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chronoline.js is a library for making a chronology timeline out of events on a horizontal timescale.
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Rickshaw is a JavaScript toolkit for creating interactive time series graphs.
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http://www.freeformatter.com/
http://jsonlint.com/
http://jsbeautifier.org/
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#!/usr/bin/python
import sys
import simplejson as json
import web
urls = (
'/(.*)', 'index'
)
recursion = 0
recursion_max = 10
# template nesting function
def nestor( page ):
page = 'templates/' + page
global recursion
recursion += 1
if recursion > recursion_max:
print "[d] nestor reached max recursion limit"
print "[d] fatal error, givin' up..."
sys.exit(1)
print "[d] rendering inline template %s, recursion %s" % ( page, recursion )
try:
render = web.template.frender( page, globals = { 'nestor': nestor } )
except IOError:
print "[d] can't find page template %s" % page
print "[d] rendered content is\n%s" % render()
recursion -= 1
return render()
# define application
app = web.application( urls, globals() )
render = web.template.render( 'templates', globals = { 'nestor': nestor } )
class index:
def GET( self, argv ):
print "[d] in index function, rootdir"
return render.eq_index()
if __name__ == "__main__":
app.run()
templates/eq_index.html
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Equal-Layers</title>
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, user-scalable=no">
<link type="text/css" rel="stylesheet" href="/static/theme/css/bootstrap.min.css">
<link type="text/css" rel="stylesheet" href="/static/theme/css/font-awesome.min.css">
<link type="text/css" rel="stylesheet" href="/static/theme/css/ionicons.min.css">
<link type="text/css" rel="stylesheet" href="/static/theme/css/AdminLTE.css">
</head>
<body class="skin-blue">
<!-- body content -->
$:nestor( 'eq_body.html' )
</body>
</html>
templates/eq_body.html
<h1>Hello world!</h1>
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wget --recursive --no-parent http://ftp.fi.muni.cz/pub/linux/fedora/[ add comment ] ( 1 view ) | [ 0 trackbacks ] | permalink | related link
F I R E B U G
-------------
link is below
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Backpropagation is an algorithm used to teach feed forward artificial neural networks. It works by providing a set of input data and ideal output data to the network, calculating the actual outputs and backpropagating the calculated error (the difference between the ideal and actual outputs) using gradient descent. This is useful for learning specific patterns of input and output data in order to be able to reproduce them afterwards even from slightly different or incomplete input data. Neural networks are able to learn any function that applies to input data by doing a generalization of the patterns they are trained with.
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jVectorMap uses only native browser technologies like JavaScript, CSS, HTML, SVG or VML. No Flash or any other proprietary browser plug-in is required. This allows jVectorMap to work in all modern mobile browsers
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Sleek, intuitive, and powerful front-end framework for faster and easier web development.
http://leapfrogui.com/controlfrog/cf/documentation.html
http://leapfrogui.com/controlfrog/
http://bootstrapmaster.com/live/simpliq2/page-todo.html
https://wrapbootstrap.com/themes/page.2/sort.rank/order.asc
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