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<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="chrome=1">
<meta name="keywords" content="python spark data array open source distributed local">
<meta name="description" content="Unified interface for local and distributed multi-dimensional arrays in Python backed by Spark">
<meta property="og:image" content="http://bolt-project.org/images/header-logo-small-square.png"/>
<title>Bolt</title>
<link rel="stylesheet" href="css/styles.css">
<link rel="stylesheet" href="css/shelves.css">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.7.1/jquery.min.js"></script>
<link rel="icon" sizes="16x16 32x32" href="favicon.ico?v=2">
<meta name="viewport" content="width=device-width, initial-scale=1">
</head>
<div class='content'>
<div class="row">
<div id="side" class="column-4">
<img class='logo' src="images/header-logo-small-expanded.svg"></img>
<iframe id='badge', src="https://ghbtns.com/github-btn.html?user=bolt-project&repo=bolt&type=star&count=true&size=small" frameborder="0" scrolling="0" width="160px" height="30px"></iframe>
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<div id="main" class="column-6">
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<h1>Bringing multi-dimensional arrays to distributed settings through a unified Python interface</h1>
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<div class="row">
<img class='bars' src="images/bars.svg"></img>
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<div class="row">
<h2>Bolt is an open source library providing a Python interface to ndarrays backed by local or distributed implementations (currently targeting Spark). We want to make working with big array data in Python as easy and seamless as in local settings, while exploiting the speed of proven distributed engines.</h2>
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<div class="row">
<a href='docs/index.html'>Documentation</a>
<br>
<a href='docs/installation.html'>Installation</a>
<br>
<a href='http://try.bolt-project.org'>Live notebooks</a>
<br>
<a href='http://github.com/bolt-project/bolt'>GitHub repo</a>
<br>
<a href='https://gitter.im/bolt-project/bolt'>Chatroom</a>
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