Cardano decentralization continues: insights into our P2P deployment
Stake pools will soon be able to test automated peertopeer connections
11 May 2021 5 mins read
Decentralization of the Cardano network is key to ensuring its longterm sustainability, resilience, and independence from centralized governing entities. Now that block production is fully decentralized, our next focus is on developing our decentralized stake pool operator (SPO) ecosystem to build reliable and effective connections between distributed nodes.
Giving the power to validate blocks and transactions to stake pool operators requires enhancements to the network software. The activation of the peertopeer (P2P) governor, along with the deployment of the connection manager, enabled the release of a private P2P testnet in late April. We are now assessing this engineering testnet before deploying a semipublic P2P testnet for a group of invited SPOs to help us test and tune.
In the P2P governor post, we discussed the network’s architecture and the interaction between mini protocols and the components that enable direct and automated communication between nodes. Here, we assess how the connectivity model has matured to enable automated peer connectivity and reflect on the results of the private testnet launch.
Evolution of network connectivity
When Cardano was launched, the Byron network connectivity model operated in a federated state. In that setting, IOHK maintained core and relay nodes that connected to about 200 other relays (Figure 1).
Figure 1. Byron federated network structure
With the launch of Shelley last year, Cardano started functioning in a hybrid setting. This allowed stake pools to construct their P2P network manually by connecting to core and relay nodes and also to the seven federated relays that helped maintain the network during this transitional phase (Figure 2).
Figure 2. Shelley’s initial hybrid network structure
Since March, block production has been entirely decentralized, with stake pools following manual topologies for P2P connections. This means that SPOs have been using a list of relay nodes registered across the globe to generate their configuration for connections with other peers. To provide better efficiency, it is essential to enable automated node communication without reliance on IOrun relay nodes. Thus, the networking team is now deploying the automated P2P code, which will allow pool operators to create and run a more decentralized network.
In this way, once the P2P mainnet is deployed, Cardano will be maintained solely by communityrun nodes (Figure 3).
Figure 3. Final network structure with automated node communication
P2P testnet and node communication
The first stage in the P2P rollout was the launch of the private P2P testnet last month. This has been used to test the basic capabilities of the components:
 P2P governor: manages hot, warm, and cold sets of peers and ensures that the node meets the target number of each type of peer.
 Connection manager: creates outbound connections or registers inbound connections, tracks their state, and allows fullduplex TCP connections to be reused.
 Server: accepts connections and performs dynamic rate limiting.
 Inbound protocol governor: responsible for running and tracking the state of the inbound connection side. This includes tracking the state of each remote peer (cold, warm, or hot) and the state of each inbound miniprotocol.
The P2P system was deployed in a private environment and tested between eight nodes that connected to the mainnet and established communication with active SPO relay nodes; these further connected to other relays and blockproducing nodes. The system enabled nodes to discover stake pool relays using the onchain stake pool registry, which includes the DNS name or IP address of each relay.
Test results show that the nodes could arbitrarily select peers for communication, including those from the mainnet. The use of an ‘upstream’ metric enabled the discarding of the worstperforming peers and random selection of new peers for connection. This policy has been demonstrated in largescale simulations (10,000 nodes), providing closetooptimal results. In the live testing, the team saw many iterations of the optimization procedure. The team also observed that a range of peer connections occurred – with both nearby and faraway peers from different locations, which was inherent to all the eight nodes run in different parts of the world.
The networking and DevOps teams are now working together to improve the testnet environment, so all SPOs invited to the semipublic testnet can establish direct peer connections. This includes work on feature enhancements and testing processes to deliver the most efficient results. Thus, to introduce new targets for local root peers, the team is finalizing the tests for such related features as targets for known, established, and active peers.
We will be soon launching the semipublic P2P testnet, with the support of a small group of SPO partners to help with initial testing, before broadening this out to the wider SPO community. As ever, early feedback and ideas from our community are central to test, iterate, and improve processes as we progress towards a fully automated and decentralized P2P architecture for the Cardano mainnet.
Additional contributions from Karl Knutsson, Duncan Coutts, Neil Davies, Prashanti Naik, and Olga Hryniuk.
Cardano’s path to decentralization
Three miniprotocols are vital to the network’s operation
9 July 2020 6 mins read
The next releases of Cardano and the Ouroboros protocol contain changes that guide us towards decentralization and the Shelley era. This Deep Dive post explains how we are approaching this phase. With the release of the Praos algorithm for Shelley, which comes with the staking process, stake pools can be set up so ada owners can delegate their stake. The networking team is focused now on two features that will enable us to run a fully decentralized system. Let me first briefly describe how the networking is designed and engineered and give an overview of where we are at the moment. This post will start at the top of our abstractions and go down the stack. Hopefully, this will be an interesting journey through our design.
Typed protocols
At the very top of the stack is IOHK’s typedprotocols framework, which allows us to design applicationlevel protocols. The toplevel goal of protocol design for Ouroboros is to distribute chains of blocks and transactions among participants in the network and that is achieved by three miniprotocols:
 chainsync is used to efficiently sync a chain of headers;
 blockfetch allows us to pull blocks;
 txsubmission is used to submit transactions.
All three miniprotocols were carefully designed after considering the threats that can arise running a decentralized system. This is very important, because cyber attacks are very common, especially against targets that present strong incentives. There is a range of possible attacks at this level that we need to be able to defend against and one type that we were very careful about is resourceconsumption attacks. To defend against such attacks, the protocols allow the consumer side to stay in control of how much data it will receive, and ultimately keep use of its resources (eg, memory, CPU, and open file descriptors) below a certain level.
If you are interested in more details about typedprotocols, we gave talks and ran workshops at Haskell events last year and these were very well received by the engineering community. In particular, see the talk by Duncan Coutts talk at Haskell eXchange and the workshop I ran at Monadic Party.
Role of the multiplexer
TCP/IP protocols form the most ubiquitous protocol suite deployed on the internet. They are also some of the most studied protocols and are available on almost every operating system and computer architecture, so are a good first choice for our purposes. TCP/IP gives us access to a twoway communication channel between servers on the internet. The only highlevel requirement of typedprotocols is an ordered delivery of network packets, which is guaranteed by the TCP protocol.
Operating systems limit the number of connections at any one time. For example, Linux, by default, can open 1,024 connections per process, but on macOS the limit is just 256. To avoid excessive use of resources we use a multiplexer. This allows us to combine communication channels into a single one, so we can run all three of our miniprotocols on a single TCP connection. Another way to save resources is to use the bidirectionality of TCP: this means that one can send and receive messages at both ends simultaneously. We haven't used that feature in the Byron Reboot era, but we do want to take advantage of it in the decentralized Shelley era.
The peertopeergovernor
We want to use bidirectional connections, running all three miniprotocols in both directions, so we need to have a component that is aware which connections are currently running. When a node connects to a new peer, we can first check if it already has an open connection with that peer, which would be the case if the peer had connected to it already. But this is only one part of connection management that we will need.
Another requirement comes from the peertopeer governor. This part of the system is responsible for finding peers, and choosing some of them to connect to. Making a connection takes some time, depending on factors such as the quality of the network connection and the physical distance. Ouroboros is a realtime system, so it is good to hide some latency here. It wouldn't be good if the system was under pressure and yet still needed to connect to new peers; it's much better if the system maintains a handful of spare connections that are ready to take on any new task. A node should be able to make an educated decision about which existing connections to promote to get the best performance. For this reason we decided to have three type of peer:
 cold peers know about their existence, but there is no established network connection.
 warm peers have a connection, but it is only used for network measurements and none of the nodetonode miniprotocols is used;
 hot peers have a connection, which is being used by all three nodetonode miniprotocols.
A node can potentially know about thousands of cold peers, maintain up to hundreds of warm peers, and have tens of hot peers (20 seems a reasonable figure at the moment). There are interesting and challenging questions around the design of policies that will drive decisions for the peertopeer governor. Choice of such policies will affect network topology and alter the performance characteristics of the network, including performance under load or malicious action. This will shape the timely distribution of block diffusion (parameterized by block sizes), or transactions. Since running such a system has many unknowns, we'd like to phase it into two parts. For the first phase, which will be released in a few weeks (probably shortly after Praos, also known as the Shelley release), we want to be ready with all the peertopeer components but still running in a federated mode. In addition, we will deliver the connection manager together with implementing a server accepting connections, and its integration with the peertopeer governor. In this phase, the peertopeer governor will be used as a subscription mechanism. Running various private and public testnets, together with our extensive testing should give us enough confidence before releasing this to mainnet.
In the second phase, we will extend the miniprotocols with a gossip protocol. This will allow exchange of information about peers, finalize network quality measures, and plug them into the blockfetch logic (which decides from whom to download a block) as well as the peertopeer governor. At this stage, we would like to design and run some experiments to discover how peertopeer policies shape the network, and check how they recover from any topologies that are suboptimal (or adversarial).
I hope this gives you a good sense of where we are with the design and implementation of decentralization for Cardano, and our roadmap towards the Shelley era. You can follow further progress in our weekly reports.
This is the third of the Developer Deep Dive technical posts from our software engineering teams.
From free algebras to free monads
7 August 2018 29 mins read
In universal algebra freeness is a well defined algebraic property. We will explore equational theories which are tightly connected to free algebras. We will consider free monoids. Then we'll explain how monads can be brought into the picture in the context of monoidal categories. This will lead to a precise definition of a free monad as a free monoid.
This post requires familiarity with some very basic Category Theory and does not assume any knowledge on universal algebra. Most mathematical notions will be introduced but you might want to dig into literature for some more examples; though most of the books are quite lengthy and not suited for nonmathematicians  you've been warned ;). Knowing this I tried to bring all the required definitions, together with some very basic examples. As you read you may want to read about semigroups, monoids, groups, $G$sets, lattices, Boolean or Heyting algebras from Wikipedia articles or try to find info on nCatLab (though this is is a heavy resource, with mostly with higher categorical approach, so probably better suited for more familiar readers).
Preliminaries
We will need some preliminary definitions. Let's begin with a definition of algebra. For a set $A$ we will denote $A^n$ the $n$th cartesian product of $A$, i.e. $A^2=A\times A$.
Definition Algebra
Examples includes many classical algebraic structures, like semigroups, where there is only a single operation of arity 2, monoids which in addition have one operation of arity $0$  the unit element of multiplication. Other source of examples are Boolean algebras with two 2ary operations $\wedge$ and $\vee$ or more generally lattices, Heyting algebras. Also rings, modules, fields, vector spaces and countless other structures. Universal algebra has a very general theory describing common concepts but also deals with very special cases of some of more esoteric algebras.
Definition Homomorphism
This means that homomorphism preserve operations. For example a homomorphism of monoids is a map that preserves the multiplication and unit. For boolean algebras, it means that a homomorphism preserves the $\vee$ (also called join) and $\wedge$ (usually called meet) operations, etc.
It is an easy observations that homomorphism are closed under composition and since the identity map is always a homomorphism this leads to well defined categories, e.g. category of monoids, category of boolean algebras, category of rings, ...
Free algebras and Equational theories
Free Algebra
As you can see the definition of a free algebra requires a context, this interesting in its own! There are free monoids in the class of all monoids and there are free commutative monoids in the class of commutative monoids (i.e. monoids in which $m\cdot n=n\cdot m$ for each elements $m,n$).
Many theories allow free algebras. Let's see some other examples:

The monoid of natural numbers $\mathbb{N}$ with addition and $0$ as its unit element is a free monoid generated by $\{1\}$. It is both free in the class of all monoids and in the class of commutative ones. The $n$th cartesian product $\mathbb{N}^n$ is a free commutative monoid generated by the set $\{(1,0,\ldots,0),(0,1,0,\ldots,0),\ldots,(0,\ldots,0,1)\}$, but it's not a free monoid in the class of all monoids.

The additive group of integers $\mathbb{Z}$ is a free group with one generator, it is also free in the class of commutative groups. As in monoids: $\mathbb{Z}^n$ is a free commutative group with $n$ generators.

A free group with two generators can be pictured as the Cayley graph (which is a fractal) (note that its first quarter is the free monoid with two generators).

Every vector space is free, since every vector space admits a basis.

In the class of $G$sets, free $G$ sets are exactly all the cartesian products of $G^n$.

In the class of rings, polynomial rings with integer coefficients, usually denoted by: $\mathbb{Z}[X]$ or $\mathbb{Z}[X_1,\dots,X_n]$ for polynomials with many variables) are free (you likely have learned quite a lot about them in school, you just haven't been told the really interesting part ;)). This example was the motivation for terms, their algebra and term functions which we will discover next.
This is also true for semirings. You might have used this fact when using purescript validation library. A free semiring generated by a type `a` has type `[[a]]`; for example `[[()]]` is isomorphic to $\mathbb{N}[X]$, since (please excuse mixing Haskell and mathematical notation): $$[[()]]\simeq[\mathbb{N}]\simeq\mathbb{N}[X]$$
Free algebras play an essential role in a proof of beautiful and outstanding Birkhoff theorem. It states that a class of algebras $\mathcal{C}$ is an equational theory if and only if the class is closed under cartesian products, homomorphic images and subalgebras. Equational theories are classes of algebras which satisfy a set of equations; examples includes: semigroups, monoids, groups or boolean or Heyting algebras but also commutative (abelian) semigroups / monoids / groups, and many other classical algebraic structures.
We need to be a little bit more precise language to speak about equational theories in the full generality of universal algebra, which we are going to introduce.
Terms, term functions and their algebra
Definition Term
Let’s consider an algebra type $(f_i)_{i=1,\ldots,n}$. Then the set of terms on a set $X$ (set of variables) is inductively defined as:

each $x\in X$ is a term (of arity $0$)

each $f_i(x_1,\dots ,x_{j_i})$ is a term of arity $j_i$ for $x_1,\dots ,x_{j_i}\in X$

if $g_1,\dots g_n$ are terms of arities $j_1$ to $j_n$ respectively, and $g$ is a term of arity $n$ then $g(g_1(x_{11},\dots,x_{1j_1}),\dots, g_n(x_{n1},\dots,x_{nj_n}))$ is a term of arity $j_1+\dots+j_n$ with $x_{kl}\in X$.
We will denote the set of terms on $X$ by $\mathsf{T}^{(f_i)_{i=1,\dots,n}}(X)$ or simply $\mathsf{T}(X)$.
For example in groups: $x^{1}\cdot x$, $x\cdot y$ and $1$ (the unit of the group) are terms. Terms are just abstract expressions that one can build using algebraic operations that are supported by the algebra type. Each term $t$ defines a term function on every algebra of the given type. In groups the following terms are distinct but they define equal term function: $x^{1}\cdot x$ and $1$; on the other hand the two (distinct) terms $(x\cdot y)\cdot z$ and $x\cdot (y\cdot z)$ define equal term functions. The two terms $x\cdot y$ and $y\cdot x$ define distinct term functions (on non commutative groups or commutative monoids). Another example comes from boolean algebras (or more broadly lattice theory) where the two terms $x\wedge (y\vee z)$ and $(x\wedge y)\vee(x\wedge z)$ define equal term functions on Boolean algebras (or more generally distributive lattices). If $t$ is a term then the associated term function on an algebra $\underline{A}$ we let denote by $\tilde{t}^{\underline{A}}$. Term functions are natural to express equalities within a theory. Now we are ready to formally define equational classes of algebras.
Definition Equational Theory
For example the class of monoids is an equational theory for $$\mathbf{E}=\bigl\{(1\cdot x,\, x),\; (x\cdot 1,\, x),\; \bigl((x\cdot y)\cdot z,\, x\cdot (y\cdot z)\bigr)\bigr\}$$ i.e. all the algebras with two operations: one of arity 0 (the unit) and one of arity 2 (the multiplication), such that the $1$ is the unit for multiplication $\cdot $ and multiplication is associative. The class of commutative monoids is also an equational theory with one additional equation $(x\cdot y,\, y\cdot x)$. Groups, Boolean or Heyting algebras, lattices are also equational theories.
Coming back to free algebras: it turns out that the set of terms $\mathsf{T}^{(f_i)}(X)$ on a given set of variables $X$ has an algebra structure of type $(f_i)_{i=1,\dots,n}$: it is given by the inductive step in the definition of terms: if $t_i\in \mathsf{T}^{(f_i)}(X)$ for $i=1,\dots,j_i$ then $$ f_j^{\underline{\mathsf{T}^{(f_i)}(X)}}(t_1,\ldots,t_{j_i}) := f_j(t_1,\ldots,t_{j_i})\in \mathsf{T}(X) $$ Furthermore $\underline{\mathsf{T}^{(f_i)}(X)}$ is a free algebra over $X$ in the class of all algebras of the given type $(f_i)_{i=1,\dots,n}$. An extension of a map $h:X\rightarrow\underline{A}=(A,(f_i^{\underline{A}})_{i=1,\ldots,n})$ can be build inductively following the definition of terms and using the homomorphism property: $$ h(f_i(t_1,\ldots,f_{i_j})) := f_i^{\underline{A}}(h(t_1),\ldots,h(t_{i_j})) $$ The map $h$ is indeed a homomorphism: $$ \begin{array}{ll} h\bigl(f_i^{\underline{\mathsf{T}(X)}}(t_1,\ldots,t_{i_j})\bigr) & = h(f_i(t_1,\ldots, t_{i_j}) \\\\ & = f_i^{\underline{A}}(h(t_1),\ldots, h(t_{i_j})) \\\\ \end{array} $$ Note that the class of algebras of the same type is usually very broad, but this is the first approximation to build free algebras in an equational theory. This is just the equational theory for the empty set $\mathbf{E}$.
Let’s see this on an example and let us consider algebras of the same type as a monoid: with one nullary operation (unit $1$ or `mempty` if you like) and one 2ary operation (multiplication / `mappend`). Let $X$ be a set of variables. Then $1$ is a valid term, and also if $t_1$ and $t_2$ are terms on $X$ then also $t_1\cdot t_2$ is a term, but also $t_1\cdot 1$ and $1\cdot t_2$ are valid and distinct terms. $\mathsf{T}(X)$ resembles a monoid but it isn't. It is not associative and the unitality condition is not valid since $t\cdot 1\neq t\neq 1\cdot t$ as terms. We still need a way to enforce the laws. But note that if you have a map $f:X\rightarrow M$ to a monoid $M$ which you'd like to extend to a homomorphism $\mathsf{T}(X)\rightarrow M$ that preserves $1$ (which is not the unit, yet) and multiplication (even though it is not associative), you don’t have much choice: $\mathsf{T}(X)\rightarrow M$: $t_1\cdot t_2$ must be mapped to $f(t_1)\cdot f(t_2)\in M$.
We need a tool to enforce term equations. For that one can use
Definition Congruence relation
 reflexive: for each $a\in A$: $a\sim a$
 symmetric: for each $a,b\in A$: if $a\sim b$ then $b\sim a$
 transitive: for each $a,b,c\in A$: if $a\sim b$ and $b\sim c$ then $a\sim c$
Equivalence relations and congruences form complete lattices (partial ordered which have all suprema and minima, also infinite). If you have two equivalence relations (congruences) then their intersection (as subsets of $A^2$) is an equivalence relation (congruence).
The set of equations that defines the class of monoids generates a congruence relation on the term algebra $\underline{\mathsf{T}^{f_i}(X)}$ (i.e. an equivalence relation which is compatible with operations: $x_1\sim y_1$ and $x_2\sim y_2$ then $(x_1\cdot y_1) \sim (x_2\cdot y_2)$). One can define it as the smallest congruence relation which contains the set $\mathbf{E}$. Equivalence relation on a set $A$ is just a subset of the cartesian product $A\times A$ (which satisfy certain axioms), so it all fits together! One can describe this congruence more precisely, but we'll be happy with the fact that it exists. To show that, first one need to observe that intersection of congruences is a congruence, then the smallest congruence containing the set $\mathbf{E}$ is an intersection of all congruences that contain $\mathbf{E}$. This intersection is non empty since the set $A\times A$ is itself a congruence relation.
The key point now is that if we take the term algebra and take a quotient by the smallest congruence that contains all the pairs of terms which belong to the set $\mathbf{E}$ we will obtain a free algebra in the equational class defined by $\mathbf{E}$. We will leave the proof to a curious reader.
Free monoids
Let’s take a look on a free monoid that we can build this way. First let us consider the free algebra $\underline{\mathsf{T}(X)}$ for algebras of the same type as monoids (which include non associative monoids, which unit does not behave like a unit). And let $\sim$ be the smallest relation (congruence) that enforces $\mathsf{T}(X)/\sim$ to be a monoid.
Since monoids are associative every element in $\underline{\mathsf{T}(X)}/\sim$ can be represented as $x_1\cdot( x_2\cdot (x_3\cdot\ldots \cdot x_n))$ (where we group brackets to the right). Multiplication of $x_1\cdot( x_2\cdot (x_3\cdot\ldots \cdot x_n))$ and $y_1\cdot( y_2\cdot (y_3\cdot\ldots \cdot y_m))$ is just $x_1\cdot (x_2\cdot (x_3\cdot\ldots\cdot(x_n\cdot (y_1\cdot (y_2\cdot (y_3\cdot\ldots\;\cdot y_m)\ldots)$. In Haskell if you’d represent the set $X$ as a type $a$ then the free monoid is just the list type $[a]$ with multiplication: list concatenation and unit element: the empty list. Just think of
 A set with `n` elements corresponds
 to a type with `n` constructors:
data X = X_1⋯X_n
Free Monads
It turns out that monads in $\mathcal{Hask}$ are also an equational theory. Just the terms are higher kinded: $*\rightarrow*$ rather than $*$ as in monoids. The same construction of a free algebra works in the land of monads, but we need to look at them from another perspective. Let us first take a mathematical definition of view on monads.
Definition Monad
class Monad m where
return :: a > m a
join :: m(m a) > m a
which is unital and associative, i.e. the following law holds:
  associativity
join . join == join . fmap join
  unitality
join . return = id = join . fmap return
These axioms are easier to understand as diagrams:
It is a basic lemma that this definition a monad is equivalent to what we are used to in Haskell:
class Monad m where
return :: a > m a
>>= :: m a > (a > m b) > m b
Having `join` one defines `>>=` as
ma >>= f = join $ f <$> ma
and the other way, having `>>=` then
join = (>>= id)`
Not only these two constructions are reverse to each other, but also they translate the monad laws correctly.
Monoids in monoidal categories
To define a monoid $M$ in the category $\mathcal{Set}$ (of sets) one needs the product $M\times M$. Abstraction of this structure leads to monoidal categories.
Definition Monoidal Category
Most examples of monoidal categories are not strict but are associative and unital up to a natural transformation. Think of $(A\times B)\times C\simeq A\times(B\times C)$ in $\mathcal{Set}$ (or any category with (finite) products, like $\mathcal{Hask}$). Let me just stress out that since $\otimes$ is a bifunctor, for any two maps $f:\;a_1\rightarrow b_1$ and $g:\;a_2\rightarrow b_2$ we have a map $f\otimes g: a_1\otimes a_2\rightarrow b_1\otimes b_2$, and moreover it behaves nicely with respect to composition: $(f_1\otimes g_1) \cdot (f_2\otimes g_2) = (f_1\cdot f_2)\otimes(g_1\cdot g_2)$ for composable pairs of arrows $f_1,\;f_2$ and $g_1,\;g_2$.
Now we can generalise a definition of a monoid to such categories:
Definition Monoid in a Monoidal Category
The main point of this section is that these diagrams have exactly the same shape as associativity and unitality for monads. Indeed, a monoid in the category of endofunctors with functor composition as a monoidal product $\otimes$ and unit the identity functor is a monad. In category theory this category is strict monoidal, if you try to type this in Haskell you will end up with a non strict monoidal structure, where you will need to show penthagon equation.
These consideration suggest that we should be able to build a free monad using our algebraic approach to free algebras. And this is what we will follow in the next section.
Free monads in $\mathcal{Hask}$
Firstly, what should replace the set of generators $X$ in $\mathsf{T}(X)/\sim$? First we generalised from the category of sets $\mathcal{Set}$ to a monoidal category $(\mathcal{C},\otimes, 1)$: its clear that we just should pick an object of the category $\mathcal{C}$. Now since our category is the category of (endo) functors of $\mathcal{Hask}$ the set of generators is just a functor. So let's pick a functor `f`.
To get a free monad we need to decypher $\mathsf{T}(f)/\sim$ in the context of a monoid in a monoidal category of endofunctors. Note that here $\mathsf{T}(f)$ and $\mathsf{T}(f)/\sim$ are functors! To simplify the notation, let $\mathsf{Free}(f):=\mathsf{T}(f)/\sim$. So what is a term in this setting? It should be an expressions of a Haskell's type: $$ \begin{equation} \begin{array}{c} \bigl(\mathsf{Free}(f)\otimes\mathsf{Free}(f)\otimes\ldots\otimes \mathsf{Free}(f)\bigr)(a) \\\\ \quad\quad = \mathsf{Free}(f)\bigl(\mathsf{Free}(f)\bigl(\ldots (\mathsf{Free}(f)(a)\bigr)\ldots\bigr) \end{array} \end{equation} $$ In our setup the monoidal product $\otimes$ is just the functor composition, thus $\mathsf{Free}(f)(a)$ must be a type which (Haskell's) terms are of Haskell's types:
a, f a, f (f a), f (f (f a)), ...
The monadic `join` will take something of type $\mathsf{Free}(f)\;(\mathsf{Free}(f)\;(a))$, e.g. $f^n(b)=f\;(f\;(\dots f\;(b)\dots)$ (by abusing the notation $f^n$) where $b$ has type $f^m(a)=(f\;(f\;(\dots(f\;(a)\dots)$ and return something of type $\mathsf{Free}(f)(a)$ and it should be quite clear how to do that: just take the obvious element of type $f^{n+m}(a)$. Altogether, this is a good trace of a monad, so let us translate this into a concrete Haskell type:
data Free f a
= Return a
 ^ the terms of type a
 Free (f (Free f a))
 ^
 recursive definition which embraces
 `f a`, `f (f a)` and so on
instance Functor f => Functor (Free f) where
fmap f (Return a) = Return (f a)
fmap f (Free ff) = Free (fmap (fmap f) ff)
`Free f` is just a tree shaped by the functor `f`. This type indeed embraces all the terms of types: `a, f a, f (f a), ...` into a single type. Now the monad instance:
instance Monad (Free f a) where
return = Return
join (Return ma) = ma
 ^ stitch a tree of trees into a tree
join (Free fma) = Free $ join <$> fma
 ^ recurs to the leaves
As you can see, takes a tree of trees and outputs a bigger
tree, that's what join
does on the
Return
constructor.
Before formulating the next result let's describe morphisms between monads. Let `m` and `n` be two monads then a natural transformation `f :: forall a. m a > n a` is a homomorphism of monads iff the following two conditions are satisfied:
f . return == return
join . f == f . fmap f . join
Note that this two conditions are satisfied iff
f
is a monoid homomorphism in the category of (endo)functors
of $\mathcal{Hask}$.
Proposition
Let `f` be a functor, then `Free f` then there exists a morphism:foldFree :: Functor f => (forall x. f x > m x) > (Free f a > m a)
which restricts to an isomorphism of natural
transformations on the left hand side and monad
homomorphisms on the right hand side, and thus
Free f
is rightly colled free monad..
Proof
Let start with a defintion of `foldFree`.foldFree :: Functor f => (forall x. f x > m x) > (Free f a > m a)
foldFree _ (Return a) = return a
foldFree f (Free ff) = join $ f $ foldFree f <$> ff
It's inverse is:
liftF :: Functor f => (forall x. Free f x > m x) > (f a > m a)
liftF f fa = f $ Free $ Return <$> fa
First let's check that foldFree f
is a morhpism of monads:
foldFree f (Return a)
  by definition of (foldFree f)
= return a
foldFree f (join (Return a))
= foldFree f a
  by monad unitality axiom
= join $ return $ foldFree f $ a
  by definition of (foldFree f)
= join $ foldFree f (Return $ foldFree f a)
  by definition of functor instance of (Free f)
= join $ foldFree f $ fmap (foldFree f) $ Return a
foldFree f (join (Free ff)
  by definition of join for (Free f)
= foldFree f (Free $ fmap join $ ff)
  by definition of foldFree
= join $ f $ fmap (foldFree f) $ fmap join $ ff
= join $ f $ fmap (foldFree f . join) $ ff
  by induction hypothesis
= join $ f $ fmap (join . foldFree f . fmap (foldFree f)) $ ff
= join $ f $ fmap join $ fmap (foldFree f)
$ fmap (fmap (foldFree f)) $ ff
  f is natural transformation
= join $ fmap join $ f $ fmap (foldFree f)
$ fmap (fmap (foldFree f)) $ ff
  monad associativity
= join $ join $ f $ fmap (foldFree f)
$ fmap (fmap (foldFree f)) $ ff
  by definition of (foldFree f)
= join $ foldFree f $ Free
$ fmap (fmap (foldFree f)) $ ff
  by functor instance of (Free f)
= join $ foldFree f $ fmap (foldFree f) $ Free ff
And we have
foldFree . liftF :: (forall x. Free f x > m x) > (Free f a > m a)
(foldFree . liftF $ f) (Return x)
 ^ where f is a morphism of monads
= foldFree (liftF f) (Return x)
= return x
= f (Return x)  since f is assumed to be a morphism of monads
(foldFree . liftF $ f) (Free ff)
 ^ where f is a morphism of monads
= foldFree (liftF f) (Free ff)
= join $ liftF f $ fmap (foldFree (liftF f)) $ ff
  by induciton hypothesis
= join $ liftF f $ fmap f $ ff
  by definition of (liftF f)
= join $ f $ Free $ fmap Return $ fmap f $ ff
  by functor instance of (Free f)
= join $ f $ fmap f $ Free (Return ff)
  since f is a morphism of monads
= f $ join $ Free (Return ff)
= f $ Free ff
liftF . foldFree :: (forall x. f x > m x) > (f a > m a)
(liftF . foldFree $ f) fa
 ^ where f is a natural transformation
= liftF (foldFree f) $ fa
  by definition of liftF
= (foldFree f) $ Free $ fmap Return $ fa
  by definition of (foldFree f)
= join $ f $ fmap (foldFree f) $ fmap Return $ fa
= join $ f $ fmap (foldFree f . Return) $ fa
  by defintion of (foldFree f)
= join $ f $ fmap return $ fa
  since f is a natural transformation
= join $ fmap return $ f fa
  by monad unitality axiom
= f fa
foldFree
corresponds to foldMap
which is
defined in a very similar way
foldMap :: Monoid m => (a > m) > [a] > m
foldMap _ [] = mempty
foldMap f (a : as) = mappend (f a) (foldMap f as)
Note that foldMap
is an isomorphism onto
monoid homomorphisms with an inverse
g :: Monoid m => ([a] > m) > a > m
g f a = f [a]
Furthermore, if we had polymorphic functions over monoidal categories in our type system, `foldMap` and `foldFree` would be specialisations of the same function!
Some examples of free monads
Let us study some simple examples of free monads First let us consider the constant functor:
data Const a b = Const a
Then Free (Const a)
is isomorphic to Either a
toEither :: Free (Const a) b > Either a b
toEither (Return b) = Right b
toEither (Free (Const a)) = Left a
fromEither :: Either a b > Free (Const a) b
fromEither (Right b) = Return b
fromEither (Left a) = Free (Const a)
Since Either ()
is isomorphic with
Maybe
also Maybe
is a free
monad.
data Nat = Zero  Succ Nat
newtype Writer m a = Writer { runWriter :: (m, a) }
deriving Functor
toFree1 :: Free Identity a > Writer Nat a
toFree1 (Return a) = Writer (Zero, a)
toFree1 (Free (Identity fa)) = case toFree1 fa of
Writer (n, a) > (Succ n, a)
fromFree1 :: (Nat, a) > Free Identity a
fromFree1 (Writer (Zero, a))
= Return a
fromFree1 (Writer (Succ n, a))
= Free (Identity (fromFree1 (Free1 n a)))
Note that Nat
is the free monoid with one
generator (Nat
$\simeq$[()]
) in
the cateogry $\mathcal{Hask}$, and so is Free Identity
but in the monoidal category of
endofunctors of $\mathcal{Hask}$!
data F2 a = FX a  FY a
deriving Functor
. Then we have
data S2 = SX  SY
toFree2 :: Free F2 a > Writer [S2] a
toFree2 (Return a) = Writer ([], a)
toFree2 (Free (FX fa)) = case toM2 fa of
Writer (m, a) > Writer (SX : m, a)
toM2 (Free (FY fa)) = case toM2 fa of
Writer (m, a) > Writer (SY : m, a)
fromFree2 :: Writer [S2] a > Free F2 a
fromFree2 (Writer ([], a))
= Return a
fromFree2 (Writer (SX : xs, a))
= Free (FX (fromM2 $ Writer (xs, a)))
fromFree2 (Writer (SY : xs, a))
= Free (FY (fromM2 $ Writer (xs, a)))
toFree2
and fromFree2
are isomorphisms.
I think you see the pattern: if you take a functor with $n$
constructors you will end up with a writer monad over
a free monoid with $n$ generators. You might ask if all
the monads are free then? The answer is no: take a non
free monoid m
then the monad Writer m
is a non free monad. You can prove your self that
the writer monad Writer m
is free if and only
if the monoid m
is a free monoid in
$\mathcal{Hask}$.
Final remarks
I hope I convinced you that monads are algebraic constructs and I hope you'll find universal algebra approach useful. In many cases we are dealing with algebraic structures which we require to satisfy certain equations. Very often they fit into equational theories, which have a very clear description and which allow free objects. Freeness is the property that lets one easily interpret the free object in any other object of the same type. In the monad setting they are really useful when writing DSLs, since you will be able to interpret it in any monad, like IO or some pure monad.
References
 A Course in Universal Algebra by S. Burris, H.P. Sankappanavar
 Universal Algebra by G. Grätzer
 Category Theory for Computing Science by M.Barr and C.Wells
Note: This post originally appeared here.
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