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foreign languages and unified under a common type system. The compiler
generates the code needed to compose functions across languages and also to
direct automation of mundane tasks such as data validation, type/format
conversions, data caching, distributed computing, and file reading/writing. The
endgame is to develop morloc into a query language that returns optimized
programs from an infinite library of functions and compositions of functions.
See the manual for more information.
If you want to get straight to playing with code, go through the steps in the
installation section and then go to the project in demo/01_sequence_analysis.
Status
This project is under active development with no stability guarantees until the
v1.0 release. Pull requests, issue reports, and private messages are very
welcome.
Installation
Compile and install the package (requires the Haskell utility stack):
git clone https://github.com/morloc-project/morloc
cd morloc
stack install --fast
morloc also depends on the JSON::XS perl module from CPAN, which can be
installed as follows:
export PERL_MM_USE_DEFAULT=1
export PERL_CANARY_STABILITY_NOPROMPT=1
sudo perl -MCPAN -e 'install JSON::XS' 
For Python support, you need to download the pymorlocinternals library from
PyPi:
pip install pymorlocinternals
# or on Mac:
pip3 install pymorlocinternals
For R support, you need to install the rmorlocinternals library from github,
in an R session, run:
R> install.packages("devtools")
R> devtools::install_github("morloc-project/rmorlocinternals")
C++ support currently requires a GNU compiler that supports C++11.
morloc modules can be installed from the morloc
library with the commands such as:
morloc install cppbase
morloc install pybase
morloc install rbase
morloc install math
The morloc install commands will install the modules in the
$HOME/.morloc/lib folder.
Last of all, if you are working in vim, you can install morloc syntax highlighting as follows:
mkdir -p ~/.vim/syntax/
mkdir -p ~/.vim/ftdetect/
cp vim-syntax/loc.vim ~/.vim/syntax/
echo 'au BufRead,BufNewFile *.loc set filetype=loc' > ~/.vim/ftdetect/loc.vim
Getting Started
export hello
hello = "Hello World"
The "export" keyword exports the variable "hello" from the module.
Paste this into a file (e.g. "hello.loc") and then it can be imported by other
morloc modules or directly compiled into a program where every exported term
is a subcommand.
morloc make hello.loc
This will generate a single file named "nexus.pl". The nexus is the executable
script that the user will interact with. For this simple example, it is the
only generated file. It is currently written in Perl.
Calling "nexus.pl" with no arguemtns or with the -h flag, will print a help
message:
$ ./nexus.pl -h
The following commands are exported:
  hello
    return: Str
The return: Str phrases states that hello returns a string value.
The command hello can be called as shown below:
$ ./nexus.pl hello
Hello World
Composing C++ Functions
The following code uses only C++ functions (fold, map, add and mul).
import cppbase (fold, map, add, mul)
export square;
export sumOfSquares;
square x = mul x x;
sumOfSquares xs = fold add 0 (map square xs);
If this script is pasted into the file "example-1.loc", it can be compiled as
follows:
morloc install cppbase
morloc make example-1.loc
The install command clones the cppbase repo from github
repo into the local directory
~/.morloc/lib. The morloc make command will generate a file named
nexus.pl, which is an executable interface to the exported functions.
You can see typed usage information for the exported functions with the -h flag:
$ ./nexus.pl -h
The following commands are exported:
  square
    param 1: Num
    return: Num
  sumOfSquares
    param 1: [Num]
    return: Num
Then you can call the exported functions (arguments are in JSON format):
$ ./nexus.pl sumOfSquares '[1,2,3]'
14
The nexus.pl executable dispatches the command to the compiled C++ program,
pool-cpp.out.
Language interop
morloc can compose functions across languages. For example:
import math (fibonacci);
import rbase (plotVectorPDF, ints2reals);
export fibplot
fibplot n = plotVectorPDF (ints2reals (fibonacci n)) "fibonacci-plot.pdf";
The fibplot function calculates Fibonacci numbers using a C++ function and
plots it using an R function. The R function plotPDF is a perfectly normal R
function with no extra boilerplate:
plotPDF <- function(x, filename){
  pdf(filename)
  plot(x)
  dev.off()
}
The Morloc Type System
The first level of the morloc type system is basically System F extended
across languages. A given function will have a general type as well as a
specialized type for each language it is implemented in.
The map function has the types
map :: (a -> b) -> [a] -> [b]
map Cpp :: (a -> b) -> "std::vector<$1>" a -> "std::vector<$1>" b
map Python3 :: (a -> b) -> list a -> list b
The general signature looks almost the same as the Haskell equivalent (except
that morloc universal quantification is currently explicit). The list type
constructors for C++ are very literally "type constructors" in that they are
used to create syntactically correct C++ type strings. If the type variable a
is inferred to be int, for example, then the C++ type std::vector<int> will
be used in the generated code. The same occurs in the python type constructors
list, except here the same Python type is generated regardless of the type of
a.
The following example is available in examples/rmsWithTypes.loc:
import cppbase (fold, map, add, mul)
export square;
export sumOfSquares;
square x = mul x x;
sumOfSquares xs = fold add 0 (map square xs);
This example cannot be compiled since none of the functions are imported or
sourced, but it can be typechecked:
morloc typecheck examples/rmsWithTypes.loc
add :: Num -> Num -> Num;
add Cpp :: double -> double -> double;
mul :: Num -> Num -> Num;
mul Cpp :: double -> double -> double;
fold     :: (b -> a -> b) -> b -> [a] -> b;
fold Cpp :: (b -> a -> b) -> b -> "std::vector<$1>" a -> b;
map :: (a -> b) -> [a] -> [b];
map Cpp :: (a -> b) -> "std::vector<$1>" a
                    -> "std::vector<$1>" b;
square x = mul x x;
sumOfSquares xs = fold add 0 (map square xs);
The typechecker associates each sub-expression of the program with a set of
types. The specific type information in mul is sufficient to infer concrete
types for every other C++ function in the program. The inferred C++ type of
sumOfSquares is
"std::vector<$1>" double -> double
The general type for this expression is also inferred as:
List Num -> Num
The concrete type of mul is currently written as a binary function of
doubles. Ideally this function should accept any numbers (e.g., an int and a
double). I intend to add this functionallity eventually, perhaps with a
Haskell-style typeclass system.