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<li class="toctree-l2"><a class="reference internal" href="nep-0006-newbugtracker.html">NEP 6 — Replacing Trac with a different bug tracker</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0008-groupby_additions.html">NEP 8 — A proposal for adding groupby functionality to NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0009-structured_array_extensions.html">NEP 9 — Structured array extensions</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0011-deferred-ufunc-evaluation.html">NEP 11 — Deferred UFunc evaluation</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0012-missing-data.html">NEP 12 — Missing data functionality in NumPy</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0021-advanced-indexing.html">NEP 21 — Simplified and explicit advanced indexing</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0024-missing-data-2.html">NEP 24 — Missing data functionality - alternative 1 to NEP 12</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0025-missing-data-3.html">NEP 25 — NA support via special dtypes</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0026-missing-data-summary.html">NEP 26 — Summary of missing data NEPs and discussion</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0030-duck-array-protocol.html">NEP 30 — Duck typing for NumPy arrays - implementation</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0031-uarray.html">NEP 31 — Context-local and global overrides of the NumPy API</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0037-array-module.html">NEP 37 — A dispatch protocol for NumPy-like modules</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0047-array-api-standard.html">NEP 47 — Adopting the array API standard</a></li>
</ul>
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<li class="toctree-l1 has-children"><a class="reference internal" href="rejected.html">Rejected and Withdrawn NEPs</a><details><summary><span class="toctree-toggle" role="presentation"><i class="fa-solid fa-chevron-down"></i></span></summary><ul>
<li class="toctree-l2"><a class="reference internal" href="nep-0016-abstract-array.html">NEP 16 — An abstract base class for identifying "duck arrays"</a></li>
<li class="toctree-l2"><a class="reference internal" href="nep-0017-split-out-maskedarray.html">NEP 17 — Split out masked arrays</a></li>
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<li class="breadcrumb-item active" aria-current="page"><span class="ellipsis">NEP 14 — Plan for dropping Python 2.7 support</span></li>
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<section id="nep-14-plan-for-dropping-python-2-7-support">
<span id="nep14"></span><h1>NEP 14 — Plan for dropping Python 2.7 support<a class="headerlink" href="#nep-14-plan-for-dropping-python-2-7-support" title="Link to this heading">#</a></h1>
<dl class="field-list simple">
<dt class="field-odd">Status<span class="colon">:</span></dt>
<dd class="field-odd"><p>Final</p>
</dd>
<dt class="field-even">Resolution<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference external" href="https://mail.python.org/pipermail/numpy-discussion/2017-November/077419.html">https://mail.python.org/pipermail/numpy-discussion/2017-November/077419.html</a></p>
</dd>
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<p>The Python core team plans to stop supporting Python 2 in 2020. The NumPy
project has supported both Python 2 and Python 3 in parallel since 2010, and
has found that supporting Python 2 is an increasing burden on our limited
resources; thus, we plan to eventually drop Python 2 support as well. Now that
we’re entering the final years of community-supported Python 2, the NumPy
project wants to clarify our plans, with the goal of to helping our downstream
ecosystem make plans and accomplish the transition with as little disruption as
possible.</p>
<p>Our current plan is as follows.</p>
<p>Until <strong>December 31, 2018</strong>, all NumPy releases will fully support both
Python2 and Python3.</p>
<p>Starting on <strong>January 1, 2019</strong>, any new feature releases will support only
Python3.</p>
<p>The last Python2 supporting release will be designated as a long term support
(LTS) release, meaning that we will continue to merge bug fixes and make bug
fix releases for a longer period than usual. Specifically, it will be
supported by the community until <strong>December 31, 2019</strong>.</p>
<p>On <strong>January 1, 2020</strong> we will raise a toast to Python2, and community support
for the last Python2 supporting release will come to an end. However, it will
continue to be available on PyPI indefinitely, and if any commercial vendors
wish to extend the LTS support past this point then we are open to letting them
use the LTS branch in the official NumPy repository to coordinate that.</p>
<p>If you are a NumPy user who requires ongoing Python2 support in 2020 or later,
then please contact your vendor. If you are a vendor who wishes to continue to
support NumPy on Python2 in 2020+, please get in touch; ideally we’d like you
to get involved in maintaining the LTS before it actually hits end of life so
that we can make a clean handoff.</p>
<p>To minimize disruption, running <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">numpy</span></code> on Python 2 will continue
to give the last working release in perpetuity, but after January 1, 2019 it
may not contain the latest features, and after January 1, 2020 it may not
contain the latest bug fixes.</p>
<p>For more information on the scientific Python ecosystem’s transition
to Python3 only, see the <a class="reference external" href="https://python3statement.github.io/">python3-statement</a>.</p>
<p>For more information on porting your code to run on Python 3, see the
<a class="reference external" href="https://docs.python.org/3/howto/pyporting.html">python3-howto</a>.</p>
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