Syntax  Output  

#str 
size(str) 

t.x 
table.get(t,x) 

t['x'] 
table.get(t,x) 

t.x:2 
table.set(t,x,2) 

:f(2) 
functor 

Types  Data  

String 
"str" 

Number 
1, 2.5 

Relation 
rel(x) true; 

Functor 
Tuple(x) 

List 
[1,'2'] 
Operators  

and,or 

if,when,choose 

not,once 
Arithmetic Operators  

+  * / 

< > <= >= = != 
Conversion (casting)  

str 

num, real 
Syntax: a language's grammar.
Before doing anything, you may check that you've installed the language. By opening the language with the v flag, you should see installation version number and confirm.
Open a commandline and type,
$ cosmos v
Cosmos 0.16
If the language is installed, you'll see something akin to this.
A good way to try out a new language is by opening the interpreter, if one is available, and making statements in it. This can be done with the i flag.
We'll assume you have already downloaded the language.
$ cosmos i
> x=1
 x = 1
> x=1 or 2=x
 x = 1
 x = 2
> str='hello'
 str = 'hello'
> l=[1,2,3]
 l=[1,2,3]
This way, you should get a better idea of how the language works. Whenever you see a new kind of statement in this guide, you may use the interpreter to try it on.
Make a file hello.co
with the content,
print('hello world')
A program that writes "hello world" on the screen is one of the simplest programs you can do. This can be done with a print
command.
The file can be loaded with the l
flag.
$ cosmos l hello
'hello world'`
A simple way to make a statement in Cosmos is to use equality, aka the =
operator.
x=1
y=z
2.5=z
These are three kinds of statements you can make.
x=1
print('hello world')
io.writeln('hello world')
The first uses the relation of equality.
Then, the builtin print
relation is used to write 'hello world'.
Finally, a writeln
relation is taken from a module io
to write 'hello world'.
x=1 y=2 and x=1
Statements can be joined together with and.
Statements from separate lines are implictly joined.
x=1 y=2
... is the same as ...
x=1 and y=2
Two basic types of data we've seen so far are Number and String.
Number includes 1, 2 and 2.5.
Unlike numbers, strings refer to a piece of text surrounded by double or single quotation in code.
String includes 'hello world' and "2".
Remember that 2 is a Number but '2' is a String.
x = num(2+1*4/2)
The special num (or real) function computes the result of the mathematical operations, passing the result to x.
This is not necessary.
 x=1+2
print(x) //1+2
This is a technically correct program and saying that the value of x is 1+2 is an answer. Though, it may not be the one we want.
A logic program may sometimes,
x = 'hello'+' world'
Different data types, such as strings, may have their own interpretation of addition. We may use addition to "add" two strings together, for example.
print(str(x)) //'hello world'
This is akin to casting in procedural languages. A value like 1+2 has a different type than Number. It's stored asis before being solved by the language's arithmetic system.
Cosmos is one of the few existing languages to have CLP as the default arithmetic system.
$ cosmos i
> x=1+y
 x = 1+y
> x=num(1+y)
 x = _124
 y = _123
> x>5
 x > 5
Why?
As this is a rather unique decision, we should probably explain.
A regular language would have x>5 or y+1 simply fail. In those cases, it doesn't know the value of x or y. It wouldn't then be able to solve those equations.
As a logic language, they're simply taken as true until proven wrong. It's the same for equality, e.g. x=y would also give an error in a regular language. A logic language has constraints that are solved when needed.
This is commonly called Constraint Logic Programming (CLP). Cosmos has CLP for Reals[1] as its default arithmetic.[2] This also means that it uses floatingpoint numbers.
There are other known systems. However, they would not work well as the default arithmetics. CLP(FD) is limited to integers which would mean users couldn't use floatingpoint numbers at all.
As the default arithmetics, we wanted a system that would, (1) work under normal circumnstances, at the least, and (2) not be limited to that; if possible, explore and make use of logic programming. If it weren't possible to use numbers with decimals, it would clearly not work under the circumnstances in which procedural arithmetics do, as they do use them, thus breaking (1).
However, one can use other systems by calling the host language, and using a system from them. Furthermore, the current system may be changed by modifying core.pl.
[1] As far as we know, CLP for Reals goes back to Prolog III. See http://prologheritage.org/en/ph30.html.
[2] It should be rather be asked why a logic language would not use CLP and instead present a classical, procedural system as the default one! Even though Prolog III has it, see [1]. It's practically asking users to make incorrect programs, logically speaking.
Let's codify the intuition that "the double of x is y".
rel double(x,y)
y=num(x*2)
double(2,z)
We've seen statements that use builtin relations like print and = but this is the first time we define our own relation. Specifically,
rel
.A fine rule to understand the second step is to substitute the statement for the definition.
A statement like double(2,z)
is, by our definition, z=2*2
, once we've substituted x
by 2
and y
by z
.
In other words, the result is that z now equals 2*2.
Though double is not particularly useful, relations in general can single out pieces of code allowing for later use.
As we'll see later, relations can be kept in a module.
Cosmos™ is one of the few remaining logic programming languages. It's no surprise therefore that there's some connection.
Logic itself concerns with statements that may be true or false, such as,
```x equals 2 The double of 2 is 4. Socrates is a human. It's raining.
What these statements have in common is that they each have a _relation_. This is more evident when written in logic notation,
```x = 2
double(2, 4)
human('socrates')
rain().
The relationship in double(2, 4) is double, which we defined beforehand. Naturally, this statement is true.
Out of those, = is distinguishable enough that it doesn't need to be in logic notation. Generally, arithmetics stay in arithmetic notation.
double(4,x)
x=double(4)
Consider these two statements. Although the meaning is the same, one of them uses double as a relation and the other uses it as a function.
Any major "structure" such as rel and if are delimited by an increase in whitespace (generally, comprised of four spaces or a single tab character).
rel(true)
false
The code that comprises the if and elseparts are evident through this method.
An error is issued if there's any inconsistency. For example, if you chose the first indent to be four spaces but the second to be three.
As long as you make a consistent rule, i.e. four spaces or one tabonly, there should be no issues.
[1] As suggested by the programming language Python™, true statements can be used as placeholders.
In a logic language, these operators are more important than they may first seem. They are not only logical operators, they describe the flow of a logic language.
We've already seen them in use.
> x=1 and 2=y
 x = 1 and y = 2
> x=1 or 2=x
 x = 1
 x = 2
Logic interpretation A and B: Both A and B are true.
A or B: Either A, B or both are true.
This one is a bit more complicated.
x=1 or x=2
essentially states that x may be 1 or 2. Which is to say, we don't know what the value is!
But what about (x=1 or x=2) and x!=1
?
rel p(x)
x=1 or x=2
rel main()
p(x)
x!=1
io.writeln(x) //2
Naturally, we have said that x is 1 or 2. Since we then state that x is not 1, it's only possible for it to be 2. This is the logical interpretation of the program.
The program will then call io.writeln to write 2 on the screen.
Cosmos is a language based on logic. Still, it runs on a computer. As such, there has to be a procedural (i.e. a machinebased) explanation on how the program runs.
We might say it's a logic program that's run by a procedural "logical engine".
We may call it the logicprocedural interpretation. This would be the procedural explanation on how our logic program is run.
Procedural interpretation A and B: A and B are both evaluated, in sequence.
A or B: A is evaluated. If that fails, B is evaluated.
This is a proccess that, by the way, would not exist in a truly procedural language. A procedural program has no concept of backtracking. That is, it has no or. It's as if only and is used.
It's because this is a logic language that we must ensure our program works correctly.
This brings us to the wellknown limitations of LP.
Let's consider,
rel p(x)
p(x)
p(x)
The program will call p(x), which will call p(x). This is an example of recursion. This is an example of an infinite loop, as the program will run forever.
The problem with this is that even correct logical problems may fall into an infinite loop.
A possible counterpoint is that every language has the same problem, that is, they too can fall into infinite loops.
Couple that with the fact this occurs when you're doing recursion. Generally, if your program relies on a relation calling itself it's pretty obvious that it's doing so, and you have a hint that you should be looking out for such things.
The second point is a result of combining a query solver with a programming language. If you simply want the solver to answer a query, does it matter if it takes a few seconds (or less) longer? If you want to use it as a fast programming language, shouldn't
The programmer then wants to instead use it as a blazing fast programming language, while at the same time expecting it to be fast without doing any work on optimizing it which is not how it works in any language.
Even if it's not ideal, knowing how the program works is often necessary to optimize it in any language.
Adding to our repertoire, we have if and not.
Logically speaking, this lets us represents all kinds of statements in the form,
If X, then Y.
not X.
Which are common in logic and show up in practical programming.
```If it's raining, then someone will bring an umbrella. If someone is a human, they're mortal. (aka All humans are mortals) It's not raining.
_if_

if(true) print('condition is true') else print('condition is not true')
We may again open the interpreter to try ifstatements.
$ cosmos i
if(x!=1) x=2;  x=2 if(x!=1) x=2 or x=1;  x=2  x=1 if(x!=1) x=2;  x=2 ```
The body of the ifstm will be evaluated when the condition, e.g. x=1, is true.
> if(false) x=2 else x=1;
 x=1
> if(x=1) x=1 else x=0;
 x=1
 x=0
It's possible for an ifstatement to have an elseclause. If the condition is true, the ifpart holds, otherwise the elsepart holds.
In the latter example, the interpreter tried out both possibilities and gave two answers.
if(x=1)
y=2
elseif(x=1)
y=2
else
true
Naturally, this is just a way to write,
Logical interpretation
You may think of an ifstatement as equivalent to,
if(A) B else C; <==> (A and B) or (not A and C)
An ifstatement without else is,
if(A) B; <==> (not A) or B
Though this may not be its exact implementation.
> not x=2
 x!=2
> not 5<1
 x=1
 x=0
> not x<=2
 x>2
As you may have noted, not simply negates a statement.
Logical interpretation
The negation of A is simply false when A holds, and true when A doesn't.
We recommend keeping the conditions for an if or not to simple arithmetics.
It's easy to see that not x=1 is the same as x=1. Similarly, not x>5 is just x<=5.
If a condition is too complex for our ifstatement, an error will be given. You may try reworking your code or using an alternative conditional.
Finally, you may fall back from logic programming entirely and use functions.
Negation is actually more complicated to implement than it looks like, at least in a logic language. If you're interested in the details, see the implementation section  LogicProcedural (II).
We have not settled the mechanics for if (and not) completely. The only requirements are that,
The reason for this is that we want to allow for different optimizations and ways to implement a logical conditional/negation to be tried.
For us, being able to use a sound conditional is already an improvement. Prolog famously implemented negation in an unsound way (that also gave no warnings whatsoever).This
This has highly limited experimentation with logic programming, as two operators were rendered mostly unusable.
For relations that require a specific implementation, we use the when operator. The when is simply syntax for and/or,
when(A) B else C <==> (A and B) or (C)
As you see, this is a rather barebones conditional. It evaluates to and/or, and is therefore pure code. However, the else is redundant, as the condition is not used. A further analysis will show that when will get caught in an infinite loop in many times where if doesn't, although it will work for the first answer.
You may use it to implement your own conditional, as long as you write out the negation,
when(x=2) true else x!=2
Furthermore, it can be easily switched with other conditionals as they share similar keywords.
If it really is such a problem, a simple solution is to fall back into functions. A relation can be turned into a function by changing the rel
to a fun
keyword.
fun q(x,y)
if(p(x))
y=2
else
y=1
As functions have simple requirements when compared to full relations, an if or when will accept any conditions when inside a function[1].
Because a function is only meant to run once, there is no need to support backtracking or any other logical mechanisms.
This may mean we're abandoning relational programming (LP) for a moment, though this is restricted to q.
We'll explain this further in a later section.
[1] The semantics of if or when will be turned into that of a commitedchoice conditional. This is also the choose operator in Cosmos.
if: guaranteed to be logically sound, gives error if the condition is too complex. when: simple conversion to and/or. Even if it fulfills the condition and goes to ifcode, it may still backtrack to elsecode. Works for any condition. choose: simply checks if the condition is true, then chooses if or elsecode. It'll not backtrack, but then this may not be logically sound.
We recommend sticking to if when possible.
if works best with simple conditions, i.e. simple inequalities such as != or >=.
This is just trivia, but it may be of interest to some that the actual conditional A>B in formal logic does not have an else.
It's simply something adopted from procedural programming where we often specify what to do if a condition is not true. This has often been adopted by LP aswell.[1]
If it's raining, then I will fly.
An odd thing about the formal conditional is that it holds true when the condition is false. As we said before, if(A) B; <==> (not A) or B
.
This is actually rather arbitrary! The implication is that if we confirm that it did not rain, then this odd implication is true.
Perhaps we'd rather say: "you would not fly anyway!"
That would maybe render the implication false.
What about an implication that is always false when the condition is false? This would be arbitrary aswell.
Though this may be a moot point, we may conclude the formal implication is not the same as the implication we use in natural language.
There is no justification given for any of this.[2] It was simply deemed useful to take a conditional as true when we can't say otherwise.
It's useful in our programs to say,
If the switch is set, our program will beep.
And, if the condition doesn't hold, simply go on with our program. We're going by the assumption that our machinery is correct.
[1] See reif or (>;)
.
[2] One may consult the Principia Mathematica for a definition and explanation of the logical implication and see that, once again, it's an arbitrary definition.
It's about time we explained our use of whitespace and indendation.
Any major "structure" such as rel and if are delimited by an increase in whitespace (generally, comprised of four spaces or a single tab character).
if(true)
false
else
false
The code that comprises the if and elseparts are evident through this method.
An error is issued if there's any inconsistency. For example, if you chose the first indent to be four spaces but the second to be three.
As long as you make a consistent rule, i.e. four spaces or one tabonly, there should be no issues.
Syntaxwise, whitespace only adds ands to the end of lines (unless a keyword like else or case pops up) and ends any unindent with a semicolon.
As such, the semantics of whitespace are very easy to understand.
Coming from a procedural language, it may seem odd that a semicolon is used to end a structure.
Still, this is in line with the syntax of most LP language.
We start with a declaration.
functor(F, Functor)
By using the special relation functor, we declare that F is a functor, or rather, it's what will be used to make functors. We can now make functors with the name/label F.
F(1, 2) = F(1, a)
print(a) //2
Functors are a kind of composite data. They are what some languages call a tuple.
If 1 or 'hello' is a single value, F(1,'hello') is a value made from combining both.
We made two functors. Since they are equal to each other, we can also conclude that its values are. Hence, a=2
.
Let's say we want to represent a person in our program. We could just make a functor Person
.
functor(Person, Functor)
We can now make our first person.
bob = Person('bob', 23)
We have made the convention that the first two fields of Person
stand for name and age, though if needed we could have included more fields. This allows us to make programs about one or more persons!
This is not the only way we could represent a person, of course. Cosmos™ has objects aswell, which are very similar in that sense! We'll cover them later.
If we simply to group things together, any functor is enough. We may use a F or Tuple functor for this.
> Tuple(x,1) = Tuple('x', y)
 x='x' and y=1
A list is another kind of composite data. Let's say we want a list of things. This can easily be done with the syntax,
l = [1, 2, 3]
We've made a list with the values 1, 2 and 3.
There are operations we can make on lists. We can add, subtract or search for elements within it. These can be found in module list.
l2 = list.push(l, 55)
io.writeln(l) //[1, 2, 3]
io.writeln(l2) //[1, 2, 3, 55]
If we push value 55 into l, we'll get a new list l2 with elements.
l = [1,2,3]
list.first(l, head) //head is 1
list.rest(l, tail) //tail is [2, 3]
l=[headtail]
A common operation is to get the first element in a list, or the rest the remaining, which itself is a new list. These are sometimes called the head and tail of a list.
This is a common pattern in declarative programming, and as such there's even a special syntax for it.
l=[headtail]
The term [xy] is very different from [x,y] the latter is a list with two elements. The former is any list.
Lists are often implemented in terms of the functor Cons. These lists are identical:
l = [1, 2]
l = Cons(1, Cons(2, Cons))
"A function is a less general kind of relation."  The Cosmos Programming Language
While a relation may give multiple answers or no answer at all (in which case the statement is taken to be false), a function is guaranteed to only give one.[1]
[1] A function here is meant to mimic a typical programming function that you often see in procedural or functional languages. It's not necessarily a mathematical function. For example, it may accept more than one input.
There's no clear rule on what should or shouldn't be a function.
We'll take factorial as a good case.
fun fact(x,y)
if(x=0)
y=1
else
y=x*fact(num(x1))
A common way to introduce logical languages is by emphasizing its relation to logic. Although it's not very practical, it's as good as any tutorial or introduction nonetheless.
Let's make it clear that,
rel human(x)
x='socrates'
rel mortal(x)
human(x)
t={
rel human(x)
x='socrates'
rel mortal(x)
human(x)
}
Typically, programming is divided into four main paradigms,
Although this classification is increasingly dated, it's still used (and somewhat useful) to this day.
x=double(1)
y=x
print(y)
In the logic paradigm, or logic programming (LP), which we follow to the letter, as our language is in fact a logic programming language, this is simply a set of statements.
It's easy to see by looking at the program that this applies. We may simply look at the program and see that x equals the result of a function double, y is x, and the value is written (which we know the statement print does).
We only have to take a moment to conclude that 2 will be written if we run the program, and it is.
2
If a paradigm is a way to look at a given program, the procedural paradigm looks at it imperatively. A program is a recipe, or list of instructions to be executed by the computer.
This paradigm follows the computer program closely. It's the closest to how the computer actually acts.
The following instructions would be executed.
The difference so far is subtle, and you could take it as a procedural program asis. In fact, our language highly resembles procedural languages in syntax.
This is on purpose, the language is made so that it can be reasoned or written in this style to some extent.
Though you may often simply see the program as a series of statements in the logic paradigm, it's sometimes needed to know how the computer executes them.
After all, the program runs in a computer.
We'll call this the "LogicProcedural" paradigm (though it's a madeup term we invented). The LogicProcedural interpretation of a program is given by how our procedural logic engine executes the logic program.
Often, the only reason we need to know this is so our program has good performance. An efficient program will run as quickly as it can and not consume many memory slots.
A lot of this may be better off understood as styles.
Most important for our language is the notion of a pure logic program.
Logic programs allow us to effectively write logical statements and have the language work them out correctly.
Knowing you have written a pure relation is quite simple.
All you have to do is use pure relations! Then, your relation is also pure.
Because it's the language's main conditional, any number of optimizations may be applied to it as long as it keeps its properties as a conditional (while the operator when is kept for finetuning; if you want a minimal conditional to which you can apply your own optimizations).
Currently,
when is a sound but more barebones conditional. Implementing a pure factorial relation in when makes for a good case study.
when is a pure conditional. Still, since it requires you to manually negate the condition (which is redundant otherwise) and may not provide future optimizations, unless you implement them yourself, it's less preferred and not the default goto for conditionals.
Remember that relations may backtrack or yield more than one solution. Even if a factorial relation succeeds the first time, an illdefined program may cause on the second solution.
Let's compare this to,
rel fact(x,y) when(x=0) y=1 else y=x*fact(num(x1))
... or ...
(x=0 and y=1) or (y=x*fact(num(x1)))
While fact(1,x) would still work, it would for the first solution alone. Remember that relations may backtrack or yield more than one solution.
This would suffice were it a regular imperative or functional definition of factorial, since those are meant to run only once and never backtrack.
However, this is not so for a logical language and different reasoning is needed. If it ever tries to find a second solution, it will procceed to the second clause. The reader is invited to keep this in mind and accompany the execution of fact(1,x).
rel fact2(x,y) when(x=0) y=1 else x>0 y=x*fact2(num(x1))
As you see, we have,
The program now works soundly, even if it's not perfect! It still creates places to backtrack or choice points. This consumes memory, moreso if we call when a lot of times. But at least these are eliminated upon hitting x>0.
==
What then if we simply removed backtracking?
choose is a nonlogical conditional that doesn't backtrack.
As such, it's fit for code with sideeffects. A simple prompt, for example.
rel prompt() print('type a number') io.write('> ') io.read(x) choose(x='5') print('You typed 5!') else print('You didn't type 5!?') prompt()
Such code is nonlogical in the first place and has no need for backtracking.
The safest option is still to rely on if. It should never be unsafe to use if. For cases it can't be used, you'll invariably be given a warning or error at least. However, choose and when are available if you're aware of the limitations.