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Commitddc44b8

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Merge branch 'main' into fix-blocksize-in-sendfile
2 parents88367ab +d4dfad2 commitddc44b8

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‎.cirrus-DISABLED.yml

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‎.github/workflows/build.yml

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run:echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV
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-name:Configure ccache action
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uses:hendrikmuhs/ccache-action@v1.2
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with:
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save:false
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-name:Check Autoconf and aclocal versions
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run:|
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grep "Generated by GNU Autoconf 2.71" configure
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-name:Configure ccache action
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uses:hendrikmuhs/ccache-action@v1.2
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with:
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save:false
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-name:Configure CPython
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run:./configure --config-cache --with-pydebug --with-openssl=$OPENSSL_DIR
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-name:Build CPython
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echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV
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-name:Configure ccache action
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uses:hendrikmuhs/ccache-action@v1.2
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with:
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save:false
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-name:Setup directory envs for out-of-tree builds
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echo "CPYTHON_RO_SRCDIR=$(realpath -m ${GITHUB_WORKSPACE}/../cpython-ro-srcdir)" >> $GITHUB_ENV
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echo "PATH=/usr/lib/ccache:$PATH" >> $GITHUB_ENV
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-name:Configure ccache action
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uses:hendrikmuhs/ccache-action@v1.2
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with:
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save:${{ github.event_name == 'push' }}
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-name:Configure CPython
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run:./configure --config-cache --with-address-sanitizer --without-pymalloc
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‎.github/workflows/reusable-ubuntu.yml

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-name:Configure ccache action
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uses:hendrikmuhs/ccache-action@v1.2
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with:
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save:${{ github.event_name == 'push' }}
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max-size:"200M"
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-name:Setup directory envs for out-of-tree builds
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run:|
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echo "CPYTHON_RO_SRCDIR=$(realpath -m ${GITHUB_WORKSPACE}/../cpython-ro-srcdir)" >> $GITHUB_ENV

‎.pre-commit-config.yaml

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hooks:
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-id:sphinx-lint
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args:[--enable=default-role]
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files:^Doc/|^Misc/NEWS.d/next/
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files:^Doc/|^Misc/NEWS.d/
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-repo:meta
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hooks:

‎Doc/c-api/complex.rst

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Return the real part of *op* as a C:c:expr:`double`.
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If *op* is not a Python complex number object but has a
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:meth:`~object.__complex__` method, this method will first be called to
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convert *op* to a Python complex number object. If:meth:`!__complex__` is
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not defined then it falls back to call:c:func:`PyFloat_AsDouble` and
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returns its result. Upon failure, this method returns ``-1.0``, so one
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should call:c:func:`PyErr_Occurred` to check for errors.
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..versionchanged::3.13
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Use:meth:`~object.__complex__` if available.
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..c:function::doublePyComplex_ImagAsDouble(PyObject *op)
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Return the imaginary part of *op* as a C:c:expr:`double`.
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If *op* is not a Python complex number object but has a
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:meth:`~object.__complex__` method, this method will first be called to
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convert *op* to a Python complex number object. If:meth:`!__complex__` is
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not defined then it falls back to call:c:func:`PyFloat_AsDouble` and
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returns ``0.0`` on success. Upon failure, this method returns ``-1.0``, so
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one should call:c:func:`PyErr_Occurred` to check for errors.
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..versionchanged::3.13
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Use:meth:`~object.__complex__` if available.
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..c:function:: Py_complexPyComplex_AsCComplex(PyObject *op)
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‎Doc/c-api/object.rst

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..c:function::intPyObject_HasAttr(PyObject *o, PyObject *attr_name)
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Returns ``1`` if *o* has the attribute *attr_name*, and ``0`` otherwise. This
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is equivalent to the Python expression ``hasattr(o, attr_name)``. This function
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always succeeds.
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Returns ``1`` if *o* has the attribute *attr_name*, and ``0`` otherwise.
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This function always succeeds.
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..note::
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‎Doc/faq/design.rst

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to ``1142331976``. The hash code is then used to calculate a location in an
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internal array where the value will be stored. Assuming that you're storing
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keys that all have different hash values, this means that dictionaries take
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constant time --O(1), in Big-O notation -- to retrieve a key.
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constant time --*O*\(1), in Big-O notation -- to retrieve a key.
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Why must dictionary keys be immutable?

‎Doc/glossary.rst

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list
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A built-in Python:term:`sequence`. Despite its name it is more akin
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to an array in other languages than to a linked list since access to
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elements isO(1).
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elements is*O*\(1).
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list comprehension
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A compact way to process all or part of the elements in a sequence and

‎Doc/howto/descriptor.rst

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<function D.f at 0x00C45070>
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>>> d.f.__self__
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<__main__.D object at0x1012e1f98>
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<__main__.D object at0x00B18C90>
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If you have ever wondered where *self* comes from in regular methods or where
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*cls* comes from in class methods, this is it!

‎Doc/howto/urllib2.rst

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===============
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The response returned by urlopen (or the:exc:`~urllib.error.HTTPError` instance) has two
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useful methods:meth:`info` and:meth:`geturl` and is defined in the module
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:mod:`urllib.response`..
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useful methods:meth:`!info` and:meth:`!geturl` and is defined in the module
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:mod:`urllib.response`.
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**geturl** - this returns the real URL of the page fetched. This is useful
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because ``urlopen`` (or the opener object used) may have followed a
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redirect. The URL of the page fetched may not be the same as the URL requested.
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* **geturl** - this returns the real URL of the page fetched. This is useful
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because ``urlopen`` (or the opener object used) may have followed a
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redirect. The URL of the page fetched may not be the same as the URL requested.
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**info** - this returns a dictionary-like object that describes the page
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fetched, particularly the headers sent by the server. It is currently an
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:class:`http.client.HTTPMessage` instance.
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* **info** - this returns a dictionary-like object that describes the page
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fetched, particularly the headers sent by the server. It is currently an
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Typical headers include 'Content-length', 'Content-type', and so on. See the
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In the above example we only supplied our ``HTTPBasicAuthHandler`` to
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``build_opener``. By default openers have the handlers for normal situations
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-- ``ProxyHandler`` (if a proxy setting such as an:envvar:`http_proxy`
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-- ``ProxyHandler`` (if a proxy setting such as an:envvar:`!http_proxy`
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environment variable is set), ``UnknownHandler``, ``HTTPHandler``,
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``HTTPDefaultErrorHandler``, ``HTTPRedirectHandler``, ``FTPHandler``,
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``FileHandler``, ``DataHandler``, ``HTTPErrorProcessor``.

‎Doc/library/asyncio-policy.rst

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It works reliably even when the asyncio event loop is run in a non-main OS thread.
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There is no noticeable overhead when handling a big number of children (*O(1)* each
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There is no noticeable overhead when handling a big number of children (*O*\(1) each
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This watcher is used by default.
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The solution is safe but it has a significant overhead when
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handling a big number of processes (*O(n)* each time a
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handling a big number of processes (*O*\(*n*) each time a
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The watcher avoids disrupting other code spawning processes
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This solution is as safe as:class:`MultiLoopChildWatcher` and has the same *O(N)*
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This solution is as safe as:class:`MultiLoopChildWatcher` and has the same *O*\(*n*)
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..deprecated::3.12
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There is no noticeable overhead when handling a big number of
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children (*O*\(1) each time a child terminates).
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‎Doc/library/bisect.rst

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Keep in mind that the``O(logn)`` search is dominated by the slowO(n)
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insertion step.
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* Bisection is effective for searching ranges of values.
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* The *insort()* functions are``O(n)`` because the logarithmic search step
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* The *insort()* functions are*O*\(*n*) because the logarithmic search step
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‎Doc/library/collections.rst

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Deques are a generalization of stacks and queues (the name is pronounced "deck"
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sameO(1) performance in either direction.
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same*O*\(1) performance in either direction.
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Though:class:`list` objects support similar operations, they are optimized for
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fast fixed-length operations and incurO(n) memory movement costs for
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fast fixed-length operations and incur*O*\(*n*) memory movement costs for
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``pop(0)`` and ``insert(0, v)`` operations which change both the size and
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In addition to the above, deques support iteration, pickling, ``len(d)``,
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the:keyword:`in` operator, and subscript references such as ``d[0]`` to access
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the first element. Indexed access isO(1) at both ends but slows toO(n) in
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the first element. Indexed access is*O*\(1) at both ends but slows to*O*\(*n*) in
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‎Doc/library/contextvars.rst

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The function has anO(1) complexity, i.e. works equally fast for
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The function has an*O*\(1) complexity, i.e. works equally fast for
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contexts with a few context variables and for contexts that have
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‎Doc/library/functions.rst

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sign: "+" | "-"
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infinity: "Infinity" | "inf"
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nan: "nan"
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digitpart: `!digit` (["_"] `!digit`)*
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digit: <a Unicode decimal digit, i.e. characters in Unicode general category Nd>
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digitpart: `digit` (["_"] `digit`)*
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number: [`digitpart`] "." `digitpart` | `digitpart` ["."]
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exponent: ("e" | "E") ["+" | "-"] `digitpart`
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floatvalue: [`sign`] (`floatnumber` | `infinity` | `nan`)
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Here ``digit`` is a Unicode decimal digit (character in the Unicode general
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category ``Nd``). Case is not significant, so, for example, "inf", "Inf",
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"INFINITY", and "iNfINity" are all acceptable spellings for positive
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infinity.
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‎Doc/library/gc.rst

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..function::set_threshold(threshold0[, threshold1[,threshold2]])
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..function::set_threshold(threshold0, [threshold1, [threshold2]])
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Set the garbage collection thresholds (the collection frequency). Setting
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‎Doc/library/heapq.rst

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to move some loser (let's say cell 30 in the diagram above) into the 0 position,
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invariant is re-established. This is clearly logarithmic on the total number of
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items in the tree. By iterating over all items, you get anO(n logn) sort.
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items in the tree. By iterating over all items, you get an*O*\(*n* log*n*) sort.
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A nice feature of this sort is that you can efficiently insert new items while
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‎Doc/library/http.client.rst

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ALPN protocols with:meth:`~ssl.SSLContext.set_alpn_protocols`.
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request/response. The file has to be a:class:`~io.BufferedIOBase` reader
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As an alternative to using the:meth:`request` method described above, you can
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HTTPMessage Objects
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..class::HTTPMessage(email.message.Message)
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‎Doc/library/itertools.rst

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‎Doc/library/kde_example.png

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