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1.. _tut-morecontrol:
2
3***********************
4More Control Flow Tools
5***********************
6
7Besides the :keyword:`while` statement just introduced, Python knows the usual
8control flow statements known from other languages, with some twists.
9
10
11.. _tut-if:
12
13:keyword:`if` Statements
14========================
15
16Perhaps the most well-known statement type is the :keyword:`if` statement.  For
17example::
18
19   >>> x = int(raw_input("Please enter an integer: "))
20   Please enter an integer: 42
21   >>> if x < 0:
22   ...     x = 0
23   ...     print 'Negative changed to zero'
24   ... elif x == 0:
25   ...     print 'Zero'
26   ... elif x == 1:
27   ...     print 'Single'
28   ... else:
29   ...     print 'More'
30   ...
31   More
32
33There can be zero or more :keyword:`elif` parts, and the :keyword:`else` part is
34optional.  The keyword ':keyword:`elif`' is short for 'else if', and is useful
35to avoid excessive indentation.  An  :keyword:`if` ... :keyword:`elif` ...
36:keyword:`elif` ... sequence is a substitute for the ``switch`` or
37``case`` statements found in other languages.
38
39
40.. _tut-for:
41
42:keyword:`for` Statements
43=========================
44
45.. index::
46   statement: for
47   statement: for
48
49The :keyword:`for` statement in Python differs a bit from what you may be used
50to in C or Pascal.  Rather than always iterating over an arithmetic progression
51of numbers (like in Pascal), or giving the user the ability to define both the
52iteration step and halting condition (as C), Python's :keyword:`for` statement
53iterates over the items of any sequence (a list or a string), in the order that
54they appear in the sequence.  For example (no pun intended):
55
56.. One suggestion was to give a real C example here, but that may only serve to
57   confuse non-C programmers.
58
59::
60
61   >>> # Measure some strings:
62   ... words = ['cat', 'window', 'defenestrate']
63   >>> for w in words:
64   ...     print w, len(w)
65   ...
66   cat 3
67   window 6
68   defenestrate 12
69
70If you need to modify the sequence you are iterating over while inside the loop
71(for example to duplicate selected items), it is recommended that you first
72make a copy.  Iterating over a sequence does not implicitly make a copy.  The
73slice notation makes this especially convenient::
74
75   >>> for w in words[:]:  # Loop over a slice copy of the entire list.
76   ...     if len(w) > 6:
77   ...         words.insert(0, w)
78   ...
79   >>> words
80   ['defenestrate', 'cat', 'window', 'defenestrate']
81
82
83.. _tut-range:
84
85The :func:`range` Function
86==========================
87
88If you do need to iterate over a sequence of numbers, the built-in function
89:func:`range` comes in handy.  It generates lists containing arithmetic
90progressions::
91
92   >>> range(10)
93   [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
94
95The given end point is never part of the generated list; ``range(10)`` generates
96a list of 10 values, the legal indices for items of a sequence of length 10.  It
97is possible to let the range start at another number, or to specify a different
98increment (even negative; sometimes this is called the 'step')::
99
100   >>> range(5, 10)
101   [5, 6, 7, 8, 9]
102   >>> range(0, 10, 3)
103   [0, 3, 6, 9]
104   >>> range(-10, -100, -30)
105   [-10, -40, -70]
106
107To iterate over the indices of a sequence, you can combine :func:`range` and
108:func:`len` as follows::
109
110   >>> a = ['Mary', 'had', 'a', 'little', 'lamb']
111   >>> for i in range(len(a)):
112   ...     print i, a[i]
113   ...
114   0 Mary
115   1 had
116   2 a
117   3 little
118   4 lamb
119
120In most such cases, however, it is convenient to use the :func:`enumerate`
121function, see :ref:`tut-loopidioms`.
122
123
124.. _tut-break:
125
126:keyword:`break` and :keyword:`continue` Statements, and :keyword:`else` Clauses on Loops
127=========================================================================================
128
129The :keyword:`break` statement, like in C, breaks out of the smallest enclosing
130:keyword:`for` or :keyword:`while` loop.
131
132Loop statements may have an ``else`` clause; it is executed when the loop
133terminates through exhaustion of the list (with :keyword:`for`) or when the
134condition becomes false (with :keyword:`while`), but not when the loop is
135terminated by a :keyword:`break` statement.  This is exemplified by the
136following loop, which searches for prime numbers::
137
138   >>> for n in range(2, 10):
139   ...     for x in range(2, n):
140   ...         if n % x == 0:
141   ...             print n, 'equals', x, '*', n/x
142   ...             break
143   ...     else:
144   ...         # loop fell through without finding a factor
145   ...         print n, 'is a prime number'
146   ...
147   2 is a prime number
148   3 is a prime number
149   4 equals 2 * 2
150   5 is a prime number
151   6 equals 2 * 3
152   7 is a prime number
153   8 equals 2 * 4
154   9 equals 3 * 3
155
156(Yes, this is the correct code.  Look closely: the ``else`` clause belongs to
157the :keyword:`for` loop, **not** the :keyword:`if` statement.)
158
159When used with a loop, the ``else`` clause has more in common with the
160``else`` clause of a :keyword:`try` statement than it does that of
161:keyword:`if` statements: a :keyword:`try` statement's ``else`` clause runs
162when no exception occurs, and a loop's ``else`` clause runs when no ``break``
163occurs. For more on the :keyword:`try` statement and exceptions, see
164:ref:`tut-handling`.
165
166The :keyword:`continue` statement, also borrowed from C, continues with the next
167iteration of the loop::
168
169    >>> for num in range(2, 10):
170    ...     if num % 2 == 0:
171    ...         print "Found an even number", num
172    ...         continue
173    ...     print "Found a number", num
174    Found an even number 2
175    Found a number 3
176    Found an even number 4
177    Found a number 5
178    Found an even number 6
179    Found a number 7
180    Found an even number 8
181    Found a number 9
182
183
184.. _tut-pass:
185
186:keyword:`pass` Statements
187==========================
188
189The :keyword:`pass` statement does nothing. It can be used when a statement is
190required syntactically but the program requires no action. For example::
191
192   >>> while True:
193   ...     pass  # Busy-wait for keyboard interrupt (Ctrl+C)
194   ...
195
196This is commonly used for creating minimal classes::
197
198   >>> class MyEmptyClass:
199   ...     pass
200   ...
201
202Another place :keyword:`pass` can be used is as a place-holder for a function or
203conditional body when you are working on new code, allowing you to keep thinking
204at a more abstract level.  The :keyword:`pass` is silently ignored::
205
206   >>> def initlog(*args):
207   ...     pass   # Remember to implement this!
208   ...
209
210.. _tut-functions:
211
212Defining Functions
213==================
214
215We can create a function that writes the Fibonacci series to an arbitrary
216boundary::
217
218   >>> def fib(n):    # write Fibonacci series up to n
219   ...     """Print a Fibonacci series up to n."""
220   ...     a, b = 0, 1
221   ...     while a < n:
222   ...         print a,
223   ...         a, b = b, a+b
224   ...
225   >>> # Now call the function we just defined:
226   ... fib(2000)
227   0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
228
229.. index::
230   single: documentation strings
231   single: docstrings
232   single: strings, documentation
233
234The keyword :keyword:`def` introduces a function *definition*.  It must be
235followed by the function name and the parenthesized list of formal parameters.
236The statements that form the body of the function start at the next line, and
237must be indented.
238
239The first statement of the function body can optionally be a string literal;
240this string literal is the function's documentation string, or :dfn:`docstring`.
241(More about docstrings can be found in the section :ref:`tut-docstrings`.)
242There are tools which use docstrings to automatically produce online or printed
243documentation, or to let the user interactively browse through code; it's good
244practice to include docstrings in code that you write, so make a habit of it.
245
246The *execution* of a function introduces a new symbol table used for the local
247variables of the function.  More precisely, all variable assignments in a
248function store the value in the local symbol table; whereas variable references
249first look in the local symbol table, then in the local symbol tables of
250enclosing functions, then in the global symbol table, and finally in the table
251of built-in names. Thus, global variables cannot be directly assigned a value
252within a function (unless named in a :keyword:`global` statement), although they
253may be referenced.
254
255The actual parameters (arguments) to a function call are introduced in the local
256symbol table of the called function when it is called; thus, arguments are
257passed using *call by value* (where the *value* is always an object *reference*,
258not the value of the object). [#]_ When a function calls another function, a new
259local symbol table is created for that call.
260
261A function definition introduces the function name in the current symbol table.
262The value of the function name has a type that is recognized by the interpreter
263as a user-defined function.  This value can be assigned to another name which
264can then also be used as a function.  This serves as a general renaming
265mechanism::
266
267   >>> fib
268   <function fib at 10042ed0>
269   >>> f = fib
270   >>> f(100)
271   0 1 1 2 3 5 8 13 21 34 55 89
272
273Coming from other languages, you might object that ``fib`` is not a function but
274a procedure since it doesn't return a value.  In fact, even functions without a
275:keyword:`return` statement do return a value, albeit a rather boring one.  This
276value is called ``None`` (it's a built-in name).  Writing the value ``None`` is
277normally suppressed by the interpreter if it would be the only value written.
278You can see it if you really want to using :keyword:`print`::
279
280   >>> fib(0)
281   >>> print fib(0)
282   None
283
284It is simple to write a function that returns a list of the numbers of the
285Fibonacci series, instead of printing it::
286
287   >>> def fib2(n):  # return Fibonacci series up to n
288   ...     """Return a list containing the Fibonacci series up to n."""
289   ...     result = []
290   ...     a, b = 0, 1
291   ...     while a < n:
292   ...         result.append(a)    # see below
293   ...         a, b = b, a+b
294   ...     return result
295   ...
296   >>> f100 = fib2(100)    # call it
297   >>> f100                # write the result
298   [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
299
300This example, as usual, demonstrates some new Python features:
301
302* The :keyword:`return` statement returns with a value from a function.
303  :keyword:`return` without an expression argument returns ``None``. Falling off
304  the end of a function also returns ``None``.
305
306* The statement ``result.append(a)`` calls a *method* of the list object
307  ``result``.  A method is a function that 'belongs' to an object and is named
308  ``obj.methodname``, where ``obj`` is some object (this may be an expression),
309  and ``methodname`` is the name of a method that is defined by the object's type.
310  Different types define different methods.  Methods of different types may have
311  the same name without causing ambiguity.  (It is possible to define your own
312  object types and methods, using *classes*, see :ref:`tut-classes`)
313  The method :meth:`append` shown in the example is defined for list objects; it
314  adds a new element at the end of the list.  In this example it is equivalent to
315  ``result = result + [a]``, but more efficient.
316
317
318.. _tut-defining:
319
320More on Defining Functions
321==========================
322
323It is also possible to define functions with a variable number of arguments.
324There are three forms, which can be combined.
325
326
327.. _tut-defaultargs:
328
329Default Argument Values
330-----------------------
331
332The most useful form is to specify a default value for one or more arguments.
333This creates a function that can be called with fewer arguments than it is
334defined to allow.  For example::
335
336   def ask_ok(prompt, retries=4, complaint='Yes or no, please!'):
337       while True:
338           ok = raw_input(prompt)
339           if ok in ('y', 'ye', 'yes'):
340               return True
341           if ok in ('n', 'no', 'nop', 'nope'):
342               return False
343           retries = retries - 1
344           if retries < 0:
345               raise IOError('refusenik user')
346           print complaint
347
348This function can be called in several ways:
349
350* giving only the mandatory argument:
351  ``ask_ok('Do you really want to quit?')``
352* giving one of the optional arguments:
353  ``ask_ok('OK to overwrite the file?', 2)``
354* or even giving all arguments:
355  ``ask_ok('OK to overwrite the file?', 2, 'Come on, only yes or no!')``
356
357This example also introduces the :keyword:`in` keyword. This tests whether or
358not a sequence contains a certain value.
359
360The default values are evaluated at the point of function definition in the
361*defining* scope, so that ::
362
363   i = 5
364
365   def f(arg=i):
366       print arg
367
368   i = 6
369   f()
370
371will print ``5``.
372
373**Important warning:**  The default value is evaluated only once. This makes a
374difference when the default is a mutable object such as a list, dictionary, or
375instances of most classes.  For example, the following function accumulates the
376arguments passed to it on subsequent calls::
377
378   def f(a, L=[]):
379       L.append(a)
380       return L
381
382   print f(1)
383   print f(2)
384   print f(3)
385
386This will print ::
387
388   [1]
389   [1, 2]
390   [1, 2, 3]
391
392If you don't want the default to be shared between subsequent calls, you can
393write the function like this instead::
394
395   def f(a, L=None):
396       if L is None:
397           L = []
398       L.append(a)
399       return L
400
401
402.. _tut-keywordargs:
403
404Keyword Arguments
405-----------------
406
407Functions can also be called using :term:`keyword arguments <keyword argument>`
408of the form ``kwarg=value``.  For instance, the following function::
409
410   def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'):
411       print "-- This parrot wouldn't", action,
412       print "if you put", voltage, "volts through it."
413       print "-- Lovely plumage, the", type
414       print "-- It's", state, "!"
415
416accepts one required argument (``voltage``) and three optional arguments
417(``state``, ``action``, and ``type``).  This function can be called in any
418of the following ways::
419
420   parrot(1000)                                          # 1 positional argument
421   parrot(voltage=1000)                                  # 1 keyword argument
422   parrot(voltage=1000000, action='VOOOOOM')             # 2 keyword arguments
423   parrot(action='VOOOOOM', voltage=1000000)             # 2 keyword arguments
424   parrot('a million', 'bereft of life', 'jump')         # 3 positional arguments
425   parrot('a thousand', state='pushing up the daisies')  # 1 positional, 1 keyword
426
427but all the following calls would be invalid::
428
429   parrot()                     # required argument missing
430   parrot(voltage=5.0, 'dead')  # non-keyword argument after a keyword argument
431   parrot(110, voltage=220)     # duplicate value for the same argument
432   parrot(actor='John Cleese')  # unknown keyword argument
433
434In a function call, keyword arguments must follow positional arguments.
435All the keyword arguments passed must match one of the arguments
436accepted by the function (e.g. ``actor`` is not a valid argument for the
437``parrot`` function), and their order is not important.  This also includes
438non-optional arguments (e.g. ``parrot(voltage=1000)`` is valid too).
439No argument may receive a value more than once.
440Here's an example that fails due to this restriction::
441
442   >>> def function(a):
443   ...     pass
444   ...
445   >>> function(0, a=0)
446   Traceback (most recent call last):
447     File "<stdin>", line 1, in ?
448   TypeError: function() got multiple values for keyword argument 'a'
449
450When a final formal parameter of the form ``**name`` is present, it receives a
451dictionary (see :ref:`typesmapping`) containing all keyword arguments except for
452those corresponding to a formal parameter.  This may be combined with a formal
453parameter of the form ``*name`` (described in the next subsection) which
454receives a tuple containing the positional arguments beyond the formal parameter
455list.  (``*name`` must occur before ``**name``.) For example, if we define a
456function like this::
457
458   def cheeseshop(kind, *arguments, **keywords):
459       print "-- Do you have any", kind, "?"
460       print "-- I'm sorry, we're all out of", kind
461       for arg in arguments:
462           print arg
463       print "-" * 40
464       keys = sorted(keywords.keys())
465       for kw in keys:
466           print kw, ":", keywords[kw]
467
468It could be called like this::
469
470   cheeseshop("Limburger", "It's very runny, sir.",
471              "It's really very, VERY runny, sir.",
472              shopkeeper='Michael Palin',
473              client="John Cleese",
474              sketch="Cheese Shop Sketch")
475
476and of course it would print:
477
478.. code-block:: none
479
480   -- Do you have any Limburger ?
481   -- I'm sorry, we're all out of Limburger
482   It's very runny, sir.
483   It's really very, VERY runny, sir.
484   ----------------------------------------
485   client : John Cleese
486   shopkeeper : Michael Palin
487   sketch : Cheese Shop Sketch
488
489Note that the list of keyword argument names is created by sorting the result
490of the keywords dictionary's ``keys()`` method before printing its contents;
491if this is not done, the order in which the arguments are printed is undefined.
492
493.. _tut-arbitraryargs:
494
495Arbitrary Argument Lists
496------------------------
497
498.. index::
499  statement: *
500
501Finally, the least frequently used option is to specify that a function can be
502called with an arbitrary number of arguments.  These arguments will be wrapped
503up in a tuple (see :ref:`tut-tuples`).  Before the variable number of arguments,
504zero or more normal arguments may occur. ::
505
506   def write_multiple_items(file, separator, *args):
507       file.write(separator.join(args))
508
509
510.. _tut-unpacking-arguments:
511
512Unpacking Argument Lists
513------------------------
514
515The reverse situation occurs when the arguments are already in a list or tuple
516but need to be unpacked for a function call requiring separate positional
517arguments.  For instance, the built-in :func:`range` function expects separate
518*start* and *stop* arguments.  If they are not available separately, write the
519function call with the  ``*``\ -operator to unpack the arguments out of a list
520or tuple::
521
522   >>> range(3, 6)             # normal call with separate arguments
523   [3, 4, 5]
524   >>> args = [3, 6]
525   >>> range(*args)            # call with arguments unpacked from a list
526   [3, 4, 5]
527
528.. index::
529  statement: **
530
531In the same fashion, dictionaries can deliver keyword arguments with the ``**``\
532-operator::
533
534   >>> def parrot(voltage, state='a stiff', action='voom'):
535   ...     print "-- This parrot wouldn't", action,
536   ...     print "if you put", voltage, "volts through it.",
537   ...     print "E's", state, "!"
538   ...
539   >>> d = {"voltage": "four million", "state": "bleedin' demised", "action": "VOOM"}
540   >>> parrot(**d)
541   -- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !
542
543
544.. _tut-lambda:
545
546Lambda Expressions
547------------------
548
549Small anonymous functions can be created with the :keyword:`lambda` keyword.
550This function returns the sum of its two arguments: ``lambda a, b: a+b``.
551Lambda functions can be used wherever function objects are required.  They are
552syntactically restricted to a single expression.  Semantically, they are just
553syntactic sugar for a normal function definition.  Like nested function
554definitions, lambda functions can reference variables from the containing
555scope::
556
557   >>> def make_incrementor(n):
558   ...     return lambda x: x + n
559   ...
560   >>> f = make_incrementor(42)
561   >>> f(0)
562   42
563   >>> f(1)
564   43
565
566The above example uses a lambda expression to return a function.  Another use
567is to pass a small function as an argument::
568
569   >>> pairs = [(1, 'one'), (2, 'two'), (3, 'three'), (4, 'four')]
570   >>> pairs.sort(key=lambda pair: pair[1])
571   >>> pairs
572   [(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')]
573
574
575.. _tut-docstrings:
576
577Documentation Strings
578---------------------
579
580.. index::
581   single: docstrings
582   single: documentation strings
583   single: strings, documentation
584
585There are emerging conventions about the content and formatting of documentation
586strings.
587
588The first line should always be a short, concise summary of the object's
589purpose.  For brevity, it should not explicitly state the object's name or type,
590since these are available by other means (except if the name happens to be a
591verb describing a function's operation).  This line should begin with a capital
592letter and end with a period.
593
594If there are more lines in the documentation string, the second line should be
595blank, visually separating the summary from the rest of the description.  The
596following lines should be one or more paragraphs describing the object's calling
597conventions, its side effects, etc.
598
599The Python parser does not strip indentation from multi-line string literals in
600Python, so tools that process documentation have to strip indentation if
601desired.  This is done using the following convention. The first non-blank line
602*after* the first line of the string determines the amount of indentation for
603the entire documentation string.  (We can't use the first line since it is
604generally adjacent to the string's opening quotes so its indentation is not
605apparent in the string literal.)  Whitespace "equivalent" to this indentation is
606then stripped from the start of all lines of the string.  Lines that are
607indented less should not occur, but if they occur all their leading whitespace
608should be stripped.  Equivalence of whitespace should be tested after expansion
609of tabs (to 8 spaces, normally).
610
611Here is an example of a multi-line docstring::
612
613   >>> def my_function():
614   ...     """Do nothing, but document it.
615   ...
616   ...     No, really, it doesn't do anything.
617   ...     """
618   ...     pass
619   ...
620   >>> print my_function.__doc__
621   Do nothing, but document it.
622
623       No, really, it doesn't do anything.
624
625
626.. _tut-codingstyle:
627
628Intermezzo: Coding Style
629========================
630
631.. sectionauthor:: Georg Brandl <georg@python.org>
632.. index:: pair: coding; style
633
634Now that you are about to write longer, more complex pieces of Python, it is a
635good time to talk about *coding style*.  Most languages can be written (or more
636concise, *formatted*) in different styles; some are more readable than others.
637Making it easy for others to read your code is always a good idea, and adopting
638a nice coding style helps tremendously for that.
639
640For Python, :pep:`8` has emerged as the style guide that most projects adhere to;
641it promotes a very readable and eye-pleasing coding style.  Every Python
642developer should read it at some point; here are the most important points
643extracted for you:
644
645* Use 4-space indentation, and no tabs.
646
647  4 spaces are a good compromise between small indentation (allows greater
648  nesting depth) and large indentation (easier to read).  Tabs introduce
649  confusion, and are best left out.
650
651* Wrap lines so that they don't exceed 79 characters.
652
653  This helps users with small displays and makes it possible to have several
654  code files side-by-side on larger displays.
655
656* Use blank lines to separate functions and classes, and larger blocks of
657  code inside functions.
658
659* When possible, put comments on a line of their own.
660
661* Use docstrings.
662
663* Use spaces around operators and after commas, but not directly inside
664  bracketing constructs: ``a = f(1, 2) + g(3, 4)``.
665
666* Name your classes and functions consistently; the convention is to use
667  ``CamelCase`` for classes and ``lower_case_with_underscores`` for functions
668  and methods.  Always use ``self`` as the name for the first method argument
669  (see :ref:`tut-firstclasses` for more on classes and methods).
670
671* Don't use fancy encodings if your code is meant to be used in international
672  environments.  Plain ASCII works best in any case.
673
674
675.. rubric:: Footnotes
676
677.. [#] Actually, *call by object reference* would be a better description,
678   since if a mutable object is passed, the caller will see any changes the
679   callee makes to it (items inserted into a list).
680
681