C# Functional Programming Language Extensions

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C# Functional Programming Language Extensions

This library uses and abuses the features of C# to provide a functional-programming 'base class library' that, if you squint, can look like extensions to the language itself. The desire here is to make programming in C# much more reliable and to make the engineer's inertia flow in the direction of declarative and functional code rather than imperative.

Author on...

twitter: @paullouth
mastodon: @[email protected]

Paul Louth discussing FP for the GitHub ReadME project

Reference

Nu-get

Nu-get package	Description
LanguageExt.Core	All of the core types and functional 'prelude'. This is all that's needed to get started.
LanguageExt.Transformers	For every combination of monadic type `M<N<A>>` (i.e. `Seq<Option<A>>`), this package provides the following extension methods: `ApplyT`, `AppendT`, `BindT`, `CompareT`, `CountT`, `EqualsT`, `ExistsT`, `ForAllT`, `FoldT`, `FoldBackT`, `FilterT`, `IterT`, `MapT`, `PlusT`, `ProductT`, `SubtractT`, `DivideT`, and `SumT`. Which makes it much easier to work with those nested types (no need to manually unpack the bound values)
LanguageExt.FSharp	F# to C# interop package. Provides interop between the LanguageExt.Core types (like `Option`, `List` and `Map`) to the F# equivalents, as well as interop between core BCL types and F#
LanguageExt.Parsec	Port of the Haskell parsec library
LanguageExt.Rx	Reactive Extensions support for various types within the Core
LanguageExt.Sys	Provides an `Aff` and `Eff` wrapper around the .NET System namespace making common IO operations pure and unit-testable
LanguageExt.SysX	As above, but provides .NET5+ specific features
LanguageExt.CodeGen	Used to generate records, unions, lenses, and `With` functions automagically.

Code-gen setup

To use the code-generation features of language-ext (which are totally optional by the way), then you must include the LanguageExt.CodeGen package into your project.

To make the reference build and design time only (i.e. your project doesn't gain an additional dependencies because of the code-generator), open up your csproj and set the PrivateAssets attribute to all:

<ItemGroup>
    <PackageReference Include="LanguageExt.Core" Version="3.4.10" />

    <PackageReference Include="LanguageExt.CodeGen" Version="3.4.10"
                      PrivateAssets="all" />

    <PackageReference Include="CodeGeneration.Roslyn.BuildTime"
                      Version="0.6.1"
                      PrivateAssets="all" />

    <DotNetCliToolReference Include="dotnet-codegen" Version="0.6.1" />
</ItemGroup>

Obviously, update the Version attributes to the appropriate values. Also note that you will probably need the latest VS2019+ for this to work. Even early versions of VS2019 seem to have problems.

There's more information on the code-gen features on the wiki

Unity

This library seems compatible on the latest (at the time of writing) Unity 2018.2 with incremental compiler (which enables C# 7), so it should work well once Unity has official support for C# 7 on upcoming 2018.3. In the meanwhile, you can install incremental compiler instead. If you are concerned about writing functionally and the possible performance overheads then please take a look at this wiki page.

Getting started

To use this library, simply include LanguageExt.Core.dll in your project or grab it from NuGet, and add this to the top of each .cs file that needs it:

using LanguageExt;
using static LanguageExt.Prelude;

The namespace LanguageExt contains the core types, and LanguageExt.Prelude contains the functions that you bring into scope using static LanguageExt.Prelude.

Prologue

One of the great features of C#6+ is that it allows us to treat static classes like namespaces. This means that we can use static methods without qualifying them first. That instantly gives us access to single term method names that look exactly like functions in functional languages. i.e.

    using static System.Console;
    
    WriteLine("Hello, World");

This library tries to bring some of the functional world into C#. It won't always sit well with the seasoned C# OO programmer, especially the choice of camelCase names for a lot of functions and the seeming 'globalness' of a lot of the library.

I can understand that much of this library is non-idiomatic, but when you think of the journey C# has been on, is "idiomatic" necessarily right? A lot of C#'s idioms are inherited from Java and C# 1.0. Since then we've had generics, closures, Func, LINQ, async... C# as a language is becoming more and more like a functional language on every release. In fact, the bulk of the new features are either inspired by or directly taken from features in functional languages. So perhaps it's time to move the C# idioms closer to the functional world's idioms?

A note about naming

One of the areas that's likely to get seasoned C# heads worked up is my choice of naming style. The intent is to try and make something that feels like a functional language rather than following rules of naming conventions (mostly set out by the BCL).

There is, however, a naming guide that will keep you in good stead while reading through this documentation:

Type names are PascalCase in the normal way
The types all have constructor functions rather than public constructors that you instantiate with new. They will always be PascalCase:

    Option<int> x = Some(123);
    Option<int> y = None;
    Seq<int> items = Seq(1,2,3,4,5);
    List<int> items = List(1,2,3,4,5);
    HashMap<int, string> dict = HashMap((1, "Hello"), (2, "World"));
    Map<int, string> dict = Map((1, "Hello"), (2, "World"));

Any (non-type constructor) static function that can be used on its own by using static LanguageExt.Prelude are camelCase.

    var x = map(opt, v => v * 2);

Any extension methods, or anything "fluent" are PascalCase in the normal way

    var x = opt.Map(v => v * 2);

Even if you disagree with this non-idiomatic approach, all of the camelCase static functions have fluent variants, so you never actually have to see the non-standard stuff.

If you're not using C# 6 yet, then you can still use this library. Anywhere in the docs below where you see a camelCase function it can be accessed by prefixing with Prelude.

Features

Functional effects and IO

Location	Feature	Description
`Core`	`Aff<A>`	An asynchronous effect: an IO monad
`Core`	`Eff<A>`	A synchronous effect: an IO monad
`Core`	`Aff<RT, A>`	An asynchronous effect with injectable runtime: a unit testable IO monad
`Core`	`Eff<RT, A>`	A synchronous effect with injectable runtime: a unit testable IO monad
`Core`	Pipes	A clean and powerful stream processing system that lets you build and connect reusable streaming components

Atomic concurrency and collections

Location	Feature	Description
`Core`	`Atom<A>`	A lock-free atomically mutable reference for working with shared state
`Core`	`Ref<A>`	An atomic reference to be used in the transactional memory system
`Core`	`AtomHashMap<K, V>`	An immutable `HashMap` with a lock-free atomically mutable reference
`Core`	`AtomSeq<A>`	An immutable `Seq` with a lock-free atomically mutable reference
`Core`	`VectorClock<A>`	Understand distributed causality
`Core`	`VersionVector<A>`	A vector clock with some versioned data
`Core`	`VersionHashMap <ConflictV, K, V>`	Distrubuted atomic versioning of keys in a hash-map

Immutable collections

Location	Feature	Description
`Core`	`Arr<A>`	Immutable array
`Core`	`Seq<A>`	Immutable list with lazy behavior - a better `IEnumerable`. Very, very fast!
`Core`	`Lst<A>`	Immutable list - use `Seq` over `Lst` unless you need `InsertAt`
`Core`	`Map<K, V>`	Immutable map
`Core`	`Map<OrdK, K, V>`	Immutable map with Ord constraint on `K`
`Core`	`HashMap<K, V>`	Immutable hash-map
`Core`	`HashMap<EqK, K, V>`	Immutable hash-map with Eq constraint on `K`
`Core`	`Set<A>`	Immutable set
`Core`	`Set<OrdA, A>`	Immutable set with Ord constraint on `A`
`Core`	`HashSet<A>`	Immutable hash-set
`Core`	`HashSet<EqA, A>`	Immutable hash-set with Eq constraint on `A`
`Core`	`Que<A>`	Immutable queue
`Core`	`Stck<A>`	Immutable stack

Optional and alternative value monads

Location	Feature	Description
`Core`	`Option<A>`	Option monad that can't be used with `null` values
`Core`	`OptionAsync<A>`	OptionAsync monad that can't be used with `null` values with all value realisation does asynchronously
`Core`	`OptionUnsafe<T>`	Option monad that can be used with `null` values
`Core`	`Either<L,R>`	Right/Left choice monad that won't accept `null` values
`Core`	`EitherUnsafe<L, R>`	Right/Left choice monad that can be used with `null` values
`Core`	`EitherAsync<L, R>`	EitherAsync monad that can't be used with `null` values with all value realisation done asynchronously
`Core`	`Try<A>`	Exception handling lazy monad
`Core`	`TryAsync<A>`	Asynchronous exception handling lazy monad
`Core`	`TryOption<A>`	Option monad with third state 'Fail' that catches exceptions
`Core`	`TryOptionAsync<A>`	Asynchronous Option monad with third state 'Fail' that catches exceptions
`Core`	`Validation<FAIL,SUCCESS>`	Validation applicative and monad for collecting multiple errors before aborting an operation
`Core`	`Validation<MonoidFail, FAIL, SUCCESS>`	Validation applicative and monad for collecting multiple errors before aborting an operation, uses the supplied monoid in the first generic argument to collect the failure values.

State managing monads

Location	Feature	Description
`Core`	`Reader<E, A>`	Reader monad
`Core`	`Writer<MonoidW, W, T>`	Writer monad that logs to a `W` constrained to be a Monoid
`Core`	`State<S, A>`	State monad
`Core`	`RWS<R, W, S, A>`	Reader Writer State monad

Parser combinators

Location	Feature	Description
`Parsec`	`Parser<A>`	String parser monad and full parser combinators library
`Parsec`	`Parser<I, O>`	Parser monad that can work with any input stream type

New types - Type aliasing

Location	Feature	Description
`Core`	`NewType<SELF, A, PRED>`	Haskell `newtype` equivalent i.e: `class Hours : NewType<Hours, double> { public Hours(double value) : base(value) { } }`. The resulting type is: equatable, comparable, foldable, a functor, monadic, and iterable
`Core`	`NumType<SELF, NUM, A, PRED>`	Haskell `newtype` equivalent but for numeric types i.e: `class Hours : NumType<Hours, TDouble, double> { public Hours(double value) : base(value) { } }`. The resulting type is: equatable, comparable, foldable, a functor, a monoid, a semigroup, monadic, iterable, and can have basic artithmetic operations performed upon it.
`Core`	`FloatType<SELF, FLOATING, A, PRED>`	Haskell `newtype` equivalent but for real numeric types i.e: `class Hours : FloatType<Hours, TDouble, double> { public Hours(double value) : base(value) { } }`. The resulting type is: equatable, comparable, foldable, a functor, a monoid, a semigroup, monadic, iterable, and can have complex artithmetic operations performed upon it.

Code generation

Location	Feature	Description
`CodeGen`	Records	Generate record types automatically
`CodeGen`	Unions	Generate discriminated unions automatically
`CodeGen`	Free monads	Generate discriminated free-monads
`CodeGen`	Reader	Generate reader-monads
`CodeGen`	RWS	Generate RWS-monads
`CodeGen`	With	Add a tranformational `With` method to your records
`CodeGen`	WithLens	Add a tranformational `With` and generated Lenses method to your data types
`Core`	`Lens<A, B>`	Well behaved bidirectional transformations - i.e. the ability to easily generate new immutable values from existing ones, even when heavily nested.
`Core`	`Record<A>`	Base type for creating record types with automatic structural equality, ordering, and hash code calculation.

Pretty

Location	Feature	Description
`Core`	`Doc<A>`	Produce nicely formatted text with smart layouts

Differencing

Location	Feature	Description
`Core`	`Patch<EqA, A>`	Uses patch-theory to efficiently calculate the difference (`Patch.diff(list1, list2)`) between two collections of `A` and build a patch which can be applied (`Patch.apply(patch, list)`) to one to make the other (think git diff).

Make C# better

Location	Feature	Description
`Core`	`Nullable<T>` extensions	Extension methods for `Nullable<T>` that make it into a functor, applicative, foldable, iterable and a monad
`Core`	`Task<T>` extensions	Extension methods for `Task<T>` that make it into a functor, applicative, foldable, iterable and a monad
`Core`	Improved lambda type inference	`var add = fun( (int x, int y) => x + y)`
`Core`	Currying	Translate the evaluation of a function that takes multiple arguments into a sequence of functions, each with a single argument
`Core`	Partial application	the process of fixing a number of arguments to a function, producing another function of smaller arity
`Core`	`IQueryable<T>` extensions
`Core`	`IObservable<T>` extensions
`Core`	Memoization	An optimization technique used primarily to speed up programs by storing the results of expensive function calls and returning the cached result when the same inputs occur again

This library started out trying to deal with issues in C#, that after using Haskell and F# started to frustrate me:

Poor tuple support

NOTE: Since writing this, the csharplang team have improved tuple support in C#

I've been crying out for proper tuple support for ages. When this library was created we were no closer (C# 6). The standard way of creating them is ugly Tuple.Create(foo,bar) compared to functional languages where the syntax is often (foo,bar) and to consume them you must work with the standard properties of Item1...ItemN.

    var ab = Tuple("a","b");

Now isn't that nice?

Consuming the tuple is now handled using Map, which projects the Item1...ItemN onto a lambda function (or action):

    var name = Tuple("Paul","Louth");
    var res = name.Map( (first, last) => $"{first} {last}");

Or, you can use a more functional approach:

    var name = Tuple("Paul","Louth");
    var res = map( name, (first, last) => $"{first} {last}");

This allows the tuple properties to have names, and it also allows for fluent handling of functions that return tuples.

If you are using C#7+ then you'll know that the new Tuple type is ValueTuple. Just like with Tuple, language-ext adds many extensions to the standard BCL ValueTuple.

For example:

    var abc = ('a', 'b').Add('c');                                           // ('a', 'b', 'c')
    var abcd = ('a', 'b').Add('c').Add('d');                                 // ('a', 'b', 'c', 'd')
    var abcd5 = ('a', 'b').Add('c').Add('d').Add(5);                         // ('a', 'b', 'c', 'd', 5)

    var sum = (1, 2, 3).Sum<TInt, int>();                                    // 6
    var product = (2, 4, 8).Product<TInt, int>();                            // 64
    var flag = ("one", "two", "three").Contains<TString, string>("one");     // true
    var str = ("Hello", " ", "World").Concat<TString, string>();             // "Hello World"
    var list = (List(1, 2, 3), List(4, 5, 6)).Concat<TLst<int>, Lst<int>>(); // [1,2,3,4,5,6]

Null reference problem

NOTE: Since writing this, the csharplang team have improved null support in C#

null must be the biggest mistake in the whole of computer language history. I realise the original designers of C# had to make pragmatic decisions, it's a shame this one slipped through though. So, what to do about the "null problem"?

null is often used to indicate no value; the method called can't produce a value of the type it said it was going to produce, and therefore it gives you "nothing". The thing is that when no value is passed to the consuming code, it gets assigned to a variable of type T, the same type that the function said it was going to return, except this variable now has a timebomb in it. You must continually check if the value is null, if it's passed around it must be checked too.

As we all know it's only a matter of time before a null reference bug crops up because the variable wasn't checked. It puts C# in the realm of the dynamic languages, where you can't trust the value you're being given.

Functional languages use what's known as an option type. In F# it's called Option, in Haskell it's called Maybe. In the next section we'll see how it's used.

Option

Option<T> works in a very similar way to Nullable<T>, except it works with all types rather than just value types. It's a struct and therefore can't be null. An instance can be created by either calling Some(value), which represents a positive "I have a value" response, or None, which is the equivalent of returning null.

So why is it any better than returning T and using null? It seems we can have a non-value response again right? Yes, that's true, however you're forced to acknowledge that fact and to write code to handle both possible outcomes because you can't get to the underlying value without acknowledging the possibility of the two states that the value could be in. This bulletproofs your code. You're also explicitly telling any other programmers that "this method might not return a value, so make sure you deal with that". This explicit declaration is very powerful.

This is how you create an Option<int>:

    var optional = Some(123);

To access the value you must check that it's valid first:

    int x = optional.Match( 
                Some: v  => v * 2,
                None: () => 0 
                );

An alternative (functional) way of matching is this:

    int x = match( optional, 
                   Some: v  => v * 2,
                   None: () => 0 );

Yet another alternative ("fluent") matching method is this:

    int x = optional
               .Some( v  => v * 2 )
               .None( () => 0 );

So choose your preferred method and stick with it. It's probably best not to mix styles.

There are also some helper functions to work with default None values; you won't see a .Value or a GetValueOrDefault() anywhere in this library. This is because .Value puts us right back to where we started, and you may as well not use Option<T> in that case. GetValueOrDefault() is also just as bad because it can return null for reference types, and depends on how well defined the struct type is you're working with.

However, clearly there will be times when you don't need to do anything with the Some case. Also, sometimes you just want some code to execute in the Some case and not the None case:

    // Returns the Some case 'as is' and 10 in the None case
    int x = optional.IfNone(10);        

    // As above, but invokes a Func<T> to return a valid value for x
    int x = optional.IfNone(() => GetAlternative());        
    
    // Invokes an Action<T> if in the Some state.
    optional.IfSome(x => Console.WriteLine(x));

Of course there are functional versions of the fluent version above:

    int x = ifNone(optional, 10);
    int x = ifNone(optional, () => GetAlternative());
    ifSome(optional, x => Console.WriteLine(x));

To smooth out the process of returning Option<T> types from methods there are some implicit conversion operators and constructors:

    // Implicitly converts the integer to a Some of int
    Option<int> GetValue()
    {
        return 1000;
    }

    // Implicitly converts to a None of int
    Option<int> GetValue()
    {
        return None;
    }
    
    // Will handle either a None or a Some returned
    Option<int> GetValue(bool select) =>
        select
            ? Some(1000)
            : None;
            
    // Explicitly converts a null value to None and a non-null value to Some(value)
    Option<string> GetValue()
    {
        string value = GetValueFromNonTrustedApi();
        return Optional(value);
    }
            
    // Implicitly converts a null value to None and a non-null value to Some(value)
    Option<string> GetValue()
    {
        string value = GetValueFromNonTrustedApi();
        return value;
    }

It's actually nearly impossible to get a null out of a function, even if the T in Option<T> is a reference type and you write Some(null). Firstly, it won't compile, but you might think you can do this:

    private Option<string> GetStringNone()
    {
        string nullStr = null;
        return Some(nullStr);
    }

That will compile, but at runtime will throw a ValueIsNullException. If you do either of these (below) you'll get a None.

    private Option<string> GetStringNone()
    {
        string nullStr = null;
        return nullStr;
    }

    private Option<string> GetStringNone()
    {
        string nullStr = null;
        return Optional(nullStr);
    }

These are the coercion rules:

Converts from	Converts to
`x`	`Some(x)`
`null`	`None`
`None`	`None`
`Some(x)`	`Some(x)`
`Some(null)`	`ValueIsNullException`
`Some(None)`	`Some(None)`
`Some(Some(x))`	`Some(Some(x))`
`Some(Nullable null)`	`ValueIsNullException`
`Some(Nullable x)`	`Some(x)`
`Optional(x)`	`Some(x)`
`Optional(null)`	`None`
`Optional(Nullable null)`	`None`
`Optional(Nullable x)`	`Some(x)`

As well as the protection of the internal value of Option<T>, there's protection for the return value of the Some and None handler functions. You can't return null from those either; an exception will be thrown.

    // This will throw a ResultIsNullException exception
    string res = GetValue(true)
                     .Some(x => (string)null)
                     .None((string)null);

null goes away if you use Option<T>.

However, there are times when you may want your Some and None handlers to return null. This is mostly when you need to use something in the BCL or from a third-party library, so momentarily you need to step out of your warm and cosy protected optional bubble, but you've got an Option<T> that will throw an exception if you try.

So you can use matchUnsafe and ifNoneUnsafe:

    string x = matchUnsafe( optional,
                            Some: v => v,
                            None: () => null );

    string x = ifNoneUnsafe( optional, (string)null );
    string x = ifNoneUnsafe( optional, () => GetNull() );

And fluent versions:

    string x = optional.MatchUnsafe(
                   Some: v => v,
                   None: () => null 
                   );
    string x = optional.IfNoneUnsafe((string)null);
    string x = optional.IfNoneUnsafe(() => GetNull());

That is consistent throughout the library. Anything that could return null has the Unsafe suffix. That means that in those unavoidable circumstances where you need a null, it gives you and any other programmers working with your code the clearest possible sign that they should treat the result with care.

Option monad - gasp! Not the M word!

I know, it's that damn monad word again. They're actually not scary at all, and damn useful. But if you couldn't care less (or could care less, for my American friends), it won't stop you taking advantage of the Option<T> type. However, Option<T> type also implements Select and SelectMany and is therefore monadic, which also means it can be used in LINQ expressions and much more!

    Option<int> two = Some(2);
    Option<int> four = Some(4);
    Option<int> six = Some(6);
    Option<int> none = None;

    // This expression succeeds because all items to the right of 'in' are Some of int
    // and therefore it lands in the Some lambda.
    int r = match( from x in two
                   from y in four
                   from z in six
                   select x + y + z,
                   Some: v => v * 2,
                   None: () => 0 );     // r == 24

    // This expression bails out once it gets to the None, and therefore doesn't calculate x+y+z
    // and lands in the None lambda
    int r = match( from x in two
                   from y in four
                   from _ in none
                   from z in six
                   select x + y + z,
                   Some: v => v * 2,
                   None: () => 0 );     // r == 0

This can be great for avoiding the use of if then else, because the computation continues as long as the result is Some and bails otherwise. It is also great for building blocks of computation that you can compose and reuse. Yes, actually compose and reuse, not like OOP where the promise of composability and modularity are essentially lies.

To take this much further, all of the monads in this library implement a standard "functional set" of functions:

    Sum                 // For Option<int> it's the wrapped value.
    Count               // For Option<T> is always 1 for Some and 0 for None. 
    Bind                // Part of the definition of anything monadic - SelectMany in LINQ
    Exists              // Any in LINQ - true if any element fits a predicate
    Filter              // Where in LINQ
    Fold                // Aggregate in LINQ
    ForAll              // All in LINQ - true if all element(s) fits a predicate
    Iter                // Passes the wrapped value(s) to an Action delegate
    Map                 // Part of the definition of any 'functor'. Select in LINQ
    Lift / LiftUnsafe   // Different meaning to Haskell, this returns the wrapped value. Dangerous, should be used sparingly.
    Select
    SelectMany
    Where

This makes them into what would be known in Haskell as a Type Class (although more of a catch-all type-class than a set of well-defined type-classes).

Option and alternative-value-monads reference

Monad transformer extensions

For this section you will need the LanguageExt.Transformers nu-get package

Monad transformers extensions allow for behaviours that work with nested monadic types. Imagine functionality for working with Seq<Option<A>> or a Option<Task<A>>, etc. without having to unpack the values bound within.

One problem with C# is it can't do higher order polymorphism (imagine saying M<T> where M : Monad where the M is polymorphic like the T, and can be constrianed). There is a kind of cheat way to do it in C# through extension methods, but it still doesn't get you something that fits the pattern M<T> where M : Monad. So there are limitations in that you can't write generic functions over higher-kinds, but with a bit of cunning we can generate code to deal with every pairing of monadic types.

There's discussion later in the section on Ad-hoc Polymorphism of a more general approach, but it's a little too complicated use

As an example, below is a list of optional integers: Lst<Option<int>> (see lists later). We want to double all of the Some values, leave the None alone and keep everything in the list:

    using LanguageExt;
    using static LanguageExt.Prelude;

    var list = List(Some(1), None, Some(2), None, Some(3));

    list = list.MapT(x => x * 2);

Notice the use of MapT instead of Map. If we used Map (equivalent to Select in LINQ), it would look like this:

    var list  = List(Some(1), None, Some(2), None, Some(3));
    
    list = list.Map(x => x.Map( v => v * 2));

As you can see, the intention is much clearer in the first example, which is the point of functional programming most of the time. It's about declaring intent rather than the mechanics of delivery.

To make this work we need extension methods for List<Option<T>> that define MapT and SumT [for the one example above]. We also need one for every pair of monads in this library (for one level of nesting A<B<T>>), and for every function from the "standard functional set" listed above. That's 32 monads * 32 monads * 20 functions. That's a lot of extension methods (20,480!). Because of this, there's T4 template that generates 'monad transformers' that allows for nested monads.

This is super powerful, and means that most of the time you can leave your Option<T> or any of the monads in this library wrapped and rarely need to extract the value. You usually only need to extract the value to pass to the BCL or third-party libraries. Even then you could keep them wrapped and use Iter or IterT.

if( arg == null ) throw new ArgumentNullException("arg")

NOTE: Since writing this, the csharplang team have improved required arguments in C#

Another horrible side-effect of null is having to bullet-proof every function that takes reference arguments. This is truly tedious. Instead use this:

    public void Foo( Some<string> arg )
    {
        string value = arg;
        ...
    }

By wrapping string as Some<string> we get free runtime null checking. Essentially it's impossible (well, almost) for null to propagate through. As you can see above, the arg variable casts automatically to string value. It's also possible to get at the inner-value like so:

    public void Foo( Some<string> arg )
    {
        string value = arg.Value;
        ...
    }

Some<T> is a struct and has implicit conversion operators that convert a type of T to a type of Some<T>. The constructor of Some<T> ensures that the value of T has a non-null value.

There is also an implicit cast operator from Some<T> to Option<T>. The Some<T> will automatically put the Option<T> into a Some state. It's not possible to go the other way and cast from Option<T> to Some<T>, because the Option<T> could be in a None state which would cause the Some<T> to throw ValueIsNullException. We want to avoid exceptions being thrown, so you must explicitly match to extract the Some value.

There is one weakness to this approach: if you add a member property or field to a class which is a struct, and if you don't initialise it, then C# is happy to go along with that. This is the reason why you shouldn't normally include reference members inside structs (or if you do, have a strategy for dealing with it).

Some<T> unfortunately falls victim to this; it wraps a reference of type T. Therefore it can't realistically create a useful default. C# also doesn't call the default constructor for a struct in these circumstances, so there's no way to catch the problem early. For example:

    class SomeClass
    {
        public Some<string> SomeValue = "Hello";
        public Some<string> SomeOtherValue;
    }
    
    ...
    
    public void Greet(Some<string> arg)
    {
        Console.WriteLine(arg);
    }
    
    ...
    
    public void App()
    {
        var obj = new SomeClass();
        Greet(obj.SomeValue);
        Greet(obj.SomeOtherValue);
    }

In the example above, Greet(obj.SomeOtherValue); will work until arg is used inside of the Greet function, which puts us back into the null realm. There's nothing (that I'm aware of) that can be done about this. Some<T> will throw a useful SomeNotInitialisedException, which should make life a little easier.

    "Unitialised Some<...>"

So what's the best plan of attack to mitigate this?

Don't use Some<T> for class members. That means the class logic might have to deal with null however.
Or, always initialise Some<T> class members. Mistakes do happen though.

There's no silver bullet here unfortunately.

NOTE: Since writing this library I have come to the opinion that Some<T> isn't that useful. It's much better to protect everything else using Option<T> and immutable data structures. It doesn't fix the argument null checks unfortunately. Perhaps using a contracts library would be better.

Some and alternative-value monads reference

Lack of lambda and expression inference

NOTE: Since writing this, the csharplang team have improved lamdba inference in C#

One really annoying thing about the var type inference in C# is that it can't handle inline lambdas. For example this won't compile, even though it's obvious it's a Func<int,int,int>.

    var add = (int x, int y) => x + y;

There are some good reasons for this, so best not to bitch too much. Instead use the fun function from this library:

    var add = fun( (int x, int y) => x + y );

This will work for Func<..> and Action<..> types of up to seven generic arguments. Action<..> will be converted to Func<..,Unit>. To maintain an Action use the act function instead:

    var log = act( (int x) => Console.WriteLine(x) );

If you pass a Func<..> to act then its return value will be dropped, so Func<R> becomes Action, and Func<T,R> will become Action<T>.

To do the same for Expression<..>, use the expr function:

    var add = expr( (int x, int y) => x + y );

Note, if you're creating a Func or Action that take parameters, you must provide the type:

    // Won't compile
    var add = fun( (x, y) => x + y );

    // Will compile
    var add = fun( (int x, int y) => x + y );

fun, act, expr and prelude reference

Void isn't a real type

Functional languages have a concept of a type that has one possible value (itself) called Unit. As an example, bool has two possible values: true and false. Unit has one possible value, usually represented in functional languages as (). You can imagine that methods that take no arguments do in fact take one argument of (). Anyway, we can't use the () representation in C#, so LanguageExt now provides unit.

    public Unit Empty()
    {
        return unit;
    }

Unit is the type and unit is the value. It is used throughout the LanguageExt library instead of void. The primary reason is that if you want to program functionally then all functions should return a value and void is a type with zero possible values - and that's the type-theory reason why void is a pain in the arse in C#. This can help a lot with LINQ expressions.

Any void function or its asynchronous equivalent Task can be converted using fun and ToUnit as follows:

    public static Func<string, Unit> GetConsoleWrite() => fun<string>(Console.Write);
    public static Func<string, Task<Unit>> GetConsoleWriteAsync() => (string v) => Console.Out.WriteAsync(v).ToUnit();

    public static Unit WriteToConsole(string v) => fun(() => Console.Write(v))();
    public static Task<Unit> WriteToConsoleAsync(string v) => Console.Out.WriteAsync(v).ToUnit();

Unit reference

Mutable lists and dictionaries

With the new "get only" property syntax with C# 6 it's now much easier to create immutable types (which everyone should do). However, there's still going to be a bias towards mutable collections. There's a great library on NuGet called "Immutable Collections" which sits in the System.Collections.Immutable namespace. It brings performant immutable lists, dictionaries, etc. to C#. However, this:

    var list = ImmutableList.Create<string>();

compared to this:

    var list = new List<string>();

is annoying. There's clearly going to be a bias toward the shorter, easier to type, better known method of creating lists. In functional languages collections are often baked in (because they're so fundamental), with lightweight and simple syntax for generating and modifying them. So let's have some of that...

Lists

There's support for Cons, which is the functional way of constructing lists:

    var test = Cons(1, Cons(2, Cons(3, Cons(4, Cons(5, empty<int>())))));

    var array = test.ToArray();

    Assert.IsTrue(array[0] == 1);
    Assert.IsTrue(array[1] == 2);
    Assert.IsTrue(array[2] == 3);
    Assert.IsTrue(array[3] == 4);
    Assert.IsTrue(array[4] == 5);

Note, this isn't the strict definition of Cons, but it's a pragmatic implementation that returns an IEnumerable<T>, is lazy, and behaves the same. Functional purists, please don't get too worked up! I have yet to think of a way of implementing a proper type-safe cons (that can also represent trees, etc.) in C#.

Functional languages usually have a shortcut list constructor syntax that makes the Cons approach easier. It usually looks something like this:

    let list = [1;2;3;4;5]

In C# it looks like this:

    var array = new int[] { 1, 2, 3, 4, 5 };
    var list = new List<int> { 1, 2, 3, 4, 5 };

Or worse:

    var list = new List<int>();
    list.Add(1);
    list.Add(2);
    list.Add(3);
    list.Add(4);
    list.Add(5);

So we provide the List function that takes any number of parameters and turns them into a list:

    // Creates a list of five items
     var test = List(1, 2, 3, 4, 5);

This is much closer to the "functional way". It also returns a Lst<T> which is an immutable list implementation, making it easier to use immutable-lists than mutable ones, and requires significantly less typing.

Also Range:

    // Creates a sequence of 1000 integers lazily (starting at 500).
    var list = Range(500,1000);
    
    // Produces: [0, 10, 20, 30, 40]
    var list = Range(0,50,10);
    
    // Produces: ['a,'b','c','d','e']
    var chars = Range('a','e');

Some of the standard set of list functions are available (in LanguageExt.List):

    using static LanguageExt.List;
    ...

    // Generates 10,20,30,40,50
    var input = List(1, 2, 3, 4, 5);
    var output1 = map(input, x => x * 10);

    // Generates 30,40,50
    var output2 = filter(output1, x => x > 20);

    // Generates 120
    var output3 = fold(output2, 0, (x, s) => s + x);

    Assert.IsTrue(output3 == 120);

The above can be written in a "fluent" style as well:

    var res = List(1, 2, 3, 4, 5)
                .Map(x => x * 10)
                .Filter(x => x > 20)
                .Fold(0, (x, s) => s + x);

    Assert.IsTrue(res == 120);

List pattern matching

Here we implement the standard functional pattern for matching on list elements. In our version you must provide at least 2 handlers:

One for an empty list
One for a non-empty list

However, you can provide up to seven handlers, one for an empty list and six for deconstructing the first six items at the head of the list.

    public int Sum(IEnumerable<int> list) =>
        match( list,
               ()      => 0,
               (x, xs) => x + Sum(xs) );

    public int Product(IEnumerable<int> list) =>
        match( list,
               ()      => 0,
               x       => x,
               (x, xs) => x * Product(xs) );

    public void RecursiveMatchSumTest()
    {
        var list0 = List<int>();
        var list1 = List(10);
        var list5 = List(10,20,30,40,50);
        
        Assert.IsTrue(Sum(list0) == 0);
        Assert.IsTrue(Sum(list1) == 10);
        Assert.IsTrue(Sum(list5) == 150);
    }

    public void RecursiveMatchProductTest()
    {
        var list0 = List<int>();
        var list1 = List(10);
        var list5 = List(10, 20, 30, 40, 50);

        Assert.IsTrue(Product(list0) == 0);
        Assert.IsTrue(Product(list1) == 10);
        Assert.IsTrue(Product(list5) == 12000000);
    }

Those patterns should be very familiar to anyone who's ventured into the functional world. For those that haven't, the (x,xs) convention might seem odd. x is the item at the head of the list - list.First() in LINQ world. xs (many X-es) is the tail of the list - list.Skip(1) in LINQ. This recursive pattern of working on the head of the list until the list runs out is pretty much how loops are done in the functional world.

Be wary of recursive processing; C# will happily blow up the stack after a few thousand iterations.

Functional programming doesn't really do design patterns, but if anything is a design pattern it's the use of fold. If you put a bit of thought into it, you will realise that recursive processes all tend to follow a very similar pattern.

The two recursive examples above for calculating the sum and product of a sequence of numbers can be written as:

    // Sum
    var total = fold(list, 0, (s,x) => s + x);
    
    // Product
    var total = reduce(list, (s,x) => s * x);

reduce is fold but instead of providing an initial state value, it uses the first item in the sequence. Therefore you don't get an initial multiply by zero (unless the first item is zero!). Internally fold, foldBack, and reduce use an iterative loop rather than a recursive one, so no stack blowing problems!

Immutable collections reference

Maps

We also support dictionaries. Again the word Dictionary is such a pain to type, especially when there's a perfectly valid alternative used in the functional world: map.

To create an immutable map, you no longer have to type:

    var dict = ImmutableDictionary.Create<string,int>();

Instead you can use:

    var dict = Map<string,int>();

Map<K,V> is an implementation of an AVL Tree (self balancing binary tree). This allows us to extend the standard IDictionary set of functions to include things like findRange.

Also you can pass in a list of tuples or key-value pairs:

    var people = Map((1, "Rod"),
                     (2, "Jane"),
                     (3, "Freddy"));

To read an item call:

    Option<string> result = find(people, 1);

This allows for branching based on whether the item is in the map or not:

    // Find the item, do some processing on it and return.
    var res = match( find(people, 100),
                     Some: v  => "Hello " + v,
                     None: () => "failed" );
                   
    // Find the item and return it. If it's not there, return "failed"
    var res = find(people, 100).IfNone("failed");                   
    
    // Find the item and return it. If it's not there, return "failed"
    var res = ifNone( find(people, 100), "failed" );

Because checking for the existence of something in a dictionary (find), and then matching on its result is very common, there is a more convenient match override:

    // Find the item, do some processing on it and return.
    var res = match( people, 1,
                     Some: v  => "Hello " + v,
                     None: () => "failed" );

To set an item call:

    var newThings = setItem(people, 1, "Zippy");

Obviously because it's an immutable structure, calling add, tryAdd, addOrUpdate, addRange, tryAddRange, addOrUpdateRange, remove, setItem, trySetItem, setItems or trySetItems... will generate a new Map<K,V>. It's quite cunning though, and it only replaces the items that need to be replaced and returns a new map with the new items and shared old items. This massively reduces the memory allocation burden

By holding onto a reference to the Map before and after calling add you essentially have a perfect timeline history of the changes. Be wary that if what you're holding in the Map is mutable and you change your mutable items, then the old Map and the new Map will change, so only store immutable items in a Map or leave them alone if they're mutable.

Immutable collections reference

Map transformers

There are additional transformer functions for dealing with "wrapped" maps (i.e. Map<int, Map<int, string>>). We only cover a limited set of the full set of Map functions at the moment. You can wrap Map up to 4 levels deep and still call things like Fold and Filter. There's interesting variants of Filter and Map called FilterRemoveT and MapRemoveT, where if a filter or map operation leaves any keys at any level with an empty Map then it will auto-remove them.

    Map<int,Map<int,Map<int, Map<int, string>>>> wrapped = Map.create<int,Map<int,Map<int,Map<int,string>>();
    
    wrapped = wrapped.AddOrUpdate(1,2,3,4,"Paul");
    wrapped = wrapped.SetItemT(1,2,3,4,"Louth");
    var name = wrapped.Find(1,2,3,4);               // "Louth"

The Map transformer functions:

Note, there are only fluent versions of the transformer functions.

Find
AddOrUpdate
Remove
MapRemoveT - maps each level, checks if the map is empty, in which case it removes it
MapT
FilterT
`FilterRemoveT`` - filters each level, checks if the map is empty, in which case it removes it
Exists
ForAll
SetItemT
TrySetItemT
FoldT
more coming...

Difficulty in creating immutable record types

It's no secret that implementing immutable record types with structural equality, structural ordering, and efficient hashing solutions is a real manual head-ache of implementing Equals, GetHashCode, deriving from IEquatable<A>, IComparer<A>, and implementing the operators: ==, !=, <, <=, >, >=. It is a constant maintenance headache of making sure they're kept up to date when new fields are added to the type, with no compilation errors if you forget to do it.

`Record<A>`

This can now be achieved simply by deriving your type from Record<A> where A is the type you want to have structural equality and ordering:

    public class TestClass : Record<TestClass>
    {
        public readonly int X;
        public readonly string Y;
        public readonly Guid Z;

        public TestClass(int x, string y, Guid z)
        {
            X = x;
            Y = y;
            Z = z;
        }
    }

This gives you Equals, IEquatable.Equals, IComparer.CompareTo, GetHashCode, operator==, operator!=, operator >, operator >=, operator <, and operator <= implemented by default. It also gives you a default ToString() implementation and ISerializable.GetObjectData() with a deserialisation constructor.

Note that only fields or field backed properties (including auto-properties) are used in the structural comparisons and hash-code building. There are also Attributes for opting fields out of the equality testing, ordering comparisons, hash-code generation, stringification (ToString), and serialisation:

Equals() - NonEq
CompareTo() - NonOrd
GetHashCode() - NonHash
ToString() - NonShow
Serialization - NonSerializable

For example, here's a record type that opts out of various default behaviours:

    public class TestClass2 : Record<TestClass2>
    {
        [NonEq]
        public readonly int X;

        [NonHash]
        public readonly string Y;

        [NonShow]
        public readonly Guid Z;

        public TestClass2(int x, string y, Guid z)
        {
            X = x;
            Y = y;
            Z = z;
        }
    }

If you want your type to serialise with Json.NET or other serialisers, then you will need to add an extra serialisation constructor that calls the default base implementation:

    public class TestClass : Record<TestClass>
    {
        public readonly int X;
        public readonly string Y;
        public readonly Guid Z;

        public TestClass(int x, string y, Guid z)
        {
            X = x;
            Y = y;
            Z = z;
        }
        
        TestClass(SerializationInfo info, StreamingContext context) 
            : base(info, context) { }
    }

This will do full structural equality as the following examples demonstrate:

public class Cons<A> : Record<Cons<A>>
{
    public readonly A Head;
    public readonly Cons<A> Tail;

    public Cons(A head, Cons<A> tail)
    {
        Head = head;
        Tail = tail;
    }
}

public void ConsTests()
{
    var listA = new Cons<int>(1, new Cons<int>(2, new Cons<int>(3, new Cons<int>(4, null))));
    var listB = new Cons<int>(1, new Cons<int>(2, new Cons<int>(3, new Cons<int>(4, null))));
    var listC = new Cons<int>(1, new Cons<int>(2, new Cons<int>(3, null)));

    Assert.True(listA == listB);
    Assert.True(listB != listC);
    Assert.True(listA != listC);
}

public class Tree<A> : Record<Tree<A>>
{
    public readonly A Value;
    public readonly Tree<A> Left;
    public readonly Tree<A> Right;

    public Tree(A value, Tree<A> left, Tree<A> right)
    {
        Value = value;
        Left = left;
        Right = right;
    }
}

public void TreeTests()
{
    var treeA = new Tree<int>(5, new Tree<int>(3, null, null), new Tree<int>(7, null, new Tree<int>(9, null, null)));
    var treeB = new Tree<int>(5, new Tree<int>(3, null, null), new Tree<int>(7, null, new Tree<int>(9, null, null)));
    var treeC = new Tree<int>(5, new Tree<int>(3, null, null), new Tree<int>(7, null, null));

    Assert.True(treeA == treeB);
    Assert.True(treeB != treeC);
    Assert.True(treeA != treeC);
}

There are some unit tests to see this in action.

Inheritance is not supported in Record derived types, so if you derive a type from a type that derives from Record then you won't magically inherit any equality, ordering, hash-code, etc. behaviours. This feature is explicitly here to implement record-like functionality, which do not support inheritance in other functional languages. Equality of origin is explicitly checked for.

`RecordType<A>`

You can also use the "toolkit" that Record<A> uses to build this functionality in your own bespoke types (perhaps if you want to use this for struct comparisons or if you can't derive directly from Record<A>, or maybe you just want some of the functionality for ad-hoc behaviour):

The toolkit is composed of four functions:

    RecordType<A>.Hash(record);

This will provide the hash-code for the record of type A provided. It can be used for your default GetHashCode() implementation.

    RecordType<A>.Equality(record, obj);

This provides structural equality with the record of type A and the record of type object. The types must match for the equality to pass. It can be used for your default Equals(object) implementation.

    RecordType<A>.EqualityTyped(record1, record2);

This provides structural equality with the record of type A and another record of type A. It can be used for your default Equals(a, b) method for the IEquatable<A> implementation.

    RecordType<A>.Compare(this, other);

This provides a structural ordering comparison with the record of type A and another record the record of type A. It can be used for your default CompareTo(a, b) method for the IComparable<A> implementation.

Below is the toolkit in use, it's used to build a struct type that has structural equality, ordering, and hash-code implementation.

    public class TestStruct : IEquatable<TestStruct>, IComparable<TestStruct>
    {
        public readonly int X;
        public readonly string Y;
        public readonly Guid Z;

        public TestStruct(int x, string y, Guid z)
        {
            X = x;
            Y = y;
            Z = z;
        }

        public override int GetHashCode() =>
            RecordType<TestStruct>.Hash(this);

        public override bool Equals(object obj) =>
            RecordType<TestStruct>.Equality(this, obj);

        public int CompareTo(TestStruct other) =>
            RecordType<TestStruct>.Compare(this, other);

        public bool Equals(TestStruct other) =>
            RecordType<TestStruct>.EqualityTyped(this, other);
    }

Transformation of immutable types

If you're writing functional code you should treat your types as values. Which means they should be immutable. One common way to do this is to use readonly fields and provide a With function for mutation. i.e.

public class A
{
    public readonly X X;
    public readonly Y Y;

    public A(X x, Y y)
    {
        X = x;
        Y = y;
    }

    public A With(X X = null, Y Y = null) =>
        new A(
            X ?? this.X,
            Y ?? this.Y
        );
}

Then transformation can be achieved by using the named arguments feature of C# thus:

val = val.With(X: x);

val = val.With(Y: y);

val = val.With(X: x, Y: y);

`[With]`

It can be quite tedious to write the With function however. And so, if you include the LanguageExt.CodeGen nu-get package in your solution you gain the ability to use the [With] attribtue on a type. This will build the With method for you.

NOTE: The LanguageExt.CodeGen package and its dependencies will not be included in your final build - it is purely there to generate the code.

You must however:

Make the class partial
Have a constructor that takes the fields in the order they are in the type
The names of the arguments should be the same as the field, but with the first character lower-case

i.e.

[With]
public partial class A
{
    public readonly X X;
    public readonly Y Y;

    public A(X x, Y y)
    {
        X = x;
        Y = y;
    }
}

Transformation of nested immutable types with Lenses

One of the problems with immutable types is trying to transform something nested deep in several data structures. This often requires a lot of nested With methods, which are not very pretty or easy to use.

Enter the Lens<A, B> type.

Lenses encapsulate the getter and setter of a field in an immutable data structure and are composable:

[With]
public partial class Person
{
    public readonly string Name;
    public readonly string Surname;

    public Person(string name, string surname)
    {
        Name = name;
        Surname = surname;
    }

    public static Lens<Person, string> name =>
        Lens<Person, string>.New(
            Get: p => p.Name,
            Set: x => p => p.With(Name: x));

    public static Lens<Person, string> surname =>
        Lens<Person, string>.New(
            Get: p => p.Surname,
            Set: x => p => p.With(Surname: x));
}

This allows direct transformation of the value:

var person = new Person("Joe", "Bloggs");

var name = Person.name.Get(person);
var person2 = Person.name.Set(name + "l", person);  // Joel Bloggs

This can also be achieved using the Update function:

var person = new Person("Joe", "Bloggs");

var person2 = Person.name.Update(name => name + "l", person);  // Joel Bloggs

The power of lenses really becomes apparent when using nested immutable types, because lenses can be composed. So, let's first create a Role type which will be used with the Person type to represent an employee's job title and salary:

[With]
public partial class Role
{
    public readonly string Title;
    public readonly int Salary;

    public Role(string title, int salary)
    {
        Title = title;
        Salary = salary;
    }

    public static Lens<Role, string> title =>
        Lens<Role, string>.New(
            Get: p => p.Title,
            Set: x => p => p.With(Title: x));

    public static Lens<Role, int> salary =>
        Lens<Role, int>.New(
            Get: p => p.Salary,
            Set: x => p => p.With(Salary: x));
}

[With]
public partial class Person
{
    public readonly string Name;
    public readonly string Surname;
    public readonly Role Role;

    public Person(string name, string surname, Role role)
    {
        Name = name;
        Surname = surname;
        Role = role;
    }

    public static Lens<Person, string> name =>
        Lens<Person, string>.New(
            Get: p => p.Name,
            Set: x => p => p.With(Name: x));

    public static Lens<Person, string> surname =>
        Lens<Person, string>.New(
            Get: p => p.Surname,
            Set: x => p => p.With(Surname: x));

    public static Lens<Person, Role> role =>
        Lens<Person, Role>.New(
            Get: p => p.Role,
            Set: x => p => p.With(Role: x));
}

We can now compose the lenses within the types to access the nested fields:

var cto = new Person("Joe", "Bloggs", new Role("CTO", 150000));

var personSalary = lens(Person.role, Role.salary);

var cto2 = personSalary.Set(170000, cto);

`[WithLens]`

Typing the lens fields out every time is even more tedious than writing the With function, and so there is code generation for that too: using the [WithLens] attribute. Next, we'll use some of the built-in lenses in the Map type to access and mutate a Appt type within a map:

[WithLens]
public partial class Person : Record<Person>
{
    public readonly string Name;
    public readonly string Surname;
    public readonly Map<int, Appt> Appts;

    public Person(string name, string surname, Map<int, Appt> appts)
    {
        Name = name;
        Surname = surname;
        Appts = appts;
    }
}

[WithLens]
public partial class Appt : Record<Appt>
{
    public readonly int Id;
    public readonly DateTime StartDate;
    public readonly ApptState State;

    public Appt(int id, DateTime startDate, ApptState state)
    {
        Id = id;
        StartDate = startDate;
        State = state;
    }
}

public enum ApptState
{
    NotArrived,
    Arrived,
    DNA,
    Cancelled
}

So, here we have a Person with a map of Appt types. And we want to update an appointment state to be Arrived:

// Generate a Person with three Appts in a Map
var person = new Person("Paul", "Louth", Map(
    (1, new Appt(1, DateTime.Parse("1/1/2010"), ApptState.NotArrived)),
    (2, new Appt(2, DateTime.Parse("2/1/2010"), ApptState.NotArrived)),
    (3, new Appt(3, DateTime.Parse("3/1/2010"), ApptState.NotArrived))));

// Local function for composing a new lens from 3 other lenses
Lens<Person, ApptState> setState(int id) => 
    lens(Person.appts, Map<int, Appt>.item(id), Appt.state);

// Transform
var person2 = setState(2).Set(ApptState.Arrived, person);

Notice the local-function which takes an ID and uses that with the item lens in the Map type to mutate an Appt. Very powerful stuff.

There are a number of useful lenses in the collection types that can do common things like mutate by index, head, tail, last, etc.

The awful `out` parameter

This has to be one of the most awful patterns in C#:

    int result;
    if( Int32.TryParse(value, out result) )
    {
        ...
    }
    else
    {
        ...
    }

There's all kinds of wrong there. Essentially the function needs to return two pieces of information:

Whether the parse was a success or not
The successfully parsed value

This is a common theme throughout the .NET framework. For example on IDictionary.TryGetValue

    int value;
    if( dict.TryGetValue("thing", out value) )
    {
       ...
    }
    else
    {
       ...
    }

So to solve it we now have methods that instead of returning bool, return Option<T>. If the operation fails it returns None. If it succeeds it returns Some(the value) which can then be matched. Here's some usage examples:

    
    // Attempts to parse the value, uses 0 if it can't
    int res = parseInt("123").IfNone(0);

    // Attempts to parse the value, uses 0 if it can't
    int res = ifNone(parseInt("123"), 0);

    // Attempts to parse the value, doubles it if can, returns 0 otherwise
    int res = parseInt("123").Match(
                  Some: x => x * 2,
                 None: () => 0
              );

    // Attempts to parse the value, doubles it if can, returns 0 otherwise
    int res = match( parseInt("123"),
                     Some: x => x * 2,
                     None: () => 0 );

out method variants

IDictionary<K, V>.TryGetValue
IReadOnlyDictionary<K, V>.TryGetValue
int.TryParse becomes parseInt
long.TryParse becomes parseLong
short.TryParse becomes parseShort
char.TryParse becomes parseChar
sbyte.TryParse becomes parseSByte
byte.TryParse becomes parseByte
ulong.TryParse becomes parseULong
uint.TryParse becomes parseUInt
ushort.TryParse becomes parseUShort
float.TryParse becomes parseFloat
double.TryParse becomes parseDouble
decimal.TryParse becomes parseDecimal
bool.TryParse becomes parseBool
Guid.TryParse becomes parseGuid
DateTime.TryParse becomes parseDateTime
DateTimeOffset.TryParse becomes parseDateTimeOffset
TimeSpan.TryParse becomes parseTimeSpan
Enum.TryParse becomes parseEnum

any others you think should be included, please get in touch

Ad-hoc polymorphism

This is where things get a little crazy! This section is taking what's possible with C# to its limits. None of what follows is essential for 99% of the use cases for this library. However, the seasoned C# programmer will recognise some of the issues raised (like no common numeric base-type); and experienced functional programmers will recognise the category theory creeping in... Just remember, this is all optional, but also pretty powerful if you want to go for it.

Ad-hoc polymorphism has long been believed to not be possible in C#. However with some cunning it is. Ad-hoc polymorphism allows programmers to add traits to a type later. For example in C# it would be amazing if we had an interface called INumeric for numeric types like int, long, double, etc. The reason this doesn't exist is if you write a function like:

    INumeric Add(INumeric x, INumeric y) => x + y;

Then it would cause boxing. Which is slow (well, slower). I can only assume that's why it wasn't added by the BCL team. Anyway, it's possible to create a numeric type, very much like a type-class in Haskell, and ad-hoc instances of the numeric type-class that allow for generic numeric operations without boxing.

From now on I will call them type-classes and class-instances, or just instances. This is not exactly the same as Haskell's type-classes. If anything it's closer to Scala's implicits. However to make it easier to discuss them I will steal from Haskell's lexicon.

`Num<A>`

So for example, this is how to create a number type-class:

    public interface Num<A>
    {
        A Add(A x, A y);
        A Subtract(A x, A y);
        ...
    }

Notice how there are two arguments to Add and Subtract. Normally if I was going to implement this interface the left-hand-side of the Add and Subtract would be this. I will implement the ad-hoc class-instance to demonstrate why that is:

    public struct TInt : Num<int>
    {
        public int Add(int x, int y) => x + y;
        public int Subtract(int x, int y) => x - y;
        ...
    }

See how TInt is a struct? Structs have a useful property in C# in that they can't be null. So we can invoke the operations like so:

    int r = default(TInt).Add(10, 20);

The important thing to note is that default(TInt) gets optimisied out in a release build, so there's no cost to the invocation of Add. The Add and Subtract methods both take int and return int. So therefore there's no boxing at all.

If we now implement TFloat:

    public struct TFloat : Num<float>
    {
        public float Add(float x, float y) => x + y;
        public float Subtract(float x, float y) => x - y;
        ...
    }

Then we can see how a general function could be written to take any numeric type:

    public A DoubleIt<NumA, A>(A x) where NumA : struct, Num<A> =>
        default(NumA).Add(x, x);

The important bit is the NumA generic argument, and the constraint of struct, Num<A>. That allows us to call default(NumA) to get the type-class instance and invoke Add.

And so this can now be called by:

    int a   = DoubleIt<TInt, int>(5);        // 10
    float b = DoubleIt<TFloat, float>(5.25); // 10.5

By expanding the amount of operations that the Num<A> type-class can do, you can perform any numeric operation you like. If you like you can add new numeric types (say for complex numbers, or whatever), where the rules of the type are kept in the ad-hoc instance.

Luckily you don't need to do that, because I have created the Num<A> type (in the LanguageExt.TypeClasses namespace), as well as Floating<A> (with all of the operations from Math; like Sin, Cos, Exp, etc.). Num<A> also has a base-type of Arithmetic<A> which supports Plus, Subtract, Product, Negate. This is for types which don't need the full spec of the Num<A> type. I have also mapped all of the core numeric types to instances: TInt, TShort, TLong, TFloat, TDouble, TDecimal, TBigInt, etc. So it's possible to write truly generic numeric code once.

There's no getting around the fact that providing the class-instance in the generic arguments list is annoying (and later you'll see how annoying). The Roslyn team are looking into a type-classes like feature for a future version of C# (variously named: 'Concepts' or 'Shapes'). So this will I'm sure be rectified, and when it is, it will be implemented exactly as I am using them here.

Until then the pain of providing the generic arguments must continue. You do however get a super-powered C# in the mean-time.

The need to write this kind of super-generic code is rare; but when you need it, you need it - and right now this is simply the most powerful way.

`Eq<A>`

Next up is Eq<A>. Equality testing in C# is an absolute nightmare. From the different semantics of Equals and ==, to IEqualityComparer, and the enormous hack which is EqualityComparer.Default (which doesn't blow up at compile-time if your code is wrong).

The Eq<A> type-class looks like this:

    public interface Eq<A>
    {
        bool Equals(A x, A y);
        int GetHashCode(A x);
    }

There are Eq prefixed instances for all common types (EqInt, EqString, EqGuid etc.), as well as for all of the types in this library (EqLst, EqSet, EqTry, etc). All of the numeric types (TInt, TDouble, etc.) also implement Eq<A>.

To make it slightly prettier to use in code, you can use the Prelude equals function:

    bool x = equals<EqInt>(1, 1); // True

Or use default as shown before:

    bool x = default(EqInt).Equals(1, 1); // True

One final way is:

    bool x = EqInt.Inst.Equals(1, 1);

Inst is defined on all of the instances in lang-ext, but it's not an 'official feature'. Anybody could implement an ad-hoc implementation of Eq<A> and not provide an Inst.

For example you may call this directly:

    bool x = EqLst.Inst.Equals(List(1,2,3), List(1,2,3)); // true

Because you may be concerned about calling:

    bool x = List(1,2,3) == List(1,2,3); // ?

... as all C# programmers are at some point, because we have no idea most of the time whether == does what we think it should.

Just FYI List(1,2,3) == List(1,2,3) does work properly! As do all types in language-ext.

There are two variants of the immutable HashSet in language-ext:

    HashSet<A>
    HashSet<EqA, A> where EqA : struct, Eq<A>

What's interesting about the second one is that the equality definition is baked into the type. So this:

    HashSet<EqString, string>

Is not compatible with:

    HashSet<EqStringOrdinalIgnoreCase, string>

And if you think about that, it's right. The strings that are used as keys in the HashSet<EqString, string> do not have the same properties as the strings in HashSet<EqStringOrdinalIgnoreCase, string>. So even though they're both strings, they have different semantics (which cause wildly different behaviour for things like set intersection, unions, etc.)

Now compare that to HashSet<T> in the BCL, or ImmutableHashSet<T> in System.Collections.Immutable, where two different sets with different IEqualityComparer types injected will cause undefined results when used together.

That's hopefully a small glimpse into the potential for improving type-safeness in C#.

`Ord<A>`

Ord is for ordering. i.e. a IComparable replacement. By the way, these names Eq, Ord, Num, are all lifted from Haskell. I much prefer the short concise names that still convey meaning than the bulky and often clumsy names of the BCL.

This is Ord<A>, it derives from Eq<A>

    public interface Ord<A> : Eq<A>
    {
        int Compare(A x, A y);
    }

Usage should be self-explanatory now, but the important thing to note here is that because 'type classes' are just interfaces, they can also have an inheritance hierarchy.

This is a slightly more complex example:

    public struct OrdArray<ORD, A> : Ord<A[]>
        where ORD : struct, Ord<A>
    {
        public int Compare(A[] mx, A[] my)
        {
            if (ReferenceEquals(mx, my)) return 0;
            if (ReferenceEquals(mx, null)) return -1;
            if (ReferenceEquals(my, null)) return 1;

            var cmp = mx.Length.CompareTo(my.Length);
            if (cmp == 0)
            {
                for(var i = 0; i < mx.Length; i++)
                {
                    cmp = default(ORD).Compare(mx[i], my[i]);
                    if (cmp != 0) return cmp;
                }
                return 0;
            }
            else
            {
                return cmp;
            }
        }

        public bool Equals(A[] x, A[] y) =>
            default(EqArray<ORD, A>).Equals(x, y);

        public int GetHashCode(A[] x) =>
            hash(x);
    }

The OrdArray which is an Ord<A[]>, does itself also take an ORD generic argument, which allows the contents of the array to be compared:

    int x = OrdArray<TInt, int>.Inst.Compare(new [] {1,2}, new [] {1,2}); // 0

`Semigroup<A>`

This is where we start going a little more abstract. Semigroups are a feature of category theory, which is soooo not important for this discussion. They represent an associative binary operation, which can be invoked by calling Append.

    public interface Semigroup<A>
    {
        A Append(A x, A y);
    }

Positive numbers (for example) form a semigroup. I won't dwell on it too long, because although the Append function is super-useful, nearly everything that falls into the Semigroup category is also a Monoid...

`Monoid<A>`

A monoid has something that a semigroup doesn't, and that's the concept of identity (often meaning 'empty' or 'zero'). It looks like this:

    public interface Monoid<A> : Semigroup<A>
    {
        A Empty();
    }

This comes with some helper functions in LanguageExt.TypeClass:

    public static partial class TypeClass
    {
        public static A mempty<MONOID, A>() where MONOID : struct, Monoid<A> =>
            default(MONOID).Empty();

        public static A mconcat<MONOID, A>(IEnumerable<A> xs) where MONOID : struct, Monoid<A> =>
            xs.Fold(mempty<MONOID, A>(), (s, x) => append<MONOID, A>(s, x));

        public static A mconcat<MONOID, A>(params A[] xs) where MONOID : struct, Monoid<A> =>
            xs.Fold(mempty<MONOID, A>(), (s, x) => append<MONOID, A>(s, x));
    }

Now the semigroup Append comes to life. Examples of monoids are: TInt, MLst, TString, etc. i.e.

    var x = mconcat<TString, string>("Hello", " ", "World");   // "Hello World"
    var y = mconcat<TLst<int>, Lst<int>>(List(1), List(2, 3)); // [1,2,3]
    var z = mconcat<TInt, int>(1, 2, 3, 4, 5);                 // 15

The Empty() function is what provides the identity value for the concat operations. So for string it's "", for Lst<T> it's [] and for int it's 0. So a monoid is a semigroup with a zero.

It's surprising how much stuff just starts working when you know your type is a monoid. For example in language-ext version 1 there is a monadic type called Writer<W, T>. The writer monad collects a log as well as returning the bound value. In version 1 the log had to be an IEnumerable<W>, which isn't super flexible. In language-ext version 2 the type looks like this:

    public class Writer<MonoidW, W, A> where MonoidW : struct, Monoid<W>
    {
        ...
    }

So now it can be a running numeric total, or a Lst<W>, or a Set<W>, or whatever monoid you dream up.

Higher-kinds

Higher-order polymorphism would allow us to define a type like so:

    public interface MyType<M<A>>
    {
        M<B> Foo<B>(M<A> ma);
    }

Where not only is the A parametric, but so it M. So for example if I wanted to implement MyType for Option<A> I could do:

    public class MyOptionType<A> : MyType<Option<A>>
    {
        public Option<B> Foo<B>(Option<A> ma) => ...;
    }

It would be soooo nice if C# (well, the immutable CLR) would support this. But it doesn't. So we need to find ways around it. The way I am using for language-ext is:

    public interface MyType<MA, A>
    {
        MB Foo<MB, B>(MA ma);
    }

    public class MyOptionType<A> : MyType<Option<A>, A>
    {
        public MB Foo<MB, B>(Option<A> ma) => ...;
    }

`Monad`

This is where some of the difficulties come in. How do we return an MB if we don't know what it is? This is a problem for the Monad type. This is a simplified version:

    public interface Monad<MA, A>
    {
        MB Bind<MB, B>(MA ma, Func<A, MB> bind);
        MA Return(A a);
        MA Fail(Exception e = null);
    }

Looking at the prototype for Bind it seems at first glance that the bind argument will give us the MB value we want. But an Option might be in a None state, in which case it shouldn't run bind.

    public MB Bind<MB, B>(Option<A> ma, Func<A, MB> bind) =>
        ma.IsSome
            ? bind(ma.Value)
            : ??? ; // What do we return here?

The key is to use constraints. But it also requires an extra generic parameter for Bind:

    public interface Monad<MA, A>
    {
        MB Bind<MonadB, MB, B>(MA ma, Func<A, MB> bind) 
            where MonadB : struct, Monad<MB, B>;

        MA Return(A a);
        MA Fail(Exception e = null);
    }

So we now know that MonadB is a class-instance of the Monad<MB, B> type-class. So we can now do this:

    public MB Bind<MonadB, MB, B>(Option<A> ma, Func<A, MB> f) 
        where MonadB : struct, Monad<MB, B> =>
            ma.IsSome
                ? f(ma.Value)
                : default(MonadB).Fail();

The eagle eyed reader will notice that this actually allows binding to any resulting monad (not just Option<B>). I'm sure some may consider labelling this a monad as incorrect, but it works, it's type-safe, it's efficient, and performs the exact same function and so I am happy to use the term.

The actual definition of Monad is more complex than this, in order to unify monadic types that take arguments (Reader and State) and monads that carry internal state (Writer and State), as well as to support asynchronous monads (TryAsync and TryOption). I won't muddy the waters too much right now, but unified and type-safe they are. There are no hacks.

You should see that the Return and Fail functions are trivial to implement:

    public Option<A> Return(A a) =>
        Optional(a);

    public Option<A> Fail(Exception e = null) =>
        None;

What that means is that any function that has been constrained by a monad instance can create new instances of them:

    public M CreateNewIntegerMonad<MonadInt, M, int>(int x) 
        where MonadInt : struct, Monad<M, int> =>
            default(MonadInt).Return(x);

This is one of the key breakthroughs. Imagine trying to create a Monad type the old way:

    public interface Monad<A>
    {
        Monad<B> Bind<B>(Func<A, Monad<B>> bind);
    }

    public class Option<A> : Monad<A>
    {
        public Monad<B> Bind<B>(Monad<A> ma, Func<A, Monad<B>> bind) =>
            IsSome
                ? bind(Value)
                : None;
    }

    public Monad<int> CreateNewIntegerMonad(int x) =>
        ????; // How?

Maybe we could parameterise it?

    public Monad<int> CreateNewIntegerMonad<M>(int x) where M : Monad<int> =>
        ????; // We still can't call new M(x)

But that doesn't work either because we still can't call new M(x). Being able to paramterise generic functions at the point where you know the concrete types (and therefore know the concrete class-instance) means that the generic functions can invoke the instance functions to create the concrete types.

Here's a super generic example of a function that takes two monad arguments, they're both of the same type, and their bound values are Num<A>.

    public static MA Add<MonadA, MA, NumA, A>(MA ma, MA mb)
        where MonadA  : struct, Monad<MA, A>
        where NumA    : struct, Num<A> =>
            default(MonadA).Bind<MonadA, MA, A>(ma, a =>
            default(MonadA).Bind<MonadA, MA, A>(mb, b =>
            default(MonadA).Return(default(NumA).Plus(a, b))));

You may notice that the two Bind calls followed by the Return are basically a much less attractive version of this:

        from a in ma
        from b in mb
        select default(NumA).Plus(a, b);

And so I can now add two options:

    var x = Some(10);
    var y = Some(20);
    var z = Option<int>.None;

    var r1 = Add<MOption<int>, Option<int>, TInt, int>(x, y); // Some(30)
    var r2 = Add<MOption<int>, Option<int>, TInt, int>(x, z); // None

    Assert.True(r1 == Some(30));
    Assert.True(r2 == None);

Or two lists:

    var x = List(1, 2, 3);
    var y = List(4, 5, 6);
    var z = List<int>();

    var r1 = Add<MLst<int>, Lst<int>, TInt, int>(x, y);
    var r2 = Add<MLst<int>, Lst<int>, TInt, int>(x, z);

    Assert.True(r1 == List(5, 6, 7,  6, 7, 8,  7, 8, 9));
    Assert.True(r2 == z);

Or any two monads. They will follow the built in rules for the type, and produce concrete values efficiently and without any boxing or dynamic casting.

Transformer types

Often you'll find yourself with nested monadic types Option<Lst<A>>, Seq<Either<L, R>>, Try<Validation<Fail, Success>>, ..., and you want to work with the bound value(s) of A without having to unwrap/match the values away. And so there are around 100,000 lines of generated code for working with 'transformer types'.

There is a new MonadTrans. It does all the heavy lifting, and it is what the generated code uses (it's also what you'd need to use if you create your own monadic types and you want to build transformers for the various pairs of monadic types).

For every pair of nested monads: Lst<Option<A>>, Try<Either<L, A>>, etc. there are the following extension methods (this is for Arr<Lst<A>>):

// Sums all the bound value(s)
A SumT<NumA, A>(this Arr<Lst<A>> ma);

// Counts all the bound value(s)
int CountT<A>(this Arr<Lst<A>> ma);

// Monadic bind on the inner monad
Arr<Lst<B>> BindT<A, B>(this Arr<Lst<A>> ma, Func<A, Lst<B>> f);

// Flips the inner and outer monads (using the rules of the inner and outer 
// monads to compose the result) and performs a map operation on the bound values
Lst<Arr<B>> Traverse<A, B>(this Arr<Lst<A>> ma, Func<A, B> f);

// Flips the inner and outer monads (using the rules of the inner and outer 
// monads to compose the result) 
Lst<Arr<A>> Sequence<A>(this Arr<Lst<A>> ma);

// Maps the bound value(s)
Arr<Lst<B>> MapT<A, B>(this Arr<Lst<A>> ma, Func<A, B> f);

// Folds the bound value(s)
S FoldT<S, A>(this Arr<Lst<A>> ma, S state, Func<S, A, S> f);

// Reverse folds the bound value(s)
S FoldBackT<S, A>(this Arr<Lst<A>> ma, S state, Func<S, A, S> f);

// Returns true if f(x) returns true for any of the bound value(s)
bool ExistsT<A>(this Arr<Lst<A>> ma, Func<A, bool> f);

// Returns true if f(x) returns true for all of the bound value(s)
bool ForAllT<A>(this Arr<Lst<A>> ma, Func<A, bool> f);

// Iterates all of the bound values
Unit IterT<A>(this Arr<Lst<A>> ma, Action<A> f);

// Filters the bound value(s) with the predicate
Arr<Lst<A>> FilterT< A>(this Arr<Lst<A>> ma, Func<A, bool> pred);

// Filters the bound value(s) with the predicate
Arr<Lst<A>> Where<A>(this Arr<Lst<A>> ma, Func<A, bool> pred);

// Maps the bound value(s)
Arr<Lst<A>> Select<A, B>(this Arr<Lst<A>> ma, Func<A, B> f);

// LINQ monadic bind and project on the bound value(s)
Arr<Lst<C>> SelectMany<A, B, C>(
        this Arr<Lst<A>> ma,
        Func<A, Lst<B>> bind,
        Func<A, B, C> project);

// Plus operation on the bound value(s)
Arr<Lst<A>> PlusT<NUM, A>(this Arr<Lst<A>> x, Arr<Lst<A>> y) where NUM : struct, Num<A>;

// Subtraction operation on the bound value(s)
Arr<Lst<A>> SubtractT<NUM, A>(this Arr<Lst<A>> x, Arr<Lst<A>> y) where NUM : struct, Num<A>;

// Product operation on the bound value(s)
Arr<Lst<A>> ProductT<NUM, A>(this Arr<Lst<A>> x, Arr<Lst<A>> y) where NUM : struct, Num<A> =>
        ApplyT(default(NUM).Product, x, y);

// Divide operation on the bound value(s)
Arr<Lst<A>> DivideT<NUM, A>(this Arr<Lst<A>> x, Arr<Lst<A>> y) where NUM : struct, Num<A>;

// Semigroup append operation on the bound value(s)
AppendT<SEMI, A>(this Arr<Lst<A>> x, Arr<Lst<A>> y) where SEMI : struct, Semigroup<A>;

// Comparison operation on the bound value(s)
int CompareT<ORD, A>(this Arr<Lst<A>> x, Arr<Lst<A>> y) where ORD : struct, Ord<A>;

// Equality operation on the bound value(s)
bool EqualsT<EQ, A>(this Arr<Lst<A>> x, Arr<Lst<A>> y) where EQ : struct, Eq<A>;

// Applicative apply operation on the bound value(s)
Arr<Lst<A>> ApplyT<A, B>(this Func<A, B> fab, Arr<Lst<A>> fa);

// Application apply operation on the bound value(s)
Arr<Lst<C>> ApplyT<A, B, C>(this Func<A, B, C> fabc, Arr<Lst<A>> fa, Arr<Lst<A>> fb);

The number of functions has increased dramatically. Some of the special ones are Traverse and Sequence which flips the inner and outer types. So for example:

    Lst<Option<int>> x = List(Some(1), Some(2), Some(3), Some(4), Some(5));
    Option<Lst<int>> y = x.Sequence();

    Assert.True(y == Some(List(1, 2, 3, 4, 5)));

As you can see, the list is now inside the option.

    Lst<Option<int>> x = List(Some(1), Some(2), Some(3), None, Some(5));
    Option<Lst<int>> y = x.Sequence();

    Assert.True(y == None);

In this case there is a None in the Lst so when the Lst<Option<>> becomes a Option<Lst<>> the rules of the Option take over, and one None means all None.

This can be quite useful for Either:

    var x = List<Either<string, int>>(1, 2, 3, 4, "error");

    var y = x.Sequence();

    Assert.True(y.IsLeft && y == "error");

This collects the first error it finds, or returns Right if there is no error.

Traverse is the same as Sequence except it applies a mapping function to each bound value as it's transforming the types. Here's an example that runs 6 tasks in parallel, and collects their results:

    var start = DateTime.UtcNow;

    var f1 = Task.Run(() => { Thread.Sleep(3000); return 1; });
    var f2 = Task.Run(() => { Thread.Sleep(3000); return 2; });
    var f3 = Task.Run(() => { Thread.Sleep(3000); return 3; });
    var f4 = Task.Run(() => { Thread.Sleep(3000); return 4; });
    var f5 = Task.Run(() => { Thread.Sleep(3000); return 5; });
    var f6 = Task.Run(() => { Thread.Sleep(3000); return 6; });

    var res = await List(f1, f2, f3, f4, f5, f6).Traverse(x => x * 2);

    Assert.True(toSet(res) == Set(2, 4, 6, 8, 10, 12));

    var ms = (int)(DateTime.UtcNow - start).TotalMilliseconds;
    Assert.True(ms < 3500, $"Took {ms} ticks");

So there is a List of Tasks that becomes a single awaitable Task of List.

As well as the extensions, there are also static classes for the transformer types. There is one for each type of monad. So for example, Option has a LanguageExt.OptionT type. Whenever you have a pair of nested monads, and Option is the inner monad, then you would use OptionT:

    var ma = List(Some(1),Some(2),Some(3),Some(4),Some(5));

    var total = OptionT.foldT(ma, 0, (s, x) => s + x); // 15
    var total = OptionT.sumT<TInt, int>(ma); // 15
    var mb    = OptionT.filterT(ma, x > 3); // List(Some(3), Some(4))

Contributing & Code of Conduct

If you would like to get involved with this project, please first read the Contribution Guidelines and the Code of Conduct.

Name		Name	Last commit message	Last commit date
Latest commit History 3,038 Commits
.github		.github
Images		Images
LanguageExt.Benchmarks		LanguageExt.Benchmarks
LanguageExt.CodeGen		LanguageExt.CodeGen
LanguageExt.Core		LanguageExt.Core
LanguageExt.FSharp		LanguageExt.FSharp
LanguageExt.Parsec		LanguageExt.Parsec
LanguageExt.Rx		LanguageExt.Rx
LanguageExt.Sys		LanguageExt.Sys
LanguageExt.SysX		LanguageExt.SysX
LanguageExt.Tests		LanguageExt.Tests
LanguageExt.Transformers		LanguageExt.Transformers
Samples		Samples
pjv		pjv
.editorconfig		.editorconfig
.gitattributes		.gitattributes
.gitignore		.gitignore
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
LICENSE.md		LICENSE.md
Performance.md		Performance.md
README.md		README.md
inc.bat		inc.bat
language-ext.sln		language-ext.sln
pack.bat		pack.bat
version-2-migration-notes.md		version-2-migration-notes.md
version-2-release-notes.md		version-2-release-notes.md

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C# Functional Programming Language Extensions

Contents

Reference

Nu-get

Code-gen setup

Unity

Getting started

Prologue

A note about naming

Features

Functional effects and IO

Atomic concurrency and collections

Immutable collections

Optional and alternative value monads

State managing monads

Parser combinators

New types - Type aliasing

Code generation

Pretty

Differencing

Make C# better

Poor tuple support

Null reference problem

Option

Option monad - gasp! Not the M word!

if( arg == null ) throw new ArgumentNullException("arg")

Lack of lambda and expression inference

Void isn't a real type

Mutable lists and dictionaries

Lists

List pattern matching

Maps

Map transformers

Difficulty in creating immutable record types

Record<A>

RecordType<A>

Transformation of immutable types

[With]

Transformation of nested immutable types with Lenses

[WithLens]

The awful out parameter

Ad-hoc polymorphism

Num<A>

Eq<A>

Ord<A>

Semigroup<A>

Monoid<A>

Higher-kinds

Monad

Transformer types

Contributing & Code of Conduct

About

Resources

License

Stars

Watchers

Forks

Releases

Packages 0

Languages

`Record<A>`

`RecordType<A>`

`[With]`

`[WithLens]`

The awful `out` parameter

`Num<A>`

`Eq<A>`

`Ord<A>`

`Semigroup<A>`

`Monoid<A>`

`Monad`

Packages