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Merge pull request #60 from mattip/bitbucket-heptapod
Change some blogpost links from bitbucket
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posts/2017/10/cape-of-good-hope-for-pypy-hello-from-3656631725712879033.html

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slow logic;</li>
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<li>implement freelists to allocate the cpyext versions of <tt class="docutils literal">int</tt> and
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<tt class="docutils literal">tuple</tt> objects, as CPython does;</li>
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<li>the <a class="reference external" href="https://bitbucket.org/pypy/pypy/commits/branch/cpyext-avoid-roundtrip">cpyext-avoid-roundtrip</a> branch: crossing the RPython/C border is
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<li>the <a class="reference external" href="https://foss.heptapod.net/pypy/pypy/-/merge_requests/573">cpyext-avoid-roundtrip</a> branch: crossing the RPython/C border is
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slowish, but the real problem was (and still is for many cases) we often
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cross it many times for no good reason. So, depending on the actual API
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call, you might end up in the C land, which calls back into the RPython
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<br>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="float: left; margin-right: 1em; text-align: left;"><tbody>
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<tr><td style="text-align: center;"><a href="https://bytebucket.org/pypy/extradoc/raw/extradoc/sprintinfo/cape-town-2017/2017-10-04-155524.jpg" style="margin-left: auto; margin-right: auto;"><img border="0" height="360" src="https://bytebucket.org/pypy/extradoc/raw/extradoc/sprintinfo/cape-town-2017/2017-10-04-155524.jpg" width="640"></a></td></tr>
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<tr><td style="text-align: center;"><a href="https://foss.heptapod.net/pypy/extradoc/-/blob/branch/extradoc/sprintinfo/cape-town-2017/2017-10-04-155524.jpg" style="margin-left: auto; margin-right: auto;"><img border="0" height="360" src="https://bytebucket.org/pypy/extradoc/raw/extradoc/sprintinfo/cape-town-2017/2017-10-04-155524.jpg" width="640"></a></td></tr>
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<tr><td class="tr-caption" style="text-align: center;">The panorama we looked at instead of staring at cpyext code</td></tr>
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</tbody></table></body></html>

posts/2017/10/cape-of-good-hope-for-pypy-hello-from-3656631725712879033.meta

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.. title: (Cape of) Good Hope for PyPy
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.. slug: cape-of-good-hope-for-pypy-hello-from-3656631725712879033
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.. date: 2017-10-18 13:31:00
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.. tags: sprint,unicode,cpyext
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.. tags: sprint,unicode,cpyext,profile,speed
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.. description:
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.. authors: Antonio Cuni
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.. id: 3656631725712879033

posts/2017/10/how-to-make-your-code-80-times-faster-1424098117108093942.html

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Generation 4: ... [population = 500] [33.75 secs]
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</pre>
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Ouch! We are ~5.5x slower than CPython. This was kind of expected: numpy is
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based on cpyext, which is infamously slow. (Actually, <a class="reference external" href="https://morepypy.blogspot.it/2017/10/cape-of-good-hope-for-pypy-hello-from.html">we are working on
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based on cpyext, which is infamously slow. (Actually, <a class="reference external" href="https://pypy.org/posts/2017/10/cape-of-good-hope-for-pypy-hello-from-3656631725712879033.html">we are working on
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that</a> and on the <tt class="docutils literal"><span class="pre">cpyext-avoid-roundtrip</span></tt> branch we are already faster than
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CPython, but this will be the subject of another blog post.)<br>
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<br>
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operations. The operations emitted for the line <tt class="docutils literal"><span class="pre">np.dot(...)</span> +
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self.constant</tt> are listed between lines 1217 and 1456. Here is the excerpt
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which calls <tt class="docutils literal"><span class="pre">np.dot(...)</span></tt>; most of the ops are cheap, but at line 1232 we
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see a call to the RPython function <a class="reference external" href="https://bitbucket.org/pypy/pypy/src/89d1f31fabc86778cfaa1034b1102887c063de66/pypy/module/micronumpy/ndarray.py?at=default&amp;fileviewer=file-view-default#ndarray.py-1168">descr_dot</a>; by looking at the
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see a call to the RPython function <a class="reference external" href="https://foss.heptapod.net/pypy/pypy/-/blob/release-pypy3.5-v5.10.0/pypy/module/micronumpy/ndarray.py#L1160">descr_dot</a>; by looking at the
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implementation we see that it creates a new <tt class="docutils literal">W_NDimArray</tt> to store the
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result, which means it has to do a <tt class="docutils literal">malloc()</tt>:<br>
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<div class="separator" style="clear: both; text-align: center;">
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$ {python,pypy} -m ev.main
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</pre>
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</div>
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</div></body></html>
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</div></body></html>

posts/2017/10/how-to-make-your-code-80-times-faster-1424098117108093942.meta

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.. title: How to make your code 80 times faster
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.. slug: how-to-make-your-code-80-times-faster-1424098117108093942
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.. date: 2017-10-30 10:15:00
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.. tags:
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.. tags: jit, profiling, speed
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.. description:
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.. authors: Antonio Cuni
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.. id: 1424098117108093942

posts/2018/09/the-first-15-years-of-pypy-3412615975376972020.html

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posts/2018/09/the-first-15-years-of-pypy-3412615975376972020.meta

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.. title: The First 15 Years of PyPy — a Personal Retrospective
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.. slug: the-first-15-years-of-pypy-3412615975376972020
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.. date: 2018-09-09 14:50:00
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.. tags:
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.. tags: roadmap
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.. description:
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.. authors: Carl Friedrich Bolz-Tereick
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.. id: 3412615975376972020

posts/2019/01/pypy-for-low-latency-systems-613165393301401965.html

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<br>
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Combining these two functions, it is possible to take control of the GC to
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make sure it runs only when it is acceptable to do so. For an example of
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usage, you can look at the implementation of a <a class="reference external" href="https://bitbucket.org/antocuni/pypytools/src/0273afc3e8bedf0eb1ef630c3bc69e8d9dd661fe/pypytools/gc/custom.py?at=default&amp;fileviewer=file-view-default">custom GC</a> inside <a class="reference external" href="https://pypi.org/project/pypytools/">pypytools</a>.
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usage, you can look at the implementation of a <a class="reference external" href="https://github.com/antocuni/pypytools/blob/master/pypytools/gc/custom.py">custom GC</a> inside <a class="reference external" href="https://pypi.org/project/pypytools/">pypytools</a>.
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The peculiarity is that it also defines a "<tt class="docutils literal">with <span class="pre">nogc():"</span></tt> context manager
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which you can use to mark performance-critical sections where the GC is not
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allowed to run.<br>
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available in the nightly builds of PyPy, and will be included in the next
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release: take this as a New Year present :)<br>
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<br>
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Antonio Cuni and the PyPy team</body></html>
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Antonio Cuni and the PyPy team</body></html>

posts/2022/04/how-is-pypy-tested.rst

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A few historical notes on the PyPy project and its relationship to testing: The
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PyPy project `was started in 2004`_. At the time when the project was started,
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Extreme Programming and Agile Software Development where up and coming. On the
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Extreme Programming and Agile Software Development were up and coming. On the
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methodology side, PyPy was heavily influenced by these, and started using
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Test-Driven Development and pair programming right from the start.
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