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<div class="section" id="introducing-llpython">
<h1>Introducing LLPython<a class="headerlink" href="#introducing-llpython" title="Permalink to this headline">¶</a></h1>
<p>In this article, we introduce the llpython package. The primary goal
of the llpython package is to provide a Python dialect/subset that
maps directly to LLVM code. LLPython differs from its originating
LLVM translator, Numba, in the following aspects:</p>
<blockquote>
<div><ul class="simple">
<li>LLPython code is not intended to work in Python if not translated
and wrapped.</li>
<li>The LLPython translator only uses LLVM types.</li>
<li>LLPython is explicitly typed, and does not support type inference.
LLPython does not support implicit casts, all casts must be explicit.</li>
<li>LLPython supports code that directly calls the C API, the Python C
API, and the llvm.core.Builder methods.</li>
</ul>
</div></blockquote>
<p>Additionally, we designed the sub-package to have the following
engineering properties:</p>
<blockquote>
<div><ul class="simple">
<li>Usable from Python 2.7, and 3.X. At the time of writing, we plan
to support Python 2.6.</li>
<li>Clean from Numba dependencies (other than llvmpy), and can be used
as a standalone code generator without a full Numba installation.</li>
<li>Provides a series of Python bytecode passes that can be easily
used by other projects.</li>
</ul>
</div></blockquote>
<div class="section" id="llpython-origins">
<h2>LLPython Origins<a class="headerlink" href="#llpython-origins" title="Permalink to this headline">¶</a></h2>
<p>We developed LLPython with the initial goal of simplifying writing
LLVM code.</p>
</div>
<div class="section" id="llpython-internals">
<h2>LLPython Internals<a class="headerlink" href="#llpython-internals" title="Permalink to this headline">¶</a></h2>
<p>In this section, we describe the various passes performed by the
LLPython translator.</p>
</div>
<div class="section" id="conclusions">
<h2>Conclusions<a class="headerlink" href="#conclusions" title="Permalink to this headline">¶</a></h2>
<p>LLPython is neat.</p>
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<li><a class="reference internal" href="#">Introducing LLPython</a><ul>
<li><a class="reference internal" href="#llpython-origins">LLPython Origins</a></li>
<li><a class="reference internal" href="#llpython-internals">LLPython Internals</a></li>
<li><a class="reference internal" href="#conclusions">Conclusions</a></li>
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