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<section id="nep-49-data-allocation-strategies">
<span id="nep49"></span><h1>NEP 49 — Data allocation strategies<a class="headerlink" href="#nep-49-data-allocation-strategies" title="Link to this heading">#</a></h1>
<dl class="field-list simple">
<dt class="field-odd">Author<span class="colon">:</span></dt>
<dd class="field-odd"><p>Matti Picus</p>
</dd>
<dt class="field-even">Status<span class="colon">:</span></dt>
<dd class="field-even"><p>Final</p>
</dd>
<dt class="field-odd">Type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Standards Track</p>
</dd>
<dt class="field-even">Created<span class="colon">:</span></dt>
<dd class="field-even"><p>2021-04-18</p>
</dd>
<dt class="field-odd">Resolution<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference external" href="https://mail.python.org/archives/list/numpy-discussion@python.org/thread/YZ3PNTXZUT27B6ITFAD3WRSM3T3SRVK4/#PKYXCTG4R5Q6LIRZC4SEWLNBM6GLRF26">https://mail.python.org/archives/list/numpy-discussion@python.org/thread/YZ3PNTXZUT27B6ITFAD3WRSM3T3SRVK4/#PKYXCTG4R5Q6LIRZC4SEWLNBM6GLRF26</a></p>
</dd>
</dl>
<section id="abstract">
<h2>Abstract<a class="headerlink" href="#abstract" title="Link to this heading">#</a></h2>
<p>The <code class="docutils literal notranslate"><span class="pre">numpy.ndarray</span></code> requires additional memory allocations
to hold <code class="docutils literal notranslate"><span class="pre">numpy.ndarray.strides</span></code>, <code class="docutils literal notranslate"><span class="pre">numpy.ndarray.shape</span></code> and
<code class="docutils literal notranslate"><span class="pre">numpy.ndarray.data</span></code> attributes. These attributes are specially allocated
after creating the python object in <code class="docutils literal notranslate"><span class="pre">__new__</span></code> method.</p>
<p>This NEP proposes a mechanism to override the memory management strategy used
for <code class="docutils literal notranslate"><span class="pre">ndarray->data</span></code> with user-provided alternatives. This allocation holds
the data and can be very large. As accessing this data often becomes
a performance bottleneck, custom allocation strategies to guarantee data
alignment or pinning allocations to specialized memory hardware can enable
hardware-specific optimizations. The other allocations remain unchanged.</p>
</section>
<section id="motivation-and-scope">
<h2>Motivation and scope<a class="headerlink" href="#motivation-and-scope" title="Link to this heading">#</a></h2>
<p>Users may wish to override the internal data memory routines with ones of their
own. Two such use-cases are to ensure data alignment and to pin certain
allocations to certain NUMA cores. This desire for alignment was discussed
multiple times on the mailing list <a class="reference external" href="https://numpy-discussion.scipy.narkive.com/MvmMkJcK/numpy-arrays-data-allocation-and-simd-alignement">in 2005</a>, and in <a class="reference external" href="https://github.com/numpy/numpy/issues/5312">issue 5312</a> in 2014,
which led to <a class="reference external" href="https://github.com/numpy/numpy/pull/5457">PR 5457</a> and more mailing list discussions <a class="reference external" href="https://mail.python.org/archives/list/numpy-discussion@python.org/thread/YPC5BGPUMKT2MLBP6O3FMPC35LFM2CCH/#YPC5BGPUMKT2MLBP6O3FMPC35LFM2CCH">here</a> <a class="reference external" href="https://mail.python.org/archives/list/numpy-discussion@python.org/thread/IQK3EPIIRE3V4BPNAMJ2ZST3NUG2MK2A/#IQK3EPIIRE3V4BPNAMJ2ZST3NUG2MK2A">and here</a>. In
a comment on the issue <a class="reference external" href="https://github.com/numpy/numpy/issues/5312#issuecomment-315234656">from 2017</a>, a user described how 64-byte alignment
improved performance by 40x.</p>
<p>Also related is <a class="reference external" href="https://github.com/numpy/numpy/issues/14177">issue 14177</a> around the use of <code class="docutils literal notranslate"><span class="pre">madvise</span></code> and huge pages on
Linux.</p>
<p>Various tracing and profiling libraries like <a class="reference external" href="https://github.com/pythonspeed/filprofiler/blob/master/design/allocator-overrides.md">filprofiler</a> or <a class="reference external" href="https://github.com/boundarydevices/efence">electric fence</a>
override <code class="docutils literal notranslate"><span class="pre">malloc</span></code>.</p>
<p>The long CPython discussion of <a class="reference external" href="https://bugs.python.org/issue18835">BPO 18835</a> began with discussing the need for
<code class="docutils literal notranslate"><span class="pre">PyMem_Alloc32</span></code> and <code class="docutils literal notranslate"><span class="pre">PyMem_Alloc64</span></code>. The early conclusion was that the
cost (of wasted padding) vs. the benefit of aligned memory is best left to the
user, but then evolves into a discussion of various proposals to deal with
memory allocations, including <a class="reference external" href="https://www.python.org/dev/peps/pep-0445/">PEP 445</a> <a class="reference external" href="https://docs.python.org/3/c-api/memory.html#customize-memory-allocators">memory interfaces</a> to
<code class="docutils literal notranslate"><span class="pre">PyTraceMalloc_Track</span></code> which apparently was explicitly added for NumPy.</p>
<p>Allowing users to implement different strategies via the NumPy C-API will
enable exploration of this rich area of possible optimizations. The intention
is to create a flexible enough interface without burdening normative users.</p>
</section>
<section id="usage-and-impact">
<h2>Usage and impact<a class="headerlink" href="#usage-and-impact" title="Link to this heading">#</a></h2>
<p>The new functions can only be accessed via the NumPy C-API. An example is
included later in this NEP. The added <code class="docutils literal notranslate"><span class="pre">struct</span></code> will increase the size of the
<code class="docutils literal notranslate"><span class="pre">ndarray</span></code> object. It is a necessary price to pay for this approach. We
can be reasonably sure that the change in size will have a minimal impact on
end-user code because NumPy version 1.20 already changed the object size.</p>
<p>The implementation preserves the use of <code class="docutils literal notranslate"><span class="pre">PyTraceMalloc_Track</span></code> to track
allocations already present in NumPy.</p>
</section>
<section id="backward-compatibility">
<h2>Backward compatibility<a class="headerlink" href="#backward-compatibility" title="Link to this heading">#</a></h2>
<p>The design will not break backward compatibility. Projects that were assigning
to the <code class="docutils literal notranslate"><span class="pre">ndarray->data</span></code> pointer were already breaking the current memory
management strategy and should restore
<code class="docutils literal notranslate"><span class="pre">ndarray->data</span></code> before calling <code class="docutils literal notranslate"><span class="pre">Py_DECREF</span></code>. As mentioned above, the change
in size should not impact end-users.</p>
</section>
<section id="detailed-description">
<h2>Detailed description<a class="headerlink" href="#detailed-description" title="Link to this heading">#</a></h2>
<section id="high-level-design">
<h3>High level design<a class="headerlink" href="#high-level-design" title="Link to this heading">#</a></h3>
<p>Users who wish to change the NumPy data memory management routines will use
<a class="reference internal" href="#c.PyDataMem_SetHandler" title="PyDataMem_SetHandler"><code class="xref c c-func docutils literal notranslate"><span class="pre">PyDataMem_SetHandler()</span></code></a>, which uses a <a class="reference internal" href="#c.PyDataMem_Handler" title="PyDataMem_Handler"><code class="xref c c-type docutils literal notranslate"><span class="pre">PyDataMem_Handler</span></code></a>
structure to hold pointers to functions used to manage the data memory. In
order to allow lifetime management of the <code class="docutils literal notranslate"><span class="pre">context</span></code>, the structure is wrapped
in a <code class="docutils literal notranslate"><span class="pre">PyCapsule</span></code>.</p>
<p>Since a call to <code class="docutils literal notranslate"><span class="pre">PyDataMem_SetHandler</span></code> will change the default functions, but
that function may be called during the lifetime of an <code class="docutils literal notranslate"><span class="pre">ndarray</span></code> object, each
<code class="docutils literal notranslate"><span class="pre">ndarray</span></code> will carry with it the <code class="docutils literal notranslate"><span class="pre">PyDataMem_Handler</span></code>-wrapped PyCapsule used
at the time of its instantiation, and these will be used to reallocate or free
the data memory of the instance. Internally NumPy may use <code class="docutils literal notranslate"><span class="pre">memcpy</span></code> or
<code class="docutils literal notranslate"><span class="pre">memset</span></code> on the pointer to the data memory.</p>
<p>The name of the handler will be exposed on the python level via a
<code class="docutils literal notranslate"><span class="pre">numpy.core.multiarray.get_handler_name(arr)</span></code> function. If called as
<code class="docutils literal notranslate"><span class="pre">numpy.core.multiarray.get_handler_name()</span></code> it will return the name of the
handler that will be used to allocate data for the next new <cite>ndarrray</cite>.</p>
<p>The version of the handler will be exposed on the python level via a
<code class="docutils literal notranslate"><span class="pre">numpy.core.multiarray.get_handler_version(arr)</span></code> function. If called as
<code class="docutils literal notranslate"><span class="pre">numpy.core.multiarray.get_handler_version()</span></code> it will return the version of the
handler that will be used to allocate data for the next new <cite>ndarrray</cite>.</p>
<p>The version, currently 1, allows for future enhancements to the
<code class="docutils literal notranslate"><span class="pre">PyDataMemAllocator</span></code>. If fields are added, they must be added to the end.</p>
</section>
<section id="numpy-c-api-functions">
<h3>NumPy C-API functions<a class="headerlink" href="#numpy-c-api-functions" title="Link to this heading">#</a></h3>
<dl class="c type">
<dt class="sig sig-object c" id="c.PyDataMem_Handler">
<span class="k"><span class="pre">type</span></span><span class="w"> </span><span class="sig-name descname"><span class="n"><span class="pre">PyDataMem_Handler</span></span></span><a class="headerlink" href="#c.PyDataMem_Handler" title="Link to this definition">#</a><br /></dt>
<dd><p>A struct to hold function pointers used to manipulate memory</p>
<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="k">typedef</span><span class="w"> </span><span class="k">struct</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="kt">char</span><span class="w"> </span><span class="n">name</span><span class="p">[</span><span class="mi">127</span><span class="p">];</span><span class="w"> </span><span class="cm">/* multiple of 64 to keep the struct aligned */</span>
<span class="w"> </span><span class="kt">uint8_t</span><span class="w"> </span><span class="n">version</span><span class="p">;</span><span class="w"> </span><span class="cm">/* currently 1 */</span>
<span class="w"> </span><span class="n">PyDataMemAllocator</span><span class="w"> </span><span class="n">allocator</span><span class="p">;</span>
<span class="p">}</span><span class="w"> </span><span class="n">PyDataMem_Handler</span><span class="p">;</span>
</pre></div>
</div>
<p>where the allocator structure is</p>
<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="cm">/* The declaration of free differs from PyMemAllocatorEx */</span>
<span class="k">typedef</span><span class="w"> </span><span class="k">struct</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">;</span>
<span class="w"> </span><span class="kt">void</span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="o">*</span><span class="n">malloc</span><span class="p">)</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">size</span><span class="p">);</span>
<span class="w"> </span><span class="kt">void</span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="o">*</span><span class="n">calloc</span><span class="p">)</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">nelem</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">elsize</span><span class="p">);</span>
<span class="w"> </span><span class="kt">void</span><span class="o">*</span><span class="w"> </span><span class="p">(</span><span class="o">*</span><span class="n">realloc</span><span class="p">)</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="n">ptr</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">new_size</span><span class="p">);</span>
<span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="p">(</span><span class="o">*</span><span class="n">free</span><span class="p">)</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="n">ptr</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">size</span><span class="p">);</span>
<span class="p">}</span><span class="w"> </span><span class="n">PyDataMemAllocator</span><span class="p">;</span>
</pre></div>
</div>
<p>The use of a <code class="docutils literal notranslate"><span class="pre">size</span></code> parameter in <code class="docutils literal notranslate"><span class="pre">free</span></code> differentiates this struct from
the <a class="reference external" href="https://docs.python.org/dev/c-api/memory.html#c.PyMemAllocatorEx" title="(in Python v3.14)"><code class="xref c c-type docutils literal notranslate"><span class="pre">PyMemAllocatorEx</span></code></a> struct in Python. This call signature is
used internally in NumPy currently, and also in other places for instance
<cite>C++98 <https://en.cppreference.com/w/cpp/memory/allocator/deallocate></cite>,
<cite>C++11 <https://en.cppreference.com/w/cpp/memory/allocator_traits/deallocate></cite>, and
<cite>Rust (allocator_api) <https://doc.rust-lang.org/std/alloc/trait.Allocator.html#tymethod.deallocate></cite>.</p>
<p>The consumer of the <cite>PyDataMemAllocator</cite> interface must keep track of <code class="docutils literal notranslate"><span class="pre">size</span></code> and make sure it is
consistent with the parameter passed to the <code class="docutils literal notranslate"><span class="pre">(m|c|re)alloc</span></code> functions.</p>
<p>NumPy itself may violate this requirement when the shape of the requested
array contains a <code class="docutils literal notranslate"><span class="pre">0</span></code>, so authors of PyDataMemAllocators should relate to
the <code class="docutils literal notranslate"><span class="pre">size</span></code> parameter as a best-guess. Work to fix this is ongoing in PRs
<a class="reference external" href="https://github.com/numpy/numpy/pull/15780">15780</a> and <a class="reference external" href="https://github.com/numpy/numpy/pull/15788">15788</a> but has not yet been resolved. When it is this NEP should
be revisited.</p>
</dd></dl>
<dl class="c function">
<dt class="sig sig-object c" id="c.PyDataMem_SetHandler">
<a class="reference external" href="https://docs.python.org/dev/c-api/structures.html#c.PyObject" title="(in Python v3.14)"><span class="n"><span class="pre">PyObject</span></span></a><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="sig-name descname"><span class="n"><span class="pre">PyDataMem_SetHandler</span></span></span><span class="sig-paren">(</span><a class="reference external" href="https://docs.python.org/dev/c-api/structures.html#c.PyObject" title="(in Python v3.14)"><span class="n"><span class="pre">PyObject</span></span></a><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="n"><span class="pre">handler</span></span><span class="sig-paren">)</span><a class="headerlink" href="#c.PyDataMem_SetHandler" title="Link to this definition">#</a><br /></dt>
<dd><p>Sets a new allocation policy. If the input value is <code class="docutils literal notranslate"><span class="pre">NULL</span></code>, will reset
the policy to the default. Return the previous policy, or
return NULL if an error has occurred. We wrap the user-provided
so they will still call the Python and NumPy memory management callback
hooks. All the function pointers must be filled in, <code class="docutils literal notranslate"><span class="pre">NULL</span></code> is not
accepted.</p>
</dd></dl>
<dl class="c function">
<dt class="sig sig-object c" id="c.PyDataMem_GetHandler">
<span class="k"><span class="pre">const</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/dev/c-api/structures.html#c.PyObject" title="(in Python v3.14)"><span class="n"><span class="pre">PyObject</span></span></a><span class="w"> </span><span class="p"><span class="pre">*</span></span><span class="sig-name descname"><span class="n"><span class="pre">PyDataMem_GetHandler</span></span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#c.PyDataMem_GetHandler" title="Link to this definition">#</a><br /></dt>
<dd><p>Return the current policy that will be used to allocate data for the
next <code class="docutils literal notranslate"><span class="pre">PyArrayObject</span></code>. On failure, return <code class="docutils literal notranslate"><span class="pre">NULL</span></code>.</p>
</dd></dl>
</section>
<section id="pydatamem-handler-thread-safety-and-lifetime">
<h3><code class="docutils literal notranslate"><span class="pre">PyDataMem_Handler</span></code> thread safety and lifetime<a class="headerlink" href="#pydatamem-handler-thread-safety-and-lifetime" title="Link to this heading">#</a></h3>
<p>The active handler is stored in the current <a class="reference external" href="https://docs.python.org/dev/library/contextvars.html#contextvars.Context" title="(in Python v3.14)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Context</span></code></a>
via a <a class="reference external" href="https://docs.python.org/dev/library/contextvars.html#contextvars.ContextVar" title="(in Python v3.14)"><code class="xref py py-class docutils literal notranslate"><span class="pre">ContextVar</span></code></a>. This ensures it can be configured both
per-thread and per-async-coroutine.</p>
<p>There is currently no lifetime management of <code class="docutils literal notranslate"><span class="pre">PyDataMem_Handler</span></code>.
The user of <cite>PyDataMem_SetHandler</cite> must ensure that the argument remains alive
for as long as any objects allocated with it, and while it is the active handler.
In practice, this means the handler must be immortal.</p>
<p>As an implementation detail, currently this <code class="docutils literal notranslate"><span class="pre">ContextVar</span></code> contains a <code class="docutils literal notranslate"><span class="pre">PyCapsule</span></code>
object storing a pointer to a <code class="docutils literal notranslate"><span class="pre">PyDataMem_Handler</span></code> with no destructor,
but this should not be relied upon.</p>
</section>
<section id="sample-code">
<h3>Sample code<a class="headerlink" href="#sample-code" title="Link to this heading">#</a></h3>
<p>This code adds a 64-byte header to each <code class="docutils literal notranslate"><span class="pre">data</span></code> pointer and stores information
about the allocation in the header. Before calling <code class="docutils literal notranslate"><span class="pre">free</span></code>, a check ensures
the <code class="docutils literal notranslate"><span class="pre">sz</span></code> argument is correct.</p>
<div class="highlight-c notranslate"><div class="highlight"><pre><span></span><span class="cp">#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION</span>
<span class="cp">#include</span><span class="w"> </span><span class="cpf"><numpy/arrayobject.h></span>
<span class="n">NPY_NO_EXPORT</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span>
<span class="k">typedef</span><span class="w"> </span><span class="k">struct</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">(</span><span class="o">*</span><span class="n">malloc</span><span class="p">)(</span><span class="kt">size_t</span><span class="p">);</span>
<span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">(</span><span class="o">*</span><span class="n">calloc</span><span class="p">)(</span><span class="kt">size_t</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="p">);</span>
<span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">(</span><span class="o">*</span><span class="n">realloc</span><span class="p">)(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="p">);</span>
<span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="p">(</span><span class="o">*</span><span class="n">free</span><span class="p">)(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">);</span>
<span class="p">}</span><span class="w"> </span><span class="n">Allocator</span><span class="p">;</span>
<span class="n">NPY_NO_EXPORT</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span>
<span class="n">shift_alloc</span><span class="p">(</span><span class="n">Allocator</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">sz</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="n">real</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="n">ctx</span><span class="o">-></span><span class="n">malloc</span><span class="p">(</span><span class="n">sz</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">);</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">real</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="nb">NULL</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nb">NULL</span><span class="p">;</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="n">snprintf</span><span class="p">(</span><span class="n">real</span><span class="p">,</span><span class="w"> </span><span class="mi">64</span><span class="p">,</span><span class="w"> </span><span class="s">"originally allocated %ld"</span><span class="p">,</span><span class="w"> </span><span class="p">(</span><span class="kt">unsigned</span><span class="w"> </span><span class="kt">long</span><span class="p">)</span><span class="n">sz</span><span class="p">);</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)(</span><span class="n">real</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">);</span>
<span class="p">}</span>
<span class="n">NPY_NO_EXPORT</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span>
<span class="n">shift_zero</span><span class="p">(</span><span class="n">Allocator</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">sz</span><span class="p">,</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">cnt</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="n">real</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="n">ctx</span><span class="o">-></span><span class="n">calloc</span><span class="p">(</span><span class="n">sz</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">,</span><span class="w"> </span><span class="n">cnt</span><span class="p">);</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">real</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="nb">NULL</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nb">NULL</span><span class="p">;</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="n">snprintf</span><span class="p">(</span><span class="n">real</span><span class="p">,</span><span class="w"> </span><span class="mi">64</span><span class="p">,</span><span class="w"> </span><span class="s">"originally allocated %ld via zero"</span><span class="p">,</span>
<span class="w"> </span><span class="p">(</span><span class="kt">unsigned</span><span class="w"> </span><span class="kt">long</span><span class="p">)</span><span class="n">sz</span><span class="p">);</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)(</span><span class="n">real</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">);</span>
<span class="p">}</span>
<span class="n">NPY_NO_EXPORT</span><span class="w"> </span><span class="kt">void</span>
<span class="n">shift_free</span><span class="p">(</span><span class="n">Allocator</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="n">p</span><span class="p">,</span><span class="w"> </span><span class="n">npy_uintp</span><span class="w"> </span><span class="n">sz</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">p</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="nb">NULL</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="p">;</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="n">real</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="n">p</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mi">64</span><span class="p">;</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">strncmp</span><span class="p">(</span><span class="n">real</span><span class="p">,</span><span class="w"> </span><span class="s">"originally allocated"</span><span class="p">,</span><span class="w"> </span><span class="mi">20</span><span class="p">)</span><span class="w"> </span><span class="o">!=</span><span class="w"> </span><span class="mi">0</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">fprintf</span><span class="p">(</span><span class="n">stdout</span><span class="p">,</span><span class="w"> </span><span class="s">"uh-oh, unmatched shift_free, "</span>
<span class="w"> </span><span class="s">"no appropriate prefix</span><span class="se">\\</span><span class="s">n"</span><span class="p">);</span>
<span class="w"> </span><span class="cm">/* Make C runtime crash by calling free on the wrong address */</span>
<span class="w"> </span><span class="n">ctx</span><span class="o">-></span><span class="n">free</span><span class="p">((</span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="n">p</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">10</span><span class="p">);</span>
<span class="w"> </span><span class="cm">/* ctx->free(real); */</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">npy_uintp</span><span class="w"> </span><span class="n">i</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="n">npy_uintp</span><span class="p">)</span><span class="n">atoi</span><span class="p">(</span><span class="n">real</span><span class="w"> </span><span class="o">+</span><span class="mi">20</span><span class="p">);</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">i</span><span class="w"> </span><span class="o">!=</span><span class="w"> </span><span class="n">sz</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">fprintf</span><span class="p">(</span><span class="n">stderr</span><span class="p">,</span><span class="w"> </span><span class="s">"uh-oh, unmatched shift_free"</span>
<span class="w"> </span><span class="s">"(ptr, %ld) but allocated %ld</span><span class="se">\\</span><span class="s">n"</span><span class="p">,</span><span class="w"> </span><span class="n">sz</span><span class="p">,</span><span class="w"> </span><span class="n">i</span><span class="p">);</span>
<span class="w"> </span><span class="cm">/* This happens when the shape has a 0, only print */</span>
<span class="w"> </span><span class="n">ctx</span><span class="o">-></span><span class="n">free</span><span class="p">(</span><span class="n">real</span><span class="p">);</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">ctx</span><span class="o">-></span><span class="n">free</span><span class="p">(</span><span class="n">real</span><span class="p">);</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="p">}</span>
<span class="p">}</span>
<span class="n">NPY_NO_EXPORT</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span>
<span class="n">shift_realloc</span><span class="p">(</span><span class="n">Allocator</span><span class="w"> </span><span class="o">*</span><span class="n">ctx</span><span class="p">,</span><span class="w"> </span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="n">p</span><span class="p">,</span><span class="w"> </span><span class="n">npy_uintp</span><span class="w"> </span><span class="n">sz</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">p</span><span class="w"> </span><span class="o">!=</span><span class="w"> </span><span class="nb">NULL</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="n">real</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="n">p</span><span class="w"> </span><span class="o">-</span><span class="w"> </span><span class="mi">64</span><span class="p">;</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">strncmp</span><span class="p">(</span><span class="n">real</span><span class="p">,</span><span class="w"> </span><span class="s">"originally allocated"</span><span class="p">,</span><span class="w"> </span><span class="mi">20</span><span class="p">)</span><span class="w"> </span><span class="o">!=</span><span class="w"> </span><span class="mi">0</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">fprintf</span><span class="p">(</span><span class="n">stdout</span><span class="p">,</span><span class="w"> </span><span class="s">"uh-oh, unmatched shift_realloc</span><span class="se">\\</span><span class="s">n"</span><span class="p">);</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">realloc</span><span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="w"> </span><span class="n">sz</span><span class="p">);</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)((</span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="n">ctx</span><span class="o">-></span><span class="n">realloc</span><span class="p">(</span><span class="n">real</span><span class="p">,</span><span class="w"> </span><span class="n">sz</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">)</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">);</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="k">else</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="n">real</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">(</span><span class="kt">char</span><span class="w"> </span><span class="o">*</span><span class="p">)</span><span class="n">ctx</span><span class="o">-></span><span class="n">realloc</span><span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="w"> </span><span class="n">sz</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">);</span>
<span class="w"> </span><span class="k">if</span><span class="w"> </span><span class="p">(</span><span class="n">real</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="nb">NULL</span><span class="p">)</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="nb">NULL</span><span class="p">;</span>
<span class="w"> </span><span class="p">}</span>
<span class="w"> </span><span class="n">snprintf</span><span class="p">(</span><span class="n">real</span><span class="p">,</span><span class="w"> </span><span class="mi">64</span><span class="p">,</span><span class="w"> </span><span class="s">"originally allocated "</span>
<span class="w"> </span><span class="s">"%ld via realloc"</span><span class="p">,</span><span class="w"> </span><span class="p">(</span><span class="kt">unsigned</span><span class="w"> </span><span class="kt">long</span><span class="p">)</span><span class="n">sz</span><span class="p">);</span>
<span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="p">(</span><span class="kt">void</span><span class="w"> </span><span class="o">*</span><span class="p">)(</span><span class="n">real</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">64</span><span class="p">);</span>
<span class="w"> </span><span class="p">}</span>
<span class="p">}</span>
<span class="k">static</span><span class="w"> </span><span class="n">Allocator</span><span class="w"> </span><span class="n">new_handler_ctx</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="n">malloc</span><span class="p">,</span>
<span class="w"> </span><span class="n">calloc</span><span class="p">,</span>
<span class="w"> </span><span class="n">realloc</span><span class="p">,</span>
<span class="w"> </span><span class="n">free</span>
<span class="p">};</span>
<span class="k">static</span><span class="w"> </span><span class="n">PyDataMem_Handler</span><span class="w"> </span><span class="n">new_handler</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="s">"secret_data_allocator"</span><span class="p">,</span>
<span class="w"> </span><span class="mi">1</span><span class="p">,</span>
<span class="w"> </span><span class="p">{</span>
<span class="w"> </span><span class="o">&</span><span class="n">new_handler_ctx</span><span class="p">,</span>
<span class="w"> </span><span class="n">shift_alloc</span><span class="p">,</span><span class="w"> </span><span class="cm">/* malloc */</span>
<span class="w"> </span><span class="n">shift_zero</span><span class="p">,</span><span class="w"> </span><span class="cm">/* calloc */</span>
<span class="w"> </span><span class="n">shift_realloc</span><span class="p">,</span><span class="w"> </span><span class="cm">/* realloc */</span>
<span class="w"> </span><span class="n">shift_free</span><span class="w"> </span><span class="cm">/* free */</span>
<span class="w"> </span><span class="p">}</span>
<span class="p">};</span>
</pre></div>
</div>
</section>
</section>
<section id="related-work">
<h2>Related work<a class="headerlink" href="#related-work" title="Link to this heading">#</a></h2>
<p>This NEP is being tracked by the <a class="reference external" href="https://quansight.github.io/pnumpy/stable/index.html">pnumpy</a> project and a <a class="reference external" href="https://github.com/numpy/numpy/pull/17582#issuecomment-809145547">comment in the PR</a>
mentions use in orchestrating FPGA DMAs.</p>
</section>
<section id="implementation">
<h2>Implementation<a class="headerlink" href="#implementation" title="Link to this heading">#</a></h2>
<p>This NEP has been implemented in <a class="reference external" href="https://github.com/numpy/numpy/pull/17582">PR 17582</a>.</p>
</section>
<section id="alternatives">
<h2>Alternatives<a class="headerlink" href="#alternatives" title="Link to this heading">#</a></h2>
<p>These were discussed in <a class="reference external" href="https://github.com/numpy/numpy/issues/17467">issue 17467</a>. <a class="reference external" href="https://github.com/numpy/numpy/pull/5457">PR 5457</a> and <a class="reference external" href="https://github.com/numpy/numpy/pull/5470">PR 5470</a> proposed a
global interface for specifying aligned allocations.</p>
<p><code class="docutils literal notranslate"><span class="pre">PyArray_malloc_aligned</span></code> and friends were added to NumPy with the
<cite>numpy.random</cite> module API refactor. and are used there for performance.</p>
<p><a class="reference external" href="https://github.com/numpy/numpy/pull/390">PR 390</a> had two parts: expose <code class="docutils literal notranslate"><span class="pre">PyDataMem_*</span></code> via the NumPy C-API, and a hook
mechanism. The PR was merged with no example code for using these features.</p>
</section>
<section id="discussion">
<h2>Discussion<a class="headerlink" href="#discussion" title="Link to this heading">#</a></h2>
<p>The discussion on the mailing list led to the <code class="docutils literal notranslate"><span class="pre">PyDataMemAllocator</span></code> struct
with a <code class="docutils literal notranslate"><span class="pre">context</span></code> field like <a class="reference external" href="https://docs.python.org/dev/c-api/memory.html#c.PyMemAllocatorEx" title="(in Python v3.14)"><code class="xref c c-type docutils literal notranslate"><span class="pre">PyMemAllocatorEx</span></code></a> but with a different
signature for <code class="docutils literal notranslate"><span class="pre">free</span></code>.</p>
</section>
<section id="references-and-footnotes">
<h2>References and footnotes<a class="headerlink" href="#references-and-footnotes" title="Link to this heading">#</a></h2>
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<span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id4">1</a><span class="fn-bracket">]</span></span>
<p>Each NEP must either be explicitly labeled as placed in the public domain (see
this NEP as an example) or licensed under the <a class="reference external" href="https://www.opencontent.org/openpub/">Open Publication License</a>.</p>
</aside>
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<h2>Copyright<a class="headerlink" href="#copyright" title="Link to this heading">#</a></h2>
<p>This document has been placed in the public domain. <a class="footnote-reference brackets" href="#id1" id="id4" role="doc-noteref"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></a></p>
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<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#usage-and-impact">Usage and impact</a></li>
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<li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#pydatamem-handler-thread-safety-and-lifetime"><code class="docutils literal notranslate"><span class="pre">PyDataMem_Handler</span></code> thread safety and lifetime</a></li>
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