4.More Control Flow Tools¶
As well as thewhile
statement just introduced, Python uses a few morethat we will encounter in this chapter.
4.1.if
Statements¶
Perhaps the most well-known statement type is theif
statement. Forexample:
>>>x=int(input("Please enter an integer: "))Please enter an integer: 42>>>ifx<0:...x=0...print('Negative changed to zero')...elifx==0:...print('Zero')...elifx==1:...print('Single')...else:...print('More')...More
There can be zero or moreelif
parts, and theelse
part isoptional. The keyword ‘elif
’ is short for ‘else if’, and is usefulto avoid excessive indentation. Anif
…elif
…elif
… sequence is a substitute for theswitch
orcase
statements found in other languages.
If you’re comparing the same value to several constants, or checking for specific types orattributes, you may also find thematch
statement useful. For moredetails seematch Statements.
4.2.for
Statements¶
Thefor
statement in Python differs a bit from what you may be usedto in C or Pascal. Rather than always iterating over an arithmetic progressionof numbers (like in Pascal), or giving the user the ability to define both theiteration step and halting condition (as C), Python’sfor
statementiterates over the items of any sequence (a list or a string), in the order thatthey appear in the sequence. For example (no pun intended):
>>># Measure some strings:>>>words=['cat','window','defenestrate']>>>forwinwords:...print(w,len(w))...cat 3window 6defenestrate 12
Code that modifies a collection while iterating over that same collection canbe tricky to get right. Instead, it is usually more straight-forward to loopover a copy of the collection or to create a new collection:
# Create a sample collectionusers={'Hans':'active','Éléonore':'inactive','景太郎':'active'}# Strategy: Iterate over a copyforuser,statusinusers.copy().items():ifstatus=='inactive':delusers[user]# Strategy: Create a new collectionactive_users={}foruser,statusinusers.items():ifstatus=='active':active_users[user]=status
4.3.Therange()
Function¶
If you do need to iterate over a sequence of numbers, the built-in functionrange()
comes in handy. It generates arithmetic progressions:
>>>foriinrange(5):...print(i)...01234
The given end point is never part of the generated sequence;range(10)
generates10 values, the legal indices for items of a sequence of length 10. Itis possible to let the range start at another number, or to specify a differentincrement (even negative; sometimes this is called the ‘step’):
>>>list(range(5,10))[5, 6, 7, 8, 9]>>>list(range(0,10,3))[0, 3, 6, 9]>>>list(range(-10,-100,-30))[-10, -40, -70]
To iterate over the indices of a sequence, you can combinerange()
andlen()
as follows:
>>>a=['Mary','had','a','little','lamb']>>>foriinrange(len(a)):...print(i,a[i])...0 Mary1 had2 a3 little4 lamb
In most such cases, however, it is convenient to use theenumerate()
function, seeLooping Techniques.
A strange thing happens if you just print a range:
>>>range(10)range(0, 10)
In many ways the object returned byrange()
behaves as if it is a list,but in fact it isn’t. It is an object which returns the successive items ofthe desired sequence when you iterate over it, but it doesn’t really makethe list, thus saving space.
We say such an object isiterable, that is, suitable as a target forfunctions and constructs that expect something from which they canobtain successive items until the supply is exhausted. We have seen thatthefor
statement is such a construct, while an example of a functionthat takes an iterable issum()
:
>>>sum(range(4))# 0 + 1 + 2 + 36
Later we will see more functions that return iterables and take iterables asarguments. In chapterData Structures, we will discuss in more detail aboutlist()
.
4.4.break
andcontinue
Statements¶
Thebreak
statement breaks out of the innermost enclosingfor
orwhile
loop:
>>>forninrange(2,10):...forxinrange(2,n):...ifn%x==0:...print(f"{n} equals{x} *{n//x}")...break...4 equals 2 * 26 equals 2 * 38 equals 2 * 49 equals 3 * 3
Thecontinue
statement continues with the nextiteration of the loop:
>>>fornuminrange(2,10):...ifnum%2==0:...print(f"Found an even number{num}")...continue...print(f"Found an odd number{num}")...Found an even number 2Found an odd number 3Found an even number 4Found an odd number 5Found an even number 6Found an odd number 7Found an even number 8Found an odd number 9
4.5.else
Clauses on Loops¶
In afor
orwhile
loop thebreak
statementmay be paired with anelse
clause. If the loop finishes withoutexecuting thebreak
, theelse
clause executes.
In afor
loop, theelse
clause is executedafter the loop finishes its final iteration, that is, if no break occurred.
In awhile
loop, it’s executed after the loop’s condition becomes false.
In either kind of loop, theelse
clause isnot executed if theloop was terminated by abreak
. Of course, other ways of ending theloop early, such as areturn
or a raised exception, will also skipexecution of theelse
clause.
This is exemplified in the followingfor
loop,which searches for prime numbers:
>>>forninrange(2,10):...forxinrange(2,n):...ifn%x==0:...print(n,'equals',x,'*',n//x)...break...else:...# loop fell through without finding a factor...print(n,'is a prime number')...2 is a prime number3 is a prime number4 equals 2 * 25 is a prime number6 equals 2 * 37 is a prime number8 equals 2 * 49 equals 3 * 3
(Yes, this is the correct code. Look closely: theelse
clause belongs tothefor
loop,not theif
statement.)
One way to think of the else clause is to imagine it paired with theif
inside the loop. As the loop executes, it will run a sequence likeif/if/if/else. Theif
is inside the loop, encountered a number of times. Ifthe condition is ever true, abreak
will happen. If the condition is nevertrue, theelse
clause outside the loop will execute.
When used with a loop, theelse
clause has more in common with theelse
clause of atry
statement than it does with that ofif
statements: atry
statement’selse
clause runs when no exceptionoccurs, and a loop’selse
clause runs when nobreak
occurs. For more onthetry
statement and exceptions, seeHandling Exceptions.
4.6.pass
Statements¶
Thepass
statement does nothing. It can be used when a statement isrequired syntactically but the program requires no action. For example:
>>>whileTrue:...pass# Busy-wait for keyboard interrupt (Ctrl+C)...
This is commonly used for creating minimal classes:
>>>classMyEmptyClass:...pass...
Another placepass
can be used is as a place-holder for a function orconditional body when you are working on new code, allowing you to keep thinkingat a more abstract level. Thepass
is silently ignored:
>>>definitlog(*args):...pass# Remember to implement this!...
4.7.match
Statements¶
Amatch
statement takes an expression and compares its value to successivepatterns given as one or more case blocks. This is superficiallysimilar to a switch statement in C, Java or JavaScript (and manyother languages), but it’s more similar to pattern matching inlanguages like Rust or Haskell. Only the first pattern that matchesgets executed and it can also extract components (sequence elementsor object attributes) from the value into variables.
The simplest form compares a subject value against one or more literals:
defhttp_error(status):matchstatus:case400:return"Bad request"case404:return"Not found"case418:return"I'm a teapot"case_:return"Something's wrong with the internet"
Note the last block: the “variable name”_
acts as awildcard andnever fails to match. If no case matches, none of the branches is executed.
You can combine several literals in a single pattern using|
(“or”):
case401|403|404:return"Not allowed"
Patterns can look like unpacking assignments, and can be used to bindvariables:
# point is an (x, y) tuplematchpoint:case(0,0):print("Origin")case(0,y):print(f"Y={y}")case(x,0):print(f"X={x}")case(x,y):print(f"X={x}, Y={y}")case_:raiseValueError("Not a point")
Study that one carefully! The first pattern has two literals, and canbe thought of as an extension of the literal pattern shown above. Butthe next two patterns combine a literal and a variable, and thevariablebinds a value from the subject (point
). The fourthpattern captures two values, which makes it conceptually similar tothe unpacking assignment(x,y)=point
.
If you are using classes to structure your datayou can use the class name followed by an argument list resembling aconstructor, but with the ability to capture attributes into variables:
classPoint:def__init__(self,x,y):self.x=xself.y=ydefwhere_is(point):matchpoint:casePoint(x=0,y=0):print("Origin")casePoint(x=0,y=y):print(f"Y={y}")casePoint(x=x,y=0):print(f"X={x}")casePoint():print("Somewhere else")case_:print("Not a point")
You can use positional parameters with some builtin classes that provide anordering for their attributes (e.g. dataclasses). You can also define a specificposition for attributes in patterns by setting the__match_args__
specialattribute in your classes. If it’s set to (“x”, “y”), the following patterns are allequivalent (and all bind they
attribute to thevar
variable):
Point(1,var)Point(1,y=var)Point(x=1,y=var)Point(y=var,x=1)
A recommended way to read patterns is to look at them as an extended form of what youwould put on the left of an assignment, to understand which variables would be set towhat.Only the standalone names (likevar
above) are assigned to by a match statement.Dotted names (likefoo.bar
), attribute names (thex=
andy=
above) or class names(recognized by the “(…)” next to them likePoint
above) are never assigned to.
Patterns can be arbitrarily nested. For example, if we have a shortlist of Points, with__match_args__
added, we could match it like this:
classPoint:__match_args__=('x','y')def__init__(self,x,y):self.x=xself.y=ymatchpoints:case[]:print("No points")case[Point(0,0)]:print("The origin")case[Point(x,y)]:print(f"Single point{x},{y}")case[Point(0,y1),Point(0,y2)]:print(f"Two on the Y axis at{y1},{y2}")case_:print("Something else")
We can add anif
clause to a pattern, known as a “guard”. If theguard is false,match
goes on to try the next case block. Notethat value capture happens before the guard is evaluated:
matchpoint:casePoint(x,y)ifx==y:print(f"Y=X at{x}")casePoint(x,y):print(f"Not on the diagonal")
Several other key features of this statement:
Like unpacking assignments, tuple and list patterns have exactly thesame meaning and actually match arbitrary sequences. An importantexception is that they don’t match iterators or strings.
Sequence patterns support extended unpacking:
[x,y,*rest]
and(x,y,*rest)
work similar to unpacking assignments. Thename after*
may also be_
, so(x,y,*_)
matches a sequenceof at least two items without binding the remaining items.Mapping patterns:
{"bandwidth":b,"latency":l}
captures the"bandwidth"
and"latency"
values from a dictionary. Unlike sequencepatterns, extra keys are ignored. An unpacking like**rest
is alsosupported. (But**_
would be redundant, so it is not allowed.)Subpatterns may be captured using the
as
keyword:case(Point(x1,y1),Point(x2,y2)asp2):...
will capture the second element of the input as
p2
(as long as the input isa sequence of two points)Most literals are compared by equality, however the singletons
True
,False
andNone
are compared by identity.Patterns may use named constants. These must be dotted namesto prevent them from being interpreted as capture variable:
fromenumimportEnumclassColor(Enum):RED='red'GREEN='green'BLUE='blue'color=Color(input("Enter your choice of 'red', 'blue' or 'green': "))matchcolor:caseColor.RED:print("I see red!")caseColor.GREEN:print("Grass is green")caseColor.BLUE:print("I'm feeling the blues :(")
For a more detailed explanation and additional examples, you can look intoPEP 636 which is written in a tutorial format.
4.8.Defining Functions¶
We can create a function that writes the Fibonacci series to an arbitraryboundary:
>>>deffib(n):# write Fibonacci series less than n..."""Print a Fibonacci series less than n."""...a,b=0,1...whilea<n:...print(a,end=' ')...a,b=b,a+b...print()...>>># Now call the function we just defined:>>>fib(2000)0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
The keyworddef
introduces a functiondefinition. It must befollowed by the function name and the parenthesized list of formal parameters.The statements that form the body of the function start at the next line, andmust be indented.
The first statement of the function body can optionally be a string literal;this string literal is the function’s documentation string, ordocstring.(More about docstrings can be found in the sectionDocumentation Strings.)There are tools which use docstrings to automatically produce online or printeddocumentation, or to let the user interactively browse through code; it’s goodpractice to include docstrings in code that you write, so make a habit of it.
Theexecution of a function introduces a new symbol table used for the localvariables of the function. More precisely, all variable assignments in afunction store the value in the local symbol table; whereas variable referencesfirst look in the local symbol table, then in the local symbol tables ofenclosing functions, then in the global symbol table, and finally in the tableof built-in names. Thus, global variables and variables of enclosing functionscannot be directly assigned a value within a function (unless, for globalvariables, named in aglobal
statement, or, for variables of enclosingfunctions, named in anonlocal
statement), although they may bereferenced.
The actual parameters (arguments) to a function call are introduced in the localsymbol table of the called function when it is called; thus, arguments arepassed usingcall by value (where thevalue is always an objectreference,not the value of the object).[1] When a function calls another function,or calls itself recursively, a newlocal symbol table is created for that call.
A function definition associates the function name with the function object inthe current symbol table. The interpreter recognizes the object pointed to bythat name as a user-defined function. Other names can also point to that samefunction object and can also be used to access the function:
>>>fib<function fib at 10042ed0>>>>f=fib>>>f(100)0 1 1 2 3 5 8 13 21 34 55 89
Coming from other languages, you might object thatfib
is not a function buta procedure since it doesn’t return a value. In fact, even functions without areturn
statement do return a value, albeit a rather boring one. Thisvalue is calledNone
(it’s a built-in name). Writing the valueNone
isnormally suppressed by the interpreter if it would be the only value written.You can see it if you really want to usingprint()
:
>>>fib(0)>>>print(fib(0))None
It is simple to write a function that returns a list of the numbers of theFibonacci series, instead of printing it:
>>>deffib2(n):# return Fibonacci series up to n..."""Return a list containing the Fibonacci series up to n."""...result=[]...a,b=0,1...whilea<n:...result.append(a)# see below...a,b=b,a+b...returnresult...>>>f100=fib2(100)# call it>>>f100# write the result[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
This example, as usual, demonstrates some new Python features:
The
return
statement returns with a value from a function.return
without an expression argument returnsNone
. Falling offthe end of a function also returnsNone
.The statement
result.append(a)
calls amethod of the list objectresult
. A method is a function that ‘belongs’ to an object and is namedobj.methodname
, whereobj
is some object (this may be an expression),andmethodname
is the name of a method that is defined by the object’s type.Different types define different methods. Methods of different types may havethe same name without causing ambiguity. (It is possible to define your ownobject types and methods, usingclasses, seeClasses)The methodappend()
shown in the example is defined for list objects; itadds a new element at the end of the list. In this example it is equivalent toresult=result+[a]
, but more efficient.
4.9.More on Defining Functions¶
It is also possible to define functions with a variable number of arguments.There are three forms, which can be combined.
4.9.1.Default Argument Values¶
The most useful form is to specify a default value for one or more arguments.This creates a function that can be called with fewer arguments than it isdefined to allow. For example:
defask_ok(prompt,retries=4,reminder='Please try again!'):whileTrue:reply=input(prompt)ifreplyin{'y','ye','yes'}:returnTrueifreplyin{'n','no','nop','nope'}:returnFalseretries=retries-1ifretries<0:raiseValueError('invalid user response')print(reminder)
This function can be called in several ways:
giving only the mandatory argument:
ask_ok('Doyoureallywanttoquit?')
giving one of the optional arguments:
ask_ok('OKtooverwritethefile?',2)
or even giving all arguments:
ask_ok('OKtooverwritethefile?',2,'Comeon,onlyyesorno!')
This example also introduces thein
keyword. This tests whether ornot a sequence contains a certain value.
The default values are evaluated at the point of function definition in thedefining scope, so that
i=5deff(arg=i):print(arg)i=6f()
will print5
.
Important warning: The default value is evaluated only once. This makes adifference when the default is a mutable object such as a list, dictionary, orinstances of most classes. For example, the following function accumulates thearguments passed to it on subsequent calls:
deff(a,L=[]):L.append(a)returnLprint(f(1))print(f(2))print(f(3))
This will print
[1][1,2][1,2,3]
If you don’t want the default to be shared between subsequent calls, you canwrite the function like this instead:
deff(a,L=None):ifLisNone:L=[]L.append(a)returnL
4.9.2.Keyword Arguments¶
Functions can also be called usingkeyword argumentsof the formkwarg=value
. For instance, the following function:
defparrot(voltage,state='a stiff',action='voom',type='Norwegian Blue'):print("-- This parrot wouldn't",action,end=' ')print("if you put",voltage,"volts through it.")print("-- Lovely plumage, the",type)print("-- It's",state,"!")
accepts one required argument (voltage
) and three optional arguments(state
,action
, andtype
). This function can be called in anyof the following ways:
parrot(1000)# 1 positional argumentparrot(voltage=1000)# 1 keyword argumentparrot(voltage=1000000,action='VOOOOOM')# 2 keyword argumentsparrot(action='VOOOOOM',voltage=1000000)# 2 keyword argumentsparrot('a million','bereft of life','jump')# 3 positional argumentsparrot('a thousand',state='pushing up the daisies')# 1 positional, 1 keyword
but all the following calls would be invalid:
parrot()# required argument missingparrot(voltage=5.0,'dead')# non-keyword argument after a keyword argumentparrot(110,voltage=220)# duplicate value for the same argumentparrot(actor='John Cleese')# unknown keyword argument
In a function call, keyword arguments must follow positional arguments.All the keyword arguments passed must match one of the argumentsaccepted by the function (e.g.actor
is not a valid argument for theparrot
function), and their order is not important. This also includesnon-optional arguments (e.g.parrot(voltage=1000)
is valid too).No argument may receive a value more than once.Here’s an example that fails due to this restriction:
>>>deffunction(a):...pass...>>>function(0,a=0)Traceback (most recent call last): File"<stdin>", line1, in<module>TypeError:function() got multiple values for argument 'a'
When a final formal parameter of the form**name
is present, it receives adictionary (seeMapping Types — dict) containing all keyword arguments except forthose corresponding to a formal parameter. This may be combined with a formalparameter of the form*name
(described in the next subsection) whichreceives atuple containing the positionalarguments beyond the formal parameter list. (*name
must occurbefore**name
.) For example, if we define a function like this:
defcheeseshop(kind,*arguments,**keywords):print("-- Do you have any",kind,"?")print("-- I'm sorry, we're all out of",kind)forarginarguments:print(arg)print("-"*40)forkwinkeywords:print(kw,":",keywords[kw])
It could be called like this:
cheeseshop("Limburger","It's very runny, sir.","It's really very, VERY runny, sir.",shopkeeper="Michael Palin",client="John Cleese",sketch="Cheese Shop Sketch")
and of course it would print:
-- Do you have any Limburger ?-- I'm sorry, we're all out of LimburgerIt's very runny, sir.It's really very, VERY runny, sir.----------------------------------------shopkeeper : Michael Palinclient : John Cleesesketch : Cheese Shop Sketch
Note that the order in which the keyword arguments are printed is guaranteedto match the order in which they were provided in the function call.
4.9.3.Special parameters¶
By default, arguments may be passed to a Python function either by positionor explicitly by keyword. For readability and performance, it makes sense torestrict the way arguments can be passed so that a developer need only lookat the function definition to determine if items are passed by position, byposition or keyword, or by keyword.
A function definition may look like:
def f(pos1, pos2, /, pos_or_kwd, *, kwd1, kwd2): ----------- ---------- ---------- | | | | Positional or keyword | | - Keyword only -- Positional only
where/
and*
are optional. If used, these symbols indicate the kind ofparameter by how the arguments may be passed to the function:positional-only, positional-or-keyword, and keyword-only. Keyword parametersare also referred to as named parameters.
4.9.3.1.Positional-or-Keyword Arguments¶
If/
and*
are not present in the function definition, arguments maybe passed to a function by position or by keyword.
4.9.3.2.Positional-Only Parameters¶
Looking at this in a bit more detail, it is possible to mark certain parametersaspositional-only. Ifpositional-only, the parameters’ order matters, andthe parameters cannot be passed by keyword. Positional-only parameters areplaced before a/
(forward-slash). The/
is used to logicallyseparate the positional-only parameters from the rest of the parameters.If there is no/
in the function definition, there are no positional-onlyparameters.
Parameters following the/
may bepositional-or-keyword orkeyword-only.
4.9.3.3.Keyword-Only Arguments¶
To mark parameters askeyword-only, indicating the parameters must be passedby keyword argument, place an*
in the arguments list just before the firstkeyword-only parameter.
4.9.3.4.Function Examples¶
Consider the following example function definitions paying close attention to themarkers/
and*
:
>>>defstandard_arg(arg):...print(arg)...>>>defpos_only_arg(arg,/):...print(arg)...>>>defkwd_only_arg(*,arg):...print(arg)...>>>defcombined_example(pos_only,/,standard,*,kwd_only):...print(pos_only,standard,kwd_only)
The first function definition,standard_arg
, the most familiar form,places no restrictions on the calling convention and arguments may bepassed by position or keyword:
>>>standard_arg(2)2>>>standard_arg(arg=2)2
The second functionpos_only_arg
is restricted to only use positionalparameters as there is a/
in the function definition:
>>>pos_only_arg(1)1>>>pos_only_arg(arg=1)Traceback (most recent call last): File"<stdin>", line1, in<module>TypeError:pos_only_arg() got some positional-only arguments passed as keyword arguments: 'arg'
The third functionkwd_only_arg
only allows keyword arguments as indicatedby a*
in the function definition:
>>>kwd_only_arg(3)Traceback (most recent call last): File"<stdin>", line1, in<module>TypeError:kwd_only_arg() takes 0 positional arguments but 1 was given>>>kwd_only_arg(arg=3)3
And the last uses all three calling conventions in the same functiondefinition:
>>>combined_example(1,2,3)Traceback (most recent call last): File"<stdin>", line1, in<module>TypeError:combined_example() takes 2 positional arguments but 3 were given>>>combined_example(1,2,kwd_only=3)1 2 3>>>combined_example(1,standard=2,kwd_only=3)1 2 3>>>combined_example(pos_only=1,standard=2,kwd_only=3)Traceback (most recent call last): File"<stdin>", line1, in<module>TypeError:combined_example() got some positional-only arguments passed as keyword arguments: 'pos_only'
Finally, consider this function definition which has a potential collision between the positional argumentname
and**kwds
which hasname
as a key:
deffoo(name,**kwds):return'name'inkwds
There is no possible call that will make it returnTrue
as the keyword'name'
will always bind to the first parameter. For example:
>>>foo(1,**{'name':2})Traceback (most recent call last): File"<stdin>", line1, in<module>TypeError:foo() got multiple values for argument 'name'>>>
But using/
(positional only arguments), it is possible since it allowsname
as a positional argument and'name'
as a key in the keyword arguments:
>>>deffoo(name,/,**kwds):...return'name'inkwds...>>>foo(1,**{'name':2})True
In other words, the names of positional-only parameters can be used in**kwds
without ambiguity.
4.9.3.5.Recap¶
The use case will determine which parameters to use in the function definition:
deff(pos1,pos2,/,pos_or_kwd,*,kwd1,kwd2):
As guidance:
Use positional-only if you want the name of the parameters to not beavailable to the user. This is useful when parameter names have no realmeaning, if you want to enforce the order of the arguments when the functionis called or if you need to take some positional parameters and arbitrarykeywords.
Use keyword-only when names have meaning and the function definition ismore understandable by being explicit with names or you want to preventusers relying on the position of the argument being passed.
For an API, use positional-only to prevent breaking API changesif the parameter’s name is modified in the future.
4.9.4.Arbitrary Argument Lists¶
Finally, the least frequently used option is to specify that a function can becalled with an arbitrary number of arguments. These arguments will be wrappedup in a tuple (seeTuples and Sequences). Before the variable number of arguments,zero or more normal arguments may occur.
defwrite_multiple_items(file,separator,*args):file.write(separator.join(args))
Normally, thesevariadic arguments will be last in the list of formalparameters, because they scoop up all remaining input arguments that arepassed to the function. Any formal parameters which occur after the*args
parameter are ‘keyword-only’ arguments, meaning that they can only be used askeywords rather than positional arguments.
>>>defconcat(*args,sep="/"):...returnsep.join(args)...>>>concat("earth","mars","venus")'earth/mars/venus'>>>concat("earth","mars","venus",sep=".")'earth.mars.venus'
4.9.5.Unpacking Argument Lists¶
The reverse situation occurs when the arguments are already in a list or tuplebut need to be unpacked for a function call requiring separate positionalarguments. For instance, the built-inrange()
function expects separatestart andstop arguments. If they are not available separately, write thefunction call with the*
-operator to unpack the arguments out of a listor tuple:
>>>list(range(3,6))# normal call with separate arguments[3, 4, 5]>>>args=[3,6]>>>list(range(*args))# call with arguments unpacked from a list[3, 4, 5]
In the same fashion, dictionaries can deliver keyword arguments with the**
-operator:
>>>defparrot(voltage,state='a stiff',action='voom'):...print("-- This parrot wouldn't",action,end=' ')...print("if you put",voltage,"volts through it.",end=' ')...print("E's",state,"!")...>>>d={"voltage":"four million","state":"bleedin' demised","action":"VOOM"}>>>parrot(**d)-- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !
4.9.6.Lambda Expressions¶
Small anonymous functions can be created with thelambda
keyword.This function returns the sum of its two arguments:lambdaa,b:a+b
.Lambda functions can be used wherever function objects are required. They aresyntactically restricted to a single expression. Semantically, they are justsyntactic sugar for a normal function definition. Like nested functiondefinitions, lambda functions can reference variables from the containingscope:
>>>defmake_incrementor(n):...returnlambdax:x+n...>>>f=make_incrementor(42)>>>f(0)42>>>f(1)43
The above example uses a lambda expression to return a function. Another useis to pass a small function as an argument. For instance,list.sort()
takes a sorting key functionkey which can be a lambda function:
>>>pairs=[(1,'one'),(2,'two'),(3,'three'),(4,'four')]>>>pairs.sort(key=lambdapair:pair[1])>>>pairs[(4, 'four'), (1, 'one'), (3, 'three'), (2, 'two')]
4.9.7.Documentation Strings¶
Here are some conventions about the content and formatting of documentationstrings.
The first line should always be a short, concise summary of the object’spurpose. For brevity, it should not explicitly state the object’s name or type,since these are available by other means (except if the name happens to be averb describing a function’s operation). This line should begin with a capitalletter and end with a period.
If there are more lines in the documentation string, the second line should beblank, visually separating the summary from the rest of the description. Thefollowing lines should be one or more paragraphs describing the object’s callingconventions, its side effects, etc.
The Python parser does not strip indentation from multi-line string literals inPython, so tools that process documentation have to strip indentation ifdesired. This is done using the following convention. The first non-blank lineafter the first line of the string determines the amount of indentation forthe entire documentation string. (We can’t use the first line since it isgenerally adjacent to the string’s opening quotes so its indentation is notapparent in the string literal.) Whitespace “equivalent” to this indentation isthen stripped from the start of all lines of the string. Lines that areindented less should not occur, but if they occur all their leading whitespaceshould be stripped. Equivalence of whitespace should be tested after expansionof tabs (to 8 spaces, normally).
Here is an example of a multi-line docstring:
>>>defmy_function():..."""Do nothing, but document it....... No, really, it doesn't do anything.... """...pass...>>>print(my_function.__doc__)Do nothing, but document it.No, really, it doesn't do anything.
4.9.8.Function Annotations¶
Function annotations are completely optional metadatainformation about the types used by user-defined functions (seePEP 3107 andPEP 484 for more information).
Annotations are stored in the__annotations__
attribute of the function as a dictionary and have no effect on any other part of thefunction. Parameter annotations are defined by a colon after the parameter name, followedby an expression evaluating to the value of the annotation. Return annotations aredefined by a literal->
, followed by an expression, between the parameterlist and the colon denoting the end of thedef
statement. Thefollowing example has a required argument, an optional argument, and the returnvalue annotated:
>>>deff(ham:str,eggs:str='eggs')->str:...print("Annotations:",f.__annotations__)...print("Arguments:",ham,eggs)...returnham+' and '+eggs...>>>f('spam')Annotations: {'ham': <class 'str'>, 'return': <class 'str'>, 'eggs': <class 'str'>}Arguments: spam eggs'spam and eggs'
4.10.Intermezzo: Coding Style¶
Now that you are about to write longer, more complex pieces of Python, it is agood time to talk aboutcoding style. Most languages can be written (or moreconcise,formatted) in different styles; some are more readable than others.Making it easy for others to read your code is always a good idea, and adoptinga nice coding style helps tremendously for that.
For Python,PEP 8 has emerged as the style guide that most projects adhere to;it promotes a very readable and eye-pleasing coding style. Every Pythondeveloper should read it at some point; here are the most important pointsextracted for you:
Use 4-space indentation, and no tabs.
4 spaces are a good compromise between small indentation (allows greaternesting depth) and large indentation (easier to read). Tabs introduceconfusion, and are best left out.
Wrap lines so that they don’t exceed 79 characters.
This helps users with small displays and makes it possible to have severalcode files side-by-side on larger displays.
Use blank lines to separate functions and classes, and larger blocks ofcode inside functions.
When possible, put comments on a line of their own.
Use docstrings.
Use spaces around operators and after commas, but not directly insidebracketing constructs:
a=f(1,2)+g(3,4)
.Name your classes and functions consistently; the convention is to use
UpperCamelCase
for classes andlowercase_with_underscores
for functionsand methods. Always useself
as the name for the first method argument(seeA First Look at Classes for more on classes and methods).Don’t use fancy encodings if your code is meant to be used in internationalenvironments. Python’s default, UTF-8, or even plain ASCII work best in anycase.
Likewise, don’t use non-ASCII characters in identifiers if there is only theslightest chance people speaking a different language will read or maintainthe code.
Footnotes
[1]Actually,call by object reference would be a better description,since if a mutable object is passed, the caller will see any changes thecallee makes to it (items inserted into a list).