Author: Matti Picus <[email protected]>
Branch: extradoc
Changeset: r952:1d7194367707
Date: 2019-08-24 21:33 +0300
http://bitbucket.org/pypy/pypy.org/changeset/1d7194367707/
Log: remove references to numpypy, numpy is now just a "normal"
c-extension module
Maybe someday we will revive it ...
diff --git a/download.html b/download.html
--- a/download.html
+++ b/download.html
@@ -81,7 +81,6 @@
</li>
<li><a class="reference internal" href="#installing">Installing</a>
(optional)</li>
<li><a class="reference internal" href="#installing-more-modules">Installing
more modules</a></li>
-<li><a class="reference internal" href="#installing-numpy">Installing
NumPy</a> (optional)</li>
<li><a class="reference internal" href="#building-from-source">Building from
source</a></li>
<li><a class="reference internal" href="#packaging">Packaging</a></li>
<li><a class="reference internal" href="#checksums">Checksums</a></li>
@@ -215,50 +214,6 @@
into a virtualenv. If you try to build a module and the build process complains
about “missing Python.h”, you may need to install the pypy-dev
package.</p>
</div>
-<div class="section" id="installing-numpy">
-<h1>Installing NumPy</h1>
-<p><strong>There are two different versions of NumPy for PyPy.</strong> For
details see this
-<a class="reference external"
href="http://doc.pypy.org/en/latest/faq.html#should-i-install-numpy-or-numpypy";>FAQ
question</a>.</p>
-<div class="section" id="standard-numpy">
-<h2>1. Standard NumPy</h2>
-<p>Installation works on any recent PyPy (the <a class="reference internal"
href="#release">release</a> above is fine).
-For example, without using a virtualenv:</p>
-<pre class="literal-block">
-$ ./pypy-xxx/bin/pypy -m ensurepip
-$ ./pypy-xxx/bin/pip install cython numpy
-</pre>
-<p>(See the general <a class="reference external"
href="http://doc.pypy.org/en/latest/install.html";>installation
documentation</a> for more.)</p>
-</div>
-<div class="section" id="numpypy">
-<h2>2. NumPyPy</h2>
-<p>The “numpy” module can also be installed from <a
class="reference external" href="https://bitbucket.org/pypy/numpy";>our own
repository</a> rather
-than from the official source. This version uses our
-built-in <tt class="docutils literal">_numpypy</tt> multiarray replacement
module, written in RPython.
-This module is not complete, but if it works it should give correct answers.
-Its performance is hard to predict exactly. For regular NumPy
-source code that handles large arrays, it is likely to be slower than
-the standard NumPy. It is faster on pure python code that loop over ndarrays
-doing things on an element-by-element basis.</p>
-<p>Installation (see the <a class="reference external"
href="http://doc.pypy.org/en/latest/install.html";>installation
documentation</a> for installing <tt class="docutils literal">pip</tt>):</p>
-<pre class="literal-block">
-pypy -m pip install git+https://bitbucket.org/pypy/numpy.git
-</pre>
-<p>Alternatively, the direct way:</p>
-<pre class="literal-block">
-git clone https://bitbucket.org/pypy/numpy.git
-cd numpy
-pypy setup.py install
-</pre>
-<p>If you installed to a system directory, you need to also run this once:</p>
-<pre class="literal-block">
-sudo pypy -c 'import numpy'
-</pre>
-<p>Note again that this version is incomplete: many things do
-not work and those that do may not be any faster than NumPy on CPython.
-For further instructions see <a class="reference external"
href="https://bitbucket.org/pypy/numpy";>the pypy/numpy repository</a> and the
-<a class="reference external"
href="http://doc.pypy.org/en/latest/faq.html#should-i-install-numpy-or-numpypy";>FAQ
question</a> about the difference between the two.</p>
-</div>
-</div>
<div class="section" id="building-from-source">
<span id="translate"></span><h1>Building from source</h1>
<p>(see more build <a class="reference external"
href="http://pypy.readthedocs.org/en/latest/build.html";>instructions</a>)</p>
diff --git a/performance.html b/performance.html
--- a/performance.html
+++ b/performance.html
@@ -245,7 +245,9 @@
</pre>
<p>the JIT cannot optimize out intermediate copies. This code is
actually quadratic in the total size of the mylist strings due to
-repeated string copies of ever-larger prefix segments.</p>
+repeated string copies of ever-larger prefix segments. (Such code
+is always fine for bytearrays, because in this case <tt class="docutils
literal">+=</tt> is an
+in-place operation.)</p>
<p>This:</p>
<pre class="literal-block">
parts = []
diff --git a/source/download.txt b/source/download.txt
--- a/source/download.txt
+++ b/source/download.txt
@@ -35,7 +35,6 @@
* `Installing`_ (optional)
* `Installing more modules`_
- * `Installing NumPy`_ (optional)
* `Building from source`_
* `Packaging`_
* `Checksums`_
@@ -250,63 +249,6 @@
.. _installation documentation: http://doc.pypy.org/en/latest/install.html
-
-
-Installing NumPy
--------------------------------
-
-**There are two different versions of NumPy for PyPy.** For details see this
-`FAQ question`_.
-
-1. Standard NumPy
-+++++++++++++++++
-
-Installation works on any recent PyPy (the release_ above is fine).
-For example, without using a virtualenv::
-
- $ ./pypy-xxx/bin/pypy -m ensurepip
- $ ./pypy-xxx/bin/pip install cython numpy
-
-(See the general `installation documentation`_ for more.)
-
-
-2. NumPyPy
-++++++++++
-
-The "numpy" module can also be installed from `our own repository`__ rather
-than from the official source. This version uses our
-built-in ``_numpypy`` multiarray replacement module, written in RPython.
-This module is not complete, but if it works it should give correct answers.
-Its performance is hard to predict exactly. For regular NumPy
-source code that handles large arrays, it is likely to be slower than
-the standard NumPy. It is faster on pure python code that loop over ndarrays
-doing things on an element-by-element basis.
-
-.. __: https://bitbucket.org/pypy/numpy
-
-Installation (see the `installation documentation`_ for installing ``pip``)::
-
- pypy -m pip install git+https://bitbucket.org/pypy/numpy.git
-
-Alternatively, the direct way::
-
- git clone https://bitbucket.org/pypy/numpy.git
- cd numpy
- pypy setup.py install
-
-If you installed to a system directory, you need to also run this once::
-
- sudo pypy -c 'import numpy'
-
-Note again that this version is incomplete: many things do
-not work and those that do may not be any faster than NumPy on CPython.
-For further instructions see `the pypy/numpy repository`__ and the
-`FAQ question`_ about the difference between the two.
-
-.. __: https://bitbucket.org/pypy/numpy
-.. _`FAQ question`:
http://doc.pypy.org/en/latest/faq.html#should-i-install-numpy-or-numpypy
-
-
.. _translate:
Building from source
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