TAMGU is a FIL programming language: Functional, Imperative and Logical.
TAMGU is a multithreaded programming language that provides:
- an imperative formalism close to Python, but with a strong and powerful type system.
- a functional formalism inspired by Haskell, which can freely mix with the imperative paradigm
- a logical formalism inspired by Prolog, which can freely mix with the imperative and functional paradigms
For each specific problem in your programming, choose the most appropriate formalism and freely mix functional, imperative and logical approaches to implement the most expressive but also the most compact code possible.
TAMGU provides also an annotation language implementation (see below for an example), which allows for an efficient way to detect complex patterns in text.
The language provides many features but also many libraries, which helps design and implement annotation schemes for complex documents.
Below is an example of the kind of code that you can implement with Tamgu.
//An imperative language
int i=10;
string s="20";
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//Containers
map m = {'a':1, 'b':2}; //all sorts of containers
treemap t = {"u":10, 'v':'toto'};
vector v = [1,2,3,"a","b"];
ivector iv = [1..10]; //iv = [1,2,3,4,5,6,7,8,9,10]
iv = [1,3..10]; //iv = [1,3,5,9]
------------------------------------------------------------------------------------
//Functions, threads and frames
function mycall(int i, string s) {...} //functions
thread mythread(int i, string s) {...} //threads
frame myclass {...} //class definition
------------------------------------------------------------------------------------
//Native Korean string support
s="에버랜드 알쏭달쏭 Quiz";
if (s[0].ishangul()) println("Ok");
uvector dec = s.jamo(); //['ᄋ','ᅦ','ᄇ','ᅥ','ᄅ','ᅢ','ᆫ','ᄃ','ᅳ'...]
dec = s.romanization(); //['-/ng','e','b','eo','r/l','ae','n','d',...]
------------------------------------------------------------------------------------
//Functional approach based on Haskell
ivector iv = [1..20]; //a list of integers between 1 and 20
iv.shuffle(); //The order of the elements is now random.
<fastsort([]) = []>; //if the list is empty, we return an empty "list"
<fastsort([fv:v]) = minlist &&& fv &&& maxlist where //we merge the different list...
let minlist = fastsort(<filter (<=fv) v>), //we sort the list with elements smaller than fv
let maxlist = fastsort(<filter (>fv) v>)>; //we sort the list with elements larger than fv
//we can call a functional definition as regular code
v=fastsort(iv);
------------------------------------------------------------------------------------
//Predicates
concat([],?X,?X).
concat([?H|?T],?Y, [?H|?Z]) :- concat(?T,?Y,?Z).
//You can mix freely your predicate definition with some regular tamgu code
v=concat(["english",'russian',"french"],['spanish'],?L);
println(v); //["english",'russian',"french","spanish"]
Tamgu also provides an integrated rule mechanism, which combines both lexicons and rules to detect complex patterns in texts.
//We define some lexical rules (starting with a "@")
@food <- burger.
@food <- tartare.
//Our rule: if "the food" word is found in a sentence, then we return a "meal" label
meal <- "the", #food.
//We need a specific object to scan a sentence
annotator r;
//a sentence
string sentence="Here, the burger and the tartare are delicious.";
vector v = r.parse(sentence);
//Result: v = [['meal',[10,16]],['meal',[25,32]]]
//It reads: two 'meal' were found at position 10-16 and position 25-32...Note: Releases for Windows, Mac OS and Linux are available at: https://github.com/naver/tamgu/releases
We also provide a Dockerfile, together with precompiled versions of Tamgu and its libraries for Ubuntu 22.04.
Move into the docker directory. You can then create your own docker image with the command:
docker build -t tamgu-interpreter .To execute the docker:
docker run -it tamgu-interpreterExamples are available both as a folder: https://github.com/naver/tamgu/tree/master/examples or as an archive in: https://github.com/naver/tamgu/releases/tag/tamgu.examples.
The TAMGU project has been implemented in C++. It can be compiled on most platforms:
- Windows: see https://github.com/naver/tamgu/wiki/1.1-Compiling-on-Windows
- Mac OS: see https://github.com/naver/tamgu/wiki/1.2-Compiling-on-Mac-OS
- Linux: see https://github.com/naver/tamgu/wiki/1.3-Compiling-on-Linux
Tamgu also provides different libraries:
Compiling libraries: https://github.com/naver/tamgu/wiki/1.4-Compiling-libraries-(Linux-&-Mac-OS)
These two libraries need the following DLL on Windows, which you can obtained from: http://www.mingw.org
libgcc_s_sjlj-1.dll
libltdl-7.dll
libstdc++-6.dll
libwinpthread-1.dll
Furthermore, Tamgu provides a bi-directional library, which can be used to execute Tamgu code from Python (and conversely, Python code in Tamgu)
See: https://github.com/naver/tamgu/wiki/1.5-Compiling-Python for more information
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