CSV Reader

1. Introduction
2. Requirement
3. “Hello World!” Sample
- 3.1. Quick load – Data First Approach
- 3.2. Code First Approach
- 3.3. Configuration First Approach
- 3.4. Code First with declarative configuration
4. Reading All Records
5. Read Records Manually
6. Customize CSV Record
7. Customize CSV Header
8. Customize CSV Fields
- 8.1. DefaultValue
- 8.2. ChoFallbackValue
- 8.3. Type Converters
  - 8.3.1. Declarative Approach
  - 8.3.2. Configuration Approach
- 8.4. Validations
9. Excel Field Separator
10. Callback Mechanism
- 10.1 Using CSVReader events
- 10.2 Implementing IChoNotifyRecordRead interface
- 10.3 BeginLoad
- 10.4 EndLoad
- 10.5 BeforeRecordLoad
- 10.6 AfterRecordLoad
- 10.7 RecordLoadError
- 10.8 BeforeRecordFieldLoad
- 10.9 AfterRecordFieldLoad
- 10.10 RecordLoadFieldError
10. Customization
11. AsDataReader Helper Method
12. AsDataTable Helper Method
13. Using Dynamic Object
- 13.1. DefaultValue
- 13.2. ChoFallbackValue
- 13.3. FieldType
- 13.4. Type Converters
- 13.5. Validations
14. Working with sealed POCO object
15. Exceptions
16. Tips
- 16.1 Multiline CSV column value
- 16.2 CSV column value with field separator
- 16.3 CSV column value with single quotes
17. Using MetadataType Annotation
18. Configuration Choices
- 18.1 Manual Configuration
- 18.2 Auto Map Configuration
- 18.3 Attaching MetadataType class
19. LoadText Helper Method
20. Advanced Topics
- 20.1 Override Converters Format Specs
- 20.2 Currency Support
- 20.3 Enum Support
- 20.4 Boolean Support
- 20.5 DateTime Support
21. Fluent API
- 21.1 WithDelimiter
- 21.2 WithFirstLineHeader
- 21.3 WithFields
- 21.4 WithField
- 21.5 QuoteAllFields
- 21.6 ColumnCountStrict
- 21.6 ColumnOrderStrict
- 21.8 NotifyAfter
- 21.9 Configure
- 21.10 Setup
21. FAQ
- 21.1 I want to write file with headers
- 21.1 File has lines I want to skip them from loading
- 21.2 Not all characters are read from data file
- 21.3 How to handle multiline records
- 21.4 How to handle errors and log them
- 21.5 How to handle column headers having spaces or special characters in them?
- 21.6 Failed to format DateTime during load?
- 21.7 How to handle duplicate CSV columns?
- 21.8 What if CSV header is found other than first line?
- 21.9 How to turn off ‘Records loaded’ or other trace messages?
- 21.10 How to specify default values to CSV columns?
- 21.11 Does Cinchoo ETL support hierarchical object support?

1. Introduction

ChoETL is an open source ETL (extract, transform and load) framework for .NET. It is a code based library for extracting data from multiple sources, transforming, and loading into your very own data warehouse in .NET environment. You can have data in your data warehouse in no time.

This article talks about using CSVReader component offered by ChoETL framework. It is a simple utility class to extract CSV data from file / source.

UPDATE: Corresponding CSVWriter article can be found here.

Features:

Ultra-fast CSV Reader, parses CSV file with 15 columns / 500,000 records in 15 seconds.
Stream based parsers allow for ultimate performance, low resource usage, and nearly unlimited versatility scalable to any size data file, even tens or hundreds of gigabytes.
Event based data manipulation and validation allows total control over the flow of data during the bulk insert process.
Follows CSV standard file rules. Gracefully handles data fields that contain commas and line breaks.
In addition to comma, most delimiting characters can be used, including tab delimited fields.
Exposes IEnumarable list of objects – which is often used with LINQ query for projection, aggregation and filtration etc.
Supports deferred reading.
Supports processing files with culture specific date, currency and number formats.
Supports different character encoding.
Recognizes a wide variety of date, currency, enum, boolean and number formats when reading files.
Provides fine control of date, currency, enum, boolean, number formats when writing files.
Detailed and robust error handling, allowing you to quickly find and fix problems.

Performance:

This framework was tested with the test files containing 15 fields with different number of records (250,000, 500,000, 1M, 1.5M, 2M, 2.5M etc). The graph below shows the total time taken to load each file. The test was performed in Intel Core i5 / 8GB RAM machine.

No of Records	Run time (secs)
250,000	7
500,000	15
1,000,000	29
1,500,000	44
2,000,000	58
2,500,000	72

2. Requirement

This framework library is written in C# using .NET 4.5 Framework.

3. “Hello World!” Sample

Open VS.NET 2013 or higher
Create a sample VS.NET (.NET Framework 4.5) Console Application project
Install ChoETL via Package Manager Console using Nuget Command: Install-Package ChoETL
Use the ChoETL namespace

Let’s begin by looking into a simple example of reading CSV file having 2 columns

Listing 3.1 Sample CSV data file

Id,Name
1,Tom
2,Carl
3,Mark

There are number of ways you can get the CSV file parsing started with minimal setup

3.1. Quick load – Data First Approach

It is the zero config, quick way to load a CSV file in no time. No POCO object is required. Sample code below shows how to load the file

Listing 3.1.1 Load CSV file using iterator

foreach (dynamic e in new ChoCSVReader("Emp.csv").WithFirstLineHeader())
{            
    Console.WriteLine(String.Format("Id: {0}", e.Id));
    Console.WriteLine(String.Format("Name: {0}", e.Name));
}

Listing 3.1.2 Load CSV file using loop

var reader = new ChoCSVReader("Emp.csv").WithFirstLineHeader();
dynamic rec;
 
while ((rec = reader.Read()) != null)
{            
    Console.WriteLine(String.Format("Id: {0}", rec.Id));
    Console.WriteLine(String.Format("Name: {0}", rec.Name));
}

This model uses generaric CSVReader object for parsing the file. CSVReader auto name the columns as Column1, Column2 … in the dynamic object.

UPDATE:

With the latest Cinchoo ETL library, you can access members by index. Indexes are start by zero.

Listing 3.1.3 Access by index

foreach (dynamic e in new ChoCSVReader("Emp.csv").WithFirstLineHeader())
{            
    Console.WriteLine(String.Format("Id: {0}", e[0]));
    Console.WriteLine(String.Format("Name: {0}", e[1]));
}

3.2. Code First Approach

This is another zero config way to parse and load CSV file using POCO class. First define a simple data class to match the underlying CSV file layout

Listing 3.2.1 Simple POCO entity class

public partial class EmployeeRec
{
    public int Id { get; set; }
    public string Name { get; set; } 
}

In above, the class defines two properties matching the sample CSV file template.

Listing 3.2.2 Load CSV file

foreach (var e in new ChoCSVReader<EmployeeRec>("Emp.csv").WithFirstLineHeader())
{            
    Console.WriteLine(String.Format("Id: {0}", e.Id));
    Console.WriteLine(String.Format("Name: {0}", e.Name));
}

3.3. Configuration First Approach

In this model, we define the CSV configuration with all the necessary parsing parameters along with CSV columns matching with the underlying CSV file.

Listing 3.3.1 Define CSV configuration

ChoCSVRecordConfiguration config = new ChoCSVRecordConfiguration();
config.CSVRecordFieldConfigurations.Add(new ChoCSVRecordFieldConfiguration("Id", 1));
config.CSVRecordFieldConfigurations.Add(new ChoCSVRecordFieldConfiguration("Name", 2));

In above, the class defines two properties matching the sample CSV file template.

Listing 3.3.2 Load CSV file without POCO object

foreach (dynamic e in new ChoCSVReader("Emp.csv", config).WithFirstLineHeader())
{            
    Console.WriteLine(String.Format("Id: {0}", e.Id));
    Console.WriteLine(String.Format("Name: {0}", e.Name));
}

Listing 3.3.3 Load CSV file with POCO object

foreach (dynamic e in new ChoCSVReader<EmployeeRec>("Emp.csv", config).WithFirstLineHeader())
{            
    Console.WriteLine(String.Format("Id: {0}", e.Id));
    Console.WriteLine(String.Format("Name: {0}", e.Name));
}

3.4. Code First with declarative configuration

This is the combined approach to define POCO entity class along with CSV configuration parameters decorated declaratively. id is required column and name is optional value column with default value “XXXX“. If name is not present, it will take the default value.

Listing 3.4.1 Define POCO Object

public class EmployeeRec
{
    [ChoCSVRecordField(1)]
    [Required]
    public int Id
    {
        get;
        set;
    }
    [ChoCSVRecordField(2)]
    [DefaultValue("XXXX")]
    public string Name
    {
        get;
        set;
    }

    public override string ToString()
    {
        return "{0}. {1}.".FormatString(Id, Name);
    }
}

The code above illustrates about defining POCO object to carry the values of each record line in the input file. First thing defines property for each record field with ChoCSVRecordFieldAttribute to qualify for CSV record mapping. Each property must specify position in order to be mapped to CSV column. Position is 1 based. Id is a required property. We decorated it with RequiredAttribute. Name is given default value using DefaultValueAttribute. It means that if the Name CSV column contains empty value in the file, it will be defaulted to ‘XXXX‘ value.

It is very simple and ready to extract CSV data in no time.

Listing 3.4.2 Main Method

class Program
{
    static void Main(string[] args)
    {
        using (var stream = new MemoryStream())
        using (var reader = new StreamReader(stream))
        using (var writer = new StreamWriter(stream))
        using (var parser = new ChoCSVReader<EmployeeRec>(reader))
        {
            writer.WriteLine("1,Carl");
            writer.WriteLine("2,Mark");
            writer.WriteLine("3,");

            writer.Flush();
            stream.Position = 0;
 
            object row = null;
 
            while ((row = parser.Read()) != null)
            {
                Console.WriteLine(String.Format("Id: {0}", row.Id));
                Console.WriteLine(String.Format("Name: {0}", row.Name));
            }
        }
    }
}

We start by creating a new instance of ChoCSVReader object. That’s all. All the heavy lifting of parsing and loading CSV data stream into the objects is done by the parser under the hood.

By default, CSVReader discovers and uses default configuration parameters while loading CSV file. These can be overridable according to your needs. The following sections will give details about each configuration attributes.

4. Reading All Records

It is as easy as setting up POCO object match up with CSV file structure, you can read the whole file as enumerable pattern. It is a deferred execution mode, but take care while making any aggregate operation on them. This will load the entire file records into memory.

Listing 4.1 Read CSV File

foreach (var e in new ChoCSVReader<EmployeeRec>("Emp.csv").WithFirstLineHeader())
{            
    Console.WriteLine(String.Format("Id: {0}", e.Id));
    Console.WriteLine(String.Format("Name: {0}", e.Name));
}

or:

Listing 4.2 Read CSV file stream

foreach (var e in new ChoCSVReader<EmployeeRec>(textReader).WithFirstLineHeader())
{            
    Console.WriteLine(String.Format("Id: {0}", e.Id));
    Console.WriteLine(String.Format("Name: {0}", e.Name));
}

This model keeps your code elegant, clean, easy to read and maintain. Also leverages LINQ extension methods to to perform grouping, joining, projection, aggregation etc.

Listing 4.3 Using LINQ

var list = (from o in new ChoCSVReader<EmployeeRec>("Emp.csv").WithFirstLineHeader()
           where o.Name != null && o.Name.StartsWith("R")
           select o).ToArray();
 
foreach (var e in list)
{            
    Console.WriteLine(String.Format("Id: {0}", e.Id));
    Console.WriteLine(String.Format("Name: {0}", e.Name));
}

5. Read Records Manually

It is as easy as setting up POCO object match up with CSV file structure, you can read the whole file as enumerable pattern

Listing 5.1 Read CSV file

var reader = new ChoCSVReader<EmployeeRec>("Emp.csv").WithFirstLineHeader();
var rec = (object)null;
 
while ((rec = reader.Read()) != null)
{            
    Console.WriteLine(String.Format("Id: {0}", rec.Id));
    Console.WriteLine(String.Format("Name: {0}", rec.Name));
}

6. Customize CSV Record

Using ChoCSVRecordObjectAttribute, you can customize the POCO entity object declaratively.

Listing 6.1 Customizing POCO object for each record

[ChoCSVRecordObject(Encoding = "Encoding.UTF32", 
ErrorMode = ChoErrorMode.IgnoreAndContinue, IgnoreFieldValueMode = ChoIgnoreFieldValueMode.All)]
public class EmployeeRec
{
    [ChoCSVRecordField(1, FieldName = "id")]
    public int Id { get; set; }
    [ChoCSVRecordField(2, FieldName ="Name", QuoteField = true)]
    [Required]
    [DefaultValue("ZZZ")]
    public string Name { get; set; }
}

Here are the available attributes to carry out customization of CSV load operation on a file.

Delimiter – The value used to separate the fields in a CSV row. Default is Culture.TextInfo.ListSeparator used.
EOLDelimiter – The value used to separate CSV rows. Default is \r\n (NewLine).
CultureName – The culture name (ex. en-US, en-GB) used to read and write CSV data.
IgnoreEmptyLine – A flag to let the reader know if a record should be skipped when reading if it’s empty. A record is considered empty if all fields are empty.
Comments – The value used to denote a line that is commented out. Multiple comments can be specified. Must be separated by comma.
QuoteChar – The value used to escape fields that contain a delimiter, quote, or line ending.
QuoteAllFields – N/A for reader.
Encoding – The encoding of the CSV file.
HasExcelSeperator – N/A for reader. Reader seamlessly recognize the excel separator if specified in the CSV file and use them for parsing.
ColumnCountStrict – This flag indicates if an exception should be thrown if reading an expected field is missing.
ColumnOrderStrict – This flag indicates if an exception should be thrown if reading an expected field is in wrong position in the file. This check will be performed only when ColumnCountStrict is true.
BufferSize – The size of the internal buffer that is used when reader is from the StreamReader.
ErrorMode – This flag indicates if an exception should be thrown if reading and an expected field is failed to load. This can be overridden per property. Possible values are:
- IgnoreAndContinue – Ignore the error, record will be skipped and continue with next.
- ReportAndContinue – Report the error to POCO entity if it is of IChoNotifyRecordRead type
- ThrowAndStop – Throw the error and stop the execution
IgnoreFieldValueMode – A flag to let the reader know if a record should be skipped when reading if it’s empty / null. This can be overridden per property. Possible values are:
- Null – N/A
- DBNull – N/A
- Empty – skipped if the record value is empty
- WhiteSpace – skipped if the record value contains only whitespaces
ObjectValidationMode – A flag to let the reader know about the type of validation to be performed with record object. Possible values are:
- Off – No object validation performed.
- MemberLevel – Validation performed at the time of each CSV property gets loaded with value.
- ObjectLevel – Validation performed after all the properties are loaded to the POCO object.

7. Customize CSV Header

If the CSV file has header, you can instruct the POCO entity by using ChoCSVFileHeaderAttribute.

Listing 6.1 Customizing POCO object for file header

[ChoCSVFileHeader]
public class EmployeeRec
{
    [ChoCSVRecordField(1, FieldName = "id")]
    public int Id { get; set; }
    [ChoCSVRecordField(2, FieldName ="Name", QuoteField = true)]
    [Required]
    [DefaultValue("ZZZ")]
    public string Name { get; set; }
}

Here are the available members to add some customization to it according to your need.

FillChar – N/A for reader
Justification – N/A for reader
IgnoreCase – true, CSV column matching are done with case insensitive. Otherwise false.
TrimOption – This flag tells the reader to trim whitespace from the beginning and ending of the CSV column header when reading. Possible values are Trim, TrimStart, TrimEnd.
Truncate – N/A for reader

8. Customize CSV Fields

For each CSV column, you can specify the mapping in POCO entity property using ChoCSVRecordFieldAttribute.

Listing 6.1 Customizing POCO object for CSV columns

[ChoCSVFileHeader]
public class EmployeeRec
{
    [ChoCSVRecordField(1, FieldName = "id")]
    public int Id { get; set; }
    [ChoCSVRecordField(2, FieldName ="Name", QuoteField = true)]
    [Required]
    [DefaultValue("ZZZ")]
    public string Name { get; set; }
}

Here are the available members to add some customization to it for each property:

FieldPosition – When mapping by position, you specify the index of the CSV column that you want to use for that property. It is 1 based.
FieldName – When mapping by name, you specify the name of the CSV column that you want to use for that property. For this to work, the CSV file must have a header record. The name you specify must match with the name of the header record.
FillChar – N/A for reader.
FieldValueJustification – N/A for reader.
FieldValueTrimOption – This flag tells the reader to trim whitespace from the beginning and ending of the field value when reading. Possible values are Trim, TrimStart, TrimEnd.
Truncate – N/A for reader.
Size – N/A for reader.
QuoteField – A flag that tells the reader that the CSV column value is surrounded by quotes.
ErrorMode – This flag indicates if an exception should be thrown if reading and an expected field failed to load. Possible values are:
- IgnoreAndContinue – Ignore the error and continue to load other properties of the record.
- ReportAndContinue – Report the error to POCO entity if it is of IChoRecord type.
- ThrowAndStop – Throw the error and stop the execution.
IgnoreFieldValueMode – A flag to let the reader know if a record should be skipped when reading if it’s empty / null. Possible values are:
- Null – N/A
- DBNull – N/A
- Empty – skipped if the record value is empty.
- WhiteSpace – skipped if the record value contains only whitespaces.

8.1. DefaultValue

It is the value used and set to the property when the CSV value is empty or whitespace (controlled via IgnoreFieldValueMode).

Any POCO entity property can be specified with default value using System.ComponentModel.DefaultValueAttribute.

8.2. ChoFallbackValue

It is the value used and set to the property when the CSV value failed to set. Fallback value only set when ErrorMode is either IgnoreAndContinue or ReportAndContinue.

Any POCO entity property can be specified with fallback value using ChoETL.ChoFallbackValueAttribute.

8.3. Type Converters

Most of the primitive types are automatically converted and set them to the properties. If the value of the CSV field can’t automatically be converted into the type of the property, you can specify a custom / built-in .NET converters to convert the value. These can be either IValueConverter or TypeConverter converters.

There are couple of ways you can specify the converters for each field

Declarative Approach
Configuration Approach

8.3.1. Declarative Approach

This model is applicable to POCO entity object only. If you have POCO class, you can specify the converters to each property to carry out necessary conversion on them. Samples below shows the way to do it.

Listing 8.3.1.1 Specifying type converters

[ChoCSVFileHeader]
public class EmployeeRec
{
    [ChoCSVRecordField(1, FieldName = "id")]
    [ChoTypeConverter(typeof(IntConverter))]
    public int Id { get; set; }
    [ChoCSVRecordField(2, FieldName ="Name", QuoteField = true)]
    [Required]
    [DefaultValue("ZZZ")]
    public string Name { get; set; }
}

Listing 8.3.1.2 IntConverter implementation

public class IntConverter : IValueConverter
{
    public object Convert(object value, Type targetType, object parameter, CultureInfo culture)
    {
        return value;
    }
 
    public object ConvertBack(object value, Type targetType, object parameter, CultureInfo culture)
    {
        return value;
    }
}

In the example above, we defined custom IntConverter class. And showed how to use it with ‘Id‘ CSV property.

8.3.2. Configuration Approach

This model is applicable to both dynamic and POCO entity object. This gives freedom to attach the converters to each property at runtime. This takes the precedence over the declarative converters on POCO classes.

Listing 8.3.2.2 Specifying TypeConverters

ChoCSVRecordConfiguration config = new ChoCSVRecordConfiguration();
config.FileHeaderConfiguration.HasHeaderRecord = true;
config.ThrowAndStopOnMissingField = false;

ChoCSVRecordFieldConfiguration idConfig = new ChoCSVRecordFieldConfiguration("Id", 1);
idConfig.AddConverter(new IntConverter());
config.CSVRecordFieldConfigurations.Add(idConfig);

config.CSVRecordFieldConfigurations.Add(new ChoCSVRecordFieldConfiguration("Name", 2));
config.CSVRecordFieldConfigurations.Add(new ChoCSVRecordFieldConfiguration("Name1", 2));

In above, we construct and attach the IntConverter to ‘Id’ field using AddConverter helper method in ChoCSVRecordFieldConfiguration object.

Likewise, if you want to remove any converter from it, you can use RemoveConverter on ChoCSVRecordFieldConfiguration object.

8.4. Validations

CSVReader leverages both System.ComponentModel.DataAnnotations and Validation Block validation attributes to specify validation rules for individual fields of POCO entity. Refer to the MSDN site for a list of available DataAnnotations validation attributes.

Listing 8.4.1 Using validation attributes in POCO entity

[ChoCSVFileHeader]
[ChoCSVRecordObject(Encoding = "Encoding.UTF32", ErrorMode = ChoErrorMode.IgnoreAndContinue,
       IgnoreFieldValueMode = ChoIgnoreFieldValueMode.All, ThrowAndStopOnMissingField = false)]
public partial class EmployeeRec
{
    [ChoCSVRecordField(1, FieldName = "id")]
    [ChoTypeConverter(typeof(IntConverter))]
    [Range(1, int.MaxValue, ErrorMessage = "Id must be > 0.")]
    [ChoFallbackValue(1)]
    public int Id { get; set; }
 
    [ChoCSVRecordField(2, FieldName = "Name")]
    [Required]
    [DefaultValue("ZZZ")]
    [ChoFallbackValue("XXX")]
    public string Name { get; set; }
}

In example above, used Range validation attribute for Id property. Required validation attribute to Name property. CSVReader performs validation on them during load based on Configuration.ObjectValidationMode is set to ChoObjectValidationMode.MemberLevel or ChoObjectValidationMode.ObjectLevel.

Sometime you may want override the defined declarative validation behaviors comes with POCO class, you can do with Cinchoo ETL via configuration approach. The sample below shows the way to override them.

static void ValidationOverridePOCOTest()
{
    ChoCSVRecordConfiguration config = new ChoCSVRecordConfiguration();
    var idConfig = new ChoCSVRecordFieldConfiguration("Id", 1);
    idConfig.Validators = new ValidationAttribute[] { new RequiredAttribute() };
    config.CSVRecordFieldConfigurations.Add(idConfig);
    config.CSVRecordFieldConfigurations.Add(new ChoCSVRecordFieldConfiguration("Name", 2));
    config.CSVRecordFieldConfigurations.Add(new ChoCSVRecordFieldConfiguration("Salary", 3) { FieldType = typeof(ChoCurrency) });
 
    using (var stream = new MemoryStream())
    using (var reader = new StreamReader(stream))
    using (var writer = new StreamWriter(stream))
    using (var parser = new ChoCSVReader<EmployeeRecWithCurrency>(reader, config))
    {
        writer.WriteLine("1,Carl,$100000");
        writer.WriteLine("2,Mark,$50000");
        writer.WriteLine("3,Tom,1000");
 
        writer.Flush();
        stream.Position = 0;
 
        object rec;
        while ((rec = parser.Read()) != null)
        {
            Console.WriteLine(String.Format("Id: {0}", rec.Id));
            Console.WriteLine(String.Format("Name: {0}", rec.Name));
            Console.WriteLine(String.Format("Salary: {0}", rec.Salary));
        }
    }
}
 
public class EmployeeRecWithCurrency
{
    public int? Id { get; set; }
    public string Name { get; set; }
    public ChoCurrency Salary { get; set; }
}

Some cases, you may want to take control and perform manual self validation within the POCO entity class. This can be achieved by inheriting POCO object from IChoValidatable interface.

Listing 8.4.2 Manual validation on POCO entity

[ChoCSVFileHeader]
[ChoCSVRecordObject(Encoding = "Encoding.UTF32", ErrorMode = ChoErrorMode.IgnoreAndContinue,
       IgnoreFieldValueMode = ChoIgnoreFieldValueMode.All, ThrowAndStopOnMissingField = false)]
public partial class EmployeeRec : IChoValidatable
{
    [ChoCSVRecordField(1, FieldName = "id")]
    [ChoTypeConverter(typeof(IntConverter))]
    [Range(1, int.MaxValue, ErrorMessage = "Id must be > 0.")]
    [ChoFallbackValue(1)]
    public int Id { get; set; }
 
    [ChoCSVRecordField(2, FieldName = "Name")]
    [Required]
    [DefaultValue("ZZZ")]
    [ChoFallbackValue("XXX")]
    public string Name { get; set; }
 
    public bool TryValidate(object target, ICollection<ValidationResult> validationResults)
    {
        return true;
    }
 
    public bool TryValidateFor(object target, string memberName, ICollection<ValidationResult> validationResults)
    {
        return true;
    }
 
    public void Validate(object target)
    {
    }
 
    public void ValidateFor(object target, string memberName)
    {
    }
}

Sample above shows how to implement custom self-validation in POCO object.

IChoValidatable interface exposes below methods

TryValidate – Validate entire object, return true if all validation passed. Otherwise return false.
Validate – Validate entire object, throw exception if validation is not passed.
TryValidateFor – Validate specific property of the object, return true if all validation passed. Otherwise return false.
ValidateFor – Validate specific property of the object, throw exception if validation is not passed.

9. Excel Field Separator

If the input CSV file contains Excel field separator, the reader automatically detects and use them as field separator.

Listing 9.1 Sample CSV file with Excel field separator

sep=,
1,"Eldon Base for stackable storage shelf, platinum"
2,"1.7 Cubic Foot Compact ""Cube"" Office Refrigerators"
3,"Cardinal Slant-D® Ring Binder, Heavy Gauge Vinyl"
4,R380
5,Holmes HEPA Air Purifier

10. Callback Mechanism

CSVReader offers industry standard CSV parsing out of the box to handle most of the parsing needs. If the parsing is not handling any of the needs, you can use the callback mechanism offered by CSVReader to handle such situations. In order to participate in the callback mechanism, you can use either of the following models

Using event handlers exposed by CSVReader via IChoReader interface.
Inheriting POCO entity object from IChoNotifyRecordRead interface
Inheriting DataAnnotation’s MetadataType type object by IChoNotifyRecordRead interface.

Note: Any exceptions raised out of these interface methods will be ignored.

Both IChoNotifyRecordRead and IChoRecorder exposes the below methods:

BeginLoad – Invoked at the begin of the CSV file load
EndLoad – Invoked at the end of the CSV file load
BeforeRecordLoad – Raised before the CSV record load
AfterRecordLoad – Raised after CSV record load
RecordLoadError – Raised when CSV record load errors out
BeforeRecordFieldLoad – Raised before CSV column value load
AfterRecordFieldLoad – Raised after CSV column value load
RecordFieldLoadError – Raised when CSV column value errors out

10.1 Using CSVReader events

This is more direct and simplest way to subscribe to the callback events and handle your odd situations in parsing CSV files. Downside is that code can’t be reusable as you do by implementing IChoNotifyRecordRead with POCO record object.

Sample below shows how to use the BeforeRecordLoad callback method to skip lines stating with ‘%’ characters.

Listing 10.1.1 Using CSVReader callback events

static void IgnoreLineTest()
{
    using (var parser = new ChoCSVReader("IgnoreLineFile.csv").WithFirstLineHeader())
    {
        parser.Configuration.Encoding = Encoding.BigEndianUnicode;
 
        parser.BeforeRecordLoad += (o, e) =>
        {
            if (e.Source != null)
            {
                e.Skip = ((string)e.Source).StartsWith("%");
            }
        };
        foreach (var e in parser)
            Console.WriteLine(e.ToStringEx());
    }
}

Likewise you can use other callback methods as well with CSVReader.

10.2 Implementing IChoNotifyRecordRead interface

Listing 10.2.1 Direct POCO callback mechanism implementation

[ChoCSVFileHeader]
[ChoCSVRecordObject(Encoding = "Encoding.UTF32", ErrorMode = ChoErrorMode.IgnoreAndContinue,
       IgnoreFieldValueMode = ChoIgnoreFieldValueMode.All, ThrowAndStopOnMissingField = false)]
public partial class EmployeeRec : IChoNotifyRecordRead
{
    [ChoCSVRecordField(1, FieldName = "id")]
    [ChoTypeConverter(typeof(IntConverter))]
    [Range(1, int.MaxValue, ErrorMessage = "Id must be > 0.")]
    [ChoFallbackValue(1)]
    public int Id { get; set; }
    
    [ChoCSVRecordField(2, FieldName = "Name", QuoteField = true)]
    [Required]
    [DefaultValue("ZZZ")]
    [ChoFallbackValue("XXX")]
    public string Name { get; set; }
 
    public bool AfterRecordFieldLoad(object target, int index, string propName, object value)
    {
        throw new NotImplementedException();
    }
 
    public bool AfterRecordLoad(object target, int index, object source)
    {
        throw new NotImplementedException();
    }
 
    public bool BeforeRecordFieldLoad(object target, int index, string propName, ref object value)
    {
        throw new NotImplementedException();
    }
 
    public bool BeforeRecordLoad(object target, int index, ref object source)
    {
        throw new NotImplementedException();
    }
 
    public bool BeginLoad(object source)
    {
        throw new NotImplementedException();
    }
 
    public void EndLoad(object source)
    {
        throw new NotImplementedException();
    }
 
    public bool RecordFieldLoadError(object target, int index, string propName, object value, Exception ex)
    {
        throw new NotImplementedException();
    }
 
    public bool RecordLoadError(object target, int index, object source, Exception ex)
    {
        throw new NotImplementedException();
    }
}

Listing 10.2.2 MetaDataType based callback mechanism implementation

[ChoCSVFileHeader]
[ChoCSVRecordObject(Encoding = "Encoding.UTF32", ErrorMode = ChoErrorMode.IgnoreAndContinue,
       IgnoreFieldValueMode = ChoIgnoreFieldValueMode.All, ThrowAndStopOnMissingField = false)]
public class EmployeeRecMeta : IChoNotifyRecordRead
{
    [ChoCSVRecordField(1, FieldName = "id")]
    [ChoTypeConverter(typeof(IntConverter))]
    [Range(1, int.MaxValue, ErrorMessage = "Id must be > 0.")]
    [ChoFallbackValue(1)]
    public int Id { get; set; }

    [ChoCSVRecordField(2, FieldName = "Name", QuoteField = true)]
    [Required]
    [DefaultValue("ZZZ")]
    [ChoFallbackValue("XXX")]
    public string Name { get; set; }
 
    public bool AfterRecordFieldLoad(object target, int index, string propName, object value)
    {
        throw new NotImplementedException();
    }
 
    public bool AfterRecordLoad(object target, int index, object source)
    {
        throw new NotImplementedException();
    }
 
    public bool BeforeRecordFieldLoad(object target, int index, string propName, ref object value)
    {
        throw new NotImplementedException();
    }
 
    public bool BeforeRecordLoad(object target, int index, ref object source)
    {
        throw new NotImplementedException();
    }
 
    public bool BeginLoad(object source)
    {
        throw new NotImplementedException();
    }
 
    public void EndLoad(object source)
    {
        throw new NotImplementedException();
    }
 
    public bool RecordFieldLoadError(object target, int index, string propName, object value, Exception ex)
    {
        throw new NotImplementedException();
    }
 
    public bool RecordLoadError(object target, int index, object source, Exception ex)
    {
        throw new NotImplementedException();
    }
} 

[MetadataType(typeof(EmployeeRecMeta))]
public partial class EmployeeRec
{
    [ChoCSVRecordField(1, FieldName = "id")]
    [ChoTypeConverter(typeof(IntConverter))]
    [Range(1, int.MaxValue, ErrorMessage = "Id must be > 0.")]
    [ChoFallbackValue(1)]
    public int Id { get; set; }
    
    [ChoCSVRecordField(2, FieldName = "Name", QuoteField = true)]
    [Required]
    [DefaultValue("ZZZ")]
    [ChoFallbackValue("XXX")]
    public string Name { get; set; }
}

10.3 BeginLoad

This callback invoked once at the beginning of the CSV file load. source is the CSV file stream object. In here you have chance to inspect the stream, return true to continue the CSV load. Return false to stop the parsing.

Listing 10.3.1 BeginLoad Callback Sample

public bool BeginLoad(object source)
{
    StreamReader sr = source as StreamReader;
    return true;
}

10.4 EndLoad

This callback invoked once at the end of the CSV file load. source is the CSV file stream object. In here you have chance to inspect the stream, do any post steps to be performed on the stream.

Listing 10.4.1 EndLoad Callback Sample

public void EndLoad(object source)
{
    StreamReader sr = source as StreamReader;
}

10.5 BeforeRecordLoad

This callback invoked before each record line in the CSV file is loaded. target is the instance of the POCO record object. index is the line index in the file. source is the CSV record line. In here you have chance to inspect the line, and override it with new line if want to.

TIP: If you want to skip the line from loading, set the source to null.

TIP: If you want to take control of parsing and loading the record properties by yourself, set the source to String.Empty.