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gh-96265: Fix some formatting in faq/design.rst #96924

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60 changes: 32 additions & 28 deletions Doc/faq/design.rst
Original file line number Diff line number Diff line change
Expand Up @@ -62,7 +62,7 @@ and think it is a bug in Python. It's not. This has little to do with Python,
and much more to do with how the underlying platform handles floating-point
numbers.

The :class:`float` type in CPython uses a C ``double`` for storage. A
The :class:`float` type in CPython uses a C :c:type:`double` for storage. A
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There's no double type defined in Python's documentation (since its defined in the C standard) or auto-linked/formatted by Sphinx and this apparently isn't given any special formatting by the current Python docs theme. Maybe this should be rolled back, or we should fix the theme to format C-domain types correctly? Or perhaps this has something to do with enabling the legacy C domain syntax mode in conf.py that @AA-Turner 's been working on getting rid of the need for?

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If I recall, I believe that regular literals (double backticks) are how you've handled this sort of thing elsewhere.

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Doing a quick search through the repo I'm seeing more (23 vs 5) in the form of :c:type:`double`, so keeping it would be more in line with what's currently being done.

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Okay, I see. Still, it is strange that it is formatted as prose rather than as a literal, as we'd (and I assume the original authors) would expect—perhaps something changed in the theme, Sphinx or the configuration that resulted in that not happening as expected.

:class:`float` object's value is stored in binary floating-point with a fixed
precision (typically 53 bits) and Python uses C operations, which in turn rely
on the hardware implementation in the processor, to perform floating-point
Expand Down Expand Up @@ -129,7 +129,7 @@ reference or call the method from a particular class. In C++, if you want to
use a method from a base class which is overridden in a derived class, you have
to use the ``::`` operator -- in Python you can write
``baseclass.methodname(self, <argument list>)``. This is particularly useful
for :meth:`__init__` methods, and in general in cases where a derived class
for :meth:`~object.__init__` methods, and in general in cases where a derived class
method wants to extend the base class method of the same name and thus has to
call the base class method somehow.

Expand All @@ -155,7 +155,7 @@ Why can't I use an assignment in an expression?

Starting in Python 3.8, you can!

Assignment expressions using the walrus operator `:=` assign a variable in an
Assignment expressions using the walrus operator ``:=`` assign a variable in an
expression::

while chunk := fp.read(200):
Expand Down Expand Up @@ -232,7 +232,8 @@ Similar methods exist for bytes and bytearray objects.
How fast are exceptions?
------------------------

A try/except block is extremely efficient if no exceptions are raised. Actually
A :keyword:`try`/:keyword:`except` block is extremely efficient if no exceptions
are raised. Actually
catching an exception is expensive. In versions of Python prior to 2.0 it was
common to use this idiom::

Expand Down Expand Up @@ -352,7 +353,7 @@ will probably run out of file descriptors::
c = f.read(1)

Indeed, using CPython's reference counting and destructor scheme, each new
assignment to *f* closes the previous file. With a traditional GC, however,
assignment to ``f`` closes the previous file. With a traditional GC, however,
those file objects will only get collected (and closed) at varying and possibly
long intervals.

Expand All @@ -376,10 +377,10 @@ Python to work with it.)

Traditional GC also becomes a problem when Python is embedded into other
applications. While in a standalone Python it's fine to replace the standard
malloc() and free() with versions provided by the GC library, an application
embedding Python may want to have its *own* substitute for malloc() and free(),
``malloc()`` and ``free()`` with versions provided by the GC library, an application
embedding Python may want to have its *own* substitute for ``malloc()`` and ``free()``,
and may not want Python's. Right now, CPython works with anything that
implements malloc() and free() properly.
implements ``malloc()`` and ``free()`` properly.


Why isn't all memory freed when CPython exits?
Expand All @@ -401,14 +402,15 @@ Why are there separate tuple and list data types?

Lists and tuples, while similar in many respects, are generally used in
fundamentally different ways. Tuples can be thought of as being similar to
Pascal records or C structs; they're small collections of related data which may
Pascal ``records`` or C ``structs``; they're small collections of related data which may
be of different types which are operated on as a group. For example, a
Cartesian coordinate is appropriately represented as a tuple of two or three
numbers.
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Lists, on the other hand, are more like arrays in other languages. They tend to
hold a varying number of objects all of which have the same type and which are
operated on one-by-one. For example, ``os.listdir('.')`` returns a list of
operated on one-by-one. For example, :func:`os.listdir('.') <os.listdir>`
returns a list of
strings representing the files in the current directory. Functions which
operate on this output would generally not break if you added another file or
two to the directory.
Expand Down Expand Up @@ -444,9 +446,9 @@ far) under most circumstances, and the implementation is simpler.

Dictionaries work by computing a hash code for each key stored in the dictionary
using the :func:`hash` built-in function. The hash code varies widely depending
on the key and a per-process seed; for example, "Python" could hash to
-539294296 while "python", a string that differs by a single bit, could hash
to 1142331976. The hash code is then used to calculate a location in an
on the key and a per-process seed; for example, ``'Python'`` could hash to
``-539294296`` while ``'python'``, a string that differs by a single bit, could hash
to ``1142331976``. The hash code is then used to calculate a location in an
internal array where the value will be stored. Assuming that you're storing
keys that all have different hash values, this means that dictionaries take
constant time -- O(1), in Big-O notation -- to retrieve a key.
Expand Down Expand Up @@ -497,7 +499,8 @@ Some unacceptable solutions that have been proposed:

There is a trick to get around this if you need to, but use it at your own risk:
You can wrap a mutable structure inside a class instance which has both a
:meth:`__eq__` and a :meth:`__hash__` method. You must then make sure that the
:meth:`~object.__eq__` and a :meth:`~object.__hash__` method.
You must then make sure that the
hash value for all such wrapper objects that reside in a dictionary (or other
hash based structure), remain fixed while the object is in the dictionary (or
other structure). ::
Expand Down Expand Up @@ -528,7 +531,7 @@ is True``) then ``hash(o1) == hash(o2)`` (ie, ``o1.__hash__() == o2.__hash__()``
regardless of whether the object is in a dictionary or not. If you fail to meet
these restrictions dictionaries and other hash based structures will misbehave.

In the case of ListWrapper, whenever the wrapper object is in a dictionary the
In the case of :class:`!ListWrapper`, whenever the wrapper object is in a dictionary the
wrapped list must not change to avoid anomalies. Don't do this unless you are
prepared to think hard about the requirements and the consequences of not
meeting them correctly. Consider yourself warned.
Expand Down Expand Up @@ -581,9 +584,9 @@ exhaustive test suites that exercise every line of code in a module.
An appropriate testing discipline can help build large complex applications in
Python as well as having interface specifications would. In fact, it can be
better because an interface specification cannot test certain properties of a
program. For example, the :meth:`append` method is expected to add new elements
program. For example, the :meth:`list.append` method is expected to add new elements
to the end of some internal list; an interface specification cannot test that
your :meth:`append` implementation will actually do this correctly, but it's
your :meth:`list.append` implementation will actually do this correctly, but it's
trivial to check this property in a test suite.

Writing test suites is very helpful, and you might want to design your code to
Expand All @@ -599,14 +602,14 @@ Why is there no goto?
In the 1970s people realized that unrestricted goto could lead
to messy "spaghetti" code that was hard to understand and revise.
In a high-level language, it is also unneeded as long as there
are ways to branch (in Python, with ``if`` statements and ``or``,
``and``, and ``if-else`` expressions) and loop (with ``while``
and ``for`` statements, possibly containing ``continue`` and ``break``).
are ways to branch (in Python, with :keyword:`if` statements and :keyword:`or`,
:keyword:`and`, and :keyword:`if`/:keyword:`else` expressions) and loop (with :keyword:`while`
and :keyword:`for` statements, possibly containing :keyword:`continue` and :keyword:`break`).

One can also use exceptions to provide a "structured goto"
that works even across
function calls. Many feel that exceptions can conveniently emulate all
reasonable uses of the "go" or "goto" constructs of C, Fortran, and other
reasonable uses of the ``go`` or ``goto`` constructs of C, Fortran, and other
languages. For example::

class label(Exception): pass # declare a label
Expand All @@ -620,7 +623,7 @@ languages. For example::
...

This doesn't allow you to jump into the middle of a loop, but that's usually
considered an abuse of goto anyway. Use sparingly.
considered an abuse of ``goto`` anyway. Use sparingly.


Why can't raw strings (r-strings) end with a backslash?
Expand Down Expand Up @@ -652,7 +655,7 @@ If you're trying to build a pathname for a DOS command, try e.g. one of ::
Why doesn't Python have a "with" statement for attribute assignments?
---------------------------------------------------------------------

Python has a 'with' statement that wraps the execution of a block, calling code
Python has a :keyword:`with` statement that wraps the execution of a block, calling code
on the entrance and exit from the block. Some languages have a construct that
looks like this::

Expand All @@ -679,13 +682,13 @@ For instance, take the following incomplete snippet::
with a:
print(x)

The snippet assumes that "a" must have a member attribute called "x". However,
The snippet assumes that ``a`` must have a member attribute called ``x``. However,
there is nothing in Python that tells the interpreter this. What should happen
if "a" is, let us say, an integer? If there is a global variable named "x",
will it be used inside the with block? As you see, the dynamic nature of Python
if ``a`` is, let us say, an integer? If there is a global variable named ``x``,
will it be used inside the :keyword:`with` block? As you see, the dynamic nature of Python
makes such choices much harder.

The primary benefit of "with" and similar language features (reduction of code
The primary benefit of :keyword:`with` and similar language features (reduction of code
volume) can, however, easily be achieved in Python by assignment. Instead of::

function(args).mydict[index][index].a = 21
Expand All @@ -710,7 +713,8 @@ Why don't generators support the with statement?
For technical reasons, a generator used directly as a context manager
would not work correctly. When, as is most common, a generator is used as
an iterator run to completion, no closing is needed. When it is, wrap
it as "contextlib.closing(generator)" in the 'with' statement.
it as :func:`contextlib.closing(generator) <contextlib.closing>`
in the :keyword:`with` statement.


Why are colons required for the if/while/def/class statements?
Expand Down