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Another merge. Only doc stuff was affected (but this aligns the UTF-32
codec changes in trubk and branch). Hopefully the Py3k glossary wasn't different from the trunk one.
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Guido van Rossum
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.. _tut-glossary:
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********
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Glossary
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********
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.. % %% keep the entries sorted and include at least one \index{} item for each
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.. % %% cross-references are marked with \emph{entry}
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``>>>``
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The typical Python prompt of the interactive shell. Often seen for code
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examples that can be tried right away in the interpreter.
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.. index:: single: ...
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``...``
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The typical Python prompt of the interactive shell when entering code for an
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indented code block.
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.. index:: single: BDFL
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BDFL
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Benevolent Dictator For Life, a.k.a. `Guido van Rossum
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<http://www.python.org/~guido/>`_, Python's creator.
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.. index:: single: byte code
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byte code
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The internal representation of a Python program in the interpreter. The byte
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code is also cached in ``.pyc`` and ``.pyo`` files so that executing the same
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file is faster the second time (recompilation from source to byte code can be
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avoided). This "intermediate language" is said to run on a "virtual machine"
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that calls the subroutines corresponding to each bytecode.
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.. index:: single: classic class
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classic class
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Any class which does not inherit from :class:`object`. See *new-style class*.
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.. index:: single: complex number
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complex number
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An extension of the familiar real number system in which all numbers are
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expressed as a sum of a real part and an imaginary part. Imaginary numbers are
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real multiples of the imaginary unit (the square root of ``-1``), often written
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``i`` in mathematics or ``j`` in engineering. Python has builtin support for
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complex numbers, which are written with this latter notation; the imaginary part
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is written with a ``j`` suffix, e.g., ``3+1j``. To get access to complex
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equivalents of the :mod:`math` module, use :mod:`cmath`. Use of complex numbers
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is a fairly advanced mathematical feature. If you're not aware of a need for
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them, it's almost certain you can safely ignore them.
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.. index:: single: descriptor
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descriptor
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Any *new-style* object that defines the methods :meth:`__get__`,
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:meth:`__set__`, or :meth:`__delete__`. When a class attribute is a descriptor,
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its special binding behavior is triggered upon attribute lookup. Normally,
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writing *a.b* looks up the object *b* in the class dictionary for *a*, but if
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*b* is a descriptor, the defined method gets called. Understanding descriptors
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is a key to a deep understanding of Python because they are the basis for many
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features including functions, methods, properties, class methods, static
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methods, and reference to super classes.
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.. index:: single: dictionary
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dictionary
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An associative array, where arbitrary keys are mapped to values. The use of
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:class:`dict` much resembles that for :class:`list`, but the keys can be any
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object with a :meth:`__hash__` function, not just integers starting from zero.
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Called a hash in Perl.
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.. index:: single: duck-typing
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duck-typing
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Pythonic programming style that determines an object's type by inspection of its
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method or attribute signature rather than by explicit relationship to some type
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object ("If it looks like a duck and quacks like a duck, it must be a duck.")
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By emphasizing interfaces rather than specific types, well-designed code
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improves its flexibility by allowing polymorphic substitution. Duck-typing
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avoids tests using :func:`type` or :func:`isinstance`. Instead, it typically
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employs :func:`hasattr` tests or *EAFP* programming.
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.. index:: single: EAFP
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EAFP
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Easier to ask for forgiveness than permission. This common Python coding style
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assumes the existence of valid keys or attributes and catches exceptions if the
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assumption proves false. This clean and fast style is characterized by the
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presence of many :keyword:`try` and :keyword:`except` statements. The technique
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contrasts with the *LBYL* style that is common in many other languages such as
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C.
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.. index:: single: __future__
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__future__
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A pseudo module which programmers can use to enable new language features which
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are not compatible with the current interpreter. To enable ``new_feature`` ::
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from __future__ import new_feature
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By importing the :mod:`__future__` module and evaluating its variables, you
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can see when a new feature was first added to the language and when it will
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become the default::
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>>> import __future__
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>>> __future__.division
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_Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)
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.. index:: single: generator
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generator
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A function that returns an iterator. It looks like a normal function except
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that values are returned to the caller using a :keyword:`yield` statement
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instead of a :keyword:`return` statement. Generator functions often contain one
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or more :keyword:`for` or :keyword:`while` loops that :keyword:`yield` elements
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back to the caller. The function execution is stopped at the :keyword:`yield`
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keyword (returning the result) and is resumed there when the next element is
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requested by calling the :meth:`__next__` method of the returned iterator.
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.. index:: single: generator expression
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generator expression
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An expression that returns a generator. It looks like a normal expression
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followed by a :keyword:`for` expression defining a loop variable, range, and an
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optional :keyword:`if` expression. The combined expression generates values for
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an enclosing function::
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>>> sum(i*i for i in range(10)) # sum of squares 0, 1, 4, ... 81
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285
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.. index:: single: GIL
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GIL
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See *global interpreter lock*.
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.. index:: single: global interpreter lock
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global interpreter lock
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The lock used by Python threads to assure that only one thread can be run at
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a time. This simplifies Python by assuring that no two processes can access
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the same memory at the same time. Locking the entire interpreter makes it
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easier for the interpreter to be multi-threaded, at the expense of some
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parallelism on multi-processor machines. Efforts have been made in the past
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to create a "free-threaded" interpreter (one which locks shared data at a
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much finer granularity), but performance suffered in the common
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single-processor case.
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.. index:: single: IDLE
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IDLE
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An Integrated Development Environment for Python. IDLE is a basic editor and
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interpreter environment that ships with the standard distribution of Python.
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Good for beginners, it also serves as clear example code for those wanting to
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implement a moderately sophisticated, multi-platform GUI application.
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.. index:: single: immutable
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immutable
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An object with fixed value. Immutable objects are numbers, strings or tuples
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(and more). Such an object cannot be altered. A new object has to be created
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if a different value has to be stored. They play an important role in places
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where a constant hash value is needed, for example as a key in a dictionary.
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.. index:: single: integer division
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integer division
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Mathematical division including any remainder. The result will always be a
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float. For example, the expression ``11/4`` evaluates to ``2.75``. Integer
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division can be forced by using the ``//`` operator instead of the ``/``
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operator.
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.. index:: single: interactive
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interactive
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Python has an interactive interpreter which means that you can try out things
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and immediately see their results. Just launch ``python`` with no arguments
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(possibly by selecting it from your computer's main menu). It is a very powerful
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way to test out new ideas or inspect modules and packages (remember
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``help(x)``).
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.. index:: single: interpreted
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interpreted
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Python is an interpreted language, as opposed to a compiled one. This means
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that the source files can be run directly without first creating an executable
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which is then run. Interpreted languages typically have a shorter
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development/debug cycle than compiled ones, though their programs generally also
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run more slowly. See also *interactive*.
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.. index:: single: iterable
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iterable
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A container object capable of returning its members one at a time. Examples of
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iterables include all sequence types (such as :class:`list`, :class:`str`, and
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:class:`tuple`) and some non-sequence types like :class:`dict` and :class:`file`
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and objects of any classes you define with an :meth:`__iter__` or
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:meth:`__getitem__` method. Iterables can be used in a :keyword:`for` loop and
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in many other places where a sequence is needed (:func:`zip`, :func:`map`, ...).
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When an iterable object is passed as an argument to the builtin function
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:func:`iter`, it returns an iterator for the object. This iterator is good for
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one pass over the set of values. When using iterables, it is usually not
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necessary to call :func:`iter` or deal with iterator objects yourself. The
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``for`` statement does that automatically for you, creating a temporary unnamed
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variable to hold the iterator for the duration of the loop. See also
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*iterator*, *sequence*, and *generator*.
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.. index:: single: iterator
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iterator
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An object representing a stream of data. Repeated calls to the iterator's
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:meth:`__next__` method return successive items in the stream. When no more
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data is available a :exc:`StopIteration` exception is raised instead. At this
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point, the iterator object is exhausted and any further calls to its
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:meth:`__next__` method just raise :exc:`StopIteration` again. Iterators are
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required to have an :meth:`__iter__` method that returns the iterator object
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itself so every iterator is also iterable and may be used in most places where
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other iterables are accepted. One notable exception is code that attempts
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multiple iteration passes. A container object (such as a :class:`list`)
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produces a fresh new iterator each time you pass it to the :func:`iter` function
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or use it in a :keyword:`for` loop. Attempting this with an iterator will just
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return the same exhausted iterator object used in the previous iteration pass,
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making it appear like an empty container.
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.. index:: single: LBYL
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LBYL
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Look before you leap. This coding style explicitly tests for pre-conditions
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before making calls or lookups. This style contrasts with the *EAFP* approach
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and is characterized by the presence of many :keyword:`if` statements.
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.. index:: single: list comprehension
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list comprehension
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A compact way to process all or a subset of elements in a sequence and return a
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list with the results. ``result = ["0x%02x" % x for x in range(256) if x % 2 ==
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0]`` generates a list of strings containing hex numbers (0x..) that are even and
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in the range from 0 to 255. The :keyword:`if` clause is optional. If omitted,
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all elements in ``range(256)`` are processed.
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.. index:: single: mapping
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mapping
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A container object (such as :class:`dict`) that supports arbitrary key lookups
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using the special method :meth:`__getitem__`.
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.. index:: single: metaclass
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metaclass
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The class of a class. Class definitions create a class name, a class
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dictionary, and a list of base classes. The metaclass is responsible for taking
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those three arguments and creating the class. Most object oriented programming
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languages provide a default implementation. What makes Python special is that
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it is possible to create custom metaclasses. Most users never need this tool,
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but when the need arises, metaclasses can provide powerful, elegant solutions.
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They have been used for logging attribute access, adding thread-safety, tracking
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object creation, implementing singletons, and many other tasks.
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.. index:: single: mutable
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mutable
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Mutable objects can change their value but keep their :func:`id`. See also
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*immutable*.
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.. index:: single: namespace
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namespace
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The place where a variable is stored. Namespaces are implemented as
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dictionaries. There are the local, global and builtin namespaces as well as
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nested namespaces in objects (in methods). Namespaces support modularity by
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preventing naming conflicts. For instance, the functions
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:func:`__builtin__.open` and :func:`os.open` are distinguished by their
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namespaces. Namespaces also aid readability and maintainability by making it
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clear which module implements a function. For instance, writing
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:func:`random.seed` or :func:`itertools.izip` makes it clear that those
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functions are implemented by the :mod:`random` and :mod:`itertools` modules
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respectively.
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.. index:: single: nested scope
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nested scope
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The ability to refer to a variable in an enclosing definition. For instance, a
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function defined inside another function can refer to variables in the outer
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function. Note that nested scopes work only for reference and not for
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assignment which will always write to the innermost scope. In contrast, local
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variables both read and write in the innermost scope. Likewise, global
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variables read and write to the global namespace.
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.. index:: single: new-style class
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new-style class
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Any class that inherits from :class:`object`. This includes all built-in types
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like :class:`list` and :class:`dict`. Only new-style classes can use Python's
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newer, versatile features like :meth:`__slots__`, descriptors, properties,
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:meth:`__getattribute__`, class methods, and static methods.
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.. index:: single: Python3000
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Python3000
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A mythical python release, not required to be backward compatible, with
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telepathic interface.
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.. index:: single: __slots__
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__slots__
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A declaration inside a *new-style class* that saves memory by pre-declaring
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space for instance attributes and eliminating instance dictionaries. Though
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popular, the technique is somewhat tricky to get right and is best reserved for
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rare cases where there are large numbers of instances in a memory-critical
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application.
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.. index:: single: sequence
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sequence
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An *iterable* which supports efficient element access using integer indices via
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the :meth:`__getitem__` and :meth:`__len__` special methods. Some built-in
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sequence types are :class:`list`, :class:`str`, :class:`tuple`, and
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:class:`unicode`. Note that :class:`dict` also supports :meth:`__getitem__` and
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:meth:`__len__`, but is considered a mapping rather than a sequence because the
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lookups use arbitrary *immutable* keys rather than integers.
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.. index:: single: Zen of Python
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Zen of Python
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Listing of Python design principles and philosophies that are helpful in
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understanding and using the language. The listing can be found by typing
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"``import this``" at the interactive prompt.
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@ -41,6 +41,8 @@ language's flavor and style. After reading it, you will be able to read and
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write Python modules and programs, and you will be ready to learn more about the
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various Python library modules described in the Python Library Reference.
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The :ref:`glossary` is also worth going through.
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.. toctree::
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appetite.rst
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@ -57,4 +59,3 @@ various Python library modules described in the Python Library Reference.
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whatnow.rst
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interactive.rst
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floatingpoint.rst
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glossary.rst
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@ -158,13 +158,15 @@ and :mod:`smtplib` for sending mail::
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>>> import smtplib
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>>> server = smtplib.SMTP('localhost')
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>>> server.sendmail('soothsayer@example.org', 'jcaesar@example.org',
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"""To: jcaesar@example.org
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From: soothsayer@example.org
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Beware the Ides of March.
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""")
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... """To: jcaesar@example.org
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... From: soothsayer@example.org
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...
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... Beware the Ides of March.
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... """)
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>>> server.quit()
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(Note that the second example needs a mailserver running on localhost.)
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.. _tut-dates-and-times:
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