Fundamental Haskell
Encyclopedcal handbook for learning and undersatanding fundamentals

Table of Contents

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1 Introduction

“Employ your time in improving yourself by other men's writings so that you shall come easily by what others have labored hard for.” (Socrates by Plato)

Important notes on Haskell, category theory & related fields, terms and recommendations.

Book comes in forms:

This book is created using complex Org markup file with a lot of LaTeX and LaTeX formulas. Be aware - GitHub & GitLab only partially parse Org into HTML.

Book becomes too popular (underground scene wibe). To address that - a proper Haskell book would "avoid success at all costs" and go through proper migrations, become free from presonal Org-drill metadata, to give clean learning materials for Haskell community.

In work on the book, person basically reinvented the Zettelkasten. Since person arrived at the same design, I would recommend Zettelkasten to anyone.

Current book form also reached the limits of the radio cross-linking scaling of the Emacs Org-mode C-implemeted functions. The book would migrate into a most powerful proper Free Software Zettelkasten form there is - Org-roam - and in that transition book would gain even more versatility and possibilities.

Book also wants to be published in form of the Anki card deck for Anki users. Did you know that Anki is actually former Emacs Org-drill v1?

So in nearest time book source would go through big structural changes.

To get the full view:

  • Outline navigation
  • LaTeX formulas:

    \( {\displaystyle\left[{-\frac{\hbar^{2}}{2m}}\nabla^{2}+V(\vec{r},t)\right]\Psi({\vec{r}},t)=i\hbar{\partial\over\partial{t}}\Psi({\vec{r}},t),\quad\sum_{k,j}\left[-{\frac{\hbar^{2}}{\sqrt{a}}}{\frac{\partial}{\partial{q^{k}}}}\left({\sqrt{a}}a^{kj}{\frac{\partial}{\partial{q^{j}}}}\right)+V\right]\Psi+{\frac{\hbar}{i}}{\frac{\partial{\Psi}}{\partial{t}}}=0} \)

  • Interlinks: Interlinks

, please refere to Web book, PDF, LaTeX, of use Org-mode capable viewer/editor.

Note about the markup: <<<This is a radio target>>> - is the ancor for dynamic linking.

Users of Emacs can prettify radio targets to be shown as hyper-links with this Elisp snippet:

;;;;  2019-06-12: NOTE:
;;;;  Prettify '<<<Radio targets>>>' to be shown as '_Radio_targets_',
;;;;  when `org-descriptive-links` set.
;;;;  This is improvement of the code from: Tobias&glmorous:
;;;;  There exists library created from the sample:
(defcustom org-hidden-links-additional-re "\\(<<<\\)[[:print:]]+?\\(>>>\\)"
  "Regular expression that matches strings where the invisible-property
    of thesub-matches 1 and 2 is set to org-link."
  :type '(choice (const :tag "Off" nil) regexp)
  :group 'org-link)
(make-variable-buffer-local 'org-hidden-links-additional-re)

(defun org-activate-hidden-links-additional (limit)
  "Put invisible-property org-link on strings matching
  (if org-hidden-links-additional-re
      (re-search-forward org-hidden-links-additional-re limit t)
    (goto-char limit)

(defun org-hidden-links-hook-function ()
  "Add rule for `org-activate-hidden-links-additional'
    to `org-font-lock-extra-keywords'.
    You can include this function in `org-font-lock-set-keywords-hook'."
  (add-to-list 'org-font-lock-extra-keywords
                  (1 '(face org-target invisible org-link))
                  (2 '(face org-target invisible org-link)))))

(add-hook 'org-font-lock-set-keywords-hook #'org-hidden-links-hook-function)

SCHT: and metadata in :properties: - of my org-drill practices, please just run org-drill-strip-all-data.

2 Definitions

2.1 Algebra

\arabicfont{الجبر} al-jabr assemble parts

A system of parts based on given axioms (properties) and operations on them.


Additional meanings:

  1. Algebra - a set with its algebraic structure.
  2. Abstract algebra - the study of number systems and operations within them.
  3. Algebra - vector space over a field with a multiplication.

2.1.1 *

2.1.2 Algebraic

Composite from simple parts.

Also: Algebraic data type.

2.1.3 Algebraic structure

* includes axioms that must be satisfied and operations on the underlying (or "carrier") set.

An underlying set with * on top of it also called "an algebra".

* include groups, rings, fields, and lattices. More complex structures can be defined by introducing multiple operations, different underlying sets, or by altering the defining axioms. Examples of more complex * can be many modules, algebras and other vector spaces, and any variations that the definition includes.

Table 1: Algebraic structures
  Closure Associativity Identity Invertability Commutativity Distributive
Small Category        
Inverse Semigroup      
Abelian group  
Non-unital ring (rng) ✓ + × ✓ + × ✓ + ✓ + ✓ +
Semiring (rig) ✓ + × ✓ + × ✓ + × ✓ × ✓ +
Ring ✓ + × ✓ + × ✓ + × ✓ + × ✓ + Fundamental theorem of algebra

Any non-constant single-variable polynomial with complex coefficients has at least one complex root.

From this definition follows property that the field of complex numbers is algebraically closed. Magma

Set with a binary operation which form a closure. Semigroup

Magma with associative property of operation.

Defined in Haskell as:

class Semigroup a where
(<>) :: a -> a -> a * Monoid

Semigroup with identity element.

Ideal ground for any accumulation class.

class Semigroup m => Monoid m where
mempty :: m
mconcat :: [m] -> m
mconcat = foldr mappend mempty

More generally in category theory terms:

* - the object \( M \) equipped with two arrows:

\( \mu: \ M \ \otimes \ M \ \to M \) called multiplication or product, or tenzor product. \( \eta: \ I \ \to \ M \) called unit,

so \((M, \ \mu, \ \eta )\). By its definition category (lets call it \( \mathb{C} \) should have \( \otimes \) and \( I \). Where \( \otimes: \ \mathb{C} \ \times \ \mathb{C} \ \to \ \mathb{C} \) is any operation that combines objects and stays (closed) inside category, so it may be even already category given operation of arrow composition. And \( I \) is an identity object of \( \otimes \) operation.

Category that has one object - always a free monoid (from definition of "Category" - composition, and there is only one object so it is always also the identity object).

For example to represent the whole non-negative integers with the one object and morphism "\( 1 \)" is absolutely enough, composition operation is "\( + \)".

import Data.Monoid
  show (mempty :: Num a => Sum a)
  -- "Sum {getSum = 0}"
  show $ Sum 1
  -- "Sum {getSum = 1}"
  show $ (Sum 1) <> (Sum 1) <> (Sum 1)
  -- "Sum {getSum = 3}"
  -- ...

And backwards connection. Any monoidal category can be isomorphically transformed into one-object bicategory, thou explaining or proving it is out of the current scope.

Any monad is equivalent up to isomorphism to monoid. * Monoid properties Monoid left identity property
mempty <> x = x Monoid right identity property
x <> mempty = x Monoid associativity property
x <> mempty = x (y <> z) = (x <> y) <> z
mconcat = foldr (mempty <>)

Everything associative can be mappend. Commutative monoid

Operation that forms structure has commutativity property: \( x \circ y = y \circ x \)

Opens a big abilities in concurrent and distributed processing. * Group

Monoid that has inverse for every element. * Commutative group

Commutative monoid that is a group. * Ring

Commutative group under + & monoid under ×, + × connected by distributive property.

  • and × are generalized binary operations of addition and multiplication. × has no requirement for commutativity.

Example: set of same size square matricies of numbers with matrix operations form a ring. *

2.1.4 Modular arithmetic

System for integers where numbers wrap around the certain values (single - modulus, plural - moduli).

Example - 12-hour clock. * Modulus

Special numbers where arithmetic wraps around in modular arithmetic. *

Moduli - plural.

2.2 Category theory

Category \( \mathcal{C} \) consists of the basis:


  1. Objects - \( a^{\mathcal{C}} \). A node. Object of some type. Often sets, than it is Set category.
  2. Arrows - \( {(a,b)}^{\mathcal{C}} \) (AKA morphisms mappings).
  3. Arrow (morphism) composition - binary operation: \( {(a, b)}^{\mathcal{C}} \circ {(b, c)}^{\mathcal{C}} \equiv {(a, c)}^{\mathcal{C}} \ | \ \forall a, b, c \in \mathcal{C} \) AKA principle of compositionality for arrows.

Properties (or axioms):

  1. Associativity of morphisms: \( {h} \circ ({g} \circ {f}) \equiv ({h} \circ {g}) \circ {f} \ \ | \ \ {f}_{a \to b}, {g}_{b \to c}, {h}_{c \to d} \)
  2. Every object has (two-sided) identity morphism (& in fact - exactly one): \( {1}_x \circ {f}_{a \to x} \equiv {f}_{a \to x}, \ \ {g}_{x \to b} \circ {1_x} \equiv {g}_{x \to b } \ \ | \ \ \forall x \ \exists {1}_{x}, \forall {f}_{a \to x}, \forall {g}_{x \to b} \)
  3. Principle of compositionality.

From these axioms, can be proven that there is exactly one identity morphism for every object.

Object and morphism are complete abstractions for anything. In majority of cases under object is a state and morphism is a change.

2.2.2 Abelian category

Generalised category for homological algebra (having a possibility of basic constructions and techniques for it).

Category which:

Abelian category is a stable structure; for example it is regular and satisfy the snake lemma. The class of Abelian categories is closed under several categorical constructions.

There is notion of Abelian monoid (AKS Commutative monoid) and Abelian group (Commutative group).

Basic examples of *:

* are widely used in algebra, algebraic geometry, and topology.

* has many constructions like in categories of modules:

* has disadvantage over category of modules. Objects do not necessarily have elements that can be manipulated directly, so traditional definitions do not work. Methods must be supplied that allow definition and manipulation of objects without the use of elements. *

2.2.3 Composition

Axiom of Category.

2.2.4 Endofunctor category

From the name, in this Category:

2.2.5 Functor

* full translation (map) of one category into another. Translating objects and morphisms (so as an input can take morphism or object of the source category).

"Full translation" means every part gets represented in some shape or form, but at all does not means ideal translation. For example, all categories can be translated into (mapped onto) a single object monoidal category. * - forgetful - discards part of the structure. * - faithful - gives unique isomorphic (bijective) preservation of all source morphisms (injective on Hom-sets). * - full - translation of morphisms fully covers all the morphisms between according objecs in the target categoty (functor analog of epimorphism).

For Haskell Functor type class or fmap - see Power set functor.

Definition (axiomatic properties): Functor:

  • \( \forall a^{\mathcal{C}} \ : \ \exists! F^{\mathcal{C \to D}}(a) \) - every source object is mapped to some object in the target category.
  • \( \forall \overrightarrow{(a, b)}^{\mathcal{C}} \ : \ \exists! \overrightarrow{(F^{\mathcal{C \to D}}(a),F^{\mathcal{C \to D}}(b))}^{\mathcal{D} }\) - every source morphism is mapped inside target to some morphism between corresponding objects.

From those two tautologically goes:

  • \( \forall {x^{\mathcal{C}}}, y=\overrightarrow{f}^{\mathcal{C}}(x), \forall \overrightarrow{g}^{\mathcal{C}}(y) \ : \ F^{\mathcal{C \to D}}(\overrightarrow{g}^{\mathcal{C}} \circ \overrightarrow{f}^{\mathcal{C}}) = F^{\mathcal{C \to D}}(\overrightarrow{g}^{\mathcal{C}}) \circ F^{\mathcal{C \to D}}(\overrightarrow{f}^{\mathcal{C}})\) - every composition in \( \mathcal{C} \) translates as a composition of according morphisms in \( \mathcal{D} \), in other words - composition translates directly.

So, the composition of functors equal to one functor with composition of all morphisms. This process called functor fusion.

In Haskell Hask functor axioms have a form:

fmap f id = id f :: (f -> f) -- All objects (f) in Hask can be mapped to Hask.
fmap id id :: (a -> a)  -- fmap can map objects. This is constructed identity endofunctor on Hask.
fmap id :: (f a -> f a)  -- fmap can map objects, algebraic also (which includes funcitons (morphisms))
(\ x -> fmap x id) :: (a -> b) -> (a -> b)
(flip fmap id) :: (a -> b) -> (a -> b) -- & functions (morphisms) just as well, polymorphism means functions are also simple type objects, and in Haskell functions are first class
-- This is enough to prove fmap is a functor, composition property derives from this two

In Haskell type functor axioms have a form:

fmap id = id
fmap (f . g) = fmap f . fmap g
-- OR free-forming functor laws more expicitly:
(fmap id) a = id a -- Remaps all source objects (a) to object, in identity case maps all a to a
(fmap f) a = (f a) -- Remaps all source objects using a specialized functor by declaring a the funciton that does remapping of objects
(fmap hof@((a -> b) -> c)) fun@(a -> b) = (hof fun) = (a -> b) -> c -- Because of polymorphicity - in Haskell morphisms are also can be objects for Hask category - `fmap` instantiated functor translates not only objects, but all morphisms to morphisms as well.
(fmap (a -> b)) anything = ((a -> b) anything) -- On Hask subcategory (f x), this is an endofunctor: f a -> f b. 
(fmap f) . (fmap g) = (fmap $ f . g) -- Composition law

Since * is 1-1 mapping of initial objects - it is a memoizable dictionary with cardinality of initial objects. Also in Hask category functors are obviously endofunctors ∴ they are special kinds of containers for the parametric values (AKA product type). In Haskell product type * are endofunctors from polymorphic type into a functor wrapper of a polymorphic type.

* translates in one direction, and does not provide algorythm of reversing itself or retriving the parametric value. *

Functors Functorial - something that has functor properties, and so also is a functor. Power set functor

\( \mathcal{P^{S \to P(S)}} \)

* - functor from set \( S \) to its power set \( \mathcal{P}(S) \).

In Haskell terms - a power set functor additionally accepts function parametrisation.

Functor type class in Haskell defines a * as fmap in a form of bifunctor. It allows to do function application inside type structure layers (denoted \( f \) or \( m \)). IO is also such structure. Power set is unique to the set, * is unique to the data type (to the category also). Any endofunctor embodies into *. It is easily seen from Haskell definition - that the * is the polymorphic generalization over any endofunctor in a category.

Application of a function to * gives a particular endofunctor (see Hask category).

class Functor f where
  fmap :: (a -> b) -> f a -> f b

Functor instance must be of kind ( * -> * ), so instance for higher-kinded data type must be applied until this kind.

Composed * can lift functions through any layers of structures that belong to Functor type class.

* can be used to filter-out the structure through strucure composition, for example - composition with error cases (Nothing & Left cases) in Maybe, Either and related types. * Power set functor properties

Type instance of functor should abide this properties: * Power set functor identity property

Functor translates object & its identity morphism to target object & its identity morphism.

fmap id == id Power set functor composition property

Full transparency of composition translation. So order of composition and translation does not metter, the result is always the same.

fmap (f . g) == fmap f . fmap g

Including cases: a) translate everything one-by-one and assemble at destination category. b) assemble everything in source cetegory and translate in one go once.

Composing in source category and translating at once - is a much-much more effective computation (known as "functor fusion"). Lift
fmap :: (a -> b) -> (f a -> f b)

Functor takes function a -> b and returns a function f a -> f b this is called lifting a function. Lift does a function application through the data structure. * Power set functor is a free monad


  • \( \forall e \in S : \ \exists \{e\} \, \in \, {\mathcal{P}(S)} \ \vDash \ \ \forall e \in S : \ \exists (e \to \{e\}) \equiv unit \)
  • \( \forall \mathcal{P}(S) : \ \mathcal{P}(S) \in \mathcal{P}(S) \ \vDash \ \ \forall \mathcal{P}(S) : \ \exists (\mathcal{P}(\mathcal{P}(S)) \to \mathcal{P}(S)) \equiv join \) Forgetful functor

Functor that forgets part or all of what defines structure in domain category. \( F^{\mathbf {Grp} \to \mathbf {Set}} \) that translates groups into their underlying sets. Constant functor is another example. * Identity functor

Maps all category to itself. All objects and morphisms to themselves.

Denotation: \( 1^{\mathcal{C \to C}} \) Endofunctor

Is a functor which source (domain) and target (codomain) are the same category.

\( F^{\mathcal{C \to C}}, E^{\mathcal{C \to C}} \) * Applicative functor

* - Computer science term. Category theory name - lax monoidal functor. And in category \( Set \), and so in category \( Hask \) all applicatives and monads are strong (have tensorial strength).

* - sequences functorial computations (plain functors can't).

(<*>) :: f (a -> b) -> f a -> f b

Requires Functor to exist. Requires Monoidal structure.

Has monoidal structure rules, separated form function application inside structure.

Data type can have several applicative implementations.

Standard definition:

class Functor f => Applicative f
  (<*>) :: f (a -> b) -> f a -> f b
  pure :: a -> f a

pure - if a functor, identity Kleisli arrow, natural transformation.

Composition of * always produces *, contrary to monad (monads are not closed under composition).

Control.Monad has an old function ap that is old implementation of <*>:

ap :: Monad m => m (a -> b) -> m a -> m b * Applicative identity property
pure id <*> v = v Applicative composition property

Function composition works regularly.

pure (.) <*> u <*> v <*> w = u <*> (v <*> w) Applicative homomorphism property

Internal function application doesn't change the structure around values.

pure f <*> pure x = pure (f x) Applicative interchange property

On condition that internal order of evaluation is preserved - order of operands is not relevant.

u <*> pure y = pure ($ y) <*> u Applicative function liftA* liftA

Essentially a fmap.

:type liftA
liftA :: Applicative f => (a -> b) -> f a -> f b

Lifts function into applicative function. liftA2

Lifts binary function across two Applicative functors.

liftA2 :: Applicative f => (a -> b -> c) -> f a -> f b -> f c
liftA2 f x y == pure f <*> x <*> y <<<liftA2 (<*>)>>>

liftA2 (<*>) is an applicative that lifts a binary operation over the two layers (2x2). Pretty useful to remember it.

liftA2 :: (  a        ->  b  ->  c ) -> f     a         ->  f    b   ->  f   c
<*> ::    (f (a -> b) -> f a -> f b)
liftA2 (<*>) ::                        f1 (f2 (a -> b)) -> f1 (f2 a) -> f1 (f2 b) liftA2 (liftA2 (<*>))

liftA2 (<*>) 3-layer version. liftA3

liftA2 3-parameter version.

liftA3 f x y z == pure f <*> x <*> y <*> z Conditional applicative computations
when :: Applicative f => Bool -> f () -> f ()

Only when True - perform an applicative computation.

unless :: Applicative f => Bool -> f () -> f ()

Only when False - perform an applicative computation. Special applicatives Identity applicative
-- Applicative f =>
-- f ~ Identity
type Id = Identity
instance Applicative Id
    pure :: a -> Id a
    (<*>) :: Id (a -> b) -> Id a -> Id b

mkId = Identity
xs = [1, 2, 3]

const <$> mkId xs <*> mkId xs'
-- [1,2,3] Constant applicative

It holds only to one value. The function does not exist and last parameter is a phantom.

-- Applicative f =>
-- f ~ Constant e
type C = Constant
instance Applicative C
  pure :: a -> C e a
  (<*>) :: C e (a -> b) -> C e a -> C e b Maybe applicative

"There also can be no function at all."

If function might not exist - embed f in Maybe structure, and use Maybe applicative.

-- f ~ Maybe
type M = Maybe
pure :: a -> M a
(<*>) :: M (a -> b) -> M a -> M b Either applicative

pure is Right. Defaults to Left. And if there is two Left's - to Left of the first argument. Validation applicative

The Validation data type isomorphic to Either, but has accumulative Applicative on the Left side. Validation data type does not have a monad implemented. For Either monad monad has simple implementation: Left case drops computation and returns Left value. Monad needs to process the result of computation - for Validation - it requires to be able to process all Left error statement cases for Validation, it is or non-terminaring Monad or one which is impossible to implement in polymorphic way with Validation. Monad

\textgreek{μόνος} monos sole

\textgreek{μονάδα} monáda unit

In loose terms, * - is an ability built over structures that allows to compose functions that produce that structures.

Since it is possible to express unpure functions with equivalent pure functions that produce a structure, * become widely used in Haskell for those cases also. * with lazy evaluation also allows controll over the continuation of calculations by early terminations.

* - lax monoid in endofunctor category, that relies on \( \eta \) (unit) and \( \mu \) (join) natural transformations to form an equivalent of identity.

Monad on \( \mathcal{C} \) is \( \{E^{\mathcal{C \to C}}, \, \eta, \, \mu\} \):

  • \( E^{\mathcal{C \to C}} \) - is an endofunctor
  • two natural transformations, \( 1^c \to E \) and \( E \circ E \to E \):
    • \( \eta^{1^{\mathcal{C}} \to E} = {unit}^{Identity \to E}(x) = f^{ x \to E(x)}(x) \)
    • \( \mu^{(E \circ E) \to E} = {join}^{(E \circ E) \to (Identity \circ E)}(x) = | y = E(x) | = f^{E (y) \to y}(y) \)


Definition with \( \{E^{\mathcal{C \to C}}, \, \eta, \, \mu\} \) (in Hask: (\( \{e \, :: \, f \, a \, \to \, f \, b, \ pure, \ join\} \))) - is classic categorical, in Haskell minimal complete definition is \( \{fmap, \, pure, \, (>>=)\} \).

While \( T \) is mode classical Category theory notation, we used the \( E \equiv T \) substitution for purposes of notation being more understandable.

If there is a structure \( S \), and a way of taking object \( x \) into \( S \) and a way of collapsing \( S \circ S \) - there probably a monad.

Monad structure:

\begin{tikzcd} & & {} \arrow[d, "\eta", Rightarrow] & & \\ C \arrow[rrrr, "Id", bend left=49] \arrow[rrrr, "E"] \arrow[rrrr, "E^{2}", bend right=49] & & {} & & C \\ & & {} \arrow[u, "\mu", Rightarrow] \end{tikzcd}

Mostly monads used for sequencing actions (computations) (that looks like imperative programming), with ability to dependend on previous chains. Note if monad is commutative - it does not order actions.

Monad can shorten/terminate sequence of computations. It is implemented inside Monad instance. For example Maybe monad on Nothing drops chain of computation and returns Nothing.

* inherits the Applicative instance methods:

import Control.Monad (ap)
return == pure
ap == (<*>) -- + Monad requirement
Table 2: Monad in mathematics and Haskell
Math Meaning Cat/Fctr \( X \in C \) Type Haskell
\( Id \) endofunctor "Id" \( C \to C \) \( X \to Id (X) \) \( a \to a \) id
\( E \) endofunctor "monad" \( C \to C \) \( X \to E (X) \) \( m \ a \to m \ b \) fmap
\( \eta \) natural transformation "unit" \( Id \to E \) \( Id (X) \to E (X) \) \( a \to m \ a \) pure
\( \mu \) natural transformation "multiplication" \( E \circ E \to E \) \( E (E(X)) \to E (X) \) \( m \ (m \ a) \to m \ a \) join

Internals of Monad are Haskell data types, and as such - they can be consumed any number of times.

Composition of monadic types does not always results in monadic type. * Monad property

Monad corresponds to functor properties & applicative properties and additionally: * Monad left identity property
pure x >>= f == f x


>>= :: Monad f =>    f a  -> (a -> f b) -> f b
                  pure x >>=     f      == f x

Rule that >>= must get first argument structure internals and apply to the function that is the second argument.

Diagram on category level:

\begin{tikzcd} & & {} \arrow[dd, "\eta", Rightarrow] & & & & {} \arrow[dd, "I", Rightarrow] & & \\ C \arrow[rrrr, "Id", bend left=49] \arrow[rrrr, "T", bend right=49] \arrow[rrrrrrrr, "T", bend right=75] & & & & C \arrow[rrrr, "T", bend left=49] \arrow[rrrr, "T", bend right=49] & & & & C \\ & & {} & & {} \arrow[dd, "\mu", Rightarrow] & & {} & & \\ & & & & & & & & \\ & & & & {} \end{tikzcd}

Diagram on endomorphism level:

\begin{tikzcd} Id \circ T \arrow[rr, "\eta \circ I"] \arrow[rrdd, no head, Rightarrow] & & T^{2} \arrow[dd, "\mu"] \\ & & \\ & & T \end{tikzcd} Monad right identity property
f >>= pure == f


>>= :: Monad f => f a  -> (a -> f b) -> f b
                  f   >>=    pure    == f

AKA it is a tacit description of a monad bind as endofunctor.

Diagram on category level:

\begin{tikzcd} & & {} \arrow[dd, "I", Rightarrow] & & & & {} \arrow[dd, "\eta", Rightarrow] & & \\ C \arrow[rrrr, "T", bend left=49] \arrow[rrrr, "T", bend right=49] \arrow[rrrrrrrr, "T", bend right=75] & & & & C \arrow[rrrr, "Id", bend left=49] \arrow[rrrr, "T", bend right=49] & & & & C \\ & & {} & & {} \arrow[dd, "\mu", Rightarrow] & & {} & & \\ & & & & & & & & \\ & & & & {} \end{tikzcd}

Diagram on endomorphism level:

\begin{tikzcd} T^{2} \arrow[dd, "\mu"] & & T \circ Id \arrow[ll, "I \circ \eta"] \arrow[lldd, no head, Rightarrow] \\ & & \\ T \end{tikzcd} Monad associativity property
join (join (m m) m) == join (m join (m m))
(m >>= f) >>= g == m >>= (\ x -> f x >>= g)

In diagram form:

Category level:

\begin{tikzcd} & & {} \arrow[dd, "I", Rightarrow] & & & & {} \arrow[dd, "\mu", Rightarrow] & & \\ C \arrow[rrrr, "T", bend left=49] \arrow[rrrr, "T", bend right=49] \arrow[rrrrrrrr, "T", bend right=75] & & & & C \arrow[rrrr, "T^{2}", bend left=49] \arrow[rrrr, "T", bend right=49] & & & & C \\ & & {} & & {} \arrow[dd, "\mu", Rightarrow] & & {} & & \\ & & & & & & & & \\ & & & & {} \end{tikzcd}

is \( = \) to:

\begin{tikzcd} & & {} \arrow[dd, "\mu", Rightarrow] & & & & {} \arrow[dd, "I", Rightarrow] & & \\ C \arrow[rrrr, "T^{2}", bend left=49] \arrow[rrrr, "T", bend right=49] \arrow[rrrrrrrr, "T", bend right=75] & & & & C \arrow[rrrr, "T", bend left=49] \arrow[rrrr, "T", bend right=49] & & & & C \\ & & {} & & {} \arrow[dd, "\mu", Rightarrow] & & {} & & \\ & & & & & & & & \\ & & & & {} \end{tikzcd}

So, \( \mu \circ (\mu \circ I) = \mu \circ (I \circ \mu) \)

Endomorphism level:

\begin{tikzcd} & & T^{3} \arrow[dd, "\mu \circ I", bend right=49] \arrow[dd, "I \circ \mu", bend left=49] & & \\ & & & & \\ & & T^{2} \arrow[dd, "\mu"] & & \\ & & & & \\ & & T \end{tikzcd} Monad type class
class Applicative m => Monad m where
  (>>=) :: m a -> (a -> m b) -> m b
  (>>) :: m a -> m b -> m b
  return :: a -> m a MonadPlus type class

Is a monoid over monad, with additional rules. The precise set of rules (properties) not agreed upon. Class instances obey monoid & left zero rules, some additionally obey left catch and others left distribution.

Overall there * currently reforms (MonadPlus reform proposal) in several smaller nad strictly defined type classes.

Subclass of an Alternative. * Functor -> Applicative -> Monad progression
<$> :: Functor     f =>   (a -> b)   -> f a -> f b
<*> :: Applicative f => f (a -> b)   -> f a -> f b
=<< :: Monad       f =>   (a -> f b) -> f a -> f b

pure & join are Natural transformations for the fmap. Monad function Return function
return == pure

Nonstrict. Join function
join :: Monad m => m (m a) -> m a

Generales knowledge of concat.

Kleisli composition that flattens two layers of structure into one.

The way to express ordering in lambda calculus is to nest. * join . fmap == (=<<)
-- b = f b
fmap        :: Monad f => (a -> f b) -> f a -> f (f b)
join        :: Monad f =>                      f (f a) -> f a
join . fmap :: Monad f => (a -> f b) -> f a            -> f b
flip    >>= :: Monad f => (a -> f b) -> f a            -> f b Bind function
>>=         :: Monad f => f a -> (a -> f b) -> f b
join . fmap :: Monad f => (a -> f b) -> f a -> f b


The most ubiqutous way to >>= something is to use Lambda function:

getLine >>= \name -> putStrLn "age pls:"

Also a neet way is to bundle and handle Monad - is to bundle it with bind, and leave applied partially. And use that partial bundle as a function - every evaluation of the function would trigger evaluation of internal Monad structure. Thumbs up.

printOneOf :: Bool -> IO ()
printOneOf False = putStr "1"
printOneOf  True = putStr "2"

quant :: (Bool -> IO b) -> IO b
quant = (>>=) (randomRIO (False, True))

recursePrintOneOf :: Monad m => (t -> m a) -> t -> m b
recursePrintOneOf f x = (f x) >> (recursePrintOneOf f x)

main :: IO ()
main = recursePrintOneOf (quant) $ printOneOf * Sequencing operator (>> ) \equiv ( *>):

Sequencing operator, analog to the semicolon (or newline) in imperative languages. Discard value result of the action, sequentially add next (compose with) next action. Applicative has a similar operator.

(>>) :: m a -> m b -> m b
(*>) :: f a -> f b -> f b Monadic versions of list functions
sequence :: (Traversable t, Monad m) => t (m a) -> m (t a)

Sequence gets the traversable of monadic computations and swaps it into monad computation of taverse. In the result the collection of monadic computations turns into one long monadic computation on traverse of data.

If some step of this long computation fails - monad fails.

mapM :: (Traversable t, Monad m) => (a -> m b) -> t a -> m (t b)

mapM gets the AMB function, then takes traversable data. Then applies AMB function to traversable data, and returns converted monadic traversable data.

foldM :: (Foldable t, Monad m) => (b -> a -> m b) -> b -> t a -> m b
foldl ::  Foldable t           => (b -> a ->   b) -> b -> t a ->   b

* is a monadic foldl.

b is initial comulative value, m b is a comulative bank. Right folding achieved by reversing the input list.

filterM :: Applicative m => (a -> m Bool) -> [a] -> m [a]
filter ::                   (a ->   Bool) -> [a] ->   [a]

Take Boolean monadic computation, filter the list by it.

zipWithM :: Applicative m => (a -> b -> m c) -> [a] -> [b] -> m [c]
zipWith  ::                  (a -> b ->   c) -> [a] -> [b] ->   [c]

Take monadic combine function and combine two lists with it.

msum :: (Foldable t, MonadPlus m) => t (m a) -> m a
sum  :: (Foldable t, Num a)       => t    a  ->   a liftM* liftM

Essentially a fmap.

liftM :: Monad m => (a -> b) -> m a -> m b

Lifts a function into monadic equivalent. liftM2

Monadic liftA2.

liftM2 :: Monad m => (a -> b -> c) -> m a -> m a -> m c

Lifts binary function into monadic equivalent. Comonad

Category \( \mathcal{C} \) comonad is a monad of opposite category \( \mathcal{C}^{op} \). Kleisli arrow

Morphism that while doing computation also adds monadic-able structure.

a -> m b Kleisli composition

Composition of Kleisli arrows.

(<=<) :: Monad m => (b -> m c) -> (a -> m b) -> a -> m c infixr 1
;; compare
(.)   ::            (b ->  c ) -> (a ->  b ) -> a ->  c

Often used left-to-right version:

(>=>) :: Monad m => (a -> m b) -> (b -> m c) -> a -> m c
;; compare
(>>=) :: Monad m =>       m a  -> (a -> m b)      -> m b

Which allows to replace monadic bind chain with Kleisli composition.

f1 arg >>= f2 >>= f3
f1 >=> f2 >=> f3 $ arg
f3 <=< f2 <=< f1 $ arg Kleisli category

Category \( \mathcal{C} \), \( 〈E, \overrightarrow{\eta}, \overrightarrow{\mu}〉 \) monad over \( \mathcal{C} \).

Kleisli category \( \mathcal{C}_{T} \) of \( \mathcal{C} \):

\( \mathrm{Obj}(\mathcal{C}_{T}) \ = \ \mathrm{Obj}(\mathcal{C}) \) \( \mathrm{Hom}_{\mathcal{C}_{T}}(x,y) \ = \ \mathrm{Hom}_{\mathcal{C}}(x,E(y)) \) Special monad Identity monad

Wraps data in the Identity constructor.

Useful: Creates monads from monad transformers.

Bind: Applies internal value to the bound function.

Code: (see: coerce)

newtype Identity a = Identity { runIdentity :: a }

instance Functor Identity where
  fmap     = coerce

instance Applicative Identity where
  pure     = Identity
  (<*>)    = coerce

instance Monad Identity where
  m >>= k  = k (runIdentity m)


-- derive the State monad using the StateT monad transformer
type State s a = StateT s Identity a Maybe monad

Something that may not be or not return a result. Any lookups into the real world, database querries.

Bind: Nothing input gives Nothing output, Just x input uses x as input to the bound function.

When some computation results in Nothing - drops the chain of computations and returns Nothing.

Zero: Nothing Plus: result in first occurence of Just else Nothing.


data Maybe a = Nothing | Just a

instance Monad Maybe where
  return         = Just
  fail           = Nothing
  Nothing  >>= _ = Nothing
  (Just x) >>= f = f x

instance MonadPlus Maybe where
  mzero             = Nothing
  Nothing `mplus` x = x
  x `mplus` _       = x

Example: Given 3 dictionaries:

  1. Full names to email addresses,
  2. Nicknames to email addresses,
  3. Email addresses to email preferences.

Create a function that finds a person's email preferences based on either a full name or a nickname.

data MailPref = HTML | Plain
data MailSystem = ...

getMailPrefs :: MailSystem -> String -> Maybe MailPref
getMailPrefs sys name =
  do let nameDB = fullNameDB sys
         nickDB = nickNameDB sys
         prefDB = prefsDB sys
  addr <- (lookup name nameDB) `mplus` (lookup name nickDB)
  lookup addr prefDB Either monad

When computation results in Left - drops other computations & returns the recieved Left. Error monad

Someting that can fail, throw exceptions.

The failure process records the description of a failure. Bind function uses successful values as input to the bound function, and passes failure information on without executing the bound function.

Useful: Composing functions that can fail. Handle exceptions, crate error handling structure.

Zero: empty error. Plus: if first argument failed then execute second argument. List monad

Computations which may return 0 or more possible results.

Bind: The bound function is applied to all possible values in the input list and the resulting lists are concatenated into list of all possible results.

Useful: Building computations from sequences of non-deterministic operations.

Zero: [] Plus: (++) * Reader monad

Creates a read-only shared environment for computations.

The pure function ignores the environment, while >>= passes the inherited environment to both subcomputations.

Today it is defined though ReaderT transformer:

type Reader r = ReaderT r Identity   -- equivalent to ((->) e), (e ->)

Old definition was:

newtype Reader e a = Reader { runReader :: (e -> a) }

For (e ->):

fmap :: (b -> c) -> (a -> b) -> a -> c
fmap = (.)
pure :: a -> b -> a
pure x _ = x
  • (<*>) is:
(<*>) :: (a -> b -> c) -> (a -> b) -> a -> c
(<*>) f g = \a -> f a (g a)
(>>=) :: (a -> b) -> (b -> a -> c) -> a -> c
(>>=) m k = Reader $ \r ->
  runReader (k (runReader m r)) r

join :: (e -> e -> a) -> e -> a
join f x = f x x
  :: Reader r a  -- the Reader to run
  -> r  -- an initial environment
  -> a  -- extracted final value


data Env = ...

createEnv :: IO Env
createEnv = ...

f :: Reader Env a
f = do
  a <- g
  pure a

g :: Reader Env a
g = do
  env <- ask  -- "Open the environment namespace into env"
  a <- h env  -- give env to h
  pure a

h :: Env -> a
...  -- use env and produce the result

main :: IO ()
main = do
  env <- createEnv
  a = runReader g env

In Haskell under normal circumstances impure functions should not directy call impure functions. h is an impure function, and createEnv is impure function, so they should have intermediary. Writer monad

Computations which accumulate monoid data to a shared Haskell storage. So * is parametrized by monoidal type.

Accumulator is maintained separately from the returned values.

Shared value modified through Writer monad methods.

* frees creator and code from manually keeping the track of accumulation.

Bind: The bound function is applied to the input value, bound function allowed to <> to the accumulator.

type Writer r = WriterT r Identity


f :: Monoid b => a -> (a, b)
f a = if _condition_
         then runWriter $ g a
         else runWriter do
           a1 <- h a
           pure a1

g :: Monoid b => Writer b a
g a = do
  tell _value1_  -- accumulator <> _value1_
  pure a  -- observe that accumulator stored inside monad
          -- and only a main value needs to be returned.

h :: Monoid b => Writer b a
h a = do
  tell _value2_  -- accumulator <> _value_
  pure a
runWriter :: Writer w a -> (a, w)  -- Unwrap a writer computation
                                   -- as a (result, accumulator) pair.
                                   -- The inverse of writer.

WriterT, Writer unnecessarily keeps the entire logs in the memory. Use fast-logger for logging. State monad

Computations that pass-over a state.

The bound function is applied to the input value to produce a state transition function which is applied to the input state.

Pure functional language cannot update values in place because it violates referential transparency.

type State s = StateT s Identity

Binding copies and transforms the state parameter through the sequence of the bound functions so that the same state storage is never used twice. Overall this gives the illusion of in-place update to the programmer and in the code, while in fact the autogenerated transition functions handle the state changes.

Example type: State st a

State describes functions that consume a state and produce a tuple of result and an updated state.

Monad manages the state with the next process:

Sorry, your browser does not support SVG.


  • f - processsor making function
  • pA, pAB, pB - state processors
  • sN - states
  • vN - values

Bind with a processor making function from state procesor (pA) creates a new state processor (pAB). The wrapping and unwrapping by State/runState is implicit. Monad transformer

* is a practical solution to the current functional programming situation that generally monads do not have composition ability. In other words many monads can not be composed.

* is a special monad that extends other monad with extra funcitonality, it is a convinience mechanism, the functionality itself always can be developed in some other way. Sometimes transformers can make things way harder (especially profound for concurrency (Michael Snoyman - Monad Transformer State)) then other ways of implementation, especially when transformers hold some structure information (state-like information, in ExceptT, StateT)

Monad is not closed under compostion. Composition of monadic types does not always results in monadic type.

Basic case: during implementation of monadic composition, as a result type m T m a arises, which does not allow join transformation for the m monadic layers or to have a regular unit transformation.

Monads that are * are the monads that have own properties as also ability to compose with any other monadand extend it with own properties. * use their implementation to solve the compostion type layering and allow to attach desirable property to result.

* solve monad composition and type layering by using own structure and information about itself. It is often that process involves a catamorphism of a * type layer.

Transformers have a light wrapper around the data that tags the modification with this transformer.

In type signatures of transformers *T m - m is already an extended monad, so *T is just a wrapper to point that out.

Main monadic structure m is wrapped around the internal data (core is a). The structure that corresponds to the transformer creation properties (if it emitted by \( \eta \) of a transformer), goes into m . Open parameters go external to the m.

newtype ExceptT e m a =
  ExceptT { runExceptT :: m (Either e a) }

newtype MaybeT m a =
  MaybeT { runMaybeT :: m (Maybe a) }

newtype ReaderT r m a =
  ReaderT { runReaderT :: r -> m a }

This has an effect that on stacking monad transformers, m becomes monad stack, and every next transformer injects the transformer creation-specific properies \( \eta \) inside the stack, so out-most transformer has inner-most structure. Base monad is structurally the outermost. MaybeT

* extends monads by injecting Maybe layer underneath monad, and processing that structure:

newtype MaybeT m a = MaybeT { runMaybeT :: m (Maybe a) } EitherT

* extends monads by injecting Either layer underneath monad, and processing that structure:

newtype EitherT e m a = EitherT { runEitherT :: m (Either e a) }

EitherT of either package gets replaced by ExceptT of transformers or mtl packages. * ReaderT


newtype ReaderT r m a = ReaderT { runReaderT :: r -> m a }

* functions: input monad m a, out: m a wrapped it in a free-variable r (partially applied function). That allows to use transformed m a, now it requires and can use the r passed environment.

To create a Reader monad:

type Reader r = ReaderT r Identity MonadTrans type class

Allows to lift monadic actions into a larger context in a neutral way.

pure takes a parametric type and embodies it into constructed structure (talking of monad transformers - structure of the stacked monads).

lift takes monad and extends it with a transformer.

In fact, for monad transformers - lift is a last stage of the pure, it follows from the lift property.


lift :: Monad m => m a -> t m a

Lift a computation from the argument monad to the constructed monad.

Neutral means:

lift . return = return

lift (m >>= f) = lift m >>= (lift . f)

The general pattern with MonadTrans instances is that it is usually lifts the injection of the known structure of transformer over some Monad.

lift embeds one monadic action into monad transformer.

The difference between pure, lift and MaybeT contructor becomes clearer if you look at the types:

Example, for MaybeT IO a:

pure      ::      a  -> MaybeT IO a
lift   ::    IO a  -> MaybeT IO a
MaybeT :: IO (Maybe a) -> MaybeT IO a

x = (undefined :: IO a)

:t (pure x)
(pure x) :: Applicative t => t (IO a)  -- t recieves one argument of product type
:t (pure x :: MaybeT IO a)
-- Expected type: MaybeT IO a1
--   Actual type: MaybeT IO (IO a0)

-- While the real type would be
:t (pure x :: MaybeT IO (IO a))
(pure x :: MaybeT IO (IO a)) :: MaybeT IO (IO a)
-- This goes into a conflict of what type&kind (* -> *) transformer constructor
-- awaits, and `m (m a)` is a layering we not interested in.

:t (lift x)
(lift x) :: MonadTrans t => t IO a  -- result is a proper expected product type

-- To belabour
:t (lift x :: MaybeT IO a)
(lift x) :: MonadTrans t => t IO a  -- result is a proper expected product type

lift is a natural transformation \( \eta \) from an Identity monad (functor) with other monad as content into transformer monad (functor), with the preservation of the conteined monad:

-- Abstract monads with content as parameters. Define '~>' as a family of
-- morphisms that translate one functor into another (natural transformation)
type f ~> g = forall x. f x -> g x
-- follows
lift :: m ~> t m MonadIO type class

* - allows to lift IO action until reaching the IO monad layer at the top of the Monad stack (which is allways in the Haskell code that does IO).

class (Monad m) => MonadIO m where
  liftIO :: IO a -> m a

liftIO properties:

liftIO . pure = pure

liftIO (m >>= f) = liftIO m >>= (liftIO . f)

Which is identical properties to MonadTrans lift.

Since lift is one step, and liftIO all steps - all steps defined in terms of one step and all other steps, so the most frequent implementation is self-recursive lift . liftIO:

liftIO ioa = lift $ liftIO ioa * Alternative type class

Monoid over applicative. Has left catch property.

Allows to run simultaneously several instances of a computation (or computations) and from them yeld one result by property from (<|>) :: Type -> Type -> Type.

Minimal complete definition:

empty :: f a    -- The identity element of <|>
(<|>) :: f a -> f a -> f a    -- Associative binary operation

Additional functions some and many defined (automatically derived) as the least solutions to the equations:

some v = (:) <$> v <*> many v
many v = some v <|> pure []
-- => some v = (:) <$> v <*> $ some v <|> pure []
some :: f a -> f [a]    -- One or more. Keep trying applying f to a until it succeeds at least once, and then keep doing it until it fails.
more :: f a -> f [a]    -- Zero or more. Apply f to a as many times as you can until failure.

So there in the process should be found a definitive case of failure termination rule or otherwise process would never terminate.

To start understand intuitive difference:

> some Nothing
> many Nothing
Just []

Perhaps it helps to see how some would be written with monadic do syntax:

some f = do
  x <- f
  xs <- many f
  return (x:xs)

So some f runs f once, then "many" times, and conses the results. many f runs f "some" times, or "alternative'ly" just returns the empty list. The idea is that they both run f as often as possible until it "fails", and after that - compose the list of results. The difference is that some f fails if f fails immediately, while many f will succeed and "return" the empty list. But what this all means exactly depends on how <|> is defined.

Is it only useful for parsing? Let's see what it does for the instances in base: Maybe, [] and STM.

First Maybe. Nothing means failure, so some Nothing fails as well and evaluates to Nothing while many Nothing succeeds and evaluates to Just []. Both some (Just ()) and many (Just ()) never return, because Just () never fails! In a sense they evaluate to Just (repeat ()).

For lists, [] means failure, so some [] evaluates to [] (no answers) while many [] evaluates to [[]] (there's one answer and it is the empty list). Again some [()] and many [()] don't return. Expanding the instances, some [()] means fmap (():) (many [()]) and many [()] means some [()] ++ [[]], so you could say that many [()] is the same as tails (repeat ()).

For STM, failure means that the transaction has to be retried. So some retry will retry itself, while many retry will simply return the empty list. some f and many f will run f repeatedly until it retries. I'm not sure if this is useful thing, but I'm guessing it isn't.

So, for Maybe, [] and STM many and some don't seem to be that useful. It is only useful if the applicative has some kind of state that makes failure increasingly likely when running the same thing over and over. For parsers this is the input which is shrinking with every successful match. * $>

Get & set a value inside Functor. *

<$ Multifunctor

Functor that takes as an argument the product of types.

Or if combine it with product - accepts multiple argumets, so from that constructs "source" product category (Cartesian product) of categories, and realizes a functor from product category to target category.

Concept works over N type arguments instead of one.

Generalizes the concept of functor between categories, canonical morphisms between multicategories.

Any product or sum in a Cartesian category is a *.

In Haskell there is only one category, Hask, so in Haskell * is still endofunctor \( (Hask \times Hask) \rightarrow Hask \Rightarrow | (Hask \times Hask) \equiv Hask | \Rightarrow Hask \rightarrow Hask \).

Code definition:

class Bifunctor f
  bimap :: (a -> a') -> (b -> b') -> f a b -> f a' b'
  bimap f g = first f . second g
  first :: (a -> a') -> f a b -> f a' b
  first f = bimap f id
  second :: (b -> b') -> f a b -> f a b'
  second = bimap id *

2.2.6 Hask category

Category of Haskell where objects are types and morphisms are functions.

It is a hypothetical category at the moment, since undefined and bottom values break the theory, is not Cartesian closed, it does not have sums, products, or initial object, () is not a terminal object, monad identities fail for almost all instances of the Monad class.

That is why Haskell developers think in subset of Haskell where types do not have bottom values. This only includes functions that terminate, and typically only finite values. The corresponding category has the expected initial and terminal objects, sums and products, and instances of Functor and Monad really are endofunctors and monads.

Hask contains subcategories, like Lst containing only list types.

Haskell and Category concepts: *

2.2.7 Morphism

\textgreek{μορφή} morphe form

Arrow between two objects inside a category.

Morphism can be anything.

Morphism is a generalization (\( f(x*y) \equiv f(x) \diamond f(y) \)) of homomorphism (\( f(x*y) \equiv f(x) * f(y) \)).

Since general morphisms not so much often ment and discussed - under morphism people almost always really mean the meaning of homomorphism-like properties, hense they discuss the algebraic structures (types) and homomorphisms between them.

In most usage, on a level under the objects: * is most often means a map (relation) that translates from one mathematical structure (that source object represents) to another (that target object represents) (that is called (somewhat, somehow) "structure-preserving", but that phrase still means that translation can be lossy and irrevertable, so it is only bear reassemblence of preservation), and in the end the morphism can be anything and not hold to this conditions.

Morphism needs to correspond to function requirements to be it. * Homomorphism

\textgreek{ὁμός} homos same (was chosen becouse of initial Anglish mistranslation to "similar")

\textgreek{μορφή} morphe form

similar form

* map between two algebraic structures of the same type that preserves the operations.

\( f(x*y) \equiv f(x) * f(y) \), where for \( f^{A \to B} \) - \( A, B \) are sets with additonal algebraic structures (algebras) that include operation ∗; \( x,\ y \) are elements of the set \( B \).

* sends identity morphisms to identity morphisms and inverses to inverses.

The concept of * has been generalized under the name of morphism to many structures that either do not have an underlying set, or are not algebraic, or do not preserve the operation. * Identity morphism

Identity morphism - or simply identity: \( x \in C : \; id_{x}=1_{x} : x \to x \) Composed with other morphism gives same morphism.

Corresponds to Reflexivity and Automorphism. Identity

Identity only possible with morphism. See Identity morphism.

There is also distinct Zero value. Two-sided identity of a predicate

\( P(e,a)=P(a,e)=a \ | \ \exists e \in S, \forall a \in S \) \( P() \) is commutative.

Predicate Left identity of a predicate

\( \exists e \in S, \forall a \in S : \; P(e,a)=a \)

Predicate Right identity of a predicate

\( P(a,e)=a \; | \; \exists e \in S, \forall a \in S \)

Predicate Identity function

Return itself. (\ x.x)

id :: a -> a Monomorphism

\textgreek{μονο} mono only

\textgreek{μορφή} morphe form

Maps one to one (uniquely), so invertable (always has inverse morphism), so preserves the information/structure. Domain can be equal or less to the codomain.

\( f^{X \to Y}, \ \forall x \in X \, \exists! y=f(x) \vDash f(x) \equiv f_{mono}(x) \) - from homomorphism context \( f_{mono} \circ g1 = f_{mono} \circ g2 \ \vDash \ g1 \equiv g2 \) - from general morphism context Thus * is left canselable.

If * is a function - it is injective. Initial set of f is fully uniquely mapped onto the image of f. Epimorphism

\textgreek{επι} epi on, over

\textgreek{μορφή} morphe form

* is end-equating morphism. Since epimorphism covers target fully - ∀ morphisms composed to its end (target) are fully active in composition and so fully comparable between each other.

Term end-equating is more direct, easy and clear then classic right-canselable. Since "right" is collision between direction of composition (right to left) (and sometimes composition gets writted left to right), way it is drawn (left to right), and written \( C \to D \) (left to right).

\( f^{X \to Y}, \forall y \in Y \, \exists f(x) \vDash f(x) \equiv f_{epi}(x) \) - from homomorphism context \( g_1 \circ f_{epi} = g_2 \circ f_{epi} \Rightarrow \; g_1 \equiv g_2 \) - from general morphism context

In Set category if * is a function - it is surjective (image of it fully uses codomain) Codomain is a called a projection of the domain.

* fully maps into the target. * Isomorphism

\textgreek{ἴσος} isos equal

\textgreek{μορφή} morphe form

Not equal, but equal for current intents and purposes. Morphism that has inverse. Almost equal, but not quite: (Integer, Bool) & (Bool, Integer) - but can be transformed losslessly into one another.

Bijective homomorphism is also isomorphism.

\( f^{-1, b \to a} \circ f^{a \to b} \equiv 1^a, \; f^{a \to b} \circ f^{-1, b \to a} \equiv 1^b \)

2 reasons for non-isomorphism:

Categories are isomorphic if there \( R \circ L = ID \) * Lax

Holds up to isomorphism. (upon the transformation can be used as the same) Endomorphism

\textgreek{ενδο} endo internal

\textgreek{μορφή} morphe form

Arrow from object to itself. Endomorphism forms a monoid (object exists and category requirements already in place). Automorphism

\textgreek{αυτο} auto self

\textgreek{μορφή} form form

Isomorphic endomorphism.

Corresponds to identity, reflexivity, permutation. * Catamorphism

\textgreek{κατά} kata downward

\textgreek{μορφή} morphe form

Unique arrow from an initial algebra structure into different algebra structure.

* in FP is a generalization folding, deconstruction of a data structure into more primitive data structure using a functor F-algebra structure.

* reduces the structure to a lower level structure. * creates a projection of a structure to a lower level structure. Catamorphism property
Table 3: Catamorphism properties in Haskell
Rule name Haskell
cata-cancel cata phi . InF = phi . fmap (cata phi)
cata-refl cata InF = id
cata-fusion f . phi = phi . fmap f => f . cata phi = cata phi
cata-compose eps :: f :~> g => cata phi . cata (In . eps) = cata (phi . eps) Hylomorphism

catamorphism \( \circ \) anamorphism

Expanding and collapsing the structure. * Anamorphism

Generalizes unfold.

Dual concept to catamorphism.

Increases the structure.

Morphism from a coalgebra to the final coalgebra for that endofunctor.

Is a function that generates a sequence by repeated application of the function to its previous result. * Kernel

Kernel of a homomorphism is a number that measures the degree homomorphism fails to meet injectivity (AKA be monomorphic). It is a number of domain elements that fail injectivity:

  • elements not included into morphism
  • elements that collapse into one element in codomain

thou Kernel \( [ x | x \leftarrow 0 || x \ge 2 ] \).

Denotation: \( \operatorname{ker}T = \{ \mathbf{v} \in V:T(\mathbf{v}) = \mathbf{0}_{W} \} \). Kernel homomorphism

Morphism of elements from the kernel. Complementary morphism of elements that make main morphism not monomorphic.

2.2.8 Set category

Category in which objects are sets, morphisms are functions.

Denotation: \( Set \)

2.2.9 Natural transformation

Roughly * is:

trans :: F a -> G a

, while a is polymorphic variable.

Naturality condition: \( \forall \ a \ \exists \ (F \ a \to G \ a) \), or , analogous to parametric polymorphism in functions. Since * in a category, stating \( \forall (F \ a \to G \ a) \) Naturality condition means that all morphisms that take part in homotopy of source functor to target functor must exist, and that is the same, diagrams that take part in transformation, should commute, and different paths brins same result: if \( \alpha \) - natural transformation, \( \alpha_{a} \) natural transformation component - \( G \ f \circ \alpha_{a} = \alpha_{b} \circ F \ f \). Since * are just a type of parametric polymorphic function - they can compose.

* (\( \overrightarrow{\eta}^{\mathcal{D}} \)) is transforming : \( \overrightarrow{\eta}^{\mathcal{D}} \circ F^{\mathcal{C \to D}} = G^{\mathcal{C \to D}} \). * abstraction creates higher-language of Category theory, allowing to talk about the composition and transformation of complex entities.

It is a process of transforming \( F^{\mathcal{C \to D}} \) into \( G^{\mathcal{C \to D}} \) using existing morphisms in target category \( \mathcal{D} \).

Since it uses morphisms - it is structure-preserving transformation of one functor into another. Iy mostly a lossy transformation. Only existing morphisms cab make it exist.

Existence of * between two functors can be seen as some relation.

Can be observed to be a "morphism of functors", especially in functor category. * by \( \overrightarrow{\eta}^{\mathcal{D}}_{y^{\mathcal{C}}}(\overrightarrow{(x,y)}^{\mathcal{C}}) \circ F^{\mathcal{C \to D}}(\overrightarrow{(x,y)}^{\mathcal{C}}) = G^{\mathcal{C \to D}}(\overrightarrow{(x,y)}^{\mathcal{C}}) \circ \overrightarrow{\eta}^{\mathcal{D}}_{x^{\mathcal{C}}}(\overrightarrow{(x,y)}^{\mathcal{C}}) \), often written short \( \overrightarrow{\eta}_{b} \circ F(\overrightarrow{f}) = G(\overrightarrow{f}) \circ \overrightarrow{\eta}_{a} \). Notice that the \( \overrightarrow{\eta}^{\mathcal{D}}_{x^{\mathcal{C}}}(\overrightarrow{(x,y)}^{\mathcal{C}}) \) depends on objects&morphisms of \( \mathcal{C} \).

In words: * depends on \( F \) and \( G \) functors, ability of \( D \) morphisms to do a homotopy of \( F \) to \( G \), and *:

Also see: Natural transformation in Haskell

Knowledge of * forms a 2-category.

Can be composed

  • "vertically":
\begin{tikzcd} a \arrow[rrrr, "F", bend left] \arrow[rrrr, "G", bend right] \arrow[rrrr, "H", bend right=60] & & \Downarrow{\alpha} & & b \\ & & \Downarrow{\beta} \end{tikzcd} \begin{tikzcd} a \arrow[rrrr, "F", bend left] \arrow[rrrr, "H", bend right=49] & & \Downarrow{\beta\circ\alpha} & & b \end{tikzcd}
  • "horizontally" ("Godement product"):
\begin{tikzcd} a \arrow[rr, "F_{1}", bend left] \arrow[rr, "G_{1}", bend right] & \Downarrow{\alpha} & b \arrow[rr, "F_{2}", bend left] \arrow[rr, "G_{2}", bend right] & \Downarrow{\beta} & c \end{tikzcd} \begin{tikzcd} a \arrow[rr, "F_{2} \circ F_{1}", bend left] \arrow[rr, "G_{2} \circ G_{1}", bend right] & \Downarrow{\beta * \alpha} & c \end{tikzcd}

Vertical and horizontal compositions can be done in any order, they abide the exchange property. Natural transformation component

\( \overrightarrow{\eta}^{\mathcal{D}}(x) = F^{\mathcal{D}}(x) \to G^{\mathcal{D}}(x) \ | \ x \in \mathcal{C} \) Natural transformation in Haskell

Family of parametric polymorphism functions between endofunctors.

In Hask is \( F \ a \to G \ a \). Can be analogued to repackaging data into another container, never modifies the object content, it only if - can delete it, because operation is lossy.

Can be sees as ortogonal to functors. Cat category

Category where:

  Part Is #
* object category 0-cell
morphism functor 1-cell
2-morphism natural transformation, morphisms homotopy 2-cell
\begin{tikzcd} a \arrow[rrrr, "F", bend left] \arrow[rrrr, "G", bend right] & & \Downarrow{nt} & & b \end{tikzcd}

Is Cartesian closed category. * Bicategory

2-category that is enriched and lax.

For handling relaxed associativity - introduces associator, and for identity l -eft/right unitor.

Forming from bicategories higher categories by stacking levels of abstraction of such categories - leads to explosion of special cases, differences of every level, and so overall difficulties.

Stacking groupoids (category in which are morphisms are invertable) is much more homogenous up to infinity, and forms base of the homotopy type theory.

2.2.10 Category dual

Category duality behaves like a logical inverse.

Inverse \( \mathcal{C} \) = \( \mathcal{C}^{op} \) - inverts the direction of morphisms.

Composition accordingly changes to the morphisms: \( (g \circ f)^{op} = f^{op} \circ g^{op} \)

Any statement in the terms of \( \mathcal{C} \) in \( \mathcal{C}^{op} \) has the dual - the logical inverse that is true in \( \mathcal {C}^{op} \) terms.

Opposite preserves properties:

  • products: \( (\mathcal{C} \times \mathcal{D})^{op} \cong \mathcal{C}^{op} \times \mathcal{D}^{op} \)
  • functors: \( (F^{\mathcal{C} \to \mathcal{D}})^{op} \cong F^{\mathcal{C}^{op} \to \mathcal{D}^{op}} \)
  • slices: \( (\mathcal{F} \downarrow \mathcal{G})^{op} \cong (\mathcal{G}^{op} \downarrow \mathcal{F}^{op}) \) Coalgebra

Structures that are dual (in the category-theoretic sense of reversing arrows) to unital associative algebras. Every coalgebra, by vector space duality, reversing arrows - gives rise to an algebra. In finite dimensions, this duality goes in both directions. In infinite - it should be determined.

2.2.11 Thin category

Hom sets contain zero or one morphism.

\( f \equiv g \ | \ \forall x,y \ \forall f,g: x \to y \)

A proset (preordered set).

2.2.12 Commuting diagram

Establishes equality in morphisms that have same source and target.

Draws the morphisms that are: \( f = g \Rightarrow \{f, y\}: X \to Y \)

2.2.13 Universal construction

Algorythm of constructing definitions in Category theory. Specially good to translate properties/definitions from other theories (Set theory) to Categories.


  1. Define a pattern that you defining.
  2. Establish ranking for pattern matches.
  3. The top of ranking, the best match or set of matches - is the thing you was looking for. Matches are isomorphic for defined rules.

* uses Yoneda lemma, and as such constructions are defined until isomorphism, and so isomorphic betweem each-other.

2.2.14 Product

Universal construction:

\begin{matrix} && c^{\prime} && \\ & {}^p\swarrow\phantom{{}^{p}} & {\tiny \phantom{!}}\downarrow{\tiny !} & \phantom{{}^q}\searrow^q& \\ a & \underset{\pi_a}{\leftarrow} & c & \underset{\pi_b}{\rightarrow} & b \end{matrix}

Pattern: \( p: c \to a, \ q: c \to b \)

Ranking: \( \max{\sum^{\forall}{(!: c\prime \to c \ | \ p\prime = p \circ !, \ q\prime = q \circ !)}} \)

\( c\prime \) is another candidate.

For sets - Cartesian product.

* is a pair. Corresponds to product data type in Hask (inhabited with all elements of the Cartesian product).

Dual is Coproduct. *

2.2.15 Coproduct

Universal construction:

\begin{matrix} && c\prime && \\ & {}^p\nearrow\phantom{{}^{p}} & {\tiny \phantom{!}}\uparrow{\tiny !} & \phantom{{}^q}\nwarrow^q& \\ a & \underset{\iota_a}{\rightarrow} & c & \underset{\iota_b}{\leftarrow} & b \end{matrix}

Pattern: \( i: a \to c, \ j: b \to c \)

Ranking: \( \max{\sum^{\forall}{(!: c \to c\prime \ | \ i\prime = ! \circ i, \ j\prime = ! \circ j)}} \)

\( c\prime \) is another candidate.

For sets - Disjoint union.

* is a set assembled from other two sets, in Haskell it is a tagged set (analogous to disjoint union).

Dual is Product. *

2.2.16 Free object

General particular structure. In which structure, properties autofollows from definition, axioms.

Also uses as a term when surcomstances of structures, rules, properties, axioms used coinside with the definition of a particular object ∴ form object of this type with the according properties and possibilities.

2.2.17 Internal category

Category which is includded into a bigger category.

2.2.18 Hom set

All morphisms from source object to target object.

Denotation: \( hom_{C}(X,Y) = (\forall f: X \to Y) = hom(X,Y) = C(X,Y) \) Denotation was not standartized.

Hom sets belong to Set category.

In Set category: \( \exists! (a, b) \iff \exists! Hom \), \( \forall Hom \in \ Set \). Set category is special, Hom sets are also objects of it.

Category can include Set, and hom sets, or not. * Hom-functor

\( hom:\mathcal{C}^{op} \times \mathcal{C} \to Set \) Functor from the product of \( \mathcal{C} \) with its opposite category to the category of sets.

Denotation variants: \( H_A = \mathrm{Hom}(-, A) \) \( h_A = {\cal \mathcal{C}}(-, A) \) \( Hom(A,-): \ \mathcal{C} \to Set \)

Hom-bifunctor: \( Hom(-,-): \ \mathcal{C}^{op} \times \mathcal{C} \to Set \) Exponential object

Generalises the notion of function set to internal object. As also hom set to internal hom objects.

Cartesian closed (monoidal) category strictly required, as * multiplicaton holds composition requirement:

\( \circ:hom(y,z) \otimes hom(x,y) \to hom(x,z) \)

Denotation: \( b^{a} \)

Universal construction:

\begin{tikzcd} c \arrow[dd, "u", dotted] & & c \times a \arrow[dd, "u \times 1^{a}", dotted] \arrow[rrdd, "g"] \arrow[ll] & & \\ & & & & \\ b^{a} & & b^{a} \times a \arrow[rr, "eval", dotted] \arrow[ll] & & b \end{tikzcd}

, where in Category: \( b^{a} \) - exponential object, × - product bifunctor, \( a \) - argument of *, \( b \) - result, \( c \) - candidate, \( b^{a} \equiv ( a \Rightarrow b ) \) - *.

* \( b^{a} \) (also as \( (a \Rightarrow b) \)) represent exponentiation of cardinality of \( \forall b^{a} \) possiblities. Enriched category

Uses Hom objects (exponential objects), which do not belong into Set category. Category is no longer small, now may be called large.

\( hom(x,y) \in K \).

Called: * over K (whick holds hom objects). *

2.2.19 Mag category

The category of magmas, denoted \( Mag \), has as objects - sets with a binary operation, and morphisms given by homomorphisms of operations (in the universal algebra sense).

2.3 Data type

Set of values. For type to have sence the values must share some sence, properties.

2.3.2 Actual type

Data type recieved by ->inferring->compiling->execution.

2.3.3 Algebraic data type

Composite type formed by combining other types. *

2.3.4 Cardinality

Number of possible implementations for a given type signature.

Disjunction, sum - adds cardinalities. Conjunction, product - multiplies cardinalities. *

2.3.6 Data constructor

One instance that inhabit data type.

2.3.7 data declaration

Data type declaration is the most general and versatile form to create a new data type. Form:

data [context =>] type typeVars1..n
  = con1  c1t1..i
  | ...
  | conm  cmt1..q

2.3.8 Dependent type

When type and values have relation between them. Type has restrictions for values, value of a type variable has a result on the type. *

2.3.9 Gen type

Generator. Gen type is to generate pseudo-random values for parent type. Produces a list of values that gets infinitely cycled.

2.3.10 Higher-kinded data type

Any combination of * and ->

Type that take more types as arguments.

Humbly really a function

2.3.11 newtype declaration

Create a new type from old type by attaching a new constructor, allowing type class instance declaration.

newtype FirstName = FirstName String

Data will have exactly the same representation at runtime, as the type that is wrapped.

newtype Book = Book (Int, Int)
      / \
Integer Integer

2.3.12 Principal type

The most generic data type that still typechecks.

2.3.13 Product data type

Is an algebraic data type respesentation of a product construction. Formed by logical conjunction (AND, '* *').

Haskell forms:

-- 1. As a tuple (the uncurried & most true-form)
(T1, T2)

-- 2. Curried form, data constructor that takes two types
C T1 T2

-- 3. Using record syntax. =r# <inhabitant>= would return the respective =T#=.
C { r1 :: T1
  , r2 :: T2
  } * Sequence

Enumerated (ordered) set. Set with a strict order property.


( , )
( , , )
( , , ... )

More general mathematical denotation was not established, variants: \( (n)_{n \in \mathbb{N}} \) \( \omega \to X \) \( \{ i:Ord \ | \ i < \alpha \} \)

In Haskell: Data type that stores multiple ordered values withing a single value.

Table 4: Sequence constructor naming by arity
Name Arity Denotation
Unit, empty 0 ()
Singleton 1 (_)
Tuple, pair, two-tuple 2 ( , )
Triple, three-tuple 3 ( , , )
Sequence N ( , , ...) List

Sequence of one type objects.


[ , ]
[ , , ]
[ , , ... ]

Haskell definition:

data [] a = [] | a : [a]

Definition is self-referrential (self-recursive), can be seen as anamorphism (unfold) of the [] (empty list, memory cell which is container of particular type) and : (cons operation, pointer). As such - can create non-terminating data type (and computation), in other words - infinite.

2.3.14 Proxy type

Proxy type holds no data, but has a phantom parameter of arbitrary type (or even kind). Able to provide type information, even though has no value of that type (or it can be may too costly to create one).

data Proxy a = ProxyValue

let proxy1 = (ProxyValue :: Proxy Int) -- a has kind `Type`
let proxy2 = (ProxyValue :: Proxy List) -- a has kind `Type -> Type`

2.3.15 Static typing

Type check takes place at compile level, so compiled program already has expectations of types it should recieve.

2.3.16 Structural type

Mathematical type. They form into structural type system. *

2.3.17 Structural type system

Strict global hierarchy and relationships of types and their properties. Haskell type system is *. In most languages typing is name-based, not structural. *

2.3.18 Sum data type

Algebraic data type formed by logical disjunction (OR '|').

2.3.19 Type alias

Create new type constructor, and use all data structure of the base type.

2.3.20 Type class

Type system construct that adds a support of ad hoc polymorphism.

Type class makes a nice way for defining behaviour, properties over many types/objects at once. * Arbitrary type class

Type class of QuickCheck.Arbitrary (that is reexported by QuickCheck) for creating a generator/distribution of values. Useful function is arbitrary - that autogenerates values. Arbitrary function

Depends on type and generates values of that type. CoArbitrary type class

Pseudogenerates a function basing on resulting type.

coarbitrary :: CoArbitrary a => a -> Gen b -> Gen b * Typeable type class

Allows dynamic type checking in Haskell for a type. Shift a typechecking of type from compile time to runtime. * type gets wrapped in the universal type, that shifts the type checks to runtime.

Also allows: * Derived instance

Type class instances sometimes can be automatically derived from the parent types.

Type classes such as Eq, Enum, Ord, Show can have instances generated based on definition of data type.


Language options:

  • DeriveAnyClass
  • DeriveDataTypeable
  • DeriveFoldable
  • DeriveFunctor
  • DeriveGeneric
  • DeriveLift
  • DeriveTraversable
  • DerivingStrategies
  • DerivingVia
  • GeneralisedNewtypeDeriving
  • StandaloneDeriving *

2.3.22 Type constructor

Name of the data type.

Constructor that takes type as an argument and produces new type.

2.3.23 type declaration

Synonim for existing type. Uses the same data constructor.

type FirstName = String

Used to distinct one entities from other entities, while they have the same type. Also main type functions can operate on a new type.

2.3.24 Typed hole

* - is a _ or _name in the expression. On evaluation GHC would show the derived type information which should be in place of the *. That information helps to fill in the gap. *

2.3.25 Type inference

Automatic data type detection for expression.

2.3.26 Type class instance

Block of implementations of functions, based on unique type class->type pairing.

2.3.27 Type rank

Weak ordering of types.

The rank of polymorphic type shows at what level of nesting forall quantifier appears. Count-in only quantifiers that appear to the left of arrows.

f1 :: forall a b. a -> b -> a
-- =
f1 :: a -> b -> c

g1 :: forall a b. (Ord a, Eq b) => a -> b -> a
-- =
g1 :: (Ord a, Eq b) => a -> b -> a

f1, g1 - rank-1 types. Haskell itself implicitly adds universal quantification.

f2 :: (forall a. a->a) -> Int -> Int
g2 :: (forall a. Eq a => [a] -> a -> Bool) -> Int -> Int

f2, g2 - rank-2 types. Quantificator is on the left side of a →. Quantificator shows that type on the left can be overloaded.

Type inference in Rank-2 is possible, but not higher.

f3 :: ((forall a. a->a) -> Int) -> Bool -> Bool

f3 - rannk3-type. Has rank-2 types on the left of a →.

f :: Int -> (forall a. a -> a)
g :: Int -> Ord a => a -> a

f, g are rank 1. Quantifier appears to the right of an arrow, not to the left. These types are not Haskell 98. They are supported in RankNTypes.

2.3.28 Type variable

Refers to an unspecified parametric polymorphic type (maybe with ad-hoc polymorphism constraints) (keeps a naturality condition) in Haskell type signature.

In Haskell are always introduced with keyword forall explicit or implicit.

2.3.29 Unlifted type

Type that directly exist on the hardware. The type abstraction can be completely removed. With unlifted types Haskel type system directly manages data in the hardware. *

2.3.30 Linear type

Type system and algebra that also track the multiplicity of data. There are 3 general linear type groups:

  • 0 - exists only at type level and is not allowed to be used at value level. Aka s in ST-Trick.
  • 1 - data that is not duplicated
  • 1< - all other data, that can be duplicated multiple times. *

2.3.31 NonEmpty list data type

Data.List.NonEmpty Has a Semigroup instance but can't have a Monoid instance. It never can be an empty list.

data NonEmpty a = a :| [a]
  deriving (Eq, Ord, Show)

:| - an infix data costructor that takes two (type) arguments. In other words :| returns a product type of left and right

2.3.32 Session type

* - allows to check that behaviour conforms to the protocol.

So far very complex, not very productive (or well-established) topic.

2.3.33 Binary tree

Tree where every element is a Leaf (structure stub, Nothing) or a Node (split of branches):

data BinaryTree a
  = Leaf
  | Node (BinaryTree a) a (BinaryTree a)

2.3.34 Bottom value

A _ non-value in the type or pattern match expression, placeholder, fits for enything.


_ *

2.3.35 Bound

Haskell * type class means to have lowest value & highest value, so a bounded range of values. *

2.3.37 Context

Type constraints for polymorphic variables. Written before the main type signature, denoted:

TypeClass a => ... *

2.3.38 Inhabit

Values that is a component of data type set.

2.3.39 Maybe

data Maybe
  = Nothing
  | Just a

Does not represent the information why Nothing happened. For error - use Either. Do not propagate *.

Handle * locally to where it is produced. Nothing does not hold useful info for debugging & short-circuits the processes. Do not expect code type being bug-free, do not return Maybe to end user since it would be impossible to debug, return something that preserves error information. *

2.3.40 Expected type

Data type inferred from the text of the code.

2.3.42 Concrete type

Fully resolved, definitive, non-polymorphic type.

2.3.43 Type punning

When type constructor and data constructor have the same name.

Theoretically if person knows the rules - * can be solved, because in Haskell type and data declaration have different places of use.

2.3.44 Kind

Kind -> Type -> Data *

2.3.45 IO

There is only one way to "perform" an I/O action: bind it to Main.main of the program. For function I/O it should be in IO monad and evaluated from Main.main.

Type for values whose evaluations has a posibility to cause side effects or return unpredictable result. Haskell standard uses monad for constructing and transforming IO actions. IO action can be evaluated multiple times.

IO data type has unpure imperative actions inside. Haskell is pure Lambda calculus, and unpure IO integrates in the Haskell purely (type system abstracts IO unpurity inside IO data type).

IO sequences effect computation one after another in order of needed computation, or occurence:

twoBinds :: IO ()
twoBinds =
  putStrLn "First:" >>
  getLine >>=
  \a ->
  putStrLn "Second:" >>
  getLine >>=
  \b ->
  putStrLn ("\nFirst: "
    ++ a ++ ".\nSecond "
    ++ b ++ ".")
main = twoBinds

Sequencing is achieved by compilation of effects performing only while they recieve the sugared-in & passed around the RealWorld fake type value, that value in the every computation gets the new "value" and then passed to the next requestes computation. But special thing is about this parameter, this RealWorld type value passed, but never looked at. GHC realizes, since value is never used, - it means value and type can be equated to () and moreover reduced from the code, and sequencing stays.

2.4 Expression

Finite combination of symbols that is well-formed according to context-free grammar.

Generally meaningless. Meaning gets derived from an * & context (and/or content words) by congruency with knowledge & expirience.

2.4.1 *

2.4.2 Closed-form expression

* - mathematical expression that can be evaluated in a finite number of operations.

May contain:

2.4.3 RHS

Right-hand side of the expression.

2.4.4 LHS

Left-hand side of the expression.

2.4.6 Concatenate

Link together sequences, expressions.

2.4.7 Alpha equivalence

Equivalence of a processes in expressions. If expressions have according parameters different, but the internal processes are literally the same process.

2.4.8 Ground expression

Expression that does not contain any free variables. *

2.4.9 Variable

A name for expression.


There fequently can be heard: one of most notable Haskell properties is Haskell has immutable "variables" (and term here used in the sence that imperative programmers frequently use). Logically we see statement is contradictory with itself: "variables" - something that has change as a defining propery - are not changing; it is a nonsencical statement. Please, read the saying as: Haskell has immutable values, due to following the value semantics: see "Value". And Haskell expressions are functions (that are referentially transparent - meaning itself immutable) - and they are also values (hense term "functional programming" means - functions are first-class values). Since values bind to variables - people are wrongly mix-up terms and say their names (according "*") are immutable.

As you see in the code - Haskell variables (same names) hold different values at different times. Variables are reused, meaning "names are reused" - binded to different values on scope changes. But all values that Haskell holds - are, by the design of the language, are treated immutable, any transformations Haskell resolves by creating new values, and frees the space by freeing-up from no longer needed values. *

2.5 Function

Full dependency of one quantity from another quantity.

Denotation: \( y = f(x) \) \( f: X \to Y \), where \( X \) is domain, \( Y \) is codomain.

Directionality and property of invariability emerge from one another.

-- domain func codomain
   *      ->   *

\( y(x) = (zx^{2} + bx + 3 \ | \ b = 5) \) ^ ^ ^^ ^ ^

      \\( \textsubscript{Var} \)\\( \textsubscript{Constant} \)
    \\( \textsubscript{Bound variable} \)
  \\( \textsubscript{Free variable} \)
\\( \textsubscript{Parameter} \)

\\( \textsubscript{Name of the function} \)

Lambda abstraction is a function. Function is a mathematical operation.

Function = Total function = Pure function. Function theoretically can be to memoized.

Also see: Partial function Inverse function - often partially exists (partial function).

2.5.2 Arity

Number of parameters of the function.

  • nullary - f()
  • unary - f(x)
  • binary - f(x,y)
  • ternary - f(x,y,z)
  • n-ary - f(x,y,z..)

2.5.3 Bijection

Function is a complete one-to-one pairing of elements of domain and codomain (image). It means function both surjective (so image == codomain) and injective (every domain element has unique correspondence to the image element).

For bijection inverse always exists.

Bijective operation holds the equivalence of domain and codomain.


f : X ⤖ Y

LaTeX needed to combine symbols: \( \newcommand*{\twoheadrghtarrowtail}{\mathrel{\rightarrowtail\kern-1.9ex\twoheadrightarrow}} f : X \twoheadrghtarrowtail Y \)

Corersponds to isomorphism.

2.5.4 Combinator

Function without free variables. Higher-order function that uses only function application and other combinators.

\a -> a
\ a b -> a b
\f g x -> f (g x)
\f g x y -> f (g x y)

Not combinators:

\ xs -> sum xs

Informal broad meaning: referring to the style of organizing libraries centered around the idea of combining things. Ψ-combinator

Transforms two of the same type, applying same mediate transformation, and then transforming those into the result.

import Data.Function (on)
on :: (b -> b -> c) -> (a -> b) -> a -> a -> c
    * ---c

2.5.6 Function body

Expression that haracterizes the process.

2.5.7 Function composition

(.) :: (b -> c) -> (a -> b) -> a -> c

a -> (a -> b) -> (b -> c) -> c

In Haskell inline composition requires:

h.g.f $ i

2.5.8 Function head

Is a part with name of the function and it's paramenters. AKA: \( f(x) \)

2.5.9 Function range

The range of a function refers to either the codomain or the image of the function, depending upon usage. Modern usage almost always uses range to mean image. So, see Function image.

2.5.10 Higher-order function

Function that has arity > 1.


HOF is:

Application of an argument to * produces a function that has arity - 1. *

HOF Fold

Catamorphism of a structure to a lower type of structure. Often to a single value.

* is a higher-order function that takes a function which operates with both main structure and accumulator structure, * applies units of data structure to a function wich works with accumulator. Upoun traversing the whole structure - the accumulator is returned.

2.5.11 Injection

Function one-to-one injects from domain into codomain.

Keeps distinct pairing of elements of domain and image. Every element in image coresponds to one element in domain.

\( \forall a,b \in X, \; f(a)=f(b) \Rightarrow a=b \)

\( \exists (inverse \ function) \ | \ \forall (injective \ function) \)


f : X ↣ Y

\(f : X \rightarrowtail Y\)

Corresponds to Monomorphism.

2.5.12 Partial function

One that does not cover all domain. Unsafe and causes trouble.

2.5.13 Purity

* means properly abstracted.

If the contrary - abstraction is unpure.

Also see: pure function. *

2.5.15 Sectioning

Writing function in a parentheses. Allows to pass around partially applied functions.

2.5.16 Surjection

Function uses codomain fully.

\( \forall y \in Y, \exists x \in X \)

Denotation: \( f : X \twoheadrightarrow Y \)

Corresponds to Epimorphism.

2.5.17 Unsafe function

Function that does not cover at least one edge case. *

2.5.18 Variadic

* - having variable arity (often up to indefinite).

2.5.19 Domain

Source set of a function. \( X \) in \( X \to Y \).

2.5.20 Codomain

\( Y \) in \(X \to Y\). Codomain - target set of a function.

2.5.21 Open formula

Logical function that has arity and produces proposition.

2.5.22 Recursion

Repeated function application when sometimes the same function gets called.

Allows computations that may require indefinite amount of work. * Base case

A part of a recursive function that trivially produces result. Tail recursion

Tail calls are recursive invocantions of itself. Polymorphic recursion

Type of the parameter changes in recursive invocations of function.

Is always a higher-ranked type.

2.5.23 Free variable

Variable in the fuction that is not bound by the head. Until there are * - function stays partially applied.

2.5.24 Closure

\( f(x) = f^{\mathcal{X \to X}} \ | \ \forall x \in \mathcal{X} \), \( \mathcal{X} \) is closed under \( f \), it is a trivial case when operation is legitimate for all values of the domain.

Operation on members of the domain always produces a members of the domain. The domain is closed under the operation.

In the case when there is a domain values for which operation is not legitimate/not exists:

\( f(x) = f^{\mathcal{V \to X}} \ | \ \mathcal{V \in X}, \forall x \in \mathcal{V} \), \( \mathcal{X} \) is closed under \( f \). *

2.5.25 Parameter

παρά para subsidiary μέτρον metron measure

Named varible of a function.

Argument is a supplied value to a function parameter.

Parameter (formal parameter) is an irrefutable pattern, and implemeted that way in Haskell.

2.5.27 Well-formed formula

Expression, logical function that is/can produce a proposition.

2.6 Homotopy

ὁμός homós same

One can be "continuously deformed" into the other.

For example - functions, functors. Natural transformation is a homotopy of functors.

2.7 Lambda calculus

Universal model of computation. Which means * can implement any Turing machine. Based on function abstraction and application by substituting variables and binding values.

* has lambda terms:

2.7.2 Lambda cube

λ-cube shows the 3 dimentions of generalizations from simply typed Lambda calculus to Calculus of constructions.


\begin{tikzcd} \label{org61506a0} {Polymorphic \ types} \\ & {Type \ opertations} \\ 0 \arrow[uu] \arrow[ur] \arrow[rr] & & {Dependent \ types} \end{tikzcd} \begin{tikzcd}[row sep=scriptsize,column sep=scriptsize] \label{orgd11eb3a} & \lambda \omega \arrow[rr] \arrow[from=dd] & & \lambda C \\ \lambda 2 \arrow[ur] \arrow[rr, crossing over] & & \lambda P 2 \arrow[ur] \\ & \lambda \underline{\omega} \arrow[rr] & & \lambda P \underline{\omega} \arrow[uu] \\ \lambda \arrow[rr] \arrow[uu] \arrow[ur] & & \lambda P \arrow[uu, crossing over] \arrow[ur] \end{tikzcd}

Each dimension of the cube corresponds to extensions (a new type of relation of objects depending on objects):

Table 5: Three degrees of type systems generalizations
Denotation Name Programming New type of relations
2 Polymorphic types First-class polymorphism of types Terms depending on types
ω Type operation Type class, type families Types depending on types
P Dependent types Higher-rank polymorphism, dependent types Types depending on terms
Table 6: λ-cube: Names of the type systems
Denotation Logical system
\( \lambda\to \) (First Order) Propositional Calculus
\( \lambda2 \) Second Order Propositional Caculus
\( \lambda\omega \) Weakly Higher Order Propositional Calculus
\( \lambda \underline{\omega} \) Higher Order Propositional Calculus
\( \lambda P \) (First Order) Predicate Logic
\( \lambda P 2 \) Second Order Predicate Calculus
\( \lambda P \undeline{\omega} \) Weak Higher Order Predicate Calculus
\( \lambda C \) Calculus of Constructions *

2.7.3 Lambda function

Function of Lambda calculus. \( \lambda x y.x^2 + y^3 \) ^^ ^ ^


\__parameter (_) \___HEAD * Anonymous lambda function

Lambda function that is not binded to any name. Uncurry

Replace sequenced lambda functions into single function taking sequence/product of values as argument.

2.7.4 β-reduction

Equation of a parameter to a bound variable, then reducing parameter from the head.

2.7.5 Calculus of constructions

Extends the Curry–Howard correspondence to the proofs in the full intuitionistic predicate calculus (includes proofs of quantified statements). Type theory, typed programming language, and constructivism (phylosophy) foundation for mathematics. Directly relates to Coq programming language. *


2.7.6 Curry–Howard correspondence

Equivalence of {First-order logic, computer programming, Category theory}. They represent each-other, possible in one - possible in the other, so all the definitions and theorems have analogues in other two.

Gives a ground to the equivalence of computer programs and mathematical proofs.

Lambek added analogue to Cartesian closed category, which can be used to model logic and type theory.

Table 7: Table of basic correspondence
Logic Type Category
True () (any inhabited type) Terminal
False Void Initial
a ∧ b (a, b) a × b
a ∨ b (a | b) a | b
a ⇒ b a → b ba

Algebra correspondence to types:

\( a^{b \ + \ c}^{} \) ~ ( b | c \to a) \( a^{b} \times a^{c} \) ~ (b \to a, c \to a)

\( a^{b^{c} }\) ~ (c \to b \to a) \( a^{b \times c} \) ~ ((b, c) \to a)

2.7.7 Currying

Translating the evaluation of a multiple argument function (or a tuple of arguments) into evaluating a sequence of functions, each with a single argument. *

2.7.9 Reduction

Take out something from a structure, make simplier.

See Beta reduction *

2.7.11 η-abstraction

\( (\lambda x.Mx) \xleftarrow[\eta]{} M \)

\ x -> g . f $ x
\ x -> g . f     --eta-abstraction

2.7.12 Lambda expression

See Lambda calculus (Lambda terms) and Expression. In majority cases meaning some Lambda function.

2.8 Operation

Calculation into output value. Can have zero & more inputs.

2.8.2 Binary operation

\( \forall (a,b) \in S, \exists P(a,b)=f(a,b): S \times S \to S \) *

2.8.3 Operator

Denotation symbol/name for the operation. Shift operator

Shift operator defined by Lagrange through Differential operator. \( T^{t} \, = \, e^{t{\frac{d}{dx}}} \) *

Shift Differential operator

Denotation. \( \frac{d}{dx}, \, D, \, D_{x}, \, \partial_{x}. \) Last one is partial.

\( e^{t{\frac{d}{dx}}} \) - Shift operator. *

2.8.4 Infix

Form of writing of operator or function in-between variables for application.

For priorities see Fixity.

2.8.5 Fixity

Declares the presedence of action of a function/operator.

Funciton application has presedence higher then all infix operators/functions (virtually giving it a priority 10).

Table 8: Haskell operators priority and fixity association
P L Non R
10     F.A.
9 !!   .
8     ^ ^^ **
7 */ div    
6 +-    
5     : , ++
4   <comparison> elem  
3     &&
2     OR
1 >> >>=    
0     $ $! seq

Any operator lacking a fixity declaration is assumed to be infixl 9.

2.8.6 Zero

* is the value with which operation always yelds Zero value. \( zero, n \in C : \forall n, zero*n=zero \)

* is distinct from Identity value.

2.8.7 Bind

Establishing equality between two objects.

Most often: *

2.8.8 Declaration

Binding name to expression.

2.8.9 Dispatch

Sort-out & send.

2.8.10 Evaluation

For FP see Bind.

2.10 Point-free

Paradigm where function only describes the morphism itself.

Process of converting function to point-free. If brackets () can be changed to $ then $ equal to composition:

\ x -> g (f x)
\ x -> g $ f x
\ x -> g . f $ x
\ x -> g . f     --eta-abstraction

\ x1 x2 -> g (f x1 x2)
\ x1 x2 -> g $ f x1 x2
\ x1 x2 -> g . f x1 $ x2
\ x1    -> g . f x1

2.10.2 Blackbird

(.).(.) :: (b -> c) -> (a1 -> a2 -> b) -> a1 -> a2 -> c

Composition of compositions (.).(.). Allows to compose-in a binary function f1(c) (.).(.) f2(a,b).

\ f g x y -> f (g x y)

2.10.3 Swing

swing :: (((a -> b) -> b) -> c -> d) -> c -> a -> d
swing = flip . (. flip id)
swing f = flip (f . runCont . return)
swing f c a = f ($ a) c

2.10.4 Squish

f >>= a . b . c =<< g

2.11 Polymorphism

\textgreek{πολύς} polús many

At once several forms.

In Haskell - abstract over data types.

* types:

2.11.1 *

2.11.2 Levity polymorphism

Extending polymorphism to work with unlifted and lifted types.

2.11.3 Parametric polymorphism

Abstracting over data types by parameter.

In most languages named as 'Generics' (generic programming).

Types: Let-bound polymorphism

It is property chosen for Haskell type system. Haskell is based on Hindley-Milner type system, it is let-bound. To have strict type inference with * - if let and where declarations are polymorphic - λ declarations - should be not.

See: Good: In Haskell parameters bound by lambda declaration instantiate to only one concrete type. Constrained polymorphism Ad hoc polymorphism

Artificial constrained polymorphism dependent on incoming data type. It is interface dispatch mechanism of data types. Achieved by creating a type class instance functions.

Commonly known as overloading. Impredicative polymorphism

* allows type τ entities with polymorphic types that can contain type τ itself. \( T = \forall X. X \to X : \; T \in X \vDash T \in T \)

The most powerful form of parametric polymorphism. See: Impredicative.

This approach has Girard's paradox (type systems Russell's paradox). Higher-rank polymorphism

Means that polymorphic types can apper within other types (types of function). There is a cases where higher-rank polymorphism than the a Ad hoc - is needed. For example where ad hoc polymorphism is used in constraints of several different implementations of functions, and you want to build a function on top - and use the abstract interface over these functions.

-- ad-hoc polymorphism
f1 :: forall a. MyType Class a => a -> String    ==    f1 :: MyType Class a => a  -> String
f1 = -- ...

-- higher-rank polymorphism
f2 :: Int -> (forall a. MyType Class a => a -> String) -> Int
f2 = -- ...

By moving forall inside the function - we can achive higher-rank polymorphism.


Higher-rank polymorphism is formalized using System F, and there are a few
implementations of (incomplete, but decidable) type inference for it
- see e.g. Daan Leijen's research page [1] about it, or my experimental
implementation [2] of one of his papers. Higher-rank types also have some
limited support in OCaml and Haskell.

Useful example aslo a ST-Trick monad. *

2.11.4 Subtype polymorphism

Allows to declare usage of a Type and all of its Subtypes. T - Type S - Subtype of Type <: - subtype of \( S <: T = S \le T \)

Subtyping is: If it can be done to T, and there is subtype S - then it also can be done to S. \( S <:T : \; f^{T \to X} \Rightarrow f^{S \to X} \)

2.11.5 Row polymorphism

Is a lot like Subtype polymorphism, but alings itself on allowence (with | r) of subtypes and types with requested properties.

printX :: { x :: Int | r } -> String
printX rec = show rec.x

printY :: { y :: Int | r } -> String
printY rec = show rec.y

-- type is inferred as `{x :: Int, y :: Int | r } -> String`
printBoth rec = printX rec ++ printY rec

2.11.6 Kind polymorphism

Achieved using a phantom type argument in the data type declaration.

;;         * -> *
data Proxy a = ProxyValue

Then, by default the data type can be inhabited and fully work being partially defined. But multiple instances of kind polymorphic type can be distinguished by their particular type.

Example is the Proxy type:

data Proxy a = ProxyValue

let proxy1 = (ProxyValue :: Proxy Int) -- * :: Proxy Int
let proxy2 = (ProxyValue :: Proxy a)   -- * -> * :: Proxy a

2.11.7 Linearity polymorphism

Leverages linear types. For exampe - if fold over a dynamic array:

  1. In basic Haskell - array would be copied at every step.
  2. Use low-level unsafe functions.
  3. With Linear type function we guarantee that the array would be used only at one place at a time.

So, if we use a function (* -o * -o -o *) in foldr - the fold will use the initial value only once.

2.12 Compositionality

Complex expression is determined by the constituent expressions and the rules used to combine them.

If the meaning fully obtainable form the parts and composition - it is full, pure compositionality.

If there exists composed idiomatic expression - it is unfull, unpure compositionality, because meaning leaks-in from the sources that are not in the composition.

2.13 Referential transparency

Given the same input return the same output. So: * expression can be replaced with its corresponding resulting value without change for program's behavior. * functions are pure.

2.14 Semantics

Philosophical study of meaning. Meaning of symbols, words.

2.14.1 Operational semantics

Constructing proofs from axiomatic semantics, verifying procedures and their properties.

Good to solve in-point localized tasks.

Process of working with abstractions. Argument

arguere make clearmake known, to prove, to shine

* - evidence, proof, statement that results systematic changes. Argument of a function

A value binded to the function parameter. Value/topic that the fuction would process/deal with.

Also see Argument. * First-class

Means it:

  • Can be used as value.
  • Passed as an argument.

From 1&2 -> it can include itself. Relation

Relationship between two objects. By default it is not directed and not limited. In Set theory: some subset of a Cartesian product between sets of objects. * Context-free grammar

A grammar (set of production rules) that describe all possible properly composed expressions in a formal language.

Term is invented by Noam Chomsky. *

CFG Constructive proof

Method that demonstrates object existance by showing the process of its creation.

2.14.2 Denotational semantics

Construction of objects, that describe/tag the meanings. In Haskell often abstractions that are ment (denotations), implemented directly in the code, sometimes exist over the code - allowing to reason and implement.

* are composable.

Good to achive more broad approach/meaning.

Also see Abstraction. Abstraction

abs away from, off (in absentia)

tractus draw, haul, drag

Purified generalization.

Forgeting the details (axiomatic semantics). Simplified approach. Out of sight - out of mind.

* creates a new semantic level in which one can be absolutely precise (operational semantics).

It is a great did to name an abstraction (denotational semantics).

The ideal abstractions are:

They are ideal - because they are the basis, the beginning. Because you can not express any other obstractions without these.


This is personal idea & the thought of autor of the book regarding basic abstractions particularly. Other definitions in the book basing on this are the proof that statement has some ground truth in it. There is ongoing philosophical discussion on the topics like these. Leaky abstraction

Abstraction that leaks details that it is supposed to abstract away. * Object

Absolute abstraction.

Point that additionally can have properties.

Often abstracts something, that is why it exposes external properties on abstracting something, for example some structure, maybe mathematical. In this book objects represent algebraic structures, as we are talking about Haskell and Category theory.

Objects without process are in constant state. * Arrow

Second level of absolute abstraction.


Can have target, can have source. Both often are objects.

Often abstracts process.

Can have properties.

Also alias in Category Theory for "morphism", thou theory emposes properties. * Terminal object

One that recieves unique arrow from every object.

\( \exists ! : x \to 1 \ | \ \exists 1 \in \mathcal{C}, \ \forall x \in \mathcal{C}\)

* is an empty sequence () in Haskell.

Called a unit, so recieves terminal or unit arrow.

Dual of initial object.


Category theory \( 1 \)


() Initial object

One that emits unique arrow into every object.

\( \exists ! : \varnothing \to x \ | \ \exists \varnothing \in \mathcal{C}, \ \forall x \mathcal{C} \)

If initial object is Void (most frequently) - emitted arrows called absurd, because they can not be called.

Dual of terminal object.


Category theory: \( \varnothing \)


Void Value

What object abstracts. Without any object external structure (aka identity in Category Theory). So * is immutable. Such herecy is called "Value semantics" and leads such things as referential transparency, functional programming and Haskell.

(Except, when you hack Haskell with explicit low-level funсtions, and start to directly mute values - then you are on your own, Haskell paradigm does not expect that.) *

Value semantics Values Tensor

Object existing out of planes, thus it can translate objects from one plane into another. * can be tried to be described with knowledge existing inside planes (from projection on the plane), but representation would always be partial.

Tensor of rank 1 is a vector.

Translations with tensor can be seen as functors. * Ambigram

ambi both

\textgreek{γράμμα} grámma written character

Object that from different points of view has the same meaning.

While this word has two contradictory diametrically opposite usages, one was chosen (more frequent).

But it has… Both.

TODO: For merit of differentiating the meaning about different meaning referring to Tensor as object with many meanings. Binary

Two of something. Arbitrary

arbitrarius uncertain

Random, any one of.

Used as: Any one with this set of properties. (constraints, type, etc.).

When there is a talk about any arbitrary value - in fact it is a talk about the generalization of computations over the set of properties. Refutable

One that has an option to fail. Irrefutable

One that can not fail. Superclass

Broader parent class. Unit

Represents existence. Denoted as empty sequence.


Type () holds only self-representation constructor (), & constructor holds nothing.

Haskell code always should recieve something back, hense nothing, emptiness, void can not be theoretically addressed, practically constructed or recieved - unit in Haskell also has a role of a stub in place of emptiness, like in IO (). Nullary

Takes no entries (for example has the arity of zero). Has the trivial domain. Syntax tree

Tree of syntactic elements (each node denotes construct occurring in the language/source code) that represent the full particular composed expression/implementation. Abstract syntax tree

"Abstract" since does not represent every detail of the syntax (ex. parentheses), but rather concentrates on structure and content.

Widely used in compilers to check the code structure for accuracy and coherence. *

AST Concrete syntax tree

An ordered, rooted syntax tree that represents the syntactic structure of a string according to some context-free grammar.

"Concrete" since (in contrast to "abstract") - concretely reflects the syntax of the input language. * Stream

* an infinite sequence that forgets previous objects, and remembers only currently relevant objects.

\( E \ | \ X \to (X \times A + 1) \), the set (or object) of streams on A (final coalgebra \( A_{*} \) of \( E \)).

cycle is one of stream functions.

a = (cycle [Nothing, Nothing, Just "Fizz"])
b = (cycle [Nothing, Nothing, Nothing, Nothing, Just "Buzz"])

Can be:

  • indexed, timeless, with current object
  • timed:

* [(timescale, event)] * [(realtime, event)]

Has amalgamation with Functional Reactive Programming. Linear

Values consumed once or not used.

x^2 consumes/uses x two times (x*x). * Predicative

Non-self-referencing definition.


Antonym - Impredicative. Quantifier

Specifies the quantity of specimens.

Two most common quantifiers \( \forall \) (Forall) and \( \exists \) (Exists). \( \exists ! \) - one and only one (exists only unique).

Turns predicate into statement. Forall quantifier

In Haskell type variables are always introduced with it, explicitly or implicitly.

forall means that it will unify/fixed to any type that consumer may choose.

Permits to not infer the type, but to use any that fits. The variant depends on the LANGUAGE option used: * Idiom

* - something having a meaning that can not be derived from the conjoined meanings of * constituents. Meaning can be special for language speakers or human with particular knowledge.

* can also mean applicative functor, people better stop making idiom from the term "idiom". * Impredicative

Self-referencing definition.


Antonym - Predicative.

2.14.3 Axiomatic semantics

Empirical process of studying something complex by finding and analyzing true statements about it.

Good for examining interconnections. Property

Something has a property in the real world, and property always yealds an axiom (law) for something.

Meaningful abstraction denotation always defines through properties (axioms for that definition).

Abstraction forms nicely around the boundaries where the particular properties spread. Properties inside abstraction may have emergence effect (combination of properties result into bigger property), so in that way abstracting them simplifies outside picture, as abstraction hides plethora of internal properties and exposes only emergent properties.

In Haskell under property/law most often properties of algebraic structures.

There property testing wich does what it says. * Associativity

Joined with a common purpose.

\( P(a,P(b,c)) \equiv P(P(a,b),c) \ | \ \forall (a,b,c) \in S \),

* - the order (priority) of executions of actions can be arbitrary, as long as in the end the chain is the same - they would produce the same result. Any priority of execution of the parts of the operation chain would produce the same result, as the chain of operations is in fact flat.

Property that determines how operators of the same precedence are grouped, (in computer science also in the absence of parentheses).

Etymology: Latin associatus past participle of associare "join with", from assimilated form of ad "to" + sociare "unite with", from socius "companion, ally" from PIE *sokw-yo-, suffixed form of root *sekw- "to follow".

In Haskell * has influence on parsing when compounds have same fixity. Left-associativity

* - the operations can be done in groups the direction of actions can be from the beginning towards the end.

Example: In lambda expressions same level parts follow grouping from left to right. \( (\lambda x . x)(\lambda y . y)z \equiv ((\lambda x . x)(\lambda y . y))z \) * Right-associativity

* - the operations groups the actions from the end towards the beginning.


[1,2,3] = 1 : 2 : 3 : [] = 1 : (2 : (3 : [])) * Non-associativity

Operations can't be chained.

Often is the case when the output type is incompatible with the input type. * Basis

\( \beta\alpha\sigma\iota\varsigma \) - stepping

The initial point, unreducible axioms and terms that spawn a theory. AKA see Category theory, or Euclidian geometry basis. Contravariant

The property of basis, in which if new basis is a linear combination of the prior basis, and the change of basis inverse-proportional for the description of a Tensors in this basisis.

Denotation: Components for contravariant basis denoted in the upper indices: \( V^{i} = x \)

The inverse of a covariant transformation is a contravariant transformation. Good example of contravarint is: When a vector should stay absolute invariant even when basis changes, that is to say it represents the same geometrical or physical object having the same magnitude and direction as before - then those absolute invariant components relate to basis under the contravariant rule. Covariant

The property of basis, in which if new basis is a linear combination of the prior basis, and the change of basis proportional for a descriptions of tensors in basisis.

Denotation: Components for covariant basis denoted in the upper indices: \( V_{i} = x \) Commutativity

\( \forall (a,b) \in S : \; P(a,b) \equiv P(b,a) \)

All processes that are independent from one-another, but on manifastation of their results - their combination result into something (create curcomstances for something) - are commutative. Idempotence

First application gives a result. Then same operation can be applied multiple times without changing the result. Example: Start and Stop buttons on machines. * Distributivity

In algebra:

If × has commutative property - it is two-side distributive over +. * Effect

Observable action. Bisimulation

When systems have exact external behaviour so for observer they are the same.

Binary relation between state transition systems that match each other's moves. * Primitive operation

Operation that is axiomatic (can't be expressed from other given axioms of the system).

In program languages it is most probably implemented by lower-level programming.

In Haskell they are provided by GHC.

More: GHC Wiki/prim-ops. *

2.14.4 Content word

Words that name objects of reality and their qualities.

2.14.5 Ancient Greek and Latin prefixes

Table 9: Ancient Greek and Latin prefixes
Meaning Greek prefix Latin prefix
above, excess hyper- super-, ultra-
across, beyond, through dia- trans-
after   post-
again, back   re-
against anti- contra-, (in-, ob-)
all pan omni-
around peri- circum-
away or from apo-, ap- ab- (or de-)
bad, difficult, wrong dys- mal-
before pro- ante-, pre-
between, among   inter-
both amphi- ambi-
completely or very   de-, ob-
down   de-, ob-
four tetra- quad-
good eu- ben-, bene-
half, partially hemi- semi-
in, into en- il-, im-, in-, ir-
in front of pro- pro-
inside endo- intra-
large macro- (macro-, from Greek)
many poly- multi-
not* a-, an- de-, dis-, in-, ob-
on epi-  
one mono- uni-
out of ek- ex-, e-
outside ecto-, exo- extra-, extro-
over epi- ob- (sometimes)
self auto-, aut-,auth- ego-
small micro-  
three tri- tri-
through dia- trans-
to or toward epi- ad-, a-, ac-, as-
two di- bi-
under, insufficient hypo- sub-
with sym-, syn- co-. com-, con-
within, inside endo- intra-
without a-, an- dis- (sometimes)

2.15 Set

Well-defined collection of distinct objects.

2.15.1 *

2.15.2 Axiom of choice

\( {\displaystyle \forall X\left[\varnothing \notin X\implies \exists f\colon X\rightarrow \bigcup X\quad \forall A\in X\,(f(A)\in A)\right]} \)

Simple version:

For any inhabited sets, exists a set with exactly one element in common with each of them.

… from more wide-known variant:

Given any set X of pairwise disjoint non-empty sets, there exists at least one set C that contains exactly one element in common with each of the sets in X.

Most official formalization:

For any set X of nonempty sets, there exists a choice function f defined on X.

2.15.3 Closed set

  1. Set which complements an open set.
  2. Is form of Closed-form expression. Set can be closed in under a set of operations.

2.15.4 Power set

For some set \( \mathcal{S} \), the power set (\( \mathcal{P(S)} \)) is a set of all subsets of \( \mathcal{S} \), including \( \{\} \) & \( \mathcal{S} \) itself.

Denotation: \( \mathcal{P(S)} \)

2.15.5 Singleton

Singleton - unit set - set with exactly one element. Also 1-sequence.

2.15.6 Russell's paradox

If there exists normal set of all sets - it should contain itself, which makes it abnormal.

2.15.7 Cartesian product

\( \mathcal{A} \times \mathcal{B} \equiv \sum^{\forall}{(a,b)} \ | \ \forall a \in \mathcal{A}, \forall b \in \mathcal{B} \). Operation, returns a set of all ordered pairs \( (a, b) \)

Any function, functor is a subset of Cartesian product.

\( \sum{(elem \in (\mathcal{A} \times \mathcal{B}))} = cardinality^{A \times B} \)

Properties: Pullback

Subset of the cartesian product of two sets. *

2.15.8 Zermelo–Fraenkel set theory

Modern set theory. Axiomatic system free of paradoxes such as Russell's paradox and at the same time preserves the logical language of scientific works. *


2.16 Testing

2.16.1 Property testing

Since property yealds the according law, family of unit tests for the property can be abstracted into the function that test the law.

Unit test cases come from generator, and test the law empirically, but repeatedly and automatically. Function property

Property corresponds to the according law. In property testing you need to think additionally about generator and shrinking. Property testing type
Table 10: Property testing types
  Exhaustive Randomized Unit test (Single sample)
Whole set of values Exhaustive property test Randomised property test One element of a set
Special subset of values Exhaustive specialised property test Randomised specialised property test One element of a set Generator
Gen A -> A

Seed allows reproducibility. There is anyway a need to have some seed. Size allows setting upper bound on size of generated value. Think about infinity of list.

After failed test - shrinking tests value parts of contrexample, finds a part that still fails, and recurses shrinking. * Custom generator

When sertain theorem only works for a specific set of values - the according generator needs to be produced.

arbitrary :: Arbitrary a => Gen a
suchThat :: Gen a -> (a -> Bool) -> Gen a
elements :: [a] -> Gen a Reusing test code

Often it is convinient to abstract testing of same function properties:

It can be done with (aka TestSuite combinator):

-- Definition
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE AllowAmbiguousTypes #-}
eqSpec :: forall a. Arbitrary a => Spec

-- Usage
{-# LANGUAGE TypeApplications #-}
spec :: Spec
spec = do
  eqSpec @Int
Eq Int
  (==) :: Int -> Int -> Bool
    is reflexive
    is symetric
    is transitive
    is equivalent to (\ a b -> not $ a /= b)
  (/=) :: Int -> Int -> Bool
    is antireflexive
    is equivalent to (\ a b -> not $ a == b) Test Commutative property


:: Arbitrary a => (a -> a -> a) -> Property Test Symmetry property


:: Arbitrary a => (a -> a -> Bool) -> Property Test Equivalence property


:: (Arbitrary a, Eq b) => (a -> b) -> (a -> b) -> Property Test Inverse property
:: (Arbitrary a, Eq b) => (a -> b) -> (b -> a) -> Property QuickCheck

Target is a member of the Arbitrary type class. Target -> Bool is something Testable. This properties can be complex. Generator arbitrary gets the seed, and produces values of Target. Function quickCheck runs the loop and tests that generated Target values always comply the property. Manual automation with QuickCheck properties
import Test.QuickCheck
import Test.QuickCheck.Function
import Test.QuickCheck.Property.Common
import Test.QuickCheck.Property.Functor
import Test.QuickCheck.Property.Common.Internal

data Four' a b = Four' a a a b
  deriving (Eq, Show)

instance Functor (Four' a) where
  fmap f (Four' a b c d) = Four' a b c (f d)

instance (Arbitrary a, Arbitrary b) => Arbitrary (Four' a b) where
  arbitrary = do
    a1 <- arbitrary
    a2 <- arbitrary
    a3 <- arbitrary
    b <- arbitrary
    return (Four' a1 a2 a3 b)

-- Wrapper around `prop_FunctorId`
prop_AutoFunctorId :: Functor f => f a -> Equal (f a)
prop_AutoFunctorId = prop_FunctorId T

type Prop_AutoFunctorId f a
  = f a
  -> Equal (f a)

-- Wrapper around `prop_AutoFunctorCompose`
prop_AutoFunctorCompose :: Functor f => Fun a1 a2 -> Fun a2 c -> f a1 -> Equal (f c)
prop_AutoFunctorCompose f1 f2 = prop_FunctorCompose (applyFun f1) (applyFun f2) T

type Prop_AutoFunctorCompose structureType origType midType resultType
  = Fun origType midType
  -> Fun midType resultType
  -> structureType origType
  -> Equal (structureType resultType)

main = do
  quickCheck $ eq $ (prop_AutoFunctorId :: Prop_AutoFunctorId (Four' ())Integer)
  quickCheck $ eq $ (prop_AutoFunctorId :: Prop_AutoFunctorId (Four' ()) (Either Bool String))
  quickCheck $ eq $ (prop_AutoFunctorCompose :: Prop_AutoFunctorCompose (Four' ()) String Integer String)
  quickCheck $ eq $ (prop_AutoFunctorCompose :: Prop_AutoFunctorCompose (Four' ()) Integer String (Maybe Int))

2.16.2 Write tests algorithm

  1. Pick the right language/stack to implement features.
  2. How expensive breakage can be.
  3. Pick the right tools to test this.

2.16.3 Shrinking

Process of reducing coplexity in the test case - re-run with smaller values and make sure that the test still fails.

2.17 Logic

2.17.1 Proposition

Purely abtract & theoretical logical object (idea) that has a Boolean value.

* is expressed by a statement. * Atomic proposition

Logically undividable unit. Does not contain logical connectives.

Often abstracts the non-logical ("real") objects. * Compound proposition

Formed by connecting propositions by logical connectives. * Propositional logic

Studies propositions and argument flow.

Distinquishes logically indivisible units (atomic propositions) and abstracts them as variable and constant values of Boolean type properties. Studies consequences of those value aguments (atomic proposition) on composed propositions.

Invented by Aristotle.

Classical system that lead humanity to profound advancement. The classical * language thou is limited and so in modern day extensions (mainly First-order logic) are used in the sciences.

Not Turing-complete, for example it is impossible to construct an arbitrary loop. First-order logic

Extension of a propositional logic that adds quantifiers.

Turing-complete. Second-order logic

Extension over first-order logic that quantifies over relations. Higher-order logic

Extension over second-order logic that uses additional quantifiers, stronger semantics.

Is more expressive, but model-theoretic properties are less well-behaved.

2.17.2 Logical connective

Logical operation. * Conjunction

Logical AND.

Denotation: \( \land \)

Multiplies cardinalities.

Haskell kind:

* * Disjunction

Logical \( OR \) Denotation: \( \lor \)

Summs cardinalities.

Relates to:

2.17.3 Predicate

Function with Boolean codomain. \( P: X \to \{ true, \ false \} \) - * on \( X \).

Notation: \( P(x) \)

Im many cases includes relations, quantifiers.

2.17.4 Statement

Declarative expression that is a bearer of a proposition.

When we talk about expression or statement being true/false - in fact we refer to the proposition that they represent.

Difference between proposition, statement, expression:

  1. "2 + 3 = 5"
  2. "two plus three equals five" Antecedent

The if (requirement) part of the proposition. Consequent

else (consequential) part of the proposition. Vacuous

Nonsensical proposition that has {impossible, not full, false} premise and as such - impossible to definitely prove true nor false (under currently given tools inside the particular theory).

Such proposition falls into paradox due to property of excluded middle in the classical logic.

Requirements of the proposition (antecedent part) cannot be satisfied.

Therefore "vacuous true/false" means: "considered as, but not proven".

Is a good example of why Haskell uses total functions even for if .. then .. else .. statements.

There is also vacuous function in Haskell, see Void.

2.17.5 Iff

If and only if, exectly when, just. Denotation: \( \iff \)

2.18 Haskell structure

2.18.1 *

Haskell structures

2.18.2 Pattern match

Are not first-class. It is a set of patter match semantic notations.

Must be linear.

* precedence (especially with more then one parameter, especially with _ used) often changes the function. As-pattern
f list@(x, xs) = ...
f (x:xs)   = x:x:xs -- Can be compiled with reconstruction of x:xs
f a@(x:_) = x:a -- Reuses structure without reconstruction Wild-card

Matches anything and can not be binded. For matching someting that should pass not checked and is not used.

head (x:_)             = x
tail (_:xs)            = xs Case
case x of
  pattern1  -> ex1
  pattern2  -> ex2
  pattern3  -> ex3
  otherwise -> exDefault

Bolting guards & expressions with syntatic sugar on case:

case () of _
  | expr1     -> ex1
  | expr2     -> ex2
  | expr3     -> ex3
  | otherwise -> exDefault

Pattern matching in function definitions is realized with case expressions. Guard

Check values against the predicate and use the first match definition:

f x
  | predicate1 = definition1
  | predicate2 = definition2
  | x < 0      = definitionN
  | otherwise  = definitionZ * Pattern guard

Allows check a list of pattern matches against functions, and then proceed.

(patternMatch1) <- (funcCheck1)

, (patternMatch2) <- (funcCheck2) = RHS

lookup :: Eq a => a -> [(a, b)] -> Maybe b

addLookup l a1 a2
   | Just b1 <- lookup a1 l
   , Just b2 <- lookup a2 l
   = b1 + b2
{-...other equations...-}

Run functions, they must succeed. Then pattern match results to b1, b2. Only if successful - execute the equation.

Default in Haskell 2010. * Lazy pattern

Defers the pattern match directly to the last moment of need during execution of the code.

f (a, b) = g a b -- It would be checked that the pattern of the pair constructor
-- is present, and that parameters are present in the constructor.
-- Only after that success - work would start on the RHS, aka then construction
-- g would start only then.

f ~(a, b) = g a b -- Pattern match of (a, b) deferred to the last moment,
-- RHS starts, construction of g starts.
-- For this lazy pattern the  equivalent implementation would be:
-- f p = g (fst p) (snd p)  -- RHS starts, during construction of g
-- the arguments would be computed and found, or error would be thrown.

Due to full laziness deferring everything to the runtime execution - the lazy pattern is one-size-fits all (irrefutable), analogous to _, and so it does not produce any checks during compilation, and raises errors during runtime.

* is very useful during recursive construction of recursive structure/process, especially infinite. Pattern binding

Entire LHS is a pattern, is a lazy pattern.

fib@(1:tfib)    = 1 : 1 : [ a+b | (a,b) <- zip fib tfib ] *

2.18.3 Smart constructor

Process/code placing extra rules & constraints on the construction of values.

2.18.4 Level of code

There are these levels of Haskell code: * Type level

Level of code that works with data types. Type level declaration
type ...
newtype ...
data ...
class ...
instance ... Type check

if The type level information is complete (strongly connected graph)


Generalize the types and check if type level consistent to term level.


Infer the missing type level part from the term level. There are certain situations and structures where ambiguity arises and is unsolvable from the information of the term level (most basic example is polymorphic recursion). Complete user-specific kind signature

Type level declaration is considered to "have a CUSK" is it has enough syntatic information to warrant completeness (strongly connected graph) and start checking type level correspondence to term level, it is a ad-hock state ot type inferring.

In the future GHC would use other algorythm over/instead of CUSK. Term level

Level of code that does logical execution. Compile level

Level of code, about compilation processes/results. * Runtime level

Level of code of main program operation, when machine does computations with compiled binary code. Kind level

Level of code where kinds & kind declarations are situated, infered and checked. Kind check

Applying the type check to kind check:

if The kind level information is complete (strongly connected graph)


Check if kind level consistent to term level.


Infer the missing kind level parts from the type level. There are certain situations and structures where ambiguity arises and is unsolvable from the information of the kind level.

With StandaloneKindSignatures kind completeness happens against found (standalone) kind signature.

With CUSKs extension kind completeness happens agains "complete user-specific kind signature" *

2.18.5 Orphan instance

Situation when module provides type class but does not provide instance for some publically used type.

That allows/pushes to implement own version of instance. If upstream would add instance - now upstream instance and own instance exist. Locally that would create instance clash. Remotely, through modules usage - that should create inconsistancy problems in computations, since instances most probably not bisimilar.

If module has any orphans - then in GHC terms all module is called an "orphan module". GHC always visits the interface file of every orphan module below the module being compiled. This is usually a wasted work, but it needs to be done. So do best to have as few orphan modules as possible" ("GHC User’s Guide Documentation, Release 8.8.3"). Orphan prolongs the compilation, and moreover - compilation of all even dependent code on it, because requires recursive lookups into module dependencies.

See: Good: Handling orphan instance.

2.18.6 undefined

Placeholder value that helps to do typechecking.

2.18.7 Hierarchical module name

Hierarchical naming scheme:

Algebra                 -- Was this ever used?
    DomainConstructor   -- formerly DoCon
    Geometric           -- formerly BasGeomAlg

Codec                   -- Coders/Decoders for various data formats
    Binary                 -- these are for encoding binary data into text

    Exception           -- (opt, inc. error & undefined)
    Concurrent          -- as hslibs/concurrent
        Chan            -- these could all be moved under Data
    Parallel            -- as hslibs/concurrent/Parallel
    Monad               -- Haskell 98 Monad library
        ST              -- ST defaults to Strict variant?
            Strict      -- renaming for ST
            Lazy        -- renaming for LazyST
        State           -- defaults to Lazy
        Fix              -- to be renamed to Rec?

    Binary              -- Binary I/O
    Bool                -- &&, ||, not, otherwise
    Tuple               -- fst, snd
    Char                -- H98
    Complex             -- H98
    Maybe               -- H98
    List                -- H98
    Ratio               -- H98
    STRef               -- Same as Data.STRef.Strict
        Lazy            -- The lazy version (for Control.Monad.ST.Lazy)
    Binary              -- Haskell binary I/O
        ...             -- others (CRC ?)
    Array               -- Haskell 98 Array library
        IO              -- mutable arrays in the IO/ST monads
    Graph               -- start with GHC's DiGraph?
    Memo                -- (opt)

    Edison              -- (opt, uses multi-param type classes)
        Prelude         -- large self-contained packages should have
        Collection      -- their own hierarchy?  Like a vendor branch.
        Queue           -- Or should the whole Edison tree be placed


    ...                 -- Mirrors the MS .NET class hierarchy

Debug                   -- see also: Test
    Observe             -- choose a default amongst the variants
        Textual            -- Andy Gill's release 1
        ToXmlFile          -- Andy Gill's XML browser variant
        GHood              -- Claus Reinke's animated variant

    ForeignPtr  -- rename to FinalisedPtr?  to void confusion with Foreign.Ptr

    Exts                -- hslibs/lang/GlaExts



    Haskell             -- hslibs/hssource


Numeric                 -- exports std. H98 numeric type classes

Network                 -- (== hslibs/net/Socket), depends on FFI only
    BER                 -- Basic Encoding Rules
    Socket              -- or rename to Posix?
    URI                 -- general URI parsing
    CGI                 -- one in hslibs is ok?

Prelude                 -- Haskell98 Prelude (mostly just re-exports
                           other parts of the tree).

Sound                   -- Sound, Music, Digital Signal Processing
    SC3                 -- SuperCollider

System                  -- Interaction with the "system"
    Cmd                 -- ( system )
    CPUTime             -- H98
    Directory           -- H98
    Exit                -- ( ExitCode(..), exitWith, exitFailure )
    Environment         -- ( getArgs, getProgName, getEnv ... )
    Info                -- info about the host system
    IO                  -- H98 + IOExts - IOArray - IORef
        Unsafe          -- unsafePerformIO, unsafeInterleaveIO
    Locale              -- H98
    Mem                 -- rename from cryptic 'GC'
        Weak            -- (opt)
        StableName      -- (opt)
    Time                -- H98 + extensions
    Win32               -- the full win32 operating system API


        Lex             -- cut down lexer for "read"
        Functions       -- optional instance of Show for functions.
    Regex               -- previously RegexString
        Posix           -- Posix regular expression interface
    PrettyPrint         -- default (HughesPJ?)
    HTML                -- HTML combinator lib
    ParserCombinators   -- no default
        ReadP           -- a more efficient "ReadS"

Training                --  Collect study and learning materials
    <name of the tutor>

2.18.8 Reserved word

Haskell has special meaning for:

case, class, data, deriving, do,else, if, import,
in, infix, infixl, infixr, instance, let,
of, module, newtype, then, type, where * import

import statement by default imports identifiers from the other module, using hierarchical module name, brings into scope the identifiers to the global scope both into unqualified and qualifies by the hierarchical module name forms.

This possibilities can mix and match:

  • <modName> () - import only instances of type classes.
  • <modName> (x, y) - import only declared indentifiers.
  • qualified <modName> - discards unqialified names, forse obligatory namespace for the imports.
  • hiding (x, y) - skip import of declared identifies.
  • <modName> as <modName> - renames module namespace.
  • <type/class> (..) - import class & it's methods, or type, all its data constructors & field names. let

* expression is a set of cross-recursive lazy pattern bindings.

Declarations permitted:

It is an expression (macro) and that integrates in external lexical scope expression it applied in.


  c where

Part of the syntax of the whole function declaration, has according scope.

As part of whole declaration - can extend over definitions of the funtion (pattern matches, guards).


f match1 = y
f match2 = y
f x =
  | cond1 x = y
  | cond2 x = y
  | otherwise = y
  y = ... x ... *

2.18.10 Haskell'

Current language development mod. *

2.18.11 Lense

Library of combinators to provide Haskell (functional language without mutation) with the emulation of get-ters and set-ters of imperative language.

2.18.12 Pragma

Pragma - instruction to the compiler that specifies how a compiler should process the code. Pragma in Haskell have form:

{-# PRAGMA options #-} LANGUAGE pragma

Controls what variations of the language are permitted. It has a set of allowed options:, which can be supplied. LANGUAGE option * Useful by default
{-# LANGUAGE EmptyCase #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE InstanceSigs #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE BlockArguments    #-}
{-# LANGUAGE LambdaCase        #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE TypeApplications  #-} AllowAmbiguousTypes

Allow type signatures which appear that they would result in an unusable binding. However GHC will still check and complain about a functions that can never be called. ApplicativeDo

Enables an alternative in-depth reduction that translates the do-notation to the operators <$>, <*>, join as far as possible.

For GHC to pickup the patterns, the final statement must match one of these patterns exactly:

pure E
pure $ E
return E
return $ E

When the statements of do expression have dependencies between them, and ApplicativeDo cannot infer an Applicative type - GHC uses a heuristic \( O(n^2) \) algorithm to try to use <*> as much as possible. This algorithm usually finds the best solution, but in rare complex cases it might miss an opportunity. There is aslo \( O(n^3) \) algorithm that finds the optimal solution: -foptimal-applicative-do.

Requires ap = <*>, return = pure, which is true for the most monadic types.

The only way it shows up at the source level is that you can have a do expression with only Applicative or Functor constaint.

It is possible to see the actual translation by using -ddump-ds. ConstrainedClassMethods

Enable the definition of further constraints on individual class methods. CPP

Enable C preprocessor. DeriveFunctor

Automatic deriving of instances for the Functor type class. For type power set functor is unique, its derivation inplementation can be autochecked. ExplicitForAll

Allow explicit forall quantificator in places where it is implicit by Haskell. FlexibleContexts

Ability to use complex constraints in class declaration contexts. The only restriction on the context in a class declaration is that the class hierarchy must be acyclic.

class C a where
  op :: D b => a -> b -> b

class C a => D a where ...

\( C :> D \), so in C we can talk about D.

Synergizes with ConstraintKinds. FlexibleInstances

Allow type class instances types contain nested types.

instance C (Maybe Int) where ...

Implies TypeSynonymInstances. GeneralizedNewtypeDeriving

Enable GHC’s newtype cunning generalised deriving mechanism.

newtype Dollars = Dollars Int
  deriving (Eq, Ord, Show, Read, Enum, Num, Real, Bounded, Integral)

(In old Haskell 98 only Eq, Ord, Enum could been inherited.) ImplicitParams

Allow definition of functions expecting implicit parameters. In the Haskell that has static scoping of variables allows the dynamic scoping, such as in classic Lisp or ELisp. Sure thing this one can be puzzling as hell inside Haskell. LambdaCase

Enables expressions of the form:

\case { p1 -> e1; ...; pN -> eN }

-- OR

  p1 -> e1
  pN -> eN MultiParamTypeClasses

Implies: ConstrainedClassMethods Enable the definitions of typeclasses with more than one parameter.

class Collection c a where MultiWayIf

Enable multi-way-if syntax.

if | guard1 -> code1
   | ...
   | guardN -> codeN OverloadedStrings

Enable overloaded string literals (string literals become desugared via the IsString class).

With overload, string literals has type:

(IsString a) => a

The usual string syntax can be used, e.g. ByteString, Text, and other variations of string-like types. Now they can be used in pattern matches as char->integer translations. To pattern match Eq must be derived.

To use class IsString - import it from GHC.Ext. PartialTypeSignatures

Partial type signature containins wildcards, placeholders (_, _name). Allows programmer to which parts of a type to annotate and which to infer. Also applies to constraint part.

As untuped expression, partly typed can not polymorphicly recurse.

-Wno-partial-type-signatures supresses infer warnings. RankNTypes

Enable types of arbitrary rank. See Type rank.

Implies ExplicitForAll.

Allows forall quantifier: ScopedTypeVariables

By default type variables do not have a scope except inside type signatures where they are used.

Extension allows:

When there are internall type signatures provided in the code block (where, let, etc.) they (main type description of a function and internal type descriptions) restrain one-another and become not trully polymorphic, which creates a bounding interdependency of types that GHC would complain about.

* option provides the lexical scope inside the code block for type variables that have forall quantifier. Because they are now lexiacally scoped - those type variables are used across internal type signatures.

Implies ExplicitForAll.

See: GHC documentation, explanation blogpost, typeclasses article. TupleSections

Allow tuple section syntax:

(, True)
(, "I", , , "Love", , 1337) TypeApplications

Allow type application syntax:

read @Int 5

:type pure @[]
pure @[] :: a -> [a]

:type (<*>) @[]
(<*>) @[] :: [a -> b] -> [a] -> [b]


instance (CoArbitrary a, Arbitrary b) => Arbitrary (a -> b)

λ> ($ 0) <$> generate (arbitrary @(Int -> Int)) TypeSynonymInstances

Now type synonim can have it's own type class instances. UndecidableInstances

Permit instances which may lead to type-checker non-termination.

GHC has Instance termination rules regardless of FlexibleInstances FlexibleContexts. ViewPatterns
foo (f1 -> Pattern1) = c1
foo (fn -> Pattern2 a b) = g1 a b

(expressionpattern): take what is came to match - apply the expression, then do pattern-match, and return what originally came to match.


  • expression & pattern share the scope, so also variables.
  • expression :: t1 -> t2) && (pattern">t2)=) then (ViewPattern (/expression/ -> /pattern/) :: t1) (return what originally was recieved into pattern match) else skip

* are like pattern guards that can be nested inside of other patterns. * are a convenient way to pattern-match algebraic data type.

Additional possible usage:

foo a (f2 a -> Pattern3 b c) = g2 b c  -- only for function definitions
foo ((f,_), f -> Pattern4) = c2  -- variables can be bount to the left in data constructors and tuples DatatypeContexts

Allow contexts in data types.

data Eq a => Set a = NilSet | ConsSet a (Set a)

-- NilSet :: Set a
-- ConsSet :: Eq a => a -> Set a -> Set a

Considered misfeature. Deprecated. Going to be removed. StandaloneKindSignatures

Type signatures for type-level declarations.

type <name_1> , ... , <name_n> :: <kind>
type MonoTagged :: Type -> Type -> Type
data MonoTagged t x = MonoTagged x

type Id :: forall k. k -> k
type family Id x where
  Id x = x

type C :: (k -> Type) -> k -> Constraint
class C a b where
  f :: a b

type TypeRep :: forall k. k -> Type
data TypeRep a where
  TyInt   :: TypeRep Int
  TyMaybe :: TypeRep Maybe
  TyApp   :: TypeRep a -> TypeRep b -> TypeRep (a b)

< GHC 8.10.1 - type signatures were only for term level declarations.

Extension makes signatures feature more uniformal.

Allows to set the order of quantification, order of variables in a kind. For example when using TypeApplications.

Allows to set full kind of derivable class, solving situations with GADT return kind. * PartialTypeSignatures

Very healpful. Helps to solve type level, helps to establish type signatures and constraints. Allow to provide _ in the type signatures to automatically infere-in the type information there.

Wild cards:

f :: _ -> _ -> a
f :: _ => a -> b -> c
  • Named
f :: _x -> _x -> a

allows to identify the same wildcard. TypeOperators

Allow type signature to hold operator names:

data a + b = Plus a b

Implies ExplicitNamespaces How to make a GHC LANGUAGE extension

In libraries/ghc-boot-th/GHC/LanguageExtensions/Type.hs add new constructor to the Extension type

data Extension
  = Cpp
  | OverlappingInstances
  | Foo

/main/DynFlags.hs extend xFlagsDeps:

xFlagsDeps = [
  flagSpec "AllowAmbiguousTypes" LangExt.AllowAmbiguousTypes,
  flagSpec "Foo"                 LangExt.Foo

It is for basic case. For testing, parser see further:

2.19 Computer science

2.19.1 Guerrilla patch

* changing code/applying patch sneakily - and possibility incompatibility with other at runtime. Monkey patch is derivative term. Monkey patch

From Guerrilla patch.

* is a way for program to modify supporting system software affecting only the running instance of the program.

2.19.2 Interface

Point of mutual meeting. Code behind interface determines how data is consumed.

2.19.3 Module

Importable organizational unit.

2.19.4 Scope

Area where binds are accessible. Dynamic scope

The name resolution depends upon the program state when the name is encountered, which is determined by the execution context or calling context. Lexical scope

Scope bound by the structure of source code where the named entity is defined. * Local scope

Scope applies only in (current) area. *

2.19.5 Shadowing

When in the local scope bigger scope variable overriden by same name variable from the local scope.

2.19.6 Syntatic sugar

Artificial way to make language easier to read and write.

2.19.7 System F

Is parametric polymorphism in programming.

Extends the Lambda calculus by introducing \( \forall \) (universal quantifier) over types.

2.19.8 Tail call

Final evaluation inside the function. Produces the function result.

2.19.9 Thunk

Not evaluated calculation. Can be dragged around, until be lazily evaluated.

2.19.10 Application memory

Table 11: Application memory structural parts
Storage of Block name
All not currently processing data Heap
Function call, local variables Stack
Static and global variables Static/Global
Instructions Binary code

When even Main invoked - it work in Stack, and called Stack frame. Stack frame size for function calculated when it is compiled. When stacked Stack frames exceed the Stack size - stack overflow happens.

2.19.11 Turing machine

Mathematical model of computation that defines abstract Turing machine. Abstract machine which manipulates symbols on a strip of tape, according to a table of rules.

2.19.12 REPL

Read-eval-print loop, aka interactive shell.

2.19.13 Domain specific language

Language design/fitted for particular domain of application. Mainly should be Turing incomplete, since general-purpose language implies Turing completeness. Embedded domain specific language

DSL used inside outer language.

Two levels of embedding: *

2.19.14 Data structure Cons cell

Cell that values may inhabit. Construct
(:) :: a -> [a] -> [a] * Leaf
_ Node
/ \ Spine

Is a chain of memory cells, each points to the both value of element and to the next memory cell.


 / \
1   :
   / \
  2   :
     / \
    3  []


 / \
_   :
   / \
  _   :
     / \
    _  []

2.20 Graph theory

2.20.1 Successor

Object that recieves the arrow. Direct successor

Immidiate successor.

2.20.2 Predecessor

Object that sends arrow. Direct predecessor

Immidiate predecessor.

2.20.3 Degree

Number of arrows of object. Indegree

Number of ingoing arrows. Outdegree

Number of outgoinf arrows.

2.20.4 Adjacency matrix

Matrix of connection of odjects {-1,0,1}. InstanceSigs

Allow adding type signatures to type class function instance declaration.

2.20.5 Strongly connected

If every vertex in a graph is reachable from every other vertex.

It is possible to find all strongly connected components (and that way also test graph for strong connectivity), in linear time (Θ(V+E)).

Binary relation of being strongly connected is an equivalence relation. * Strongly connected component

Full strongly connected subgraph of some graph.

* of a directed graph G is a subgraph that is strongly connected, and has property: no additional edges or vertices from G can be included in the subgraph without breaking its property of being strongly connected.

2.21 Tagless-final

Method of embedding eDSL in a typed functional host language (Haskell). Alternative to the embedding as a (generalized) algebraic data type. For parsers of DLS expressions: (1/partial) evaluator, compiler, pretty printer, multi-pass optimizer.

* embedding is writing denotational semantics for the DSL in the host language.

Approach can be used iff eDSL is typed. Only well-typed terms become embeddable, and host language can implemen also a eDSL type system. Approach that eDSL code interpretations are type-preserving.

One of main pros of * - extensibility: implementation of DSL can be used to analyze/evaluate/transform/pretty-print/compile and interpreters can be extended to more passes, optimizations, and new versions of DSL while keeping/using/reusing the old versions.

Example fields of application: language-integrated queries, non-deterministic & probabilistic programming, delimiter continuation, computability theory, stream processsing, hardware description languages, generation of specialized numerical kernels, semantics of natural language.

2.22 Prefix notation

Operators then their operands.

2.22.1 *

2.22.2 Postfix notation

Operands then their opration.

3 Give definitions

3.3 Gen

3.7 Function image

3.7.1 *

3.10 Define LANGUAGE pragma options

3.10.2 GADTs

GADT is a generalization over parametric algebraic data types which allow explicitly denote the types (type matching) of the constructors and define data types using pattern matching on the left side of "data" statements.

3.13 Order theory

Investigates in thepth the intuitive notion of order using binary relations.

3.13.1 Domain theory

Formalizes approximation and convergense. Has close relation to Topology.

3.13.2 Lattice

Partially ordered set in which any two elements have unique supremum and infinum.

\( P = (X, \le ), \forall \{x_{1}, x_{2}\} \in X \ : \ \exists! \{inf, sup\}(\{x_{1},x_{2}\}) \)

\( x \lor (y \land x) \ = \ (x \lor y) \land x \ = \ x \)

Most of partially ordered sets are not lattices.

3.13.3 Order Preorder

RX → X : Reflexive & Transitive: \( aRa \) \( aRb, bRc \Rightarrow aRc \)

Generalization of equivalence relations partial orders.

* Antisymmetric ⇒ Partial ordering. * SymmetricEquivalence. * Total preorder

\( \forall a,b : a \le b \lor b \le a \) ⇒ Total Preorder. Partial order

A binary relation must be reflexive, antisymmetric and transitive.

Partial - not every elempents between them need to be comparable.

Good example of * is a genealogical descendancy. Only related people produce relation, not related do not. Total order Chain

Totally ordered set, aka sequence.

3.15 Relation

3.15.1 Reflexivity

\( R^{X \to X}, \forall x \in X : x R x \) Order theory: \( a \le a \)

* - each element is comparable to itself.

Corresponds to Identity and Automorphism.

3.15.2 Irreflexivity

\( R^{X \to X}, \forall x \in X : \nexists R(x, x) \)

3.15.3 Transitivity

\( \forall a,b,c \in X, \forall R^{X \to X} : (aRb \land bRc) \Rightarrow aRc \)

* - the start of a chain of precedence relations must precede the end of the chain.

3.15.4 Symmetry

\( \forall a,b \in X : (aRb \iff bRa) \)

3.15.5 Equivalence

Reflexive Symmetric Transitive
\( \forall x \in X, \exists R : x R x \) \( \forall a,b \in X : (aRb \iff bRa) \) \( \forall a,b,c \in X, \forall R^{X \to X} : (aRb \land bRc) \Rightarrow aRc \)
\( a = a \) \( a = b \iff b = a \) \( a = b, b = c \Rightarrow a = c \)

3.15.6 Antisymmetry

\( \forall a, b \in X : aRb, bRa \Rightarrow a = b \) ~ \( aRb, a \ne b \Rightarrow \nexists bRa \). Antisymmetry does not say anything about \( R(a,a) \).

* - no two different elements precede each other.

3.15.7 Asymmetry

\( \forall a,b \in X (aRb \Rightarrow \neg (bRa)) \) * \( \iff \) AntisymmetricIrreflexive. Asymmetry ≠ "not symmetric" SymmetricAsymmetric is only empty relation.

3.16 Cryptomorphism

Equivalent, interconvertable with no loss of information.

3.16.1 *

3.18 Abstract data type

Several definitions here, reduce them.

Data type mathematical model, defined by its semantics from the user point of view, listing possible values, operations on the data of the type, and behaviour of these operations.

* class of objects whose logical behaviour is defined by a set of values and set of operations (analogue to algebraic structure in mathematics).

A specification of a data type like a stack or queue where the specification does not contain any implementation details at all, only the operations for that data type. This can be thought of as the contract of the data type.

3.18.1 *

3.24 Symbolic expression

Nested tree data structure.

Introduced & used in Lisp. Lisp code and data are *.

* in Lisp: Atom or expression of the form (x . y), x and y are *.

Modern abbriviated notation of *: (x y).

3.25 Polynomial

Expression consisting of:

  • variables
  • coefficients
  • addition
  • substraction
  • multiplication (including positive integer variable exponentiation)

Polynomials form a ring. Polynomial ring.

3.25.1 *

3.26 Data family

Indexed form of data and newtype definitions.

3.27 Type synonym family

Indexed form of type synonyms.

3.28 Indexed type family

* additional stucture in language that allows ad-hoc overloading of data types. AKA are to types as type class to methods.


Defined by pattern matching the partial functions between types. Associates data types by type-level function defined by open-ended collection of valid instances of input types and corresponding output types.

Normal type classes define partial functions from types to a collection of named values by pattern matching on the input types, while type families define partial functions from types to types by pattern matching on the input types. In fact, in many uses of type families there is a single type class which logically contains both values and types associated with each instance. A type family declared inside a type class is called an associated type.

3.28.1 *

3.29 TypeFamilies

Allow use and definition of indexed type families and data families.

* are type-level programming. * are overload data types in the same way that type classes overload functions. * allow handling of dependent types. Before it Functional dependencies and GADTs were used to solve that. * useful for generic programming, creating highly parametrised interfaces for libraries, and creating interfaces with enhanced static iformation (much like dependent types).

Implies: MonoLocalBinds, KindSignatures, ExplicitNamespaces

Two types of * are:

3.30 Error

Mistake in the program that can be resolved only by fixing the program.

error is a sugar for undefined.

Distinct from Exception.

3.30.1 *

3.31 Exception

Expected but irregular situation.

Distinct from Error. Also see 5.28

3.31.1 *

3.32 ConstraintKinds

Constraints are just handled as types of a particular kind (Constraint). Any type of the kind Constraints can be used as a constraint.

type Some a = (Show a, Ord a, Arbitrary a) -- is of kind Constraint.
  • Anything form of which is not yet known, but the user has declared for it to have kind Constraint (for which they need to import it from GHC.Exts):
Foo (f :: Type -> Constraint) = forall b. f b => b -> b -- is allowed
-- as well as examples involving type families:
type family Typ a b :: Constraint
type instance Typ Int  b = Show b
type instance Typ Bool b = Num b

func :: Typ a b => a -> b -> b
func = ...

3.33 Specialisation

Turns ad hoc polymorphic function into compiled type-specific inmpementations.

3.34 Diagram

For categories C and J, a diagram of type J in C is a covariant functor D : J → C.

3.35 Cathegory theoretical presheaf

For categories C and J, a J-presheaf on C is a contravariant functor D : C → J.

3.36 Topological presheaf

If X is a topological space, then the open sets in X form a partially ordered set Open(X) under inclusion. Like every partially ordered set, Open(X) forms a small category by adding a single arrow U → V if and only if U ⊆ V. Contravariant functors on Open(X) are called presheaves on X. For instance, by assigning to every open set U the associative algebra of real-valued continuous functions on U, one obtains a presheaf of algebras on X.

3.37 Diagonal functor

The diagonal functor is defined as the functor from D to the functor category DC which sends each object in D to the constant functor at that object.

3.38 Limit functor

For a fixed index category J, if every functor J → C has a limit (for instance if C is complete), then the limit functor CJ → C assigns to each functor its limit. The existence of this functor can be proved by realizing that it is the right-adjoint to the diagonal functor and invoking the Freyd adjoint functor theorem. This requires a suitable version of the axiom of choice. Similar remarks apply to the colimit functor (which is covariant).

3.39 Dual vector space

The map which assigns to every vector space its dual space and to every linear map its dual or transpose is a contravariant functor from the category of all vector spaces over a fixed field to itself.

3.40 Fundamental group

Consider the category of pointed topological spaces, i.e. topological spaces with distinguished points. The objects are pairs (X, x0), where X is a topological space and x0 is a point in X. A morphism from (X, x0) to (Y, y0) is given by a continuous map f : X → Y with f(x0) = y0.

To every topological space X with distinguished point x0, one can define the fundamental group based at x0, denoted π1(X, x0). This is the group of homotopy classes of loops based at x0. If f : X → Y is a morphism of pointed spaces, then every loop in X with base point x0 can be composed with f to yield a loop in Y with base point y0. This operation is compatible with the homotopy equivalence relation and the composition of loops, and we get a group homomorphism from π(X, x0) to π(Y, y0). We thus obtain a functor from the category of pointed topological spaces to the category of groups.

In the category of topological spaces (without distinguished point), one considers homotopy classes of generic curves, but they cannot be composed unless they share an endpoint. Thus one has the fundamental groupoid instead of the fundamental group, and this construction is functorial.

3.41 Algebra of continuous function

A contravariant functor from the category of topological spaces (with continuous maps as morphisms) to the category of real associative algebras is given by assigning to every topological space X the algebra C(X) of all real-valued continuous functions on that space. Every continuous map f : X → Y induces an algebra homomorphism C(f) : C(Y) → C(X) by the rule C(f)(φ) = φ ∘ f for every φ in C(Y).

3.42 Tangent and cotangent bundle

The map which sends every differentiable manifold to its tangent bundle and every smooth map to its derivative is a covariant functor from the category of differentiable manifolds to the category of vector bundles.

Doing this constructions pointwise gives the tangent space, a covariant functor from the category of pointed differentiable manifolds to the category of real vector spaces. Likewise, cotangent space is a contravariant functor, essentially the composition of the tangent space with the dual space above.

3.43 Group action / representation

Every group G can be considered as a category with a single object whose morphisms are the elements of G. A functor from G to Set is then nothing but a group action of G on a particular set, i.e. a G-set. Likewise, a functor from G to the category of vector spaces, VectK, is a linear representation of G. In general, a functor G → C can be considered as an "action" of G on an object in the category C. If C is a group, then this action is a group homomorphism.

3.44 Lie algebra

Assigning to every real (complex) Lie group its real (complex) Lie algebra defines a functor.

3.45 Tensor product

If C denotes the category of vector spaces over a fixed field, with linear maps as morphisms, then the tensor product V ⊗ W defines a functor C × C → C which is covariant in both arguments.

3.46 Forgetful functor

The functor U : Grp → Set which maps a group to its underlying set and a group homomorphism to its underlying function of sets is a functor.[8] Functors like these, which "forget" some structure, are termed forgetful functors. Another example is the functor Rng → Ab which maps a ring to its underlying additive abelian group. Morphisms in Rng (ring homomorphisms) become morphisms in Ab (abelian group homomorphisms).

3.47 Free functor

Going in the opposite direction of forgetful functors are free functors. The free functor F : Set → Grp sends every set X to the free group generated by X. Functions get mapped to group homomorphisms between free groups. Free constructions exist for many categories based on structured sets. See free object.

3.48 Homomorphism group

To every pair A, B of abelian groups one can assign the abelian group Hom(A, B) consisting of all group homomorphisms from A to B. This is a functor which is contravariant in the first and covariant in the second argument, i.e. it is a functor Abop × Ab → Ab (where Ab denotes the category of abelian groups with group homomorphisms). If f : A1 → A2 and g : B1 → B2 are morphisms in Ab, then the group homomorphism Hom(f, g): Hom(A2, B1) → Hom(A1, B2) is given by φ ↦ g ∘ φ ∘ f. See Hom functor.

3.49 Representable functor

We can generalize the previous example to any category C. To every pair X, Y of objects in C one can assign the set Hom(X, Y) of morphisms from X to Y. This defines a functor to Set which is contravariant in the first argument and covariant in the second, i.e. it is a functor Cop × C → Set. If f : X1 → X2 and g : Y1 → Y2 are morphisms in C, then the group homomorphism Hom(f, g) : Hom(X2, Y1) → Hom(X1, Y2) is given by φ ↦ g ∘ φ ∘ f.

Functors like these are called representable functors. An important goal in many settings is to determine whether a given functor is representable.

3.51 Coinduction

proper definition

* dual to induction. Generalises to corecursion.

3.54 Continuation

3.54.1 Continuation passing style *


3.55 Control.Concurrent.Async

Good library for concurrency programming.

3.56 Semilattice

4 Citation

"One of the finer points of the Haskell community has been its propensity for recognizing abstract patterns in code which have well-defined, lawful representations in mathematics." (Chris Allen, Julie Moronuki - "Haskell Programming from First Principles" (2017))

5 Good code

5.1 Good: Type aliasing

Use data type aliases to deferentiate logic of values.

5.2 Good: Type wideness

Wider the type the more it is polymorphic, means it has broader application and fits more types.

The more constrained system has more usefulness.

Unconstrained means most flexible, but also most useless.

5.3 Good: Print

print :: Show a => a -> IO ()
print a = putStrLn (show a)

5.4 Good: Fold

foldr spine recursion intermediated by the folding. Can terminate at any point. foldl spine recursion is unconditional, then folding starts. Unconditionally recurses across the whole spine, if it infinite - infinitely.

5.5 Good: Computation model

Model the domain and types before thinking about how to write computations.

5.11 Good: Arbitrary

Product types can be tested as a product of random generators. Sum types require to implement generators with separate constructors, and picking one of them, use oneof or frequency to pick generators.

5.13 Good: Function composition

In Haskell inline composition requires:

h.g.f $ i

Function application has a higher priority than composition. That is why parentheses over argument are needed. This precedence allows idiomatically compose partially applied functions.

But it is a way better then:

h (g (f i))

5.14 Good: Point-free

Use Tacit very carefully - it hides types and harder to change code where it is used. Use just enough Tacit to communicate a bit better. Mostly only partial point-free communicates better.

5.14.1 Good: Point-free is great in multi-dimentions

BigData and OLAP analysis.

5.15 Good: Functor application

Function application on n levels beneath:

(fmap . fmap) function twoLevelStructure

How fmap . fmap typechecks:

(.)         :: (b -> c) -> (a -> b) -> a -> c
fmap        :: Functor f => (m -> n) -> f m -> f n
fmap        :: Functor g => (x -> y) -> g x -> g y

fmap . fmap :: (Functor f, Functor g)
              => ((g x -> g y) -> f . g x -> f . g y)
              -> ((  x ->   y) ->     g x  ->    g y)
              -> (   x ->   y) -> f . g x -> f . g y
fmap . fmap ::   (x    ->   y) -> f . g x -> f . g y

5.16 Good: Parameter order

In functions parameter order is important. It is best to use first the most reusable parameters. And as last one the one that can be the most variable, that is important to chain.

5.17 Good: Applicative monoid

There can be more than one valid Monoid for a data type. && There can be more than one valid Applicative instance for a data type. -> There can be differnt Applicatives with different Monoid implementations.

5.18 Good: Creative process

5.18.1 Pick phylosophy principles one to three the more - the harder the implementation

5.18.2 Draw the most blurred representation

5.18.3 Deduce abstractions and write remotely what they are

5.18.4 Model of computation Model the domain Model the types Think how to write computations

5.18.5 Create

5.19 Good: About operators (<$ ) ( **>) (<* ) (>> )

Where character is not present - discard the according processing of a parameter. (>> ) is an exception, it does the reverse. ignores the first parameter, in fact >> \equiv *>.

= *>= does the proper action: does calculation, but ignores the value from the first argument.

5.20 Good: About functions like {mapM, sequence}_

Trailing _ means ignoring the result.

5.21 Good: Guideliles

5.21.1 Wiki.haskell Documentation Comments write in application terms, not technical. Tell what code needs to do not how it does. Haddoc Put haddock comments to ever exposed data type and function. Haddock header
{- |
Module      :  <File name or $Header$ to be replaced automatically>
Description :  <optional short text displayed on contents page>
Copyright   :  (c) <Authors or Affiliations>
License     :  <license>

Maintainer  :  <email>
Stability   :  unstable | experimental | provisional | stable | frozen
Portability :  portable | non-portable (<reason>)

<module description starting at first column>
-} Code Try to stay closer to portable (Haskell98) code Try make lines no longer 80 chars Last char in file should be newline Symbolic infix identifiers is only library writer right Every function does one thing.

5.22 Good: Use Typed holes to progress the code

Typed holes help build code in complex situations.

5.24 Good: Use type sysnonims to differ the information

Even if there is types - define type synonims. They are free. That distinction with synonims, would allow TypeSynonymInstances, which would allow to create a diffrent type class instances and behaviour for different information.

5.25 Good: Use Control.Monad.Except instead of Control.Monad.Error

5.26 Good: Monad OR Applicative Start writing monad using 'return', 'ap', 'liftM', 'liftM2', '>>' instead of 'do','>>='

If you wrote code and really needed only those - move that code to Applicative.

return -> pure
ap -> <*>
liftM -> liftA -> <$>
>> -> *> Basic case when Applicative can be used

Can be rewriten in Applicative:

func = do
  a <- f
  b <- g
pure (a, b)

Can't be rewritten in Applicative:

somethingdoSomething' n = do
a <- f n
b <- g a
pure (a, b)

(f n) creates monadic structure, binds ot to a wich is consumed then by g. Applicative block vs Monad block

With Type Applicative every condition fails/succseeds independently. It needs a boilerplate data constructor/value pattern matching code to work. And code you can write only for so many cases and types, so boilerplate can not be so flexible as Monad that allows polymorphism. With Type Monad computation can return value that dependent from the previous computation result. So abort or dependent processing can happen.

5.27 Good: Linear type

Linear types are great to control/minimize resource usage.

5.28 Good: Exception vs Error

Many languages and Haskell have it all mixup. Here is table showing what belongs to one or other in standard libraries:

Exception Prelude.catch, Control.Exception.catch, Control.Exception.try, IOError, Control.Monad.Error
Error error, assert, Control.Exception.catch, Debug.Trace.trace

5.29 Good: Let vs. Where

let ... in ... is a separate expression. In contrast, where is bound to a surrounding syntactic construct (namespace).

5.30 Good: RankNTypes

Can powerfully synergyze with ScopedTypeVariables.

5.31 Good: Handling orphan instance

Practice to address orphan instances:

Does type class or type defined by you:

Type class Type Recommendation
  {Type, instance} in the same module
  {Type class & instance} in the same module
    {Define newtype wrap, its instances} in the same module

5.32 Good: Smart constructor

Only proper smart constructors should be exported. Do not export data type constructor, only a type.

5.34 Good: Recursion

Writing/thinking about recursion:

  1. Find the base cases, om imput of which the answer can be provided right away. There is mosly one base case, but sometimes there can be several of them. Typical base cases are: zero, the empty list, the empty tree, null, etc.
  2. Do inductive case. The recursive invocation. The argument of a recursive call needs to be smaller then the current argument. So it would be gradually closer to the base case. The idea is that processes eventually hits the base case.

Simple functional application is used in the recursion. Assume that the functions would return the right result.

5.35 Good: Monoid

<>: Sets - union. Maps - left-biased union. Number - Sum, Product form separate monoid categories.

5.36 Good: Free monad

The main case of usage of Free monads in Haskell:

Start implementation of the monad from a Free monad, drafting the base monadic operations, then add custom operations.

Gradually build on top of Free monad and try to find homomorphisms from monad to objects, and if only objects are needed - get rid of the free monad.

5.40 Good: Patternmatching is possible on monadic bind in do


instance (Monad m) => Functor (StateT s m) where
  fmap f m = StateT $ \s -> do
    (x, s') <- runStateT m s  -- Here is a pattern matching bind
    return (f x, s')

5.41 Good: Applicative vs Monad

Giving not Monad but Applicative requirement allows parralel computation, but if there should be a chaining of the intemidiate state - it must be monadic.

5.42 Good: StateT, ReaderT, WriterT

Reader trait: (r ->).

Writer trait: (a, w).

State trait is combination of both:

newtype StateT s m a =
  StateT  { runStateT  :: s -> m (a, s) }

newtype ReaderT r m a =
  ReaderT { runReaderT :: r -> m   a    }

newtype WriterT w m a =
  WriterT { runWriterT ::     m (a, w) }

State trait fully replaces writer.

5.43 Good: Working with MonadTrans and lift

From the lift . pure = pure follows that MonadTrans type can have a pure defined with lift.

Stacking of MonadTrans monads can result in a lot of chained lift and unwraps. There is many ways to cope with that but the most robust and common is to abstract representation with newtype on the Monad stack. This can reduce caining or remove the manual lifting withing the Monad. For perfect combination for contributors to be able to extend the code - keep the Internal module that has a raw representation.

5.44 Good: Don't mix Where and Let

let and where create a recursive set of definitions with can explode, don't mix them togather in code.

5.45 Good: Where vs. Let

Let is self-recursive lazy pattern. It is checked and errors only at execution time. Binds only inside expression it is binded to.

Where is a part of definition, scoped over definition implemetations and guards, not self-recursive.

5.46 Good: The proper nature algorithm that models behaviour of many objects is computation heavy

God does not care about our mathematical difficulties. He integrates empirically.

One who is found of mathematical meaning loves to apply it. But if we implement the "real" algorithms behind nature processes, we face the need to go through the computations of properties of all particles.

Computation of nature is always a middle way between ideal theory behaviour and computation simplification.

5.47 Good: In Haskell parameters bound by lambda declaration instantiate to only one concrete type

Because of let-bound polymorphism:

This is illegal in Haskell:

foo :: (Int, Char)
foo = (\f -> (f 1, f 'a')) id

Lambda-bound function (i.e., one passed as argument to another function) cannot be instantiated in two different ways, if there is a let-bound polymorphism.

5.48 Good: Instance is a good structure to drew a type line

Instances for data type can differentiate by constraints & types of arguments. So instance can preserve type boundary, and data type declaration can stay very polymorphic. If the need to extend the type boundaries arrives - the instances may extend, or new instances are created, while used data type still the same and unchanged.

5.49 Good: MTL vs. Transformers

Default ot mtl.

Transformers is Haskell 98, doesn't have funcitonal dependencies, lacks the monad classes, has manual lift of operations to the composite monad.

MTL extends trasformers, providing more instances, features and possibilities, may include alternative packages features as mtl-tf.

6 Bad code

6.1 Bad pragma

6.1.1 Bad: Dangerous LANGUAGE pragma option

7 Useful functions to remember

7.1 Prelude

show :: Show a => a -> String
sequence - Evaluate each monadic action in the structure from left to right, and collect the results.
:sprint - show variables to see what has been evaluated already.
minBound - smaller bound
maxBound - larger bound
cycle :: [a] -> [a] - indefinitely cycle s list
repeat - indefinit lis from value
elemIndex e l - return first index, returns Maybe
fromMaybe (default if Nothing) e ::Maybe a -> a
lookup :: Eq a => a -> [(a, b)] -> Maybe b

7.1.1 Ord


7.1.2 Calc

div - always makes rounding down, to infinity divMod - returns a tuple containing the result of integral division and modulo

7.1.3 List operations

concat - [ [a] ] -> [a]
elem x xs - is element a part of a list
zip :: [a] -> [b] -> [(a, b)] - zips two lists together. Zip stops when one list runs out.
zipWith :: (a -> b -> c) -> [a] -> [b] -> [c] - do the action on corresponding elements of list and store in the new list

7.2 Data.List

intersperse :: a -> [a] -> [a]  -  gets the value and incerts it between values in array
nub - remove duplicates from the list

7.3 Data.Char

ord (Char -> Int)
chr (Int -> Char)
isUpper (Char -> Bool)
toUpper (Char -> Char)

7.4 QuickCheck

quickCheck :: Testable prop => prop -> IO ()

quickCheck . verbose - run verbose mode

8 Tool

8.1 ghc-pkg

List installed packages:

ghc-pkg list

8.2 Integration of NixOS/Nix with Haskell IDE Engine (HIE) and Emacs (Spacemacs)

8.2.1 1. Install the Cachix

8.2.2 2. Installation of HIE 2.1. Provide cached builds
cachix use all-hies 2.2.a. Installation on NixOS distribution:
{ config, pkgs, ... }:


  all-hies = import (fetchTarball "") {};

in {
  environment.systemPackages = with pkgs; [

    (all-hies.selection { selector = p: { inherit (p) ghc865 ghc864; }; })


Insert your GHC versions.

Switch to new configuration:

sudo -i nixos-rebuild switch 2.2.b. Installation with Nix package manager:
nix-env -iA selection --arg selector 'p: { inherit (p) ghc865 ghc864; }' -f ''

Insert your GHC versions.

8.2.3 3. Emacs (Spacemacs) configuration:



    (lsp :variables
         default-nix-wrapper (lambda (args)
                                (append (list "nix-shell" "-I" "." "--command" )
                                        (list (mapconcat 'identity args " "))
                                (list (nix-current-sandbox))

         lsp-haskell-process-wrapper-function default-nix-wrapper

    (haskell :variables
             haskell-enable-hindent t
             haskell-completion-backend 'lsp
             haskell-process-type 'cabal-new-repl


   dotspacemacs-additional-packages '(

(defun dotspacemacs/user-config ()

  (add-hook 'haskell-mode-hook 'direnv-update-environment) ;; If direnv configured



auto-complettion configures YASnippet.

nix-sandbox ( has a great helper functions. Using nix-current-sandbox function in default-nix-wrapper that used to properly configure lsp-haskell-process-wrapper-function.

Configuration of the lsp-haskell-process-wrapper-function default-nix-wrapper is a key for HIE to work in nix-shell

Inside nix-shell the haskell-process-type 'cabal-new-repl is required.

Configuration was reassembled from: & its authors config: [[]]/

Refresh Emasc.

8.2.4 4. Open the Haskell file from a project

Open system monitor, observe the process of environment establishing, packages loading & compiling.

8.2.5 5. Be pleased writing code


Now, the powers of the Haskell, Nix & Emacs combined. It's fully in your hands now. Be cautious - you can change the world.

8.2.6 6. (optional) Debugging

  1. If recieving sort-of:
readCreateProcess : cabal-helper-wrapper failure

HIE tries to run cabal operations like on the non-Nix system. So it is a problem with detection of nix-shell environment, running inside it.

  1. If HIE keeps getting ready, failing & restarting - check that the projects ghc --version is declared in your all-hie NixOS configuration.

8.3 GHC

8.3.1 GHC code check flags

Additional to default settings it is useful to use -W, -Wcompat. -Wall is for purists and would raise noise. They can be supplied in CLI as also in .cabal ghc-option. fr

-W turns on additional useful warnings:

  • -Wunused-binds
  • -Wunused-matches
  • -Wunused-foralls
  • -Wunused-imports
  • -Wincomplete-patterns
  • -Wdodgy-exports
  • -Wdodgy-imports
  • -Wunbanged-strict-patterns

-Wall turns on all warnings that indicate potentially suspicious code.

-Weverything turns on all warnings supported by compiler.

-Wcompat turns on warnings that will be enabled by default in the future GHC releases, allows library authors make the code compatible in advance for future GHC releases.

-Werror promotes warnings into fatal errors, may be useful for CI runs.

-w turns off all warnings.

8.4 GHCI

8.4.1 Debugging in GHCI



:break 2
  :show breaks
  :delete 0


:step main

List information at the breakpoint


What been evaluated already

:sprint name


Commands to run the compile/check loop:

cabal > 3.0 command:

ghcid --command='cabal v2-repl --repl-options=-fno-code --repl-options=-fno-break-on-exception --repl-options=-fno-break-on-error --repl-options=-v1 --repl-options=-ferror-spans --repl-options=-j'

cabal < 3.0 command:

ghcid --command='cabal new-repl --ghc-options=-fno-code --ghc-options=-fno-break-on-exception --ghc-options=-fno-break-on-error --ghc-options=-v1 --ghc-options=-ferror-spans --ghc-options=-j'

nix-shell cabal > 3.0 command:

nix-shell --command 'ghcid --command="cabal v2-repl --repl-options=-fno-code --repl-options=-fno-break-on-exception --repl-options=-fno-break-on-error --repl-options=-v1 --repl-options=-ferror-spans --repl-options=-j" '

nix-shell cabal < 3.0 command:

nix-shell --command 'ghcid --command="cabal new-repl --ghc-options=-fno-code --ghc-options=-fno-break-on-exception --ghc-options=-fno-break-on-error --ghc-options=-v1 --ghc-options=-ferror-spans --ghc-options=-j" '

8.6 runghc

Run Haskell code without first having to compile them.

Official tool in GHC package.

8.7 Packaging

There is a number of good quality projects that export Cabal/Hackage to other packaging systems, big distribution systems and companies rely on them:

8.7.1 Cabal

  • v1 generation of features used/uses own cabal (now legacy) methods of handling packages.
  • v2 generation of features (current) uses Nix-like methods internally to handle packages.

Currently Cabal migrated to use of v2 generation by default.

Useful abilities:

exec - loads the GHC/GHCI env and launches the passed executable.

haddock - builds the documentaiton and places it into v1 -> dist, v2 -> dist-newstyle directories.

sdist - run a thorough process, properly follow .cabal instructions, assemble mentioned files and generate a source distribution file .tar.gz.

upload - upload source distribution file to Hackage.

8.7.2 Nix

Peter Simmons (peti) - the main creator maintainer maintainer of the Haskell stack and packages ("package set") in Nixpkgs. He is the central person that created most of the tooling and automation of importing Haskell into Nixpkgs. Nixpkgs

Besides documentation of Nixpkgs manual there is a Nixpkgs Haskell lib.

8.7.3 cabal2nix

Created/maintained by peti.

This tool runs on one compiler version.

8.7.4 hackage2nix

Allows to clones info from Hackage and convert it into Nix language. Is developed/resides/embedded in cabal2nix project.

8.7.5 cabal2spec - Cabal to RPM

Also created and maintained by peti, he uses it for OpenSUSE.

8.7.6 nix-tools

Translates Cabals project description to a Nix expression.

8.7.7 haskell.nix

Automatically translates Cabal/Stack project and dependencies into Nix code. Provides IFD (import from derivation) functions that minimize the amount of Nix code that is needed to be added. So it autogenerates Nix code hald way for your purposes.

Project of IOHK and has an active big respectable team.

8.8 Emacs/Spacemacs

In Haskell programming spacemacs/jump-to-definition is your friend, let yourself - it will guide you.

My (Anton-Latukha's) Spacemacs configuration for Haskell as at: Look there for a Haskell keyword, there is layer configuration, and the init boot config inside (defun dotspacemacs/user-config ().

8.9 Continuous integration platrorms (CIs) for Open Source Haskell projets

Since Open Source projects mostly use free tiers of CIs, and different CIs have different features - there is a constant flux of how to construct the best possible integration pipeline for Haskell projects.

The current state of affairs is best put in this quote:

Quote: 2020-02-29: Gabriel Gonzalez about CIs for Haskell Opens Source projects

Probably the biggest constraint is whether or not CI needs to test Windows or OS X, since build machines for those are harder to come by. We currently use AppVeyor for Windows builds and Travis for OS X builds since they are free. For Linux you can basically use any CI provider, but in this case I pay for a Linode VM which I use to host all Dhall-related infrastructure (i.e. all of the * domains), so I reuse that to host Hydra for Nix-related CI so that I can use more parallelism and more efficient caching to test a wider range of GHC versions on a budget.

For testing OS X and Windows platforms we use stack. The main reason we don't use Nix for either platform is that Nix only supports building release binaries on Linux (and even then it's still experimental).

So the basic summary I can give is:

For testing everything other than cross-platform support: Nix + Linux is best in my opinion

… because you get much more control and intelligent build caching, which is usually where most CI solutions fall short

For cross-platform support: stack + whatever CI provider provides free builds for that platform

Also, if you ever can pay for your own NixOS VM and you want to reuse the setup I built, you can find the NixOS configuration for here:

9 Library

9.1 Exceptions

9.1.1 Exceptions - optionally pure extensible exceptions that are compatible with the mtl

9.1.2 Safe-exceptions - safe, simple API equivalent to the underlying implementation in terms of power, encourages best practices minimizing the chances of getting the exception handling wrong.

9.1.3 Enclosed-exceptions - capture exceptions from the enclosed computation, while reacting to asynchronous exceptions aimed at the calling thread.

9.2 Memory management

9.2.1 membrain - type-safe memory units

9.3 Parsers - megaparsec

9.4 CLIs - optparse-applicative

Builds a shell API and parses tose command line options.


  • read & validate the arguments passed in any order to the command;
  • handle and report errors;
  • generate and have comprehensive docs that help user;
  • generate context-sensitive complettions for `bash`, `zsh`, `fish`.

Introduction (what library is for) Data model (diagram) – sometimes seeing at once is better then a thousand words of explanation Shortly describe where is speccing happens & belongs, where is parsing happens & belongs, where one can custom hande parsed data on top of what is provided in lib. So now readers roughly know the data model and what are structural parts and where they are

9.4.1 Modifiers {Attributes}

Settings that configure the builder.

  • long - --key
  • short - -k
  • help - info that is put into docs. Does not affet the parsing.
  • helpDoc - same as help, but with Doc type support.
  • metavar - placeholder for the argument seen in the docs. Does not affect the parsing.
  • value - value by default
  • showdefault - in the docs
  • hidden - hide from brief info
  • internal - hide from descriptions
  • style - function to apply to descriptions
  • command - add command as a subparser option.
sample :: Parser Sometype
sample = subparser $ command "hello" $ info hello $ progDesc "Show greeting"

Compose them with <>.


(  long "example"
<> short 'e'
<> metavar "ARGUMENT_HERE"
<> value "defaultVal"
<> showdefault
<> help "This would produce --example and -e keys for this parser."
        <> "It has defaultVal if key was not used."
        <> "And it would show default value in help message")

This monoid (Mod f a) should be given to according builder that accepts it.

9.4.2 Builders

Builders are the primitive atomic parsers of the library.

command argument --option optionArgument
ReadM a -> Mod ArgumentFields a -> Parser a~ General implemetation that uses given reader to parse direct argument.
IsString s => Mod ArgumentFields s -> Parser s~ To consume a string argument directly.
ReadM a -> Mod OptionFields a -> Parser a~ General implementation. Allows to use the given reader.
a {default value} -> a {active value} -> Mod FlagFields a {option modifier} -> Parser a~ Irrefutable ⇒ no termination for some or many, for them use flag'.

Mod FlagFields Bool -> Parser Bool~ Macro for Boolean flag:

switch = flag False True

Irrefutable ⇒ no termination for some or many, for them use flag'

a {active value} -> Mod FlagFields a {option modifier} -> Parser a~ Flag parser without a default value. Has sence in composite parser, or when requiring --on OR --off alternatives.
String -> Mod OptionFields (a -> a) -> Parser (a -> a)~ Always stops binary and displays a message.
IsString s => Mod OptionFields s -> Parser s~ Taking a String argument.
ParseError -> Mod OptionFields (a -> a) -> Parser (a -> a)~ Always fails immediately.
Mod CommandFields a -> Parser a~ Command parser. The command modifier can be used to specify individual commands.

9.4.3 Parsers

Definitions (if there are needed) How parsers are composed from attributes and builders Examples (if there are needed) Option readers Running a parser

9.4.4 Composing and more complex parsers

Definitions (if there are needed) Applicative on parsers Examples of the use of parsers in the program and how they tie with surrounding data types Alternative Then mention where and how to customize even over that and example

9.4.5 Error handling

9.4.6 Shell expansion

… Rename "How it works" into "How library internally implemented"

9.5 HTML - Lucid

9.6 Web applications - Servant

9.7 IO libraries

9.7.1 Conduit - practical, monolythic, guarantees termination return

9.7.2 Pipes + Pipes Parse - modular, more primitive, theoretically driven

9.8 JSON - aeson

9.9 Backpack

On 1-st compilation - * analyzes the abstract signatures without loading side modules, doing the type check with assumption that modules provide right type signatures, the process does not emitt any binary code and stores the intermediate code in a special form that allows flexibily connect modules provided. Which allows later to compile project with particular instanciations of the modules. Major work of this process being done by internal Cabal * support and * system that modifies the intermediate code to fit the module.

9.10 DSL

9.10.1 "Ivory" - eDSL, safe systems programming, effectively produce C code

10 Draft

10.1 Exception handling

Process of exception handling has:

  • raising an exception
  • gathering information and handling an exception
  • ability to finish important sessions/actions independently of whether exception happened or not. That is why it is called guaranteed finalization of important processes.

Exceptions and their handling are for the boundaries that recieve external things that are not under Haskell control. It is mainly an IO handling. The exception mechanism may be used for internal pure Haskell part - if it grew to complex to sort-out some situation try/catch mechanism can be used, but then avoid use of runtime system exceptions catch and sort programmically and generally avoid it.

Its better to promote exceptions to just checking preconditions.

Wraper with exception handler around function (f) call means that all untreated exception of function or its subfunctions would be caught by this wrapper into the scope where wrapper was used (one syntactic level above function f).

\begin{tikzcd} s \arrow[rd, "Handle/dispatch"'] & & & \\ & m \arrow[rd, "Eval \ inside"'] & & \\ & & ... \arrow[rd] & \\ & & & h \arrow[lluu, "To \ nearest \ exception \ monad"', dotted, bend right=49] \end{tikzcd}

Any monad that short-curcuits after some condition check of first argument - has exception handling potential.

Laziness as exceptions are computations - means that some issues would be skipped al togather, in parts that are/were not used would never throw exceptions, but also just as computations - exceptions would be raised at different times and states during computations.

Exception throw breaks purity, function was called buy returned a result.

Try to raise and resolve all exceptions befor aquiring external IO resources. And release all resources when or before the exeption can happen.

With concurrency thread could be killed by other threads (that is called to raise an asyncronous exception in the thread).

10.1.1 Ideal catching

  • Choose what exceptions to catch. Selection depends on the type.
  • No execution of continuation after throw, only handling.
  • Handle {,a}synchronous exceptions.

10.1.2 Control.Exception.Safe main sets of functions

  • try* - allows handle Either returning types, bridges the exception handling and basic Haskell computation.
  • handle* - describes how to handle exception before the monadic action itself.
  • catch* - describes how to handle the exception after the monadic action itself.

For asyncronous exceptions there are special function to catch them: catchAsync and handleAsync.

catch and handle are to catch specific exception type.

catches , catchesDeep and catchesAsync allows to catch matching an elements in the list, and then handle them.

10.1.3 Clean-up of actions/resources

  • bracket* - computations to aquire and release resource and computation to run in between.
  • finally - allows to run declared computations afterward (even if an exception was raised).
  • onException - run computations only if exception happened.

10.1.4 Ideal model

  • [X] Exception must include all context information that may be useful.
  • [X] Store information in a form for further probable deeper automatic diagnostic.
  • [X] Sensitive data/dummies for it - can be useful during development.
  • [X] Sensitive data should be stripped from a program logging & exceptions.
  • [X] Exception system should be extendable, data storage & representation should be easily extendable.
  • [X] Exception system should allow easy exaustive checking of errors, since the different errors can happen.
  • [X] Exception system should be automatically well-documented and transparent.
  • [X] Exception system should have controllable breaking changes downstream.
  • [X] Exception system should allow complex composite (sets) exceptions.
  • [X] Exception system should be lightweight on the type signatures of other functions.
  • [X] Exception system should automate the collection of context for a exception.
  • [X] Exception system should have properties and according functions for particular types of errors.

String is simple and convinient to throw exception, but really a mistake because it the most cumbersome choise:

  • [X] Any Exception instance can be converted to a String with either show or displayException.
  • [ ] Does not include key debugging information in the error message.
  • [ ] Does not allow developer to access/manage the Exception information.
  • [ ] Exception messages need to be constructed ahead of time, it can not be internationalized, converted to some data/file format.
  • [ ] Exception can have a sensitive information that can be useful for developer during work, but should not be logged/shown to end-user. Stripping it from Strings in the changing project is a hard task.
  • [ ] Impossible to rely on this representation for further/deeper inspection.
  • [ ] Impossible to have exhaustive checking - no knowledge no check, no warning if some cases are not handled.

10.1.5 Universal exception type

  • [X] Able to inspect every possible error case with pattern match.
  • [X] Self-documenting. Shows the hierarchical system of all exceptions.
  • [X] Transparent. Ability to discern in current situation what exceptions can happen
  • [ ] New exception constructor causes breaking change to downstream.
  • [ ] Wrongly implies completeness. Untreated Errors can happen, different exception can arrive from the outside code.

Sum type must be separate, and product type structure over it. Separate exception type of

10.1.6 Individual exception types

  • [X] Writing & seing & working with exactly what will go wrong because there is only one possible error for this type of exception. Pattern match happens only onconditions, constructors that should happen.
  • [X] Knowledge what exectly goes wrong allows wide usage of Either.
  • [ ] It is hard to handle complex exceptions in the unitary system. Real wrorld can return not a particular case, but a set of cases {object not found, path is unreachable, access is denied}.
  • [ ] Type signatures grow, and even can become complex, since every case of exception has its own type.
  • [ ] Impure throw that users can/should use for your code must account for all your exception types.

10.1.7 Abstract exception type

Exception type entirely opague and inspectable only by accessor functions.

  • [X] Updating the internals without breaking the API
  • [X] Semi-automates the context of exception with passing it to accessors.
  • [X] Predicates can be applied to more than one constructor. Which are properties that allows to make complex exceptions much easier to handle.
  • [ ] Not self-documenting.
  • [ ] Possible options by design are hidden from the downstream, documentation must be kept.
  • [ ] When you change the exception handling/throwing errors it does not shows to the downstream.

10.1.8 Composit approach

Provide the set of constructors and also a set of predicates and set of accessors. Use pattern synonyms to provide a documented accessor set without exposing internal data type.

10.1.9 The changes in GHC 8.8

The fail method of Monad has been removed in favor of the method of the same name in the MonadFail class.

MonadFail(..) is now exported from the Prelude and Control.Monad modules. The MonadFailDesugaring language extension is now deprecated, as its effects are always enabled.

So instead of:

import           Control.Monad.Fail
class MonadFail m => MonadFile m
-- use error instead of fail
Nothing     -> error ("Message " <> show x)
-- if compatibility fith old GHCs needed (ex. library)
#if __GLASGOW_HASKELL__ < 880
import           Control.Monad.Fail

10.1.10 Diversity in exceptions

Exception cause: external or internal.

Exceptions used by runtime system

div 1 0
-- *** Exception: divide by zero

Exceptions used by programmers:

  • Language feature
  • Programmable (implemented at library level)

10.1.11 Exception handling strategies

  • Ignore
  • Print
  • Repeat
  • Wait, stop, exit
  • Substitute with default
  • Throw
  • Handle
  • Rethrow
  • Emergency exit

10.1.12 Asynchronous exception

Exceptions raised as a result of an "external event", such as signal from another thread.

Are raised by throwTo. Are by termin and design should not be catched/handled, by default catching/handling functions are not catching them, if someone still wants to catch them - there are special function: catchAsync.

Further reading: termin and apparatus were introduced by "Asynchronous Exceptions in Haskell" (Simon Marlow, Simon Peyton Jones, Andrew Moran, John Reppy).

10.1.13 Monadic Error handling

(>>=) :: m a -> (a -> m b) -> m b -- λA.E ∨ A - computes and drops if error value happens.
catch :: c a -> (e -> c a) -> c a -- λE.E ∨ A - handles "errors" as "normal" values and stops when an "error" is finally handled.

10.2 Constraints

Very strong Haskell type system makes possible to work with code from the top down, an axiomatic semantics approach, from constraints into types.

  • Helps to form the type level code (aka join points of the code).
  • Uses the piling up of constraints/types information. At some point pick and satisfy constraints, can be done one at a time.
  • Provides hints through type level formulation for term level calculations, does not formulate the term level.
  • Tedious method (a lot of boilerplate and rewriting it) but pretty simple and relaxing.
  • Set of constraints.
  • When it is needed or convenient, single constraint gets a little more realistically concrete/abstracted.

Main type detail annotation thread can happen in main or special wrapper function, localization is inside functions.

  1. Rest of constraints set shifts to source type.

3.a. For the class handled or known how to handle - writte a base case instance description.

instance (Monad m) => MonadReader r (ReaderT r m)

3.b. For others write recursive instance descriptions:

All other unsolved constraints move into the source polymorphic variable.

instance (MonadError e m) => MonadError e (ReaderT r m)
instance (MonadState s m) => MonadState s (ReaderT r m)
  1. Repeat from 1 until considered done.
  2. Code condensed into terse form.

MonadError constraints is IOException, not for the String. IOException vs String.

Reverse pluck MonadReader constraint with runReader on the object.

MonadState - StateT

10.3 Monad transformers and their type classes

10.4 Layering monad transformers

Different layering of the same monad transformers is functionality is the same, but the form is different. Surrounding handling functions would need to be different.

10.5 Hoogle

10.5.1 Search

Text search (case insensitive):

  • a
  • map
  • con map

Type search:

  • :: a
  • :: a -> a

Text & type:

a -> a=

10.5.2 Scope Default

Scope is Haskell Platform (and Haskell keywords).

All Hackage packages are available to search with: Hierarchical module name system (from big letter):
  • fold +Data.Map finds results in the Data.Map module
  • file -System excludes results from modules such as System.IO, System.FilePath.Windows and Distribution.System Packages (lower case):
  • mode +platform
  • mode +cmdargs (only)
  • mode +platform +cmdargs
  • file -base (Haskell Platform, excluding the "base" package)

10.7 Either

Allows to separate and preserve information about happened, ex. error handling.

10.7.1 *

10.8 Inverse

  1. Inverse function
  2. In logic: \( P \to Q \Rightarrow \neg P \to \neg Q \), & same for category duality.
  3. For operation: element that allows reversing operation, having an element that with the dual produces the identity element.
  4. See Inversion.

10.9 Inversion

  1. Is a permutation where two elements are out of order.
  2. See Inverse

10.10 Inverse function

\( f_{x \to y} \circ ({f_{x \to y}})^{-1} = {1}_{x} \)

* \( \iff \) function is bijective. Otherwise - partial inverse

10.11 Inverse morphism

For \( f: x \to y \): \( \exists g \ : \ g \circ f = 1^{x} \) - \( g \) is left inverse of \( f \). \( \exists g \ : \ f \circ g = 1^{y} \) - \( g \) is right inverse of \( f \).

10.13 PatternSynonyms

Enables pattern synonym declaration, which always begins with the pattern word. Allows to abstract-away the structures of pattern matching.

10.14 GHC debug keys

10.14.1 -ddump-ds

Dump desugarer output. *

10.15 GHC optimize keys

10.15.1 -foptimal-applicative-do

\( O(n^3) \) Always finds optimal reduction into <*> for ApplicativeDo do notation.

10.16 Computational trinitarianism

Taken from:

Under the statements:

the following notions are equivalent:

== proposition proof (Logic)

== generalized element of an object (Category theory)

== typed program with output (Type theory & Computer science)

Table 12: Computational trinitarianism
Logic Category theory Type theory
true terminal object/(-2)-truncated object h-level 0-type/unit type
false initial object empty type
proposition (-1)-truncated object h-proposition, mere proposition
proof generalized element program
cut rule composition of classifying morphisms / pullback of display maps substitution
cut elimination for implication counit for hom-tensor adjunction beta reduction
introduction rule for implication unit for hom-tensor adjunction eta conversion
logical conjunction product product type
disjunction coproduct ((-1)-truncation of) sum type (bracket type of)
implication internal hom function type
negation internal hom into initial object function type into empty type
universal quantification dependent product dependent product type
existential quantification dependent sum ((-1)-truncation of) dependent sum type (bracket type of)
equivalence path space object identity type
equivalence class quotient quotient type
induction colimit inductive type, W-type, M-type
higher induction higher colimit higher inductive type
completely presented set discrete object/0-truncated object h-level 2-type/preset/h-set
set internal 0-groupoid Bishop set/setoid
universe object classifier type of types
modality closure operator, (idemponent) monad modal type theory, monad (in computer science)
linear logic (symmetric, closed) monoidal category linear type theory/quantum computation
proof net string diagram quantum circuit
(absence of) contraction rule (absence of) diagonal no-cloning theorem
  synthetic mathematics domain specific embedded programming language

10.16.1 *

10.17 Techniques functional programming deals with the state

10.17.1 Minimizing

Do not rely on state, try not to change the state. Use it only when it is very necessary.

10.17.2 Concentrating

Concentrate the state in one place.

10.17.3 Deferring

Defer state to the last step of the program, or to external system.

10.18 Functions

Total function uses domain fully, but takes only part of the codomain. Function allows to collapse domain values into codomain value. Meaning the function allows to loose the information. So total function is a computation that looses the information or into bigger codomains. That is why the function has a directionality, and inverse total process is partially possible.

Directionality and invertability are terms.

10.19 Void


Can not be grasped, touched.

A logically uninhabited data type.

(Since basis of logic is tautologically True and Void value can not be addressed - there is a logical paradox with the Void).

Is an object includded into the Hask category, since:

:t (id :: Void -> Void)
(id :: Void -> Void) :: Void -> Void

id for it exists.

Type system corresponds to constructive logic and not to the classical logic. Classical logic answers the question "Is this actually true". Constuctive (Intuitionistic) logic answers the question "Is this provable".

Also has functions:

-- Represents logical principle of explosion: from falsehood, anything follows.
absurd :: Void -> a

-- If Functor holds only Void - it holds no values.
vacuous :: Functor f => f Void -> f a

-- If Monad holds only Void - it holds no values.
vacuousM :: Monad m => m Void -> m a

Design pattern: use polymorphic data types and Void to get rid of possibilities when you need to.

10.19.1 *

Nothing, Haskell expressions can't return Void.

Also see: Maybe.

10.20 Intuitionistic logic

Proposition considered True due to direct evidence of existence through constructive proof using Curry-Howard isomorphism.

* does not include classic logic fundamental axioms of the excluded middle and double negation elimination. Hense * is weaker then classical logic. Classical logic includes *, all theorems of * are also in classical logic.

10.20.1 *

10.21 Principle of explosion

If asserted statement contains some error or contradiction - anything can be proven trough it. The more there is an error - the easier logic chain arrives at any target.

Ancient principle of logic. Both in classical & intuitionistic logic.

10.22 Universal property

A property of some construction which boils down to (is manifestly equivalent to) the property that an associated object is a universal initial object of some (auxiliary) category.

10.23 Yoneda lemma

Allows the embedding of any category into a category of functors (contravariant set-valued functors) defined on that category. It also clarifies how the embedded category, of representable functors and their natural transformations, relates to the other objects in the larger functor category.

The Yoneda lemma suggests that instead of studying the (locally small) category C {\displaystyle {\mathcal {C}}} \mathcal{C} , one should study the category of all functors of C {\displaystyle {\mathcal {C}}} \mathcal{C} into S e t {\displaystyle \mathbf {Set} } \mathbf{Set} (the category of sets with functions as morphisms). S e t {\displaystyle \mathbf {Set} } \mathbf{Set} is a category we think we understand well, and a functor of C {\displaystyle {\mathcal {C}}} \mathcal{C} into S e t {\displaystyle \mathbf {Set} } \mathbf{Set} can be seen as a "representation" of C {\displaystyle {\mathcal {C}}} \mathcal{C} in terms of known structures. The original category C {\displaystyle {\mathcal {C}}} \mathcal{C} is contained in this functor category, but new objects appear in the functor category, which were absent and "hidden" in C {\displaystyle {\mathcal {C}}} \mathcal{C} . Treating these new objects just like the old ones often unifies and simplifies the theory.

10.24 Monoidal category, functoriality of ADTs, Profunctors

Category equipped with tensor product.


wich is a functor for *.

Set category can be monoidal under both product (having terminal object) or coproduct (having initial object) operations, if according operation exist for all objects.

Any one-object category is *.

\( (a, ()) \sim a \) up to unique isomorphism, which is called Lax monoidal functor.

Product and coproduct are functorial, so, since: Algebraic data type construction can use:

Any algebraic data type is functorial.

10.25 Const functor

Maps all objects of source category into one (fixed) object of target category, and all morphisms to identity morphism of that fixed object.

instance Functor (Const c)
  fmap :: (a -> b) -> Const c a -> Const c b
  fmap _ (Const c) = Const c

In Category theory denoted:


Last type parameter that bears the target type of lifted function (b) and is a proxy type.

Analogy: the container that allways has an object attached to it, and everything that is put inside - changes the container type accordingly, and dissapears.

10.26 Arrow in Haskell

(->) a b = a -> b

Functorial in the last argument & called Reader functor.

newtype Reader c a = Reader (c -> a)

  fmap = ( . )

10.27 Contravariant functor

fmap :: (a -> b) -> Op c a -> Op c b
                (a -> c) -> (b -> c)
\begin{tikzcd} a \arrow[r] \arrow[rd] & b \arrow[d, dashed] \\ & c \end{tikzcd}

\( (a \to b)^{C} = (a \leftarrow b)^{C^{op}} \)

class Contravariant f
  contramap :: (b -> a) -> (f a -> f b)
\begin{tikzcd} a \arrow[r] \arrow[rd] & b \arrow[d, "contravariant", dashed] \\ & c \end{tikzcd}

If arrows does not commute Contravatiant funtor anyway allows to construct transformation between these such arrows to other arrow.

10.28 Profunctor

(->) a b

\( C^{op} \times C \to C \)

It is called profunctor.

dimap :: (a' -> a) -> (b -> b') -> p a b -> p a' b'

So, profunctor in case of arrow:

\begin{tikzcd} a \arrow[dd, "h"] & & a' \arrow[ll, "f"] \arrow[dd, "profunctor", dashed] \\ & & \\ b \arrow[rr, "g"] & & b' \end{tikzcd}
dimap :: (a' -> a) -> (b -> b') -> p a b -> p a' b'
dimap ::    f          g     -> (a -> b) -> (a' -> b') 
dimap ::    f          g     ->    h    -> (a' -> b')
dimap = g . h . f

It is contravariant functor in the first argument, and covariant functor in the second argument.

dimap id <==> fmap
(flip dimap) id <==> contramap

10.29 Coerce

Operates under condition that source and target types have same representation. Same representation means they are type aliases, or it the compiler can infer that they have the same representation. Directly shares the values from the source type to the target type. Conversion is free, there is no run-time computations.

The function implementing the transition:

coerce :: Coercible a b => a -> b

Type class implementing the instances for transitions:

class a ~R# b => Coercible (a :: k0) (b :: k0)

When compiler detects types have same structure, type class instances coerse implementation for this pairs of types. This type class does not have regular instances; instead they are created on-the-fly during type-checking. Trying to manually declare an instance of Coercible is an error.

10.29.1 *


10.30 Universal/Existential quantification

\( \forall \) Universal quantifier - a general property exists. Global solution. \( \exists \) Existential quantifier - evidence means general property, a local solution.

\( \forall \) and \( \exists \) are dualistic. Especially in Haskell universal type inside function structure has existential-like properties and backwards, existential type has universal-like properties inside function implementation.

Haskell RankNTypes option enables:

forall ... => - universal

If variable is universally quantified - the consumer of it can choose the type.

Because the consumer chooses the type the variable inside function body is quantified existentially.

=> ... forall - existential

If variable is existentially quantified - the type of it treated as it is already determined, and consumer can not reify it - consumer must accept and process the full existential type as it is.

Since the consumer is not involved into the choosing of the type - the variable inside function body quantified universally.

10.30.1 Use of existentials

Haskell existentials are always result in throwing aways type information.

Gives ability to work with data from at external world that we do not know definite type at compile time.

Some information about existentially quantified type should be preserved to be able to transrofm it.

Existential wrappers make possible from a function to return existentially quantified data. Wrapper allows to avoid unification with outer context and "escape" type variable.

There are three general degrees how much type information for existential to preserve:

Additional reading:

10.31 Propagator

Propagator is a monotone function between join-semilattices.

Where semilattices are amount of information about individual values. As information on input gained - the information on output only grows.

Join-semilattice is a idempotent commutative monoid.

If there is a system of nodes that each are join semilatice, and proparators are transformations that move information betwen them, and so transmit the information to all of them and bring the system into stable state. Number of times propagator with informaiton fired is not important - because it is idempotent. Order of propagators in the network firing is not important - it is commutative.

Under side-condition for termination (provenance) (information fullness/volume, network becoming stationatry or passing some check) - the network terminates and give a deterministic answer.

Provenance - a ad-hoc rules to determine the probability of recieving an close to trueth result from number of different approaches and informaiton sources. Also solves the contradictory data and raises the question of deciding between the contradictory world views: what is the least … to get the most accurate estimates ….

10.32 Code technics

Dependent types are used in teoretically complex code, in 1-2% of it. GADTs are fit 5-10% of the code.

Proving the easy targets & most needed ones allows much assurance and makes testing coverage more sufficcient.

Liquid Haskell are useful and its refinment types. Ideas presentation.

There is relatively rough idea that codata should use laziness and data should use strictness, which is not really true because there is a lot of cases where being lazy on strict data allows to tramendeusly shorten the computation for data.

You want confluence regardless of totality.

Metaprogramming in Haskell is mainly done through Template Haskell wich is too hard and clunky to work with, due to hard syntax structure.

Unproven Collatz conjecture is a classical computation halting problem. (If xi is even => xi+1 = 3xi+1, if odd => xi+1 = xi/2.

10.33 Algorithm of the Hackage package release

10.33.1 Form Git{Hub,Lab} pre-release

Name it pre-x.x.x.x+1, so determination of real number happens afterwards.

10.33.2 Create git branch release x.x.x.x+1

10.33.3 Open-up git diff <lastVer>..HEAD on one side of the screen

10.33.4 Open on the other side of the screen

10.33.5 Walk through diff and populate template:

# Changelog

## [x.x.x.x](<acc>/<proj>/compare/<oldVer>...<newVer>) (<short-ISO-date>)

  * Major (breaking):
    * ...

  * Medium (extending API features)
    * ...

  * Minor:
    * ...


`name` uses [PVP Versioning][1].

[1]: Populate according to PVP Major breaking changes (optional) API additions of functionality (optional) Other changes in the project, news

10.33.6 Check cabal sdist build passes

10.33.7 Think what new files can/should be included in .cabal extra-source-files

10.33.8 Update .cabal version:

10.33.9 Add a git tag <v>

10.33.10 git push --tags

10.33.11 (optional) (Remove git tag)

set fork 'f'
set ver '..'
git tag -d $ver
git push --delete $fork $ver

10.33.12 Make a cabal sdist

10.33.13 Upload package candidate to Hackage

10.33.14 (careful) Be fully ready when you upload package release to Hackage, since upload is idempotant

10.33.15 (optional) If docs not posted on Hackage

Hackage packaging have internal specifics and can refulse to build docs, to generate docs locally and upload them: (optional) Nix-shell
nix-shell Upload docs
set -e

dir=$(mktemp -d /tmp/dist-docs.XXXXXX)
trap 'rm -r "$dir"' EXIT

# assumes cabal 2.4 or later
cabal v2-haddock --builddir="$dir" --haddock-for-hackage --enable-doc

# (pasting pass does not work) Enter _by hand_: account, password
cabal upload -d --publish $dir/*-docs.tar.gz

10.34 Is power set functor is a bifunctor

bimap :: (a1 -> a2) -> (b1 -> b2) -> f a1 b1 -> f a2 b2
fmap  :: (a -> b)                 -> f a     -> f b
fmap  :: (a -> b)   -> (Id -> Id) -> f a Id  -> f b Id

10.35 IO

10.35.1 Base IO Data types IO a
data IO a

Main data type of the program run-time execution (IO).

All actions should be added to Main.main IO () to be executed. FilePath
type FilePath = String

Contents & Show are OS dependent, hold enough data to debug. Handle
data Handle
  = FileHandle Filepath ...  -- for files
  | DuplexHandle Filepath ...  -- for streams

Handle - a record used by Haskell runtime system to manage I/O external objects.

Essential properties:

  • Direction: In (readable), Out (writable) or both.
  • Status: open, semi-closed, closed. A good practice to close handlers with hClose, aslo garbage collector at some point most probaly would remove unused handlers.
  • Seekable: True | False.
  • Buffering type and always a buffer (even if buffer turned off - buffer is 0).
  • Position (there are exceptions) HandlePosn

Position in the data object. Standart handlers
  • stdin
  • stdout
  • stdin

For more info - learn this question in POSIX UNIX/Linux. IOMode
data IOMode  -- manage
  = ReadMode  -- input
  | WriteMode  -- output
  | AppendMode  -- output
  | ReadWriteMode  -- input/output File locking

Implementations should enforce locking as far as possible.

Haskell uses multiple-reader | single-writer locking.

If handle is managing:

  • output to a file - no new handls can be allocated for that file.
  • input from a file - new non-output handls can be created. Opening files
withFile :: FilePath -> IOMode -> (Handle -> IO r) -> IO r

Allows to load the file and run code for it.

openFile :: FilePath -> IOMode -> IO Handle

Directionality of these funciton are determined by IOMode. hClose
hClose :: Handle -> IO ()

Close the handle. Special cases
readFile :: FilePath -> IO String
writeFile :: FilePath -> String -> IO ()
appendFile :: FilePath -> String -> IO () Handle operation
hFileSize :: Handle -> IO Integer
hIsEOF :: Handle -> IO Bool
isEOF :: IO Bool  -- works only on stdin
hGetPosn :: Handle -> IO HandlePosn
hSetPosn :: HandlePosn -> IO () BufferMode
data BufferMode
 = NoBuffering    -- buffering is disabled if possible.
 | LineBuffering  -- line-buffering should be enabled if possible.
 | BlockBuffering (Maybe Int)
                  -- block-buffering should be enabled if possible.
                  -- Just - the size of the buffer, otherwise implementation-dependent.

Styles of buffers supported:

  • Block-buffering: the write happens when buffer oveflows its size.
  • Line-buffering: the write happens when "\n" encountered.
  • No buffering: everything is passed-through immidiately.

Buffer also gets written when hflush is used or handle is closed.

One should not flush less frequently then specified. One can flush buffers more frequently.

The default buffering mode is implementation-dependent on the file system object which is attached to that handle. By default, physical files are block-buffered and terminals are line-buffered. Buffering operation
hSetBuffering :: Handle -> BufferMode -> IO ()
hGetBuffering :: Handle -> IO BufferMode
hFlush :: Handle -> IO ()

10.35.2 Cabal Paths_pkgname

version :: Version

getBinDir :: IO FilePath
getLibDir :: IO FilePath
getDynLibDir :: IO FilePath
getDataDir :: IO FilePath
getLibexecDir :: IO FilePath
getSysconfDir :: IO FilePath

Cabal automatically generated module.

ghci would not load the module, since it was not generated, use cabal v2-repl to load it.

11 Reference

11.1 History

11.1.1 Functor-Applicative-Monad Proposal

Well known event in Haskell history:

Math justice was restored with a RETroactive CONtinuity. Invented in computer science term Applicative (lax monoidal functor) become a superclass of Monad.

& that is why:

  • return = pure
  • ap = <*>
  • >> = *>
  • liftM = liftA = fmap
  • liftM* = liftA*

Also, a side-kick - Alternative became a superclass of MonadPlus. Hense:

  • mzero = empty
  • mplus = (<|>)

Work of unification continues under:

11.1.2 Haskell 98

In 1998 first solid reference standartization of language was created. Main purpose is that implementors can be committed to rely and support Haskell 98 exactly as it is specified.

In 2002 "Haskell 98" had a minor revision. Next Haskell Report is "Haskell 2010". Old instance termination rules
  1. ∀ class constraint (C t1 .. tn): 1.1. type variables have occurances ≤ head 1.2. constructors+variables+repetitions < head 1.3. ¬ type functions (type func application can expand to arbitrary size)
  2. functional dependencies, ⟨tvs⟩left → ⟨tvs⟩right, of the class, every type variable in S(⟨tvs⟩right) must appear in S(⟨tvs⟩left), where S is the substitution mapping each type variable in the class declaration to the corresponding type in the instance head.

11.1.3 "Great moments in Haskell history" (by Type Classes) - History of Haskell

11.2 Resources

11.2.1 "State of the Haskell ecosystem"

(Gabriel Gonzalez & contributors)

Good per-direction information on state of Haskell ecosystem.

11.2.2 "Haskell performance" tools, processes, comparisons, data, information, guides


11.2.3 data Haskell - (2017) annotated links to data science & machine learning libraries, overviews and benchmarks of libraries

dataHaskell contributors

11.3 Literature

11.4 Haskell Package Versioning Policy

Version policy and dependency management.

Sorry, your browser does not support SVG.

-- Policy:      +--------- big breakage of API, big migration
--              | +------- breakage of API
--              | | +----- non-breaking API additions
--              | | | +--- changes that have no API changes

11.4.1 *


12 Giving back

\textgreek{λειτ} <- \textgreek{λαός} Laos the people \textgreek{ουργός} <- \textgreek{ἔργο} ergon work \textgreek{λειτουργία} leitourgia public work

Moral value of people developed from the community to give back, improving the community.

The life is beautiful. For all humans that make the life have more magic.

This study and work would not be possible without the community: tearchers, mathematicians, Haskellers, scientists, creators, contributors. These sides of people are fascinating.

Special accolades for the guys at Serokell. They were the force that got me inspired & gave resources to seriously learn Haskell and create this pocket guide.

Author: Anton Latukha

Created: 2020-10-03 Sat 21:07