Nateve compiler developed with python.

Overview

Adam

Adam is a Nateve Programming Language compiler developed using Python.

Nateve

Nateve is a new general domain programming language open source inspired by languages like Python, C++, JavaScript, and Wolfram Mathematica.

Nateve is an compiled language. Its first compiler, Adam, is fully built using Python 3.8.

Options of command line (Nateve)

  1. build: Transpile Nateve source code to Python 3.8
  2. run: Run Nateve source code
  3. compile: Compile Nateve source code to an executable file (.exe)
  4. run-init-loop: Run Nateve source code with an initial source and a loop source
  5. set-time-unit: Set Adam time unit to seconds or miliseconds (default: milisecond)
  6. -v: Activate verbose mode

Nateve Tutorial

In this tutorial, we will learn how to use Nateve step by step.

Step 1: Create a new Nateve project

$ cd my-project
$ COPY CON main.nateve

Hello World program

print("Hello, World!")

Is prime? program

def is_prime(n) {
    if n == 1 {
        return False
    }
    for i in range(2, n) {
        if n % i == 0 {
            return False
        }
    }
    return True
}

n = intput("Enter a number: ")

if is_prime(n) {
    print("It is a prime number.")
}
else {
    print("It is not a prime number.")
}

Comments

If you want to comment your code, you can use:

~ This is a single line comment ~

~
    And this a multiline comment
~

Under construction...

Let Statements

This language does not use variables. Instead of variables, you can only declare static values.

For declaring a value, you must use let and give it a value. For example:

let a = 1        -- Interger
let b = 1.0      -- Float
let c = "string" -- String
let d = true     -- Boolean
let e = [1,2,3]  -- List
let f = (1,2)    -- Tuple
...             

SigmaF allows data type as Integer, Float, Boolean, and String.

Lists

The Lists allow to use all the data types before mentioned, as well as lists and functions.

Also, they allow to get an item through the next notation:

let value_list = [1,2,3,4,5,6,7,8,9]
value_list[0]       -- Output: 1
value_list[0, 4]    -- Output: [1,2,3,4]
value_list[0, 8, 2] -- Output: [1, 3, 5, 7]

The struct of List CAll is example_list[<Start>, <End>, <Jump>]

Tuples

The tuples are data structs of length greater than 1. Unlike lists, they allow the following operations:

(1,2) + (3,4)      -- Output: (4,6)
(4,6,8) - (3,4,5)  -- Output: (1,2,3)
(0,1) == (0,1)     -- Output: true
(0,1) != (1,3)     -- Output: true

To obtain the values of a tuple, you must use the same notation of the list. But this data structure does not allow ranges like the lists (only you can get one position of a tuple).

E.g.

let t = (1,2,3,4,5,6)
t[1] -- Output: 2
t[5] -- Output: 6

And so on.

Operators

Warning: SigmaF have Static Typing, so it does not allow the operation between different data types.

These are operators:

Operator Symbol
Plus +
Minus -
Multiplication *
Division /
Modulus %
Exponential **
Equal ==
Not Equal !=
Less than <
Greater than >
Less or equal than <=
Greater or equal than >=
And &&
Or ||

The operator of negation for Boolean was not included. You can use the not() function in order to do this.

Functions

For declaring a function, you have to use the next syntax:

let example_function = fn <Name Argument>::<Argument Type> -> <Output Type> {
    => <Return Value>
}  

(For return, you have to use the => symbol)

For example:

let is_prime_number = fn x::int, i::int -> bool {
    if x <= 1 then {=> false;}
    if x == i then {=> true;}
    if (x % i) == 0 then {=> false;}
    => is_prime_number(x, i+1);
}

printLn(is_prime_number(11, 2)) -- Output: true

Conditionals

Regarding the conditionals, the syntax structure is:

if <Condition> then {
    <Consequence>
}
else{
    <Other Consequence>
}

For example:

if x <= 1 || x % i == 0 then {
    false;
}
if x == i then {
    true;
}
else {
    false;
}

Some Examples

-- Quick Sort
let qsort = fn l::list -> list {

	if (l == []) then {=> [];}
	else {
		let p = l[0];
		let xs = tail(l);
		
		let c_lesser = fn q::int -> bool {=> (q < p)}
		let c_greater = fn q::int -> bool {=> (q >= p)}

		=> qsort(filter(c_lesser, xs)) + [p] + qsort(filter(c_greater, xs));
	}
}

-- Filter
let filter = fn c::function, l::list -> list {
	if (l == []) then {=> [];} 

    => if (c(l[0])) then {[l[0]]} else {[]} +  filter(c, tail(l));
}

-- Map
let map = fn f::function, l::list -> list {
	if (l==[]) then {=> [];}
	
	=> [f(l[0])] + map(f, tail(l));
}

To know other examples of the implementations, you can go to e.g.


Feedback

I would really appreciatte your feedback. You can submit a new issue, or reach out me on Twitter.

Contribute

This is an opensource project, everyone can contribute and become a member of the community of SigmaF.

Why be a member of the SigmaF community?

1. A simple and understandable code

The source code of the interpreter is made with Python 3.8, a language easy to learn, also good practices are a priority for this project.

2. A great potencial

This project has a great potential to be the next programming language of the functional paradigm, to development the AI, and to development new metaheuristics.

3. Scalable development

One of the mains approaches of this project is the implementation of TDD from the beggining and the development of new features, which allows scalability.

4. Simple and power

One of the main purposes of this programming language is to create an easy-to-learn functional language, which at the same time is capable of processing large amounts of data safely and allows concurrence and parallelism.

5. Respect for diversity

Everybody is welcome, it does not matter your genre, experience or nationality. Anyone with enthusiasm can be part of this project. Anyone from the most expert to the that is beginning to learn about programming, marketing, design, or any career.

How to start contributing?

There are multiply ways to contribute, since sharing this project, improving the brand of SigmaF, helping to solve the bugs or developing new features and making improves to the source code.

  • Share this project: You can put your star in the repository, or talk about this project. You can use the hashtag #SigmaF in Twitter, LinkedIn or any social network too.

  • Improve the brand of SigmaF: If you are a marketer, designer or writer, and you want to help, you are welcome. You can contact me on Twitter like @fabianmativeal if you are interested on doing it.

  • Help to solve the bugs: if you find one bug notify me an issue. On this we can all improve this language.

  • Developing new features: If you want to develop new features or making improvements to the project, you can do a fork to the dev branch (here are the ultimate develops) working there, and later do a pull request to dev branch in order to update SigmaF.

You might also like...
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Pattern Pattern is a web mining module for Python. It has tools for: Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM par

A python framework to transform natural language questions to queries in a database query language.

__ _ _ _ ___ _ __ _ _ / _` | | | |/ _ \ '_ \| | | | | (_| | |_| | __/ |_) | |_| | \__, |\__,_|\___| .__/ \__, | |_| |_| |___/

Python library for processing Chinese text

SnowNLP: Simplified Chinese Text Processing SnowNLP是一个python写的类库,可以方便的处理中文文本内容,是受到了TextBlob的启发而写的,由于现在大部分的自然语言处理库基本都是针对英文的,于是写了一个方便处理中文的类库,并且和TextBlob

A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:
A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:

A Python package implementing a new model for text classification with visualization tools for Explainable AI 🍣 Online live demos: http://tworld.io/s

Python bindings to the dutch NLP tool Frog (pos tagger, lemmatiser, NER tagger, morphological analysis, shallow parser, dependency parser)

Frog for Python This is a Python binding to the Natural Language Processing suite Frog. Frog is intended for Dutch and performs part-of-speech tagging

A python wrapper around the ZPar parser for English.

NOTE This project is no longer under active development since there are now really nice pure Python parsers such as Stanza and Spacy. The repository w

💫 Industrial-strength Natural Language Processing (NLP) in Python

spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc

Python interface for converting Penn Treebank trees to Stanford Dependencies and Universal Depenencies

PyStanfordDependencies Python interface for converting Penn Treebank trees to Universal Dependencies and Stanford Dependencies. Example usage Start by

Comments
  • [Enhancement] Nateve Vectors don't allow non-numeric datatypes

    [Enhancement] Nateve Vectors don't allow non-numeric datatypes

    Vectors just allow to use numbers (int/float) into them, because Vectors are redifinening Python Built-in lists in the middle code generation process. A possible solution is to join Vectors and Matrices into a Linear datatypes with the syntax opener tag "$", and the to make independent the python lists

    opened by eanorambuena 0
  • [Bug] Double execution of the modules in assembling process

    [Bug] Double execution of the modules in assembling process

    We need to resolve the double execution of the modules in assembling process.

    The last Non Double Execution Patch has been deprecated because it did generate bugs of type: - Code segmentation in the driver_file

    bug help wanted 
    opened by eanorambuena 0
Releases(0.0.3)
Owner
Nateve
Repositories related to the Nateve Programming Language
Nateve
Index different CKAN entities in Solr, not just datasets

ckanext-sitesearch Index different CKAN entities in Solr, not just datasets Requirements This extension requires CKAN 2.9 or higher and Python 3 Featu

Open Knowledge Foundation 3 Dec 02, 2022
This repository contains (not all) code from my project on Named Entity Recognition in philosophical text

NERphilosophy 👋 Welcome to the github repository of my BsC thesis. This repository contains (not all) code from my project on Named Entity Recognitio

Ruben 1 Jan 27, 2022
ByT5: Towards a token-free future with pre-trained byte-to-byte models

ByT5: Towards a token-free future with pre-trained byte-to-byte models ByT5 is a tokenizer-free extension of the mT5 model. Instead of using a subword

Google Research 409 Jan 06, 2023
FB ID CLONER WUTHOT CHECKPOINT, FACEBOOK ID CLONE FROM FILE

* MY SOCIAL MEDIA : Programming And Memes Want to contact Mr. Error ? CONTACT : [ema

Mr. Error 9 Jun 17, 2021
Python bot created with Selenium that can guess the daily Wordle word correct 96.8% of the time.

Wordle_Bot Python bot created with Selenium that can guess the daily Wordle word correct 96.8% of the time. It will log onto the wordle website and en

Lucas Polidori 15 Dec 11, 2022
This project aims to conduct a text information retrieval and text mining on medical research publication regarding Covid19 - treatments and vaccinations.

Project: Text Analysis - This project aims to conduct a text information retrieval and text mining on medical research publication regarding Covid19 -

1 Mar 14, 2022
Creating an Audiobook (mp3 file) using a Ebook (epub) using BeautifulSoup and Google Text to Speech

epub2audiobook Creating an Audiobook (mp3 file) using a Ebook (epub) using BeautifulSoup and Google Text to Speech Input examples qual a pasta do seu

7 Aug 25, 2022
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

ParlAI (pronounced “par-lay”) is a python framework for sharing, training and testing dialogue models, from open-domain chitchat, to task-oriented dia

Facebook Research 9.7k Jan 09, 2023
Python3 to Crystal Translation using Python AST Walker

py2cr.py A code translator using AST from Python to Crystal. This is basically a NodeVisitor with Crystal output. See AST documentation (https://docs.

66 Jul 25, 2022
🤗🖼️ HuggingPics: Fine-tune Vision Transformers for anything using images found on the web.

🤗 🖼️ HuggingPics Fine-tune Vision Transformers for anything using images found on the web. Check out the video below for a walkthrough of this proje

Nathan Raw 185 Dec 21, 2022
Tools and data for measuring the popularity & growth of various programming languages.

growth-data Tools and data for measuring the popularity & growth of various programming languages. Install the dependencies $ pip install -r requireme

3 Jan 06, 2022
Every Google, Azure & IBM text to speech voice for free

TTS-Grabber Quick thing i made about a year ago to download any text with any tts voice, over 630 voices to choose from currently. It will split the i

16 Dec 07, 2022
Finally decent dictionaries based on Wiktionary for your beloved eBook reader.

eBook Reader Dictionaries Finally, decent dictionaries based on Wiktionary for your beloved eBook reader. Dictionaries Catalan 🚧 Ελληνικά (help welco

Mickaël Schoentgen 163 Dec 31, 2022
The Internet Archive Research Assistant - Daily search Internet Archive for new items matching your keywords

The Internet Archive Research Assistant - Daily search Internet Archive for new items matching your keywords

Kay Savetz 60 Dec 25, 2022
A sentence aligner for comparable corpora

About Yalign is a tool for extracting parallel sentences from comparable corpora. Statistical Machine Translation relies on parallel corpora (eg.. eur

Machinalis 128 Aug 24, 2022
a CTF web challenge about making screenshots

screenshotter (web) A CTF web challenge about making screenshots. It is inspired by a bug found in real life. The challenge was created by @LiveOverfl

219 Jan 02, 2023
Quick insights from Zoom meeting transcripts using Graph + NLP

Transcript Analysis - Graph + NLP This program extracts insights from Zoom Meeting Transcripts (.vtt) using TigerGraph and NLTK. In order to run this

Advit Deepak 7 Sep 17, 2022
Fast, general, and tested differentiable structured prediction in PyTorch

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

HNLP 1.1k Dec 16, 2022
topic modeling on unstructured data in Space news articles retrieved from the Guardian (UK) newspaper using API

NLP Space News Topic Modeling Photos by nasa.gov (1, 2, 3, 4, 5) and extremetech.com Table of Contents Project Idea Data acquisition Primary data sour

edesz 1 Jan 03, 2022
Auto_code_complete is a auto word-completetion program which allows you to customize it on your needs

auto_code_complete is a auto word-completetion program which allows you to customize it on your needs. the model for this program is one of the deep-learning NLP(Natural Language Process) model struc

RUO 2 Feb 22, 2022