Humanizer is a small framework that helps .Net developer turn their otherwise geeky strings, type names, enum fields, date, timespan values into a human friendly format plus a lot more.

###Installation You can install Humanizer as a nuget package: Install-Package Humanizer

###Humanize String String extensions are at the heart of this micro-framework. The foundation of this was set in the BDDfy framework where class names, method names and properties are turned into human readable sentences.

"PascalCaseInputStringIsTurnedIntoSentence".Humanize() => "Pascal case input string is turned into sentence"
    
"Underscored_input_string_is_turned_into_sentence".Humanize() => "Underscored input string is turned into sentence"
    
"Underscored_input_String_is_turned_INTO_sentence".Humanize() => "Underscored input String is turned INTO sentence"
    
// acronyms are left intact
"HTML".Humanize() => "HTML" 

You may also specify the desired letter casing:

"CanReturnTitleCase".Humanize(LetterCasing.Title) => "Can Return Title Case"
    
"Can_return_title_Case".Humanize(LetterCasing.Title) => "Can Return Title Case"
    
"CanReturnLowerCase".Humanize(LetterCasing.LowerCase) => "can return lower case"
    
"CanHumanizeIntoUpperCase".Humanize(LetterCasing.AllCaps) => "CAN HUMANIZE INTO UPPER CASE"

The LetterCasing API and the methods accepting it are legacy from V0.2 era and will be deprecated in the future. Instead of that, you can use Transform method explained below.

####Dehumanize String Much like you can humanize a computer friendly into human friendly string you can dehumanize a human friendly string into a computer friendly one:

"Pascal case input string is turned into sentence".Dehumanize() => "PascalCaseInputStringIsTurnedIntoSentence"

###Transform There is a Transform method that supercedes LetterCasing, ApplyCase and Humanize overloads that accept LetterCasing. Transform method signatue is as follows:

string Transform(this string input, params IStringTransformer[] transformers)

And there are some out of the box implemenations of IStringTransformer for letter casing:

"Sentence casing".Transform(To.LowerCase) => "sentence casing"
"Sentence casing".Transform(To.SentenceCase) => "Sentence casing"
"Sentence casing".Transform(To.TitleCase) => "Sentence Casing"
"Sentence casing".Transform(To.UpperCase) => "SENTENCE CASING"

LowerCase is a public static property on To class that returns an instance of private ToLowerCase class that implements IStringTransformer and knows how to turn a string into lower case.

The benefit of using Transform and IStringTransformer over ApplyCase and LetterCasing is that LetterCasing is an enum and you're limited to use what's in the framework while IStringTransformer is an interface you can implement in your codebase once and use it with Transform method allowing for easy extension.

###Humanize Enums Calling ToString directly on enum members usually results in less than ideal output for users. The solution to this is usually to use DescriptionAttribute data annotation and then read that at runtime to get a more friendly output. That is a great solution; but more often than not we only need to put some space between words of an enum member - which is what String.Humanize() does well. For an enum like:

public enum EnumUnderTest
{
    [Description("Custom description")]
    MemberWithDescriptionAttribute,
    MemberWithoutDescriptionAttribute,
    ALLCAPITALS
}

You will get:

// DescriptionAttribute is honored
EnumUnderTest.MemberWithDescriptionAttribute.Humanize() => "Custom description"
    
// In the absence of Description attribute string.Humanizer kicks in
EnumUnderTest.MemberWithoutDescriptionAttribute.Humanize() => "Member without description attribute" 
    
// Of course you can still apply letter casing 
EnumUnderTest.MemberWithoutDescriptionAttribute.Humanize().Transform(To.TitleCase) => "Member Without Description Attribute"

Hopefully this will help avoid littering enums with unnecessary attributes!

####Dehumanize Enums Dehumanizes a string into the Enum it was originally Humanized from! The API looks like:

public static Enum DehumanizeTo<TTargetEnum>(this string input) 

And the usage is:

"Member without description attribute".Dehumanize() => EnumUnderTest.MemberWithoutDescriptionAttribute

And just like the Humanize API it honors the Description attribute. You don't have to provide the casing you provided during humanization: it figures it out.

###Humanize DateTime This is borrowed from StackOverFlow algorithm - although I had to apply some minor fixes on top of it. I am not going to bore you with all the examples as I am sure you know what this does: you basically give it an instance of DateTime and get back a string telling how far back in time that is:

DateTime.UtcNow.AddHours(-30).Humanize() => "yesterday"

Humanizer supports local as well as UTC dates. You could also provide the date you want the input date to be compared against. If null, it will use the current date as comparison base. Here is the API signature:

public static string Humanize(this DateTime input, bool utcDate = true, DateTime? dateToCompareAgainst = null)

For dates Humanizer also supports localization.

No dehumanization for dates as the human friendly date is not reversible

###Humanize TimeSpan You can call Humanizes on a TimeSpan to a get human friendly representation for it:

TimeSpan.FromMilliseconds(1).Humanize() => "1 millisecond"
TimeSpan.FromMilliseconds(2).Humanize() => "2 milliseconds"
TimeSpan.FromDays(1).Humanize() => "1 day"
TimeSpan.FromDays(14).Humanize() => "2 weeks"

###Inflector methods There are also a few inflector methods:

####Pluralize Pluralize pluralizes the provided input while taking irregular and uncountable words into consideration:

"Man".Pluralize() => "Men" 
"string".Pluralize() => "strings"

Normally you would call Pluralize on a singular word but if you're unsure about the singularity of the word you can call the method with the optional plurality argument:

"Men".Pluralize(Plurality.CouldBeEither) => "Men" 
"Man".Pluralize(Plurality.CouldBeEither) => "Men" 
"string".Pluralize(Plurality.CouldBeEither) => "strings"

####Singularize Singularize singularizes the provided input while taking irregular and uncountable words into consideration:

"Men".Singularize() => "Man" 
"strings".Singularize() => "string"

Normally you would call Singularize on a plural word but if you're unsure about the pluralit of the word you can call the method with the optional plurality argument:

"Men".Singularize(Plurality.CouldBeEither) => "Man" 
"Man".Singularize(Plurality.CouldBeEither) => "Man" 
"strings".Singularize(Plurality.CouldBeEither) => "string"

####ToQuantity Many times you want to call Singularize and Pluralize to prefix a word with a number; e.g. "2 requests", "3 men". ToQuantity prefixes the provided word with the number and accordingly pluralizes or singularizes the word:

"case".ToQuantity(0) => "0 cases"
"case".ToQuantity(1) => "1 case"
"case".ToQuantity(5) => "5 cases"
"man".ToQuantity(0) => "0 men"
"man".ToQuantity(1) => "1 man"
"man".ToQuantity(2) => "2 men"

ToQuantity has smarts to figure out whether your input word is plural or singular and changes or leaves it depending on the input quantity:

"men".ToQuantity(2) => "2 men"
"process".ToQuantity(2) => "2 processes"
"process".ToQuantity(1) => "1 process"
"processes".ToQuantity(2) => "2 processes"
"processes".ToQuantity(1) => "1 process"

####Ordinalize numbers & strings Ordinalize turns a number into an ordinal string used to denote the position in an ordered sequence such as 1st, 2nd, 3rd, 4th:

1.Ordinalize() => "1st"
5.Ordinalize() => "5th"

You can also call Ordinalize on a numeric string and achieve the same result: "21".Ordinalize() => "21st"

####Underscore Underscore separates the input words with underscore; e.g. "SomeTitle".Underscore() => "some_title"

####Dasherize Dasherize replaces underscores with dashes in the string; e.g. "some_title".Dasherize() => "some-title"

###Fluent Date Humanizer provides a fluent API to deal with DateTime and TimeSpan as follows:

TimeSpan methods:

2.Milliseconds() => TimeSpan.FromMilliseconds(2)
2.Seconds() => TimeSpan.FromSeconds(2)
2.Minutes() => TimeSpan.FromMinutes(2)
2.Hours() => TimeSpan.FromHours(2)
2.Days() => TimeSpan.FromDays(2)
2.Weeks() => TimeSpan.FromDays(14)

There are no fluent APIs for month or year as a month could have between 28 to 31 days and a year could be 365 or 366 days.

You could use these methods to, for example, replace

DateTime.Now.AddDays(2).AddHours(3).AddMinutes(-5)

with

DateTime.Now + 2.Days() + 3.Hours() - 5.Minutes()

There are also three categories of fluent methods to deal with DateTime:

In.TheYear(2010) // Returns the first of January of 2010
In.January // Returns 1st of January of the current year
In.FebruaryOf(2009) // Returns 1st of February of 2009

In.One.Second //  DateTime.UtcNow.AddSeconds(1);
In.Two.SecondsFrom(DateTime dateTime)
In.Three.Minutes // With corresponding From method
In.Three.Hours // With corresponding From method
In.Three.Days // With corresponding From method
In.Three.Weeks // With corresponding From method
In.Three.Months // With corresponding From method
In.Three.Years // With corresponding From method

On.January.The4th // Returns 4th of January of the current year
On.February.The(12) // Returns 12th of Feb of the current year

and some extension methods:

var someDateTime = new DateTime(2011, 2, 10, 5, 25, 45, 125);

// Returns new DateTime(2008, 2, 10, 5, 25, 45, 125) changing the year to 2008
someDateTime.In(2008) 

// Returns new DateTime(2011, 2, 10, 2, 25, 45, 125) changing the hour to 2:25:45.125
someDateTime.At(2) 

// Returns new DateTime(2011, 2, 10, 2, 20, 15, 125) changing the time to 2:20:15.125
someDateTime.At(2, 20, 15) 

// Returns new DateTime(2011, 2, 10, 12, 0, 0) changing the time to 12:00:00.000
someDateTime.AtNoon() 

// Returns new DateTime(2011, 2, 10, 0, 0, 0) changing the time to 00:00:00.000
someDateTime.AtMidnight() 

Obviously you could chain the methods too; e.g. On.November.The13th.In(2010).AtNoon + 5.Minutes()

###Number to words Humanizer can change numbers to words using the ToWords extension:

1.ToWords() => "one"
10.ToWords() => "ten"
11.ToWords() => "eleven"
122.ToWords() => "one hundred and twenty-two"
3501.ToWords() => "three thousand five hundred and one"

###Number to ordinal words This is kind of mixing ToWords with Ordinalize. You can call ToOrdinalWords on a number to get an ordinal representation of the number in words!! Let me show that with an example:

0.ToOrdinalWords() => "zeroth"
1.ToOrdinalWords() => "first"
2.ToOrdinalWords() => "second"
8.ToOrdinalWords() => "eighth"
10.ToOrdinalWords() => "tenth"
11.ToOrdinalWords() => "eleventh"
12.ToOrdinalWords() => "twelfth"
20.ToOrdinalWords() => "twentieth"
21.ToOrdinalWords() => "twenty first"
121.ToOrdinalWords() => "hundred and twenty first"

###Mix this into your framework to simplify your life This is just a baseline and you can use this to simplify your day to day job. For example, in Asp.Net MVC we keep chucking Display attribute on ViewModel properties so HtmlHelper can generate correct labels for us; but, just like enums, in vast majority of cases we just need a space between the words in property name - so why not use "string".Humanize for that?!

You may find an Asp.Net MVC sample in the code that does that (although the project is excluded from the solution file to make the nuget package available for .Net 3.5 too).

This is achieved using a custom DataAnnotationsModelMetadataProvider I called HumanizerMetadataProvider. It is small enough to repeat here; so here we go:

public class HumanizerMetadataProvider : DataAnnotationsModelMetadataProvider
{
    protected override ModelMetadata CreateMetadata(
        IEnumerable<Attribute> attributes,
        Type containerType,
        Func<object> modelAccessor,
        Type modelType,
        string propertyName)
    {
        var propertyAttributes = attributes.ToList();
        var modelMetadata = base.CreateMetadata(propertyAttributes, containerType, modelAccessor, modelType, propertyName);
    
        if (IsTransformRequired(modelMetadata, propertyAttributes))
            modelMetadata.DisplayName = modelMetadata.PropertyName.Humanize();
    
        return modelMetadata;
    }
    
    private static bool IsTransformRequired(ModelMetadata modelMetadata, IList<Attribute> propertyAttributes)
    {
        if (string.IsNullOrEmpty(modelMetadata.PropertyName))
            return false;
    
        if (propertyAttributes.OfType<DisplayNameAttribute>().Any())
            return false;
    
        if (propertyAttributes.OfType<DisplayAttribute>().Any())
            return false;
    
        return true;
    }
}

This class calls the base class to extract the metadata and then, if required, humanizes the property name. It is checking if the property already has a DisplayName or Display attribute on it in which case the metadata provider will just honor the attribute and leave the property alone. For other properties it will Humanize the property name. That is all.

Now I need to register this metadata provider with Asp.Net MVC:

ModelMetadataProviders.Current = new HumanizerMetadataProvider();

... and now I can replace:

public class RegisterModel
{
    [Display(Name = "User name")]
    public string UserName { get; set; }
    
    [Display(Name = "Email address")]
    public string EmailAddress { get; set; }
    
    [Display(Name = "Confirm password")]
    public string ConfirmPassword { get; set; }
}

with:

public class RegisterModel
{
    public string UserName { get; set; }
    public string EmailAddress { get; set; }
    public string ConfirmPassword { get; set; }
}

... and the "metadata humanizer" will take care of the rest.

No need to mention that if you want title casing for your labels you can chain the method with Transform:

modelMetadata.DisplayName = modelMetadata.PropertyName.Humanize().Transform(To.TitleCase);

##How to contribute? Your contribution to Humanizer would be very welcome. If you find a bug, please raise it as an issue. Even better fix it and send me a pull request. If you like to help me out with existing bugs and feature requests just check out the list of issues and grab and fix one. I have also flagged some of the easier issues as 'jump in' so you can start with easier tasks.

I use GitHub flow for pull requests. So if you want to contribute, fork the repo, fix an issue and send a PR.

####Need your help with localisation One area Humanizer could always use your help is localisation. Currently Humanizer supports French, Belgium, Spanish, Greek, German, Arabic, Russian and Romanian languages for Date.Humanize method. Humanizer could definitely do with more translations. TimeSpan.Humanize also requires translations.

To add a translation, fork the repository if you haven't done yet, duplicate the resources.resx file, add your target locale code to the end (e.g. resources.ru.resx for Russian), translate the values to your language, commit, and send a pull request for it. Thanks.

Some languages have complex rules when it comes to dealing with numbers; for example, in Romanian "5 days" is "5 zile", while "24 days" is "24 de zile" and in Arabic "2 days" is "يومين" not "2 يوم". Obviously a normal resource file doesn't cut it in these cases as a more complex mapping is required. In cases like this in addition to creating a resource file you should also subclass DefaultFormatter in a class that represents your language; e.g. RomanianFormatter and then override the methods that need involve the complex rules. We think overriding the GetResourceKey method should be enough. To see how to do that check out RomanianFormatter and RussianFormatter. Then you return an instance of your class in the Configurator class in the getter of the Formatter property based on the current culture.

Humanizer project is built & tested continuously by TeamCity (more details here). That applies to pull requests too. Shortly after you submit a PR you can check the build and test status notification on your PR. I would appreciate if you could send me green PRs.

The current build status on the CI server is

###Author Mehdi Khalili (@MehdiKhalili)

###License Humanizer is released under the MIT License. See the bundled LICENSE file for details.