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-rw-r--r--doc/HOWTO_RELEASE.rst.txt2
-rw-r--r--doc/source/reference/arrays.classes.rst7
-rw-r--r--doc/source/reference/c-api.types-and-structures.rst6
-rw-r--r--doc/source/user/c-info.python-as-glue.rst17
-rw-r--r--doc/source/user/install.rst11
-rw-r--r--numpy/core/src/multiarray/numpyos.c2
6 files changed, 19 insertions, 26 deletions
diff --git a/doc/HOWTO_RELEASE.rst.txt b/doc/HOWTO_RELEASE.rst.txt
index 98e7aac8f..61bf71da0 100644
--- a/doc/HOWTO_RELEASE.rst.txt
+++ b/doc/HOWTO_RELEASE.rst.txt
@@ -113,7 +113,7 @@ Wine
For building Windows binaries on OS X Wine can be used. In Wine the following
needs to be installed:
-* Python 2.5-2.7 and 3.1-3.2
+* Python 2.6-2.7 and 3.2
* MakeNsis
* CpuId plugin for MakeNsis : this can be found in the NumPy source tree under
tools/win32build/cpucaps and has to be built with MinGW (see SConstruct file in
diff --git a/doc/source/reference/arrays.classes.rst b/doc/source/reference/arrays.classes.rst
index 80013060b..e77dfc31e 100644
--- a/doc/source/reference/arrays.classes.rst
+++ b/doc/source/reference/arrays.classes.rst
@@ -267,13 +267,6 @@ they inherit from the ndarray): :meth:`.flush() <memmap.flush>` which
must be called manually by the user to ensure that any changes to the
array actually get written to disk.
-.. note::
-
- Memory-mapped arrays use the the Python memory-map object which
- (prior to Python 2.5) does not allow files to be larger than a
- certain size depending on the platform. This size is always
- < 2GB even on 64-bit systems.
-
.. autosummary::
:toctree: generated/
diff --git a/doc/source/reference/c-api.types-and-structures.rst b/doc/source/reference/c-api.types-and-structures.rst
index 95272c151..473e25010 100644
--- a/doc/source/reference/c-api.types-and-structures.rst
+++ b/doc/source/reference/c-api.types-and-structures.rst
@@ -1031,9 +1031,9 @@ PyArray_Chunk
This is equivalent to the buffer object structure in Python up to
the ptr member. On 32-bit platforms (*i.e.* if :cdata:`NPY_SIZEOF_INT`
- == :cdata:`NPY_SIZEOF_INTP` ) or in Python 2.5, the len member also
- matches an equivalent member of the buffer object. It is useful to
- represent a generic single- segment chunk of memory.
+ == :cdata:`NPY_SIZEOF_INTP`), the len member also matches an equivalent
+ member of the buffer object. It is useful to represent a generic
+ single-segment chunk of memory.
.. code-block:: c
diff --git a/doc/source/user/c-info.python-as-glue.rst b/doc/source/user/c-info.python-as-glue.rst
index 0560c005e..8dfd39beb 100644
--- a/doc/source/user/c-info.python-as-glue.rst
+++ b/doc/source/user/c-info.python-as-glue.rst
@@ -65,7 +65,7 @@ high-level language for scientific and engineering programming.
Their are two basic approaches to calling compiled code: writing an
extension module that is then imported to Python using the import
command, or calling a shared-library subroutine directly from Python
-using the ctypes module (included in the standard distribution with
+using the ctypes module (included in the standard distribution since
Python 2.5). The first method is the most common (but with the
inclusion of ctypes into Python 2.5 this status may change).
@@ -902,14 +902,13 @@ libraries), or weave (for inline C-code).
ctypes
======
-Ctypes is a python extension module (downloaded separately for Python
-<2.5 and included with Python 2.5) that allows you to call an
-arbitrary function in a shared library directly from Python. This
-approach allows you to interface with C-code directly from Python.
-This opens up an enormous number of libraries for use from Python. The
-drawback, however, is that coding mistakes can lead to ugly program
-crashes very easily (just as can happen in C) because there is little
-type or bounds checking done on the parameters. This is especially
+Ctypes is a Python extension module, included in the stdlib, that
+allows you to call an arbitrary function in a shared library directly
+from Python. This approach allows you to interface with C-code directly
+from Python. This opens up an enormous number of libraries for use from
+Python. The drawback, however, is that coding mistakes can lead to ugly
+program crashes very easily (just as can happen in C) because there is
+little type or bounds checking done on the parameters. This is especially
true when array data is passed in as a pointer to a raw memory
location. The responsibility is then on you that the subroutine will
not access memory outside the actual array area. But, if you don't
diff --git a/doc/source/user/install.rst b/doc/source/user/install.rst
index 1da664e08..29aeff6a3 100644
--- a/doc/source/user/install.rst
+++ b/doc/source/user/install.rst
@@ -59,18 +59,19 @@ Prerequisites
Building NumPy requires the following software installed:
-1) Python 2.4.x, 2.5.x or 2.6.x
+1) Python 2.6.x, 2.7.x, 3.2.x or newer
- On Debian and derivative (Ubuntu): python, python-dev
+ On Debian and derivatives (Ubuntu): python, python-dev (or python3-dev)
On Windows: the official python installer at
`www.python.org <http://www.python.org>`_ is enough
Make sure that the Python package distutils is installed before
- continuing. For example, in Debian GNU/Linux, distutils is included
- in the python-dev package.
+ continuing. For example, in Debian GNU/Linux, installing python-dev
+ also installs distutils.
- Python must also be compiled with the zlib module enabled.
+ Python must also be compiled with the zlib module enabled. This is
+ practically always the case with pre-packaged Pythons.
2) Compilers
diff --git a/numpy/core/src/multiarray/numpyos.c b/numpy/core/src/multiarray/numpyos.c
index 44b32f4da..dddead7ea 100644
--- a/numpy/core/src/multiarray/numpyos.c
+++ b/numpy/core/src/multiarray/numpyos.c
@@ -507,7 +507,7 @@ NumPyOS_ascii_strtod(const char *s, char** endptr)
/*
* ## 2
*
- * At least Python versions <= 2.5.2 and <= 2.6.1
+ * At least Python versions <= 2.6.1
*
* Fails to do best-efforts parsing of strings of the form "1<DP>234"
* where <DP> is the decimal point under the foreign locale.