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Merged revisions 85572-85573,85606,85609-85622,85624,85626-85627,85629,85631,85633,85635-85636,85638-85639,85641-85642 via svnmerge from 

svn+ssh://svn.python.org/python/branches/py3k

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  r85572 | georg.brandl | 2010-10-16 20:51:05 +0200 (Sa, 16 Okt 2010) | 1 line

  #10122: typo fix.
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  r85573 | georg.brandl | 2010-10-16 20:53:08 +0200 (Sa, 16 Okt 2010) | 1 line

  #10124: typo fix.
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  r85606 | georg.brandl | 2010-10-17 08:32:59 +0200 (So, 17 Okt 2010) | 1 line

  #10058: tweak wording about exception returns.
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  r85609 | georg.brandl | 2010-10-17 11:19:03 +0200 (So, 17 Okt 2010) | 1 line

  #8556: use less confusing mapping key in example.
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  r85610 | georg.brandl | 2010-10-17 11:23:05 +0200 (So, 17 Okt 2010) | 1 line

  #8686: remove potentially confusing wording that does not add any value.
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  r85611 | georg.brandl | 2010-10-17 11:33:24 +0200 (So, 17 Okt 2010) | 1 line

  #8811: small fixes to sqlite3 docs.
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  r85612 | georg.brandl | 2010-10-17 11:37:54 +0200 (So, 17 Okt 2010) | 1 line

  #8855: add shelve security warning.
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  r85613 | georg.brandl | 2010-10-17 11:43:35 +0200 (So, 17 Okt 2010) | 1 line

  Fix hmac docs: it takes and returns bytes, except for hexdigest().
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  r85614 | georg.brandl | 2010-10-17 11:46:11 +0200 (So, 17 Okt 2010) | 1 line

  #8968: add actual name of token constants.
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  r85615 | georg.brandl | 2010-10-17 12:05:13 +0200 (So, 17 Okt 2010) | 1 line

  #459007: merge info from PC/getpathp.c and using/windows.rst to document the forming of sys.path under Windows.
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  r85616 | georg.brandl | 2010-10-17 12:07:29 +0200 (So, 17 Okt 2010) | 1 line

  Fix copy-paste error in example.
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  r85617 | georg.brandl | 2010-10-17 12:09:06 +0200 (So, 17 Okt 2010) | 1 line

  #5212: md5 weaknesses do not affect hmac, so remove the note about that.
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  r85618 | georg.brandl | 2010-10-17 12:14:38 +0200 (So, 17 Okt 2010) | 1 line

  #9086: correct wrong terminology about linking with pythonXY.dll.
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  r85619 | georg.brandl | 2010-10-17 12:15:50 +0200 (So, 17 Okt 2010) | 1 line

  Make file names consistent.
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  r85620 | georg.brandl | 2010-10-17 12:22:28 +0200 (So, 17 Okt 2010) | 1 line

  Remove second parser module example; it referred to non-readily-available example files, and this kind of discovery is much better done with the AST nowadays anyway.
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  r85621 | georg.brandl | 2010-10-17 12:24:54 +0200 (So, 17 Okt 2010) | 1 line

  #9105: move pickle warning to a bit more prominent location.
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  r85622 | georg.brandl | 2010-10-17 12:28:04 +0200 (So, 17 Okt 2010) | 1 line

  #9112: document error() and exit() methods of ArgumentParser.
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  r85624 | georg.brandl | 2010-10-17 12:34:28 +0200 (So, 17 Okt 2010) | 1 line

  Some markup and style fixes in argparse docs.
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  r85626 | georg.brandl | 2010-10-17 12:38:20 +0200 (So, 17 Okt 2010) | 1 line

  #9117: fix syntax for class definition.
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  r85627 | georg.brandl | 2010-10-17 12:44:11 +0200 (So, 17 Okt 2010) | 1 line

  #9138: reword introduction to classes in Python.
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  r85629 | georg.brandl | 2010-10-17 12:51:45 +0200 (So, 17 Okt 2010) | 1 line

  #5962: clarify sys.exit() vs. threads.
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  r85631 | georg.brandl | 2010-10-17 12:53:54 +0200 (So, 17 Okt 2010) | 1 line

  Fix capitalization.
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  r85633 | georg.brandl | 2010-10-17 12:59:41 +0200 (So, 17 Okt 2010) | 1 line

  #9204: remove mentions of removed types in the types module.
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  r85635 | georg.brandl | 2010-10-17 13:03:22 +0200 (So, 17 Okt 2010) | 1 line

  #5121: fix claims about default values leading to segfaults.
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  r85636 | georg.brandl | 2010-10-17 13:06:14 +0200 (So, 17 Okt 2010) | 1 line

  #9237: document sys.call_tracing().
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  r85638 | georg.brandl | 2010-10-17 13:13:37 +0200 (So, 17 Okt 2010) | 1 line

  Port changes to pickle docs apparently lost in py3k.
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  r85639 | georg.brandl | 2010-10-17 13:23:56 +0200 (So, 17 Okt 2010) | 1 line

  Make twisted example a bit more logical.
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  r85641 | georg.brandl | 2010-10-17 13:29:07 +0200 (So, 17 Okt 2010) | 1 line

  Fix documentation of dis.opmap direction.
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  r85642 | georg.brandl | 2010-10-17 13:36:28 +0200 (So, 17 Okt 2010) | 1 line

  #9730: fix example.
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This commit is contained in:
Georg Brandl 2010-11-26 08:49:15 +00:00
parent d6e0202931
commit ab32fec83c
32 changed files with 325 additions and 569 deletions
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3
Doc/c-api/bytearray.rst
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@ -16,7 +16,8 @@ Byte Array Objects
.. cvar:: PyTypeObject PyByteArray_Type
This instance of :ctype:`PyTypeObject` represents the Python bytearray type;
it is the same object as ``bytearray`` in the Python layer.
it is the same object as :class:`bytearray` in the Python layer.
Type check macros
^^^^^^^^^^^^^^^^^

4
Doc/c-api/bytes.rst
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@ -18,10 +18,8 @@ called with a non-bytes parameter.
.. cvar:: PyTypeObject PyBytes_Type
.. index:: single: BytesType (in module types)
This instance of :ctype:`PyTypeObject` represents the Python bytes type; it
is the same object as ``bytes`` in the Python layer. .
is the same object as :class:`bytes` in the Python layer.
.. cfunction:: int PyBytes_Check(PyObject *o)

2
Doc/c-api/complex.rst
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@ -82,7 +82,7 @@ Complex Numbers as Python Objects
.. cvar:: PyTypeObject PyComplex_Type
This instance of :ctype:`PyTypeObject` represents the Python complex number
type. It is the same object as ``complex`` and ``types.ComplexType``.
type. It is the same object as :class:`complex` in the Python layer.
.. cfunction:: int PyComplex_Check(PyObject *p)

7
Doc/c-api/dict.rst
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@ -15,13 +15,8 @@ Dictionary Objects
.. cvar:: PyTypeObject PyDict_Type
.. index::
single: DictType (in module types)
single: DictionaryType (in module types)
This instance of :ctype:`PyTypeObject` represents the Python dictionary
type. This is exposed to Python programs as ``dict`` and
``types.DictType``.
type. This is the same object as :class:`dict` in the Python layer.
.. cfunction:: int PyDict_Check(PyObject *p)

4
Doc/c-api/float.rst
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@ -15,10 +15,8 @@ Floating Point Objects
.. cvar:: PyTypeObject PyFloat_Type
.. index:: single: FloatType (in modules types)
This instance of :ctype:`PyTypeObject` represents the Python floating point
type. This is the same object as ``float`` and ``types.FloatType``.
type. This is the same object as :class:`float` in the Python layer.
.. cfunction:: int PyFloat_Check(PyObject *p)

19
Doc/c-api/intro.rst
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@ -361,15 +361,16 @@ traceback.
.. index:: single: PyErr_Occurred()
For C programmers, however, error checking always has to be explicit. All
functions in the Python/C API can raise exceptions, unless an explicit claim is
made otherwise in a function's documentation. In general, when a function
encounters an error, it sets an exception, discards any object references that
it owns, and returns an error indicator --- usually *NULL* or ``-1``. A few
functions return a Boolean true/false result, with false indicating an error.
Very few functions return no explicit error indicator or have an ambiguous
return value, and require explicit testing for errors with
:cfunc:`PyErr_Occurred`.
For C programmers, however, error checking always has to be explicit. All
functions in the Python/C API can raise exceptions, unless an explicit claim is
made otherwise in a function's documentation. In general, when a function
encounters an error, it sets an exception, discards any object references that
it owns, and returns an error indicator. If not documented otherwise, this
indicator is either *NULL* or ``-1``, depending on the function's return type.
A few functions return a Boolean true/false result, with false indicating an
error. Very few functions return no explicit error indicator or have an
ambiguous return value, and require explicit testing for errors with
:cfunc:`PyErr_Occurred`. These exceptions are always explicitly documented.
.. index::
single: PyErr_SetString()

4
Doc/c-api/list.rst
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@ -15,8 +15,8 @@ List Objects
.. cvar:: PyTypeObject PyList_Type
This instance of :ctype:`PyTypeObject` represents the Python list type. This
is the same object as ``list`` in the Python layer.
This instance of :ctype:`PyTypeObject` represents the Python list type.
This is the same object as :class:`list` in the Python layer.
.. cfunction:: int PyList_Check(PyObject *p)

2
Doc/c-api/long.rst
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@ -18,7 +18,7 @@ All integers are implemented as "long" integer objects of arbitrary size.
.. cvar:: PyTypeObject PyLong_Type
This instance of :ctype:`PyTypeObject` represents the Python integer type.
This is the same object as ``int``.
This is the same object as :class:`int` in the Python layer.
.. cfunction:: int PyLong_Check(PyObject *p)

6
Doc/c-api/slice.rst
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@ -8,10 +8,8 @@ Slice Objects
.. cvar:: PyTypeObject PySlice_Type
.. index:: single: SliceType (in module types)
The type object for slice objects. This is the same as ``slice`` and
``types.SliceType``.
The type object for slice objects. This is the same as :class:`slice` in the
Python layer.
.. cfunction:: int PySlice_Check(PyObject *ob)

6
Doc/c-api/tuple.rst
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@ -15,10 +15,8 @@ Tuple Objects
.. cvar:: PyTypeObject PyTuple_Type
.. index:: single: TupleType (in module types)
This instance of :ctype:`PyTypeObject` represents the Python tuple type; it is
the same object as ``tuple`` and ``types.TupleType`` in the Python layer..
This instance of :ctype:`PyTypeObject` represents the Python tuple type; it
is the same object as :class:`tuple` in the Python layer.
.. cfunction:: int PyTuple_Check(PyObject *p)

6
Doc/c-api/type.rst
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@ -15,10 +15,8 @@ Type Objects
.. cvar:: PyObject* PyType_Type
.. index:: single: TypeType (in module types)
This is the type object for type objects; it is the same object as ``type`` and
``types.TypeType`` in the Python layer.
This is the type object for type objects; it is the same object as
:class:`type` in the Python layer.
.. cfunction:: int PyType_Check(PyObject *o)

4
Doc/c-api/unicode.rst
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@ -204,7 +204,7 @@ APIs:
.. cfunction:: PyObject* PyUnicode_FromUnicode(const Py_UNICODE *u, Py_ssize_t size)
Create a Unicode Object from the Py_UNICODE buffer *u* of the given size. *u*
Create a Unicode object from the Py_UNICODE buffer *u* of the given size. *u*
may be *NULL* which causes the contents to be undefined. It is the user's
responsibility to fill in the needed data. The buffer is copied into the new
object. If the buffer is not *NULL*, the return value might be a shared object.
@ -214,7 +214,7 @@ APIs:
.. cfunction:: PyObject* PyUnicode_FromStringAndSize(const char *u, Py_ssize_t size)
Create a Unicode Object from the char buffer *u*. The bytes will be interpreted
Create a Unicode object from the char buffer *u*. The bytes will be interpreted
as being UTF-8 encoded. *u* may also be *NULL* which
causes the contents to be undefined. It is the user's responsibility to fill in
the needed data. The buffer is copied into the new object. If the buffer is not

20
Doc/c-api/veryhigh.rst
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@ -123,13 +123,13 @@ the same library that the Python runtime is using.
.. cfunction:: int PyRun_InteractiveOneFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)
Read and execute a single statement from a file associated with an interactive
device according to the *flags* argument. If *filename* is *NULL*, ``"???"`` is
used instead. The user will be prompted using ``sys.ps1`` and ``sys.ps2``.
Returns ``0`` when the input was executed successfully, ``-1`` if there was an
exception, or an error code from the :file:`errcode.h` include file distributed
as part of Python if there was a parse error. (Note that :file:`errcode.h` is
not included by :file:`Python.h`, so must be included specifically if needed.)
Read and execute a single statement from a file associated with an
interactive device according to the *flags* argument. The user will be
prompted using ``sys.ps1`` and ``sys.ps2``. Returns ``0`` when the input was
executed successfully, ``-1`` if there was an exception, or an error code
from the :file:`errcode.h` include file distributed as part of Python if
there was a parse error. (Note that :file:`errcode.h` is not included by
:file:`Python.h`, so must be included specifically if needed.)
.. cfunction:: int PyRun_InteractiveLoop(FILE *fp, const char *filename)
@ -138,11 +138,11 @@ the same library that the Python runtime is using.
leaving *flags* set to *NULL*.
.. cfunction:: int PyRun_InteractiveLoopFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)
.. cfunction:: int PyRun_InteractiveLoopFlags(FILE *fp, const char *filename, PyCompilerFlags *flags)
Read and execute statements from a file associated with an interactive device
until EOF is reached. If *filename* is *NULL*, ``"???"`` is used instead. The
user will be prompted using ``sys.ps1`` and ``sys.ps2``. Returns ``0`` at EOF.
until EOF is reached. The user will be prompted using ``sys.ps1`` and
``sys.ps2``. Returns ``0`` at EOF.
.. cfunction:: struct _node* PyParser_SimpleParseString(const char *str, int start)

22
Doc/faq/windows.rst
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@ -290,20 +290,18 @@ Embedding the Python interpreter in a Windows app can be summarized as follows:
1. Do _not_ build Python into your .exe file directly. On Windows, Python must
be a DLL to handle importing modules that are themselves DLL's. (This is the
first key undocumented fact.) Instead, link to :file:`python{NN}.dll`; it is
typically installed in ``C:\Windows\System``. NN is the Python version, a
first key undocumented fact.) Instead, link to :file:`python{NN}.dll`; it is
typically installed in ``C:\Windows\System``. *NN* is the Python version, a
number such as "23" for Python 2.3.
You can link to Python statically or dynamically. Linking statically means
linking against :file:`python{NN}.lib`, while dynamically linking means
linking against :file:`python{NN}.dll`. The drawback to dynamic linking is
that your app won't run if :file:`python{NN}.dll` does not exist on your
system. (General note: :file:`python{NN}.lib` is the so-called "import lib"
corresponding to :file:`python.dll`. It merely defines symbols for the
linker.)
You can link to Python in two different ways. Load-time linking means
linking against :file:`python{NN}.lib`, while run-time linking means linking
against :file:`python{NN}.dll`. (General note: :file:`python{NN}.lib` is the
so-called "import lib" corresponding to :file:`python{NN}.dll`. It merely
defines symbols for the linker.)
Linking dynamically greatly simplifies link options; everything happens at
run time. Your code must load :file:`python{NN}.dll` using the Windows
Run-time linking greatly simplifies link options; everything happens at run
time. Your code must load :file:`python{NN}.dll` using the Windows
``LoadLibraryEx()`` routine. The code must also use access routines and data
in :file:`python{NN}.dll` (that is, Python's C API's) using pointers obtained
by the Windows ``GetProcAddress()`` routine. Macros can make using these
@ -312,6 +310,8 @@ Embedding the Python interpreter in a Windows app can be summarized as follows:
Borland note: convert :file:`python{NN}.lib` to OMF format using Coff2Omf.exe
first.
.. XXX what about static linking?
2. If you use SWIG, it is easy to create a Python "extension module" that will
make the app's data and methods available to Python. SWIG will handle just
about all the grungy details for you. The result is C code that you link

6
Doc/howto/cporting.rst
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@ -50,9 +50,9 @@ Python 3.0's :func:`str` (``PyString_*`` functions in C) type is equivalent to
compatibility with 3.0, :ctype:`PyUnicode` should be used for textual data and
:ctype:`PyBytes` for binary data. It's also important to remember that
:ctype:`PyBytes` and :ctype:`PyUnicode` in 3.0 are not interchangeable like
:ctype:`PyString` and :ctype:`PyString` are in 2.x. The following example shows
best practices with regards to :ctype:`PyUnicode`, :ctype:`PyString`, and
:ctype:`PyBytes`. ::
:ctype:`PyString` and :ctype:`PyUnicode` are in 2.x. The following example
shows best practices with regards to :ctype:`PyUnicode`, :ctype:`PyString`,
and :ctype:`PyBytes`. ::
#include "stdlib.h"
#include "Python.h"

4
Doc/library/audioop.rst
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@ -230,8 +230,8 @@ and recombined later. Here is an example of how to do that::
def mul_stereo(sample, width, lfactor, rfactor):
lsample = audioop.tomono(sample, width, 1, 0)
rsample = audioop.tomono(sample, width, 0, 1)
lsample = audioop.mul(sample, width, lfactor)
rsample = audioop.mul(sample, width, rfactor)
lsample = audioop.mul(lsample, width, lfactor)
rsample = audioop.mul(rsample, width, rfactor)
lsample = audioop.tostereo(lsample, width, 1, 0)
rsample = audioop.tostereo(rsample, width, 0, 1)
return audioop.add(lsample, rsample, width)

4
Doc/library/base64.rst
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@ -157,12 +157,12 @@ The legacy interface:
An example usage of the module:
>>> import base64
>>> encoded = base64.b64encode('data to be encoded')
>>> encoded = base64.b64encode(b'data to be encoded')
>>> encoded
b'ZGF0YSB0byBiZSBlbmNvZGVk'
>>> data = base64.b64decode(encoded)
>>> data
'data to be encoded'
b'data to be encoded'
.. seealso::

5
Doc/library/difflib.rst
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@ -500,16 +500,11 @@ The :class:`SequenceMatcher` class has this constructor:
Return an upper bound on :meth:`ratio` relatively quickly.
This isn't defined beyond that it is an upper bound on :meth:`ratio`, and
is faster to compute.
.. method:: real_quick_ratio()
Return an upper bound on :meth:`ratio` very quickly.
This isn't defined beyond that it is an upper bound on :meth:`ratio`, and
is faster to compute than either :meth:`ratio` or :meth:`quick_ratio`.
The three methods that return the ratio of matching to total characters can give
different results due to differing levels of approximation, although

2
Doc/library/dis.rst
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@ -93,7 +93,7 @@ The :mod:`dis` module defines the following functions and constants:
.. data:: opmap
Dictionary mapping bytecodes to operation names.
Dictionary mapping operation names to bytecodes.
.. data:: cmp_op

2
Doc/library/functions.rst
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@ -466,7 +466,7 @@ are always available. They are listed here in alphabetical order.
.. function:: getattr(object, name[, default])
Return the value of the named attributed of *object*. *name* must be a string.
Return the value of the named attribute of *object*. *name* must be a string.
If the string is the name of one of the object's attributes, the result is the
value of that attribute. For example, ``getattr(x, 'foobar')`` is equivalent to
``x.foobar``. If the named attribute does not exist, *default* is returned if

35
Doc/library/hmac.rst
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@ -2,7 +2,8 @@
========================================================
.. module:: hmac
:synopsis: Keyed-Hashing for Message Authentication (HMAC) implementation for Python.
:synopsis: Keyed-Hashing for Message Authentication (HMAC) implementation
for Python.
.. moduleauthor:: Gerhard Häring <ghaering@users.sourceforge.net>
.. sectionauthor:: Gerhard Häring <ghaering@users.sourceforge.net>
@ -12,37 +13,34 @@ This module implements the HMAC algorithm as described by :rfc:`2104`.
.. function:: new(key, msg=None, digestmod=None)
Return a new hmac object. If *msg* is present, the method call ``update(msg)``
is made. *digestmod* is the digest constructor or module for the HMAC object to
use. It defaults to the :func:`hashlib.md5` constructor.
Return a new hmac object. *key* is a bytes object giving the secret key. If
*msg* is present, the method call ``update(msg)`` is made. *digestmod* is
the digest constructor or module for the HMAC object to use. It defaults to
the :func:`hashlib.md5` constructor.
.. note::
The md5 hash has known weaknesses but remains the default for backwards
compatibility. Choose a better one for your application.
An HMAC object has the following methods:
.. method:: hmac.update(msg)
Update the hmac object with the string *msg*. Repeated calls are equivalent to
a single call with the concatenation of all the arguments: ``m.update(a);
m.update(b)`` is equivalent to ``m.update(a + b)``.
Update the hmac object with the bytes object *msg*. Repeated calls are
equivalent to a single call with the concatenation of all the arguments:
``m.update(a); m.update(b)`` is equivalent to ``m.update(a + b)``.
.. method:: hmac.digest()
Return the digest of the strings passed to the :meth:`update` method so far.
This string will be the same length as the *digest_size* of the digest given to
the constructor. It may contain non-ASCII characters, including NUL bytes.
Return the digest of the bytes passed to the :meth:`update` method so far.
This bytes object will be the same length as the *digest_size* of the digest
given to the constructor. It may contain non-ASCII bytes, including NUL
bytes.
.. method:: hmac.hexdigest()
Like :meth:`digest` except the digest is returned as a string twice the length
containing only hexadecimal digits. This may be used to exchange the value
safely in email or other non-binary environments.
Like :meth:`digest` except the digest is returned as a string twice the
length containing only hexadecimal digits. This may be used to exchange the
value safely in email or other non-binary environments.
.. method:: hmac.copy()
@ -55,4 +53,3 @@ An HMAC object has the following methods:
Module :mod:`hashlib`
The Python module providing secure hash functions.

6
Doc/library/os.rst
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@ -1421,15 +1421,15 @@ to be ignored.
.. function:: _exit(n)
Exit to the system with status *n*, without calling cleanup handlers, flushing
Exit the process with status *n*, without calling cleanup handlers, flushing
stdio buffers, etc.
Availability: Unix, Windows.
.. note::
The standard way to exit is ``sys.exit(n)``. :func:`_exit` should normally only
be used in the child process after a :func:`fork`.
The standard way to exit is ``sys.exit(n)``. :func:`_exit` should
normally only be used in the child process after a :func:`fork`.
The following exit codes are defined and can be used with :func:`_exit`,
although they are not required. These are typically used for system programs

335
Doc/library/parser.rst
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@ -318,22 +318,8 @@ ST objects have the following methods:
Same as ``st2tuple(st, line_info)``.
.. _st-examples:
Examples
--------
.. index:: builtin: compile
The parser modules allows operations to be performed on the parse tree of Python
source code before the :term:`bytecode` is generated, and provides for inspection of the
parse tree for information gathering purposes. Two examples are presented. The
simple example demonstrates emulation of the :func:`compile` built-in function
and the complex example shows the use of a parse tree for information discovery.
Emulation of :func:`compile`
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Example: Emulation of :func:`compile`
-------------------------------------
While many useful operations may take place between parsing and bytecode
generation, the simplest operation is to do nothing. For this purpose, using
@ -367,320 +353,3 @@ readily available functions::
def load_expression(source_string):
st = parser.expr(source_string)
return st, st.compile()
Information Discovery
^^^^^^^^^^^^^^^^^^^^^
.. index::
single: string; documentation
single: docstrings
Some applications benefit from direct access to the parse tree. The remainder
of this section demonstrates how the parse tree provides access to module
documentation defined in docstrings without requiring that the code being
examined be loaded into a running interpreter via :keyword:`import`. This can
be very useful for performing analyses of untrusted code.
Generally, the example will demonstrate how the parse tree may be traversed to
distill interesting information. Two functions and a set of classes are
developed which provide programmatic access to high level function and class
definitions provided by a module. The classes extract information from the
parse tree and provide access to the information at a useful semantic level, one
function provides a simple low-level pattern matching capability, and the other
function defines a high-level interface to the classes by handling file
operations on behalf of the caller. All source files mentioned here which are
not part of the Python installation are located in the :file:`Demo/parser/`
directory of the distribution.
The dynamic nature of Python allows the programmer a great deal of flexibility,
but most modules need only a limited measure of this when defining classes,
functions, and methods. In this example, the only definitions that will be
considered are those which are defined in the top level of their context, e.g.,
a function defined by a :keyword:`def` statement at column zero of a module, but
not a function defined within a branch of an :keyword:`if` ... :keyword:`else`
construct, though there are some good reasons for doing so in some situations.
Nesting of definitions will be handled by the code developed in the example.
To construct the upper-level extraction methods, we need to know what the parse
tree structure looks like and how much of it we actually need to be concerned
about. Python uses a moderately deep parse tree so there are a large number of
intermediate nodes. It is important to read and understand the formal grammar
used by Python. This is specified in the file :file:`Grammar/Grammar` in the
distribution. Consider the simplest case of interest when searching for
docstrings: a module consisting of a docstring and nothing else. (See file
:file:`docstring.py`.) ::
"""Some documentation.
"""
Using the interpreter to take a look at the parse tree, we find a bewildering
mass of numbers and parentheses, with the documentation buried deep in nested
tuples. ::
>>> import parser
>>> import pprint
>>> st = parser.suite(open('docstring.py').read())
>>> tup = st.totuple()
>>> pprint.pprint(tup)
(257,
(264,
(265,
(266,
(267,
(307,
(287,
(288,
(289,
(290,
(292,
(293,
(294,
(295,
(296,
(297,
(298,
(299,
(300, (3, '"""Some documentation.\n"""'))))))))))))))))),
(4, ''))),
(4, ''),
(0, ''))
The numbers at the first element of each node in the tree are the node types;
they map directly to terminal and non-terminal symbols in the grammar.
Unfortunately, they are represented as integers in the internal representation,
and the Python structures generated do not change that. However, the
:mod:`symbol` and :mod:`token` modules provide symbolic names for the node types
and dictionaries which map from the integers to the symbolic names for the node
types.
In the output presented above, the outermost tuple contains four elements: the
integer ``257`` and three additional tuples. Node type ``257`` has the symbolic
name :const:`file_input`. Each of these inner tuples contains an integer as the
first element; these integers, ``264``, ``4``, and ``0``, represent the node
types :const:`stmt`, :const:`NEWLINE`, and :const:`ENDMARKER`, respectively.
Note that these values may change depending on the version of Python you are
using; consult :file:`symbol.py` and :file:`token.py` for details of the
mapping. It should be fairly clear that the outermost node is related primarily
to the input source rather than the contents of the file, and may be disregarded
for the moment. The :const:`stmt` node is much more interesting. In
particular, all docstrings are found in subtrees which are formed exactly as
this node is formed, with the only difference being the string itself. The
association between the docstring in a similar tree and the defined entity
(class, function, or module) which it describes is given by the position of the
docstring subtree within the tree defining the described structure.
By replacing the actual docstring with something to signify a variable component
of the tree, we allow a simple pattern matching approach to check any given
subtree for equivalence to the general pattern for docstrings. Since the
example demonstrates information extraction, we can safely require that the tree
be in tuple form rather than list form, allowing a simple variable
representation to be ``['variable_name']``. A simple recursive function can
implement the pattern matching, returning a Boolean and a dictionary of variable
name to value mappings. (See file :file:`example.py`.) ::
def match(pattern, data, vars=None):
if vars is None:
vars = {}
if isinstance(pattern, list):
vars[pattern[0]] = data
return True, vars
if not instance(pattern, tuple):
return (pattern == data), vars
if len(data) != len(pattern):
return False, vars
for pattern, data in zip(pattern, data):
same, vars = match(pattern, data, vars)
if not same:
break
return same, vars
Using this simple representation for syntactic variables and the symbolic node
types, the pattern for the candidate docstring subtrees becomes fairly readable.
(See file :file:`example.py`.) ::
import symbol
import token
DOCSTRING_STMT_PATTERN = (
symbol.stmt,
(symbol.simple_stmt,
(symbol.small_stmt,
(symbol.expr_stmt,
(symbol.testlist,
(symbol.test,
(symbol.and_test,
(symbol.not_test,
(symbol.comparison,
(symbol.expr,
(symbol.xor_expr,
(symbol.and_expr,
(symbol.shift_expr,
(symbol.arith_expr,
(symbol.term,
(symbol.factor,
(symbol.power,
(symbol.atom,
(token.STRING, ['docstring'])
)))))))))))))))),
(token.NEWLINE, '')
))
Using the :func:`match` function with this pattern, extracting the module
docstring from the parse tree created previously is easy::
>>> found, vars = match(DOCSTRING_STMT_PATTERN, tup[1])
>>> found
True
>>> vars
{'docstring': '"""Some documentation.\n"""'}
Once specific data can be extracted from a location where it is expected, the
question of where information can be expected needs to be answered. When
dealing with docstrings, the answer is fairly simple: the docstring is the first
:const:`stmt` node in a code block (:const:`file_input` or :const:`suite` node
types). A module consists of a single :const:`file_input` node, and class and
function definitions each contain exactly one :const:`suite` node. Classes and
functions are readily identified as subtrees of code block nodes which start
with ``(stmt, (compound_stmt, (classdef, ...`` or ``(stmt, (compound_stmt,
(funcdef, ...``. Note that these subtrees cannot be matched by :func:`match`
since it does not support multiple sibling nodes to match without regard to
number. A more elaborate matching function could be used to overcome this
limitation, but this is sufficient for the example.
Given the ability to determine whether a statement might be a docstring and
extract the actual string from the statement, some work needs to be performed to
walk the parse tree for an entire module and extract information about the names
defined in each context of the module and associate any docstrings with the
names. The code to perform this work is not complicated, but bears some
explanation.
The public interface to the classes is straightforward and should probably be
somewhat more flexible. Each "major" block of the module is described by an
object providing several methods for inquiry and a constructor which accepts at
least the subtree of the complete parse tree which it represents. The
:class:`ModuleInfo` constructor accepts an optional *name* parameter since it
cannot otherwise determine the name of the module.
The public classes include :class:`ClassInfo`, :class:`FunctionInfo`, and
:class:`ModuleInfo`. All objects provide the methods :meth:`get_name`,
:meth:`get_docstring`, :meth:`get_class_names`, and :meth:`get_class_info`. The
:class:`ClassInfo` objects support :meth:`get_method_names` and
:meth:`get_method_info` while the other classes provide
:meth:`get_function_names` and :meth:`get_function_info`.
Within each of the forms of code block that the public classes represent, most
of the required information is in the same form and is accessed in the same way,
with classes having the distinction that functions defined at the top level are
referred to as "methods." Since the difference in nomenclature reflects a real
semantic distinction from functions defined outside of a class, the
implementation needs to maintain the distinction. Hence, most of the
functionality of the public classes can be implemented in a common base class,
:class:`SuiteInfoBase`, with the accessors for function and method information
provided elsewhere. Note that there is only one class which represents function
and method information; this parallels the use of the :keyword:`def` statement
to define both types of elements.
Most of the accessor functions are declared in :class:`SuiteInfoBase` and do not
need to be overridden by subclasses. More importantly, the extraction of most
information from a parse tree is handled through a method called by the
:class:`SuiteInfoBase` constructor. The example code for most of the classes is
clear when read alongside the formal grammar, but the method which recursively
creates new information objects requires further examination. Here is the
relevant part of the :class:`SuiteInfoBase` definition from :file:`example.py`::
class SuiteInfoBase:
_docstring = ''
_name = ''
def __init__(self, tree = None):
self._class_info = {}
self._function_info = {}
if tree:
self._extract_info(tree)
def _extract_info(self, tree):
# extract docstring
if len(tree) == 2:
found, vars = match(DOCSTRING_STMT_PATTERN[1], tree[1])
else:
found, vars = match(DOCSTRING_STMT_PATTERN, tree[3])
if found:
self._docstring = eval(vars['docstring'])
# discover inner definitions
for node in tree[1:]:
found, vars = match(COMPOUND_STMT_PATTERN, node)
if found:
cstmt = vars['compound']
if cstmt[0] == symbol.funcdef:
name = cstmt[2][1]
self._function_info[name] = FunctionInfo(cstmt)
elif cstmt[0] == symbol.classdef:
name = cstmt[2][1]
self._class_info[name] = ClassInfo(cstmt)
After initializing some internal state, the constructor calls the
:meth:`_extract_info` method. This method performs the bulk of the information
extraction which takes place in the entire example. The extraction has two
distinct phases: the location of the docstring for the parse tree passed in, and
the discovery of additional definitions within the code block represented by the
parse tree.
The initial :keyword:`if` test determines whether the nested suite is of the
"short form" or the "long form." The short form is used when the code block is
on the same line as the definition of the code block, as in ::
def square(x): "Square an argument."; return x ** 2
while the long form uses an indented block and allows nested definitions::
def make_power(exp):
"Make a function that raises an argument to the exponent `exp`."
def raiser(x, y=exp):
return x ** y
return raiser
When the short form is used, the code block may contain a docstring as the
first, and possibly only, :const:`small_stmt` element. The extraction of such a
docstring is slightly different and requires only a portion of the complete
pattern used in the more common case. As implemented, the docstring will only
be found if there is only one :const:`small_stmt` node in the
:const:`simple_stmt` node. Since most functions and methods which use the short
form do not provide a docstring, this may be considered sufficient. The
extraction of the docstring proceeds using the :func:`match` function as
described above, and the value of the docstring is stored as an attribute of the
:class:`SuiteInfoBase` object.
After docstring extraction, a simple definition discovery algorithm operates on
the :const:`stmt` nodes of the :const:`suite` node. The special case of the
short form is not tested; since there are no :const:`stmt` nodes in the short
form, the algorithm will silently skip the single :const:`simple_stmt` node and
correctly not discover any nested definitions.
Each statement in the code block is categorized as a class definition, function
or method definition, or something else. For the definition statements, the
name of the element defined is extracted and a representation object appropriate
to the definition is created with the defining subtree passed as an argument to
the constructor. The representation objects are stored in instance variables
and may be retrieved by name using the appropriate accessor methods.
The public classes provide any accessors required which are more specific than
those provided by the :class:`SuiteInfoBase` class, but the real extraction
algorithm remains common to all forms of code blocks. A high-level function can
be used to extract the complete set of information from a source file. (See
file :file:`example.py`.) ::
def get_docs(fileName):
import os
import parser
source = open(fileName).read()
basename = os.path.basename(os.path.splitext(fileName)[0])
st = parser.suite(source)
return ModuleInfo(st.totuple(), basename)
This provides an easy-to-use interface to the documentation of a module. If
information is required which is not extracted by the code of this example, the
code may be extended at clearly defined points to provide additional
capabilities.

154
Doc/library/pickle.rst
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@ -23,6 +23,12 @@ into an object hierarchy. Pickling (and unpickling) is alternatively known as
"serialization", "marshalling," [#]_ or "flattening", however, to avoid
confusion, the terms used here are "pickling" and "unpickling"..
.. warning::
The :mod:`pickle` module is not intended to be secure against erroneous or
maliciously constructed data. Never unpickle data received from an untrusted
or unauthenticated source.
Relationship to other Python modules
------------------------------------
@ -63,12 +69,6 @@ The :mod:`pickle` module differs from :mod:`marshal` several significant ways:
The :mod:`pickle` serialization format is guaranteed to be backwards compatible
across Python releases.
.. warning::
The :mod:`pickle` module is not intended to be secure against erroneous or
maliciously constructed data. Never unpickle data received from an untrusted
or unauthenticated source.
Note that serialization is a more primitive notion than persistence; although
:mod:`pickle` reads and writes file objects, it does not handle the issue of
naming persistent objects, nor the (even more complicated) issue of concurrent
@ -427,33 +427,38 @@ implementation of this behaviour::
obj.__dict__.update(attributes)
return obj
.. index:: single: __getnewargs__() (copy protocol)
Classes can alter the default behaviour by providing one or several special
methods. In protocol 2 and newer, classes that implements the
:meth:`__getnewargs__` method can dictate the values passed to the
:meth:`__new__` method upon unpickling. This is often needed for classes
whose :meth:`__new__` method requires arguments.
methods:
.. index:: single: __getstate__() (copy protocol)
.. method:: object.__getnewargs__()
Classes can further influence how their instances are pickled; if the class
defines the method :meth:`__getstate__`, it is called and the returned object is
pickled as the contents for the instance, instead of the contents of the
instance's dictionary. If the :meth:`__getstate__` method is absent, the
instance's :attr:`__dict__` is pickled as usual.
In protocol 2 and newer, classes that implements the :meth:`__getnewargs__`
method can dictate the values passed to the :meth:`__new__` method upon
unpickling. This is often needed for classes whose :meth:`__new__` method
requires arguments.
.. index:: single: __setstate__() (copy protocol)
Upon unpickling, if the class defines :meth:`__setstate__`, it is called with
the unpickled state. In that case, there is no requirement for the state object
to be a dictionary. Otherwise, the pickled state must be a dictionary and its
items are assigned to the new instance's dictionary.
.. method:: object.__getstate__()
.. note::
Classes can further influence how their instances are pickled; if the class
defines the method :meth:`__getstate__`, it is called and the returned object
is pickled as the contents for the instance, instead of the contents of the
instance's dictionary. If the :meth:`__getstate__` method is absent, the
instance's :attr:`__dict__` is pickled as usual.
.. method:: object.__setstate__(state)
Upon unpickling, if the class defines :meth:`__setstate__`, it is called with
the unpickled state. In that case, there is no requirement for the state
object to be a dictionary. Otherwise, the pickled state must be a dictionary
and its items are assigned to the new instance's dictionary.
.. note::
If :meth:`__getstate__` returns a false value, the :meth:`__setstate__`
method will not be called upon unpickling.
If :meth:`__getstate__` returns a false value, the :meth:`__setstate__`
method will not be called.
Refer to the section :ref:`pickle-state` for more information about how to use
the methods :meth:`__getstate__` and :meth:`__setstate__`.
@ -462,14 +467,12 @@ the methods :meth:`__getstate__` and :meth:`__setstate__`.
At unpickling time, some methods like :meth:`__getattr__`,
:meth:`__getattribute__`, or :meth:`__setattr__` may be called upon the
instance. In case those methods rely on some internal invariant being
true, the type should implement either :meth:`__getinitargs__` or
:meth:`__getnewargs__` to establish such an invariant; otherwise, neither
:meth:`__new__` nor :meth:`__init__` will be called.
instance. In case those methods rely on some internal invariant being true,
the type should implement :meth:`__getnewargs__` to establish such an
invariant; otherwise, neither :meth:`__new__` nor :meth:`__init__` will be
called.
.. index::
pair: copy; protocol
single: __reduce__() (copy protocol)
.. index:: pair: copy; protocol
As we shall see, pickle does not use directly the methods described above. In
fact, these methods are part of the copy protocol which implements the
@ -480,58 +483,61 @@ objects. [#]_
Although powerful, implementing :meth:`__reduce__` directly in your classes is
error prone. For this reason, class designers should use the high-level
interface (i.e., :meth:`__getnewargs__`, :meth:`__getstate__` and
:meth:`__setstate__`) whenever possible. We will show, however, cases where using
:meth:`__reduce__` is the only option or leads to more efficient pickling or
both.
:meth:`__setstate__`) whenever possible. We will show, however, cases where
using :meth:`__reduce__` is the only option or leads to more efficient pickling
or both.
The interface is currently defined as follows. The :meth:`__reduce__` method
takes no argument and shall return either a string or preferably a tuple (the
returned object is often referred to as the "reduce value").
.. method:: object.__reduce__()
If a string is returned, the string should be interpreted as the name of a
global variable. It should be the object's local name relative to its module;
the pickle module searches the module namespace to determine the object's
module. This behaviour is typically useful for singletons.
The interface is currently defined as follows. The :meth:`__reduce__` method
takes no argument and shall return either a string or preferably a tuple (the
returned object is often referred to as the "reduce value").
When a tuple is returned, it must be between two and five items long. Optional
items can either be omitted, or ``None`` can be provided as their value. The
semantics of each item are in order:
If a string is returned, the string should be interpreted as the name of a
global variable. It should be the object's local name relative to its
module; the pickle module searches the module namespace to determine the
object's module. This behaviour is typically useful for singletons.
.. XXX Mention __newobj__ special-case?
When a tuple is returned, it must be between two and five items long.
Optional items can either be omitted, or ``None`` can be provided as their
value. The semantics of each item are in order:
* A callable object that will be called to create the initial version of the
object.
.. XXX Mention __newobj__ special-case?
* A tuple of arguments for the callable object. An empty tuple must be given if
the callable does not accept any argument.
* A callable object that will be called to create the initial version of the
object.
* Optionally, the object's state, which will be passed to the object's
:meth:`__setstate__` method as previously described. If the object has no
such method then, the value must be a dictionary and it will be added to the
object's :attr:`__dict__` attribute.
* A tuple of arguments for the callable object. An empty tuple must be given
if the callable does not accept any argument.
* Optionally, an iterator (and not a sequence) yielding successive items. These
items will be appended to the object either using ``obj.append(item)`` or, in
batch, using ``obj.extend(list_of_items)``. This is primarily used for list
subclasses, but may be used by other classes as long as they have
:meth:`append` and :meth:`extend` methods with the appropriate signature.
(Whether :meth:`append` or :meth:`extend` is used depends on which pickle
protocol version is used as well as the number of items to append, so both
must be supported.)
* Optionally, the object's state, which will be passed to the object's
:meth:`__setstate__` method as previously described. If the object has no
such method then, the value must be a dictionary and it will be added to
the object's :attr:`__dict__` attribute.
* Optionally, an iterator (not a sequence) yielding successive key-value pairs.
These items will be stored to the object using ``obj[key] = value``. This is
primarily used for dictionary subclasses, but may be used by other classes as
long as they implement :meth:`__setitem__`.
* Optionally, an iterator (and not a sequence) yielding successive items.
These items will be appended to the object either using
``obj.append(item)`` or, in batch, using ``obj.extend(list_of_items)``.
This is primarily used for list subclasses, but may be used by other
classes as long as they have :meth:`append` and :meth:`extend` methods with
the appropriate signature. (Whether :meth:`append` or :meth:`extend` is
used depends on which pickle protocol version is used as well as the number
of items to append, so both must be supported.)
.. index:: single: __reduce_ex__() (copy protocol)
* Optionally, an iterator (not a sequence) yielding successive key-value
pairs. These items will be stored to the object using ``obj[key] =
value``. This is primarily used for dictionary subclasses, but may be used
by other classes as long as they implement :meth:`__setitem__`.
Alternatively, a :meth:`__reduce_ex__` method may be defined. The only
difference is this method should take a single integer argument, the protocol
version. When defined, pickle will prefer it over the :meth:`__reduce__`
method. In addition, :meth:`__reduce__` automatically becomes a synonym for the
extended version. The main use for this method is to provide
backwards-compatible reduce values for older Python releases.
.. method:: object.__reduce_ex__(protocol)
Alternatively, a :meth:`__reduce_ex__` method may be defined. The only
difference is this method should take a single integer argument, the protocol
version. When defined, pickle will prefer it over the :meth:`__reduce__`
method. In addition, :meth:`__reduce__` automatically becomes a synonym for
the extended version. The main use for this method is to provide
backwards-compatible reduce values for older Python releases.
.. _pickle-persistent:

5
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@ -43,6 +43,11 @@ lots of shared sub-objects. The keys are ordinary strings.
:meth:`close` explicitly when you don't need it any more, or use a
:keyword:`with` statement with :func:`contextlib.closing`.
.. warning::
Because the :mod:`shelve` module is backed by :mod:`pickle`, it is insecure
to load a shelf from an untrusted source. Like with pickle, loading a shelf
can execute arbitrary code.
Shelf objects support all methods supported by dictionaries. This eases the
transition from dictionary based scripts to those requiring persistent storage.

16
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@ -255,23 +255,22 @@ Connection Objects
.. method:: Connection.execute(sql, [parameters])
This is a nonstandard shortcut that creates an intermediate cursor object by
calling the cursor method, then calls the cursor's
:meth:`execute<Cursor.execute>` method with the parameters given.
calling the cursor method, then calls the cursor's :meth:`execute
<Cursor.execute>` method with the parameters given.
.. method:: Connection.executemany(sql, [parameters])
This is a nonstandard shortcut that creates an intermediate cursor object by
calling the cursor method, then calls the cursor's
:meth:`executemany<Cursor.executemany>` method with the parameters given.
calling the cursor method, then calls the cursor's :meth:`executemany
<Cursor.executemany>` method with the parameters given.
.. method:: Connection.executescript(sql_script)
This is a nonstandard shortcut that creates an intermediate cursor object by
calling the cursor method, then calls the cursor's
:meth:`executescript<Cursor.executescript>` method with the parameters
given.
calling the cursor method, then calls the cursor's :meth:`executescript
<Cursor.executescript>` method with the parameters given.
.. method:: Connection.create_function(name, num_params, func)
@ -435,7 +434,7 @@ Cursor Objects
.. class:: Cursor
A SQLite database cursor has the following attributes and methods:
A :class:`Cursor` instance has the following attributes and methods.
.. method:: Cursor.execute(sql, [parameters])
@ -853,4 +852,3 @@ threads. If you still try to do so, you will get an exception at runtime.
The only exception is calling the :meth:`~Connection.interrupt` method, which
only makes sense to call from a different thread.

15
Doc/library/stdtypes.rst
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@ -1264,9 +1264,8 @@ formats in the string *must* include a parenthesised mapping key into that
dictionary inserted immediately after the ``'%'`` character. The mapping key
selects the value to be formatted from the mapping. For example:
>>> print('%(language)s has %(#)03d quote types.' % \
... {'language': "Python", "#": 2})
>>> print('%(language)s has %(number)03d quote types.' %
... {'language': "Python", "number": 2})
Python has 002 quote types.
In this case no ``*`` specifiers may occur in a format (since they require a
@ -1877,12 +1876,12 @@ pairs within braces, for example: ``{'jack': 4098, 'sjoerd': 4127}`` or ``{4098:
values are added as items to the dictionary. If a key is specified both in
the positional argument and as a keyword argument, the value associated with
the keyword is retained in the dictionary. For example, these all return a
dictionary equal to ``{"one": 2, "two": 3}``:
dictionary equal to ``{"one": 1, "two": 2}``:
* ``dict(one=2, two=3)``
* ``dict({'one': 2, 'two': 3})``
* ``dict(zip(('one', 'two'), (2, 3)))``
* ``dict([['two', 3], ['one', 2]])``
* ``dict(one=1, two=2)``
* ``dict({'one': 1, 'two': 2})``
* ``dict(zip(('one', 'two'), (1, 2)))``
* ``dict([['two', 2], ['one', 1]])``
The first example only works for keys that are valid Python identifiers; the
others work with any valid keys.

39
Doc/library/sys.rst
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@ -48,6 +48,13 @@ always available.
``modules.keys()`` only lists the imported modules.)
.. function:: call_tracing(func, args)
Call ``func(*args)``, while tracing is enabled. The tracing state is saved,
and restored afterwards. This is intended to be called from a debugger from
a checkpoint, to recursively debug some other code.
.. data:: copyright
A string containing the copyright pertaining to the Python interpreter.
@ -173,19 +180,25 @@ always available.
Exit from Python. This is implemented by raising the :exc:`SystemExit`
exception, so cleanup actions specified by finally clauses of :keyword:`try`
statements are honored, and it is possible to intercept the exit attempt at an
outer level. The optional argument *arg* can be an integer giving the exit
status (defaulting to zero), or another type of object. If it is an integer,
zero is considered "successful termination" and any nonzero value is considered
"abnormal termination" by shells and the like. Most systems require it to be in
the range 0-127, and produce undefined results otherwise. Some systems have a
convention for assigning specific meanings to specific exit codes, but these are
generally underdeveloped; Unix programs generally use 2 for command line syntax
errors and 1 for all other kind of errors. If another type of object is passed,
``None`` is equivalent to passing zero, and any other object is printed to
``sys.stderr`` and results in an exit code of 1. In particular,
``sys.exit("some error message")`` is a quick way to exit a program when an
error occurs.
statements are honored, and it is possible to intercept the exit attempt at
an outer level.
The optional argument *arg* can be an integer giving the exit status
(defaulting to zero), or another type of object. If it is an integer, zero
is considered "successful termination" and any nonzero value is considered
"abnormal termination" by shells and the like. Most systems require it to be
in the range 0-127, and produce undefined results otherwise. Some systems
have a convention for assigning specific meanings to specific exit codes, but
these are generally underdeveloped; Unix programs generally use 2 for command
line syntax errors and 1 for all other kind of errors. If another type of
object is passed, ``None`` is equivalent to passing zero, and any other
object is printed to :data:`stderr` and results in an exit code of 1. In
particular, ``sys.exit("some error message")`` is a quick way to exit a
program when an error occurs.
Since :func:`exit` ultimately "only" raises an exception, it will only exit
the process when called from the main thread, and the exception is not
intercepted.
.. data:: flags

63
Doc/library/token.rst
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@ -12,8 +12,8 @@ in the Python distribution for the definitions of the names in the context of
the language grammar. The specific numeric values which the names map to may
change between Python versions.
This module also provides one data object and some functions. The functions
mirror definitions in the Python C header files.
The module also provides a mapping from numeric codes to names and some
functions. The functions mirror definitions in the Python C header files.
.. data:: tok_name
@ -38,6 +38,65 @@ mirror definitions in the Python C header files.
Return true if *x* is the marker indicating the end of input.
The token constants are:
.. data:: ENDMARKER
NAME
NUMBER
STRING
NEWLINE
INDENT
DEDENT
LPAR
RPAR
LSQB
RSQB
COLON
COMMA
SEMI
PLUS
MINUS
STAR
SLASH
VBAR
AMPER
LESS
GREATER
EQUAL
DOT
PERCENT
BACKQUOTE
LBRACE
RBRACE
EQEQUAL
NOTEQUAL
LESSEQUAL
GREATEREQUAL
TILDE
CIRCUMFLEX
LEFTSHIFT
RIGHTSHIFT
DOUBLESTAR
PLUSEQUAL
MINEQUAL
STAREQUAL
SLASHEQUAL
PERCENTEQUAL
AMPEREQUAL
VBAREQUAL
CIRCUMFLEXEQUAL
LEFTSHIFTEQUAL
RIGHTSHIFTEQUAL
DOUBLESTAREQUAL
DOUBLESLASH
DOUBLESLASHEQUAL
AT
OP
ERRORTOKEN
N_TOKENS
NT_OFFSET
.. seealso::
Module :mod:`parser`

9
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@ -553,10 +553,9 @@ A class definition defines a class object (see section :ref:`types`):
.. productionlist::
classdef: [`decorators`] "class" `classname` [`inheritance`] ":" `suite`
inheritance: "(" [`argument_list` [","] ] ")"
inheritance: "(" [`argument_list` [","] | `comprehension`] ")"
classname: `identifier`
A class definition is an executable statement. The inheritance list usually
gives a list of base classes (see :ref:`metaclasses` for more advanced uses), so
each item in the list should evaluate to a class object which allows
@ -582,7 +581,7 @@ namespace.
Class creation can be customized heavily using :ref:`metaclasses <metaclasses>`.
Classes can also be decorated; as with functions, ::
Classes can also be decorated: just like when decorating functions, ::
@f1(arg)
@f2
@ -593,6 +592,10 @@ is equivalent to ::
class Foo: pass
Foo = f1(arg)(f2(Foo))
The evaluation rules for the decorator expressions are the same as for function
decorators. The result must be a class object, which is then bound to the class
name.
**Programmer's note:** Variables defined in the class definition are class
attributes; they are shared by instances. Instance attributes can be set in a
method with ``self.name = value``. Both class and instance attributes are

32
Doc/tutorial/classes.rst
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@ -4,26 +4,26 @@
Classes
*******
Python's class mechanism adds classes to the language with a minimum of new
syntax and semantics. It is a mixture of the class mechanisms found in C++ and
Modula-3. As is true for modules, classes in Python do not put an absolute
barrier between definition and user, but rather rely on the politeness of the
user not to "break into the definition." The most important features of classes
are retained with full power, however: the class inheritance mechanism allows
Compared with other programming languages, Python's class mechanism adds classes
with a minimum of new syntax and semantics. It is a mixture of the class
mechanisms found in C++ and Modula-3. Python classes provide all the standard
features of Object Oriented Programming: the class inheritance mechanism allows
multiple base classes, a derived class can override any methods of its base
class or classes, and a method can call the method of a base class with the same
name. Objects can contain an arbitrary amount of data.
name. Objects can contain arbitrary amounts and kinds of data. As is true for
modules, classes partake of the dynamic nature of Python: they are created at
runtime, and can be modified further after creation.
In C++ terminology, normally class members (including the data members) are
*public* (except see below :ref:`tut-private`),
and all member functions are *virtual*. As in Modula-3, there are no shorthands
for referencing the object's members from its methods: the method function is
declared with an explicit first argument representing the object, which is
provided implicitly by the call. As in Smalltalk, classes themselves are
objects. This provides semantics for importing and renaming. Unlike C++ and
Modula-3, built-in types can be used as base classes for extension by the user.
Also, like in C++, most built-in operators with special syntax (arithmetic
operators, subscripting etc.) can be redefined for class instances.
*public* (except see below :ref:`tut-private`), and all member functions are
*virtual*. As in Modula-3, there are no shorthands for referencing the object's
members from its methods: the method function is declared with an explicit first
argument representing the object, which is provided implicitly by the call. As
in Smalltalk, classes themselves are objects. This provides semantics for
importing and renaming. Unlike C++ and Modula-3, built-in types can be used as
base classes for extension by the user. Also, like in C++, most built-in
operators with special syntax (arithmetic operators, subscripting etc.) can be
redefined for class instances.
(Lacking universally accepted terminology to talk about classes, I will make
occasional use of Smalltalk and C++ terms. I would use Modula-3 terms, since

53
Doc/using/windows.rst
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@ -156,23 +156,48 @@ installation directory. So, if you had installed Python to
:file:`C:\\Python\\Lib\\` and third-party modules should be stored in
:file:`C:\\Python\\Lib\\site-packages\\`.
.. `` this fixes syntax highlighting errors in some editors due to the \\ hackery
This is how :data:`sys.path` is populated on Windows:
You can add folders to your search path to make Python's import mechanism search
in these directories as well. Use :envvar:`PYTHONPATH`, as described in
:ref:`using-on-envvars`, to modify :data:`sys.path`. On Windows, paths are
separated by semicolons, though, to distinguish them from drive identifiers
(:file:`C:\\` etc.).
* An empty entry is added at the start, which corresponds to the current
directory.
.. ``
* If the environment variable :envvar:`PYTHONPATH` exists, as described in
:ref:`using-on-envvars`, its entries are added next. Note that on Windows,
paths in this variable must be separated by semicolons, to distinguish them
from the colon used in drive identifiers (``C:\`` etc.).
Modifying the module search path can also be done through the Windows registry
under the key :file:`HKLM\\SOFTWARE\\Python\\PythonCore\\{version}\\PythonPath`.
Subkeys which have semicolon-delimited path strings as their default value will
cause each path to be searched. Multiple subkeys can be created and are
appended to the path in alphabetical order. A convenient registry editor is
:program:`regedit` (start it by typing "regedit" into :menuselection:`Start -->
Run`).
* Additional "application paths" can be added in the registry as subkeys of
:samp:`\\SOFTWARE\\Python\\PythonCore\\{version}\\PythonPath` under both the
``HKEY_CURRENT_USER`` and ``HKEY_LOCAL_MACHINE`` hives. Subkeys which have
semicolon-delimited path strings as their default value will cause each path
to be added to :data:`sys.path`. (Note that all known installers only use
HKLM, so HKCU is typically empty.)
* If the environment variable :envvar:`PYTHONHOME` is set, it is assumed as
"Python Home". Otherwise, the path of the main Python executable is used to
locate a "landmark file" (``Lib\os.py``) to deduce the "Python Home". If a
Python home is found, the relevant sub-directories added to :data:`sys.path`
(``Lib``, ``plat-win``, etc) are based on that folder. Otherwise, the core
Python path is constructed from the PythonPath stored in the registry.
* If the Python Home cannot be located, no :envvar:`PYTHONPATH` is specified in
the environment, and no registry entries can be found, a default path with
relative entries is used (e.g. ``.\Lib;.\plat-win``, etc).
The end result of all this is:
* When running :file:`python.exe`, or any other .exe in the main Python
directory (either an installed version, or directly from the PCbuild
directory), the core path is deduced, and the core paths in the registry are
ignored. Other "application paths" in the registry are always read.
* When Python is hosted in another .exe (different directory, embedded via COM,
etc), the "Python Home" will not be deduced, so the core path from the
registry is used. Other "application paths" in the registry are always read.
* If Python can't find its home and there is no registry (eg, frozen .exe, some
very strange installation setup) you get a path with some default, but
relative, paths.
Executing scripts