jaw-parser v1.0.0
jaw-parser# jaw-parser
This function breaks done .jaw documents(file type for Fullstack DataScientists).
DEPLOY FRONTEND AND BACKEND(+DATA SCIENCE AND MACHINE LEARNING LAYERS) TOGETHER BY WRITING ALL YOUR SCRIPTS IN ONE PAGE. THE STRUCTURING ON THAT SINGLE PAGE. (SUPER-WEAPON);
Data Science and Cloud Software Development b
Imagine the world where data scientists can write fullstack projects on one single manuscipt or source code that's wellpacked. Welcome to the the world of .jaw documents. The aim to is to bright a world where mathematics and direct conversion to reality can exist.
One's the parser is done executing you have an express server setup based in .You can write all your algorithms in any language in one .jaw document. PYTHON, JAVASCRIPT, C++, HTML, NODEJS. You can now unit all these languages and get the best of all worlds.
Humans can now directly design their mathematical algorithm and visual geometry can how exist.
ADVANTAGES:
- For academist who want to take advantage of the rise in data science opportunities.
- Provides less barrier for technopreneurs and data-science entrepreneurs by letting them deploy their research script to applications and public server immediately.
- If you need one framework which neatly organizes your code on a single page (enabling you brainstorm easily and see algorithms to be more of mathematicals and artistic in nature).
- You can actually do research and be ready for production in faster languages.
Gives you the best of the artificial intelligence world.
UNIFICATION.
EXAMPLE
//install your jaw-parser. sudo npm install --save jaw-parser.
//write console scipt on node. var jaw = require("jaw-parser"); jaw.parse(path_to_jaw_file);
//write your .jaw file and save.
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\/
<!DOCTYPE html>
<html>
<head>
<title>JAW EXAMPLE</title>
</head>
<body>
<!-- EXAMPLE CONTAINER -->
<!-- =================================================================== -->
<div id="app" mode={{Data.mode}}></div>
<!-- DATA STRUCTURE AND DATA ENGINEERING LAYER -->
<script type="text/javascript" data="true" language="javascript" mode={{Data.mode}} directory={{Data.directory.data.schema}} status={{Data.status.NOT_DONE}}>
Data = {
mode:'development',
status: {
DONE : 1,
NOT_DONE : 0
},
directories : {
data : {
schema : "./model/neuron.js"
},
sensor: {
request : "./public/javascripts/sensor.js"
},
processor : {
analyser : "./src/analyser.py"
}
},
}
</script>
<!-- (JAVASCRIPT) LOGIC LAYER -->
<!-- =================================================================== -->
<script type="text/javascripts" language="javascript" mode={{Data.mode}} directory={{Data.directory.sensor.request}} status={{Data.status.NOT_DONE}}>
(fuction(){alert()})()
</script>
<!-- (PYTHON) DATA DISCOVERY LAYER -->
<!-- =================================================================== -->
<script type="text/python" language="python" mode={{Data.mode}} directory={{Data.directory.processor.analyser}} status={{Data.status.NOT_DONE}}>
import pandas as pd;
import numpy as np;
import Neruone.processor as processor;
def correlations(events_filename):
dataframes = pd.read_csv(events);
pass;
def clusters(events_filename):
dataframes = pd.read_csv(events);
pass;
def learn_clusters(events_filename):
processor//learn
def learn_correlation(events_filename):
//do something.
</script>
</body>
</html>6 years ago