本章阐述 Python 表达式元素的含义。
句法注意事项: 在此及之后章节,扩展 BNF 表示法将用于描述句法,而不是词法分析。当 (一种替代) 句法规则拥有形式
name ::= othername
and no semantics are given, the semantics of this form of name are the same as for othername .
When a description of an arithmetic operator below uses the phrase “the numeric arguments are converted to a common type,” the arguments are coerced using the coercion rules listed at Coercion rules . If both arguments are standard numeric types, the following coercions are applied:
Some additional rules apply for certain operators (e.g., a string left argument to the ‘%’ operator). Extensions can define their own coercions.
Atoms are the most basic elements of expressions. The simplest atoms are identifiers or literals. Forms enclosed in reverse quotes or in parentheses, brackets or braces are also categorized syntactically as atoms. The syntax for atoms is:
atom ::= identifier | literal | enclosure enclosure ::= parenth_form | list_display | generator_expression | dict_display | set_display | string_conversion | yield_atom
作为原子出现的标识符是名称。见章节 标识符和关键词 对于词法定义和章节 命名和绑定 对于命名和绑定文档编制。
When the name is bound to an object, evaluation of the atom yields that object. When a name is not bound, an attempt to evaluate it raises a NameError 异常。
私有名称重整: When an identifier that textually occurs in a class definition begins with two or more underscore characters and does not end in two or more underscores, it is considered a 私有名称 of that class. Private names are transformed to a longer form before code is generated for them. The transformation inserts the class name, with leading underscores removed and a single underscore inserted, in front of the name. For example, the identifier __spam occurring in a class named Ham will be transformed to _Ham__spam . This transformation is independent of the syntactical context in which the identifier is used. If the transformed name is extremely long (longer than 255 characters), implementation defined truncation may happen. If the class name consists only of underscores, no transformation is done.
Python supports string literals and various numeric literals:
literal ::= stringliteral | integer | longinteger | floatnumber | imagnumber
Evaluation of a literal yields an object of the given type (string, integer, long integer, floating point number, complex number) with the given value. The value may be approximated in the case of floating point and imaginary (complex) literals. See section 文字 了解细节。
All literals correspond to immutable data types, and hence the object’s identity is less important than its value. Multiple evaluations of literals with the same value (either the same occurrence in the program text or a different occurrence) may obtain the same object or a different object with the same value.
A parenthesized form is an optional expression list enclosed in parentheses:
parenth_form ::= "(" [expression_list] ")"
A parenthesized expression list yields whatever that expression list yields: if the list contains at least one comma, it yields a tuple; otherwise, it yields the single expression that makes up the expression list.
An empty pair of parentheses yields an empty tuple object. Since tuples are immutable, the rules for literals apply (i.e., two occurrences of the empty tuple may or may not yield the same object).
Note that tuples are not formed by the parentheses, but rather by use of the comma operator. The exception is the empty tuple, for which parentheses are required — allowing unparenthesized “nothing” in expressions would cause ambiguities and allow common typos to pass uncaught.
A list display is a possibly empty series of expressions enclosed in square brackets:
list_display ::= "[" [expression_list | list_comprehension] "]" list_comprehension ::= expression list_for list_for ::= "for" target_list "in" old_expression_list [list_iter] old_expression_list ::= old_expression [("," old_expression)+ [","]] old_expression ::= or_test | old_lambda_expr list_iter ::= list_for | list_if list_if ::= "if" old_expression [list_iter]
A list display yields a new list object. Its contents are specified by providing either a list of expressions or a list comprehension. When a comma-separated list of expressions is supplied, its elements are evaluated from left to right and placed into the list object in that order. When a list comprehension is supplied, it consists of a single expression followed by at least one for clause and zero or more for or if clauses. In this case, the elements of the new list are those that would be produced by considering each of the for or if clauses a block, nesting from left to right, and evaluating the expression to produce a list element each time the innermost block is reached [1] .
For constructing a set or a dictionary Python provides special syntax called “displays”, each of them in two flavors:
Common syntax elements for comprehensions are:
comprehension ::= expression comp_for comp_for ::= "for" target_list "in" or_test [comp_iter] comp_iter ::= comp_for | comp_if comp_if ::= "if" expression_nocond [comp_iter]
The comprehension consists of a single expression followed by at least one for clause and zero or more for or if clauses. In this case, the elements of the new container are those that would be produced by considering each of the for or if clauses a block, nesting from left to right, and evaluating the expression to produce an element each time the innermost block is reached.
Note that the comprehension is executed in a separate scope, so names assigned to in the target list don’t “leak” in the enclosing scope.
生成器表达式是在括号内的紧凑生成器表示法:
generator_expression ::= "(" expression comp_for ")"
生成器表达式产生新的生成器对象。它的句法如同推导,除它是封闭在括号内而不是方括号或花括号内外。
会惰性评估生成器表达式中使用的变量,当 __next__() method is called for generator object (in the same fashion as normal generators). However, the leftmost for clause is immediately evaluated, so that an error produced by it can be seen before any other possible error in the code that handles the generator expression. Subsequent for clauses cannot be evaluated immediately since they may depend on the previous for loop. For example: (x*y for x in range(10) for y in bar(x)) .
只采用一个自变量的调用可以省略括号。见章节 调用 for the detail.
字典显示是封闭在花括号内的一系列可能为空的键/数据对:
dict_display ::= "{" [key_datum_list | dict_comprehension] "}"
key_datum_list ::= key_datum ("," key_datum)* [","]
key_datum ::= expression ":" expression
dict_comprehension ::= expression ":" expression comp_for
字典显示产生新的字典对象。
If a comma-separated sequence of key/datum pairs is given, they are evaluated from left to right to define the entries of the dictionary: each key object is used as a key into the dictionary to store the corresponding datum. This means that you can specify the same key multiple times in the key/datum list, and the final dictionary’s value for that key will be the last one given.
A dict comprehension, in contrast to list and set comprehensions, needs two expressions separated with a colon followed by the usual “for” and “if” clauses. When the comprehension is run, the resulting key and value elements are inserted in the new dictionary in the order they are produced.
Restrictions on the types of the key values are listed earlier in section 标准类型层次结构 . (To summarize, the key type should be hashable , which excludes all mutable objects.) Clashes between duplicate keys are not detected; the last datum (textually rightmost in the display) stored for a given key value prevails.
A set display is denoted by curly braces and distinguishable from dictionary displays by the lack of colons separating keys and values:
set_display ::= "{" (expression_list | comprehension) "}"
A set display yields a new mutable set object, the contents being specified by either a sequence of expressions or a comprehension. When a comma-separated list of expressions is supplied, its elements are evaluated from left to right and added to the set object. When a comprehension is supplied, the set is constructed from the elements resulting from the comprehension.
An empty set cannot be constructed with {} ; this literal constructs an empty dictionary.
A string conversion is an expression list enclosed in reverse (a.k.a. backward) quotes:
string_conversion ::= "`" expression_list "`"
A string conversion evaluates the contained expression list and converts the resulting object into a string according to rules specific to its type.
If the object is a string, a number, None , or a tuple, list or dictionary containing only objects whose type is one of these, the resulting string is a valid Python expression which can be passed to the built-in function eval() to yield an expression with the same value (or an approximation, if floating point numbers are involved).
(In particular, converting a string adds quotes around it and converts “funny” characters to escape sequences that are safe to print.)
Recursive objects (for example, lists or dictionaries that contain a reference to themselves, directly or indirectly) use ... to indicate a recursive reference, and the result cannot be passed to eval() to get an equal value ( SyntaxError will be raised instead).
内置函数 repr() performs exactly the same conversion in its argument as enclosing it in parentheses and reverse quotes does. The built-in function str() performs a similar but more user-friendly conversion.
yield_atom ::= "(" yield_expression ")"
yield_expression ::= "yield" [expression_list]
2.5 版新增。
The yield expression is only used when defining a generator function, and can only be used in the body of a function definition. Using a yield expression in a function definition is sufficient to cause that definition to create a generator function instead of a normal function.
When a generator function is called, it returns an iterator known as a generator. That generator then controls the execution of a generator function. The execution starts when one of the generator’s methods is called. At that time, the execution proceeds to the first yield expression, where it is suspended again, returning the value of expression_list to generator’s caller. By suspended we mean that all local state is retained, including the current bindings of local variables, the instruction pointer, and the internal evaluation stack. When the execution is resumed by calling one of the generator’s methods, the function can proceed exactly as if the yield expression was just another external call. The value of the yield expression after resuming depends on the method which resumed the execution.
All of this makes generator functions quite similar to coroutines; they yield multiple times, they have more than one entry point and their execution can be suspended. The only difference is that a generator function cannot control where should the execution continue after it yields; the control is always transferred to the generator’s caller.
This subsection describes the methods of a generator iterator. They can be used to control the execution of a generator function.
Note that calling any of the generator methods below when the generator is already executing raises a ValueError 异常。
Starts the execution of a generator function or resumes it at the last executed yield expression. When a generator function is resumed with a next() method, the current yield expression always evaluates to None . The execution then continues to the next yield expression, where the generator is suspended again, and the value of the expression_list is returned to next() ‘s caller. If the generator exits without yielding another value, a StopIteration 异常被引发。
再继续执行并把值 send (发送) 到生成器函数。 value argument becomes the result of the current yield expression. The send() method returns the next value yielded by the generator, or raises StopIteration if the generator exits without yielding another value. When send() is called to start the generator, it must be called with None as the argument, because there is no yield expression that could receive the value.
Raises an exception of type type at the point where generator was paused, and returns the next value yielded by the generator function. If the generator exits without yielding another value, a StopIteration exception is raised. If the generator function does not catch the passed-in exception, or raises a different exception, then that exception propagates to the caller.
引发 GeneratorExit at the point where the generator function was paused. If the generator function then raises StopIteration (by exiting normally, or due to already being closed) or GeneratorExit (by not catching the exception), close returns to its caller. If the generator yields a value, a RuntimeError is raised. If the generator raises any other exception, it is propagated to the caller. close() does nothing if the generator has already exited due to an exception or normal exit.
Here is a simple example that demonstrates the behavior of generators and generator functions:
>>> def echo(value=None): ... print "Execution starts when 'next()' is called for the first time." ... try: ... while True: ... try: ... value = (yield value) ... except Exception, e: ... value = e ... finally: ... print "Don't forget to clean up when 'close()' is called." ... >>> generator = echo(1) >>> print generator.next() Execution starts when 'next()' is called for the first time. 1 >>> print generator.next() None >>> print generator.send(2) 2 >>> generator.throw(TypeError, "spam") TypeError('spam',) >>> generator.close() Don't forget to clean up when 'close()' is called.
另请参阅
Primaries represent the most tightly bound operations of the language. Their syntax is:
primary ::= atom | attributeref | subscription | slicing | call
An attribute reference is a primary followed by a period and a name:
attributeref ::= primary "." identifier
The primary must evaluate to an object of a type that supports attribute references, e.g., a module, list, or an instance. This object is then asked to produce the attribute whose name is the identifier. If this attribute is not available, the exception AttributeError is raised. Otherwise, the type and value of the object produced is determined by the object. Multiple evaluations of the same attribute reference may yield different objects.
A subscription selects an item of a sequence (string, tuple or list) or mapping (dictionary) object:
subscription ::= primary "[" expression_list "]"
The primary must evaluate to an object of a sequence or mapping type.
If the primary is a mapping, the expression list must evaluate to an object whose value is one of the keys of the mapping, and the subscription selects the value in the mapping that corresponds to that key. (The expression list is a tuple except if it has exactly one item.)
If the primary is a sequence, the expression (list) must evaluate to a plain integer. If this value is negative, the length of the sequence is added to it (so that, e.g., x[-1] selects the last item of x .) The resulting value must be a nonnegative integer less than the number of items in the sequence, and the subscription selects the item whose index is that value (counting from zero).
A string’s items are characters. A character is not a separate data type but a string of exactly one character.
A slicing selects a range of items in a sequence object (e.g., a string, tuple or list). Slicings may be used as expressions or as targets in assignment or del statements. The syntax for a slicing:
slicing ::= simple_slicing | extended_slicing simple_slicing ::= primary "[" short_slice "]" extended_slicing ::= primary "[" slice_list "]" slice_list ::= slice_item ("," slice_item)* [","] slice_item ::= expression | proper_slice | ellipsis proper_slice ::= short_slice | long_slice short_slice ::= [lower_bound] ":" [upper_bound] long_slice ::= short_slice ":" [stride] lower_bound ::= expression upper_bound ::= expression stride ::= expression ellipsis ::= "..."
There is ambiguity in the formal syntax here: anything that looks like an expression list also looks like a slice list, so any subscription can be interpreted as a slicing. Rather than further complicating the syntax, this is disambiguated by defining that in this case the interpretation as a subscription takes priority over the interpretation as a slicing (this is the case if the slice list contains no proper slice nor ellipses). Similarly, when the slice list has exactly one short slice and no trailing comma, the interpretation as a simple slicing takes priority over that as an extended slicing.
The semantics for a simple slicing are as follows. The primary must evaluate to a sequence object. The lower and upper bound expressions, if present, must evaluate to plain integers; defaults are zero and the sys.maxint , respectively. If either bound is negative, the sequence’s length is added to it. The slicing now selects all items with index k 这样 i <= k < j where i and j are the specified lower and upper bounds. This may be an empty sequence. It is not an error if i or j lie outside the range of valid indexes (such items don’t exist so they aren’t selected).
The semantics for an extended slicing are as follows. The primary must evaluate to a mapping object, and it is indexed with a key that is constructed from the slice list, as follows. If the slice list contains at least one comma, the key is a tuple containing the conversion of the slice items; otherwise, the conversion of the lone slice item is the key. The conversion of a slice item that is an expression is that expression. The conversion of an ellipsis slice item is the built-in Ellipsis object. The conversion of a proper slice is a slice object (see section 标准类型层次结构 ) whose start , stop and step attributes are the values of the expressions given as lower bound, upper bound and stride, respectively, substituting None for missing expressions.
调用调用可调用对象 (如 function ) 采用可能空的一系列 arguments :
call ::= primary "(" [argument_list [","] | expression genexpr_for] ")" argument_list ::= positional_arguments ["," keyword_arguments] ["," "*" expression] ["," keyword_arguments] ["," "**" expression] | keyword_arguments ["," "*" expression] ["," "**" expression] | "*" expression ["," keyword_arguments] ["," "**" expression] | "**" expression positional_arguments ::= expression ("," expression)* keyword_arguments ::= keyword_item ("," keyword_item)* keyword_item ::= identifier "=" expression
A trailing comma may be present after the positional and keyword arguments but does not affect the semantics.
The primary must evaluate to a callable object (user-defined functions, built-in functions, methods of built-in objects, class objects, methods of class instances, and certain class instances themselves are callable; extensions may define additional callable object types). All argument expressions are evaluated before the call is attempted. Please refer to section 函数定义 for the syntax of formal 参数 lists.
If keyword arguments are present, they are first converted to positional arguments, as follows. First, a list of unfilled slots is created for the formal parameters. If there are N positional arguments, they are placed in the first N slots. Next, for each keyword argument, the identifier is used to determine the corresponding slot (if the identifier is the same as the first formal parameter name, the first slot is used, and so on). If the slot is already filled, a TypeError exception is raised. Otherwise, the value of the argument is placed in the slot, filling it (even if the expression is None , it fills the slot). When all arguments have been processed, the slots that are still unfilled are filled with the corresponding default value from the function definition. (Default values are calculated, once, when the function is defined; thus, a mutable object such as a list or dictionary used as default value will be shared by all calls that don’t specify an argument value for the corresponding slot; this should usually be avoided.) If there are any unfilled slots for which no default value is specified, a TypeError exception is raised. Otherwise, the list of filled slots is used as the argument list for the call.
CPython 实现细节: An implementation may provide built-in functions whose positional parameters do not have names, even if they are ‘named’ for the purpose of documentation, and which therefore cannot be supplied by keyword. In CPython, this is the case for functions implemented in C that use PyArg_ParseTuple() to parse their arguments.
If there are more positional arguments than there are formal parameter slots, a TypeError exception is raised, unless a formal parameter using the syntax *identifier is present; in this case, that formal parameter receives a tuple containing the excess positional arguments (or an empty tuple if there were no excess positional arguments).
If any keyword argument does not correspond to a formal parameter name, a TypeError exception is raised, unless a formal parameter using the syntax **identifier is present; in this case, that formal parameter receives a dictionary containing the excess keyword arguments (using the keywords as keys and the argument values as corresponding values), or a (new) empty dictionary if there were no excess keyword arguments.
若句法 *expression 出现在函数调用中, 表达式 must evaluate to an iterable. Elements from this iterable are treated as if they were additional positional arguments; if there are positional arguments x1 , ..., xN ,和 表达式 evaluates to a sequence y1 , ..., yM , this is equivalent to a call with M+N positional arguments x1 , ..., xN , y1 , ..., yM .
A consequence of this is that although the *expression syntax may appear after some keyword arguments, it is processed before the keyword arguments (and the **expression argument, if any – see below). So:
>>> def f(a, b): ... print a, b ... >>> f(b=1, *(2,)) 2 1 >>> f(a=1, *(2,)) Traceback (most recent call last): File "<stdin>", line 1, in ? TypeError: f() got multiple values for keyword argument 'a' >>> f(1, *(2,)) 1 2 Traceback (most recent call last): File "<stdin>", line 1, in ? TypeError: f() got multiple values for keyword argument 'a'
It is unusual for both keyword arguments and the *expression syntax to be used in the same call, so in practice this confusion does not arise.
若句法 **expression 出现在函数调用中, 表达式 must evaluate to a mapping, the contents of which are treated as additional keyword arguments. In the case of a keyword appearing in both 表达式 and as an explicit keyword argument, a TypeError 异常被引发。
形式参数使用句法 *identifier or **identifier cannot be used as positional argument slots or as keyword argument names. Formal parameters using the syntax (sublist) cannot be used as keyword argument names; the outermost sublist corresponds to a single unnamed argument slot, and the argument value is assigned to the sublist using the usual tuple assignment rules after all other parameter processing is done.
A call always returns some value, possibly None , unless it raises an exception. How this value is computed depends on the type of the callable object.
若它是 —
The code block for the function is executed, passing it the argument list. The first thing the code block will do is bind the formal parameters to the arguments; this is described in section 函数定义 . When the code block executes a return statement, this specifies the return value of the function call.
结果取决于解释器;见 内置函数 了解内置函数和方法的描述。
返回该类的新实例。
The corresponding user-defined function is called, with an argument list that is one longer than the argument list of the call: the instance becomes the first argument.
类必须定义 __call__() 方法;效果与调用该方法的效果相同。
The power operator binds more tightly than unary operators on its left; it binds less tightly than unary operators on its right. The syntax is:
power ::= primary ["**" u_expr]
Thus, in an unparenthesized sequence of power and unary operators, the operators are evaluated from right to left (this does not constrain the evaluation order for the operands): -1**2 产生 -1 .
The power operator has the same semantics as the built-in pow() function, when called with two arguments: it yields its left argument raised to the power of its right argument. The numeric arguments are first converted to a common type. The result type is that of the arguments after coercion.
With mixed operand types, the coercion rules for binary arithmetic operators apply. For int and long int operands, the result has the same type as the operands (after coercion) unless the second argument is negative; in that case, all arguments are converted to float and a float result is delivered. For example, 10**2 返回 100 ,但 10**-2 返回 0.01 . (This last feature was added in Python 2.2. In Python 2.1 and before, if both arguments were of integer types and the second argument was negative, an exception was raised).
引发 0.0 to a negative power results in a ZeroDivisionError . Raising a negative number to a fractional power results in a ValueError .
All unary arithmetic and bitwise operations have the same priority:
u_expr ::= power | "-" u_expr | "+" u_expr | "~" u_expr
一元 - (minus) operator yields the negation of its numeric argument.
一元 + (plus) operator yields its numeric argument unchanged.
一元 ~ (invert) operator yields the bitwise inversion of its plain or long integer argument. The bitwise inversion of x is defined as -(x+1) . It only applies to integral numbers.
In all three cases, if the argument does not have the proper type, a TypeError 异常被引发。
The binary arithmetic operations have the conventional priority levels. Note that some of these operations also apply to certain non-numeric types. Apart from the power operator, there are only two levels, one for multiplicative operators and one for additive operators:
m_expr ::= u_expr | m_expr "*" u_expr | m_expr "//" u_expr | m_expr "/" u_expr | m_expr "%" u_expr a_expr ::= m_expr | a_expr "+" m_expr | a_expr "-" m_expr
The * (multiplication) operator yields the product of its arguments. The arguments must either both be numbers, or one argument must be an integer (plain or long) and the other must be a sequence. In the former case, the numbers are converted to a common type and then multiplied together. In the latter case, sequence repetition is performed; a negative repetition factor yields an empty sequence.
The / (除法) 和 // (floor division) operators yield the quotient of their arguments. The numeric arguments are first converted to a common type. Plain or long integer division yields an integer of the same type; the result is that of mathematical division with the ‘floor’ function applied to the result. Division by zero raises the ZeroDivisionError 异常。
The % (modulo) operator yields the remainder from the division of the first argument by the second. The numeric arguments are first converted to a common type. A zero right argument raises the ZeroDivisionError exception. The arguments may be floating point numbers, e.g., 3.14%0.7 等于 0.34 (since 3.14 等于 4*0.7 + 0.34 .) The modulo operator always yields a result with the same sign as its second operand (or zero); the absolute value of the result is strictly smaller than the absolute value of the second operand [2] .
The integer division and modulo operators are connected by the following identity: x == (x/y)*y + (x%y) . Integer division and modulo are also connected with the built-in function divmod() : divmod(x, y) == (x/y, x%y) . These identities don’t hold for floating point numbers; there similar identities hold approximately where x/y 被替换通过 floor(x/y) or floor(x/y) - 1 [3] .
In addition to performing the modulo operation on numbers, the % operator is also overloaded by string and unicode objects to perform string formatting (also known as interpolation). The syntax for string formatting is described in the Python Library Reference, section 字符串格式化操作 .
从 2.3 版起弃用: The floor division operator, the modulo operator, and the divmod() function are no longer defined for complex numbers. Instead, convert to a floating point number using the abs() function if appropriate.
The + (addition) operator yields the sum of its arguments. The arguments must either both be numbers or both sequences of the same type. In the former case, the numbers are converted to a common type and then added together. In the latter case, the sequences are concatenated.
The - (subtraction) operator yields the difference of its arguments. The numeric arguments are first converted to a common type.
移位操作优先级,低于算术运算:
shift_expr ::= a_expr | shift_expr ( "<<" | ">>" ) a_expr
These operators accept plain or long integers as arguments. The arguments are converted to a common type. They shift the first argument to the left or right by the number of bits given by the second argument.
向右移位 n bits is defined as division by pow(2, n) . A left shift by n bits is defined as multiplication with pow(2, n) . Negative shift counts raise a ValueError 异常。
注意
In the current implementation, the right-hand operand is required to be at most sys.maxsize . If the right-hand operand is larger than sys.maxsize an OverflowError 异常被引发。
3 按位操作中的每个拥有不同优先级别:
and_expr ::= shift_expr | and_expr "&" shift_expr xor_expr ::= and_expr | xor_expr "^" and_expr or_expr ::= xor_expr | or_expr "|" xor_expr
The & operator yields the bitwise AND of its arguments, which must be plain or long integers. The arguments are converted to a common type.
The ^ operator yields the bitwise XOR (exclusive OR) of its arguments, which must be plain or long integers. The arguments are converted to a common type.
The | operator yields the bitwise (inclusive) OR of its arguments, which must be plain or long integers. The arguments are converted to a common type.
不像 C,Python 中的所有比较操作拥有相同优先级,低于任何算术、移位或按位操作。也不像 C,表达式像 a < b < c 拥有数学中的惯例解释:
comparison ::= or_expr ( comp_operator or_expr )* comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!=" | "is" ["not"] | ["not"] "in"
比较产生布尔值: True or False .
比较可以任意连锁,例如, x < y <= z 相当于 x < y and y <= z ,除了 y 只评估 1 次 (但在 2 种情况下, z 根本不评估当 x < y 被发现为 False)。
Formally, if a , b , c , ..., y , z are expressions and op1 , op2 , ..., opN are comparison operators, then a op1 b op2 c ... y opN z 相当于 a op1 b and b op2 c and ... y opN z , except that each expression is evaluated at most once.
注意, a op1 b op2 c doesn’t imply any kind of comparison between a and c , so that, e.g., x < y > z is perfectly legal (though perhaps not pretty).
The forms <> and != are equivalent; for consistency with C, != is preferred; where != is mentioned below <> is also accepted. The <> spelling is considered obsolescent.
运算符 < , > , == , >= , <= ,和 != compare the values of two objects. The objects need not have the same type. If both are numbers, they are converted to a common type. Otherwise, objects of different types always compare unequal, and are ordered consistently but arbitrarily. You can control comparison behavior of objects of non-built-in types by defining a __cmp__ method or rich comparison methods like __gt__ , described in section 特殊方法名称 .
(This unusual definition of comparison was used to simplify the definition of operations like sorting and the in and not in operators. In the future, the comparison rules for objects of different types are likely to change.)
Comparison of objects of the same type depends on the type:
Numbers are compared arithmetically.
Strings are compared lexicographically using the numeric equivalents (the result of the built-in function ord() ) of their characters. Unicode and 8-bit strings are fully interoperable in this behavior. [4]
Tuples and lists are compared lexicographically using comparison of corresponding elements. This means that to compare equal, each element must compare equal and the two sequences must be of the same type and have the same length.
If not equal, the sequences are ordered the same as their first differing elements. For example, cmp([1,2,x], [1,2,y]) returns the same as cmp(x,y) . If the corresponding element does not exist, the shorter sequence is ordered first (for example, [1,2] < [1,2,3] ).
Mappings (dictionaries) compare equal if and only if their sorted (key, value) lists compare equal. [5] Outcomes other than equality are resolved consistently, but are not otherwise defined. [6]
Most other objects of built-in types compare unequal unless they are the same object; the choice whether one object is considered smaller or larger than another one is made arbitrarily but consistently within one execution of a program.
运算符 in and not in test for collection membership. x in s evaluates to true if x is a member of the collection s , and false otherwise. x not in s 返回取反的 x in s . The collection membership test has traditionally been bound to sequences; an object is a member of a collection if the collection is a sequence and contains an element equal to that object. However, it make sense for many other object types to support membership tests without being a sequence. In particular, dictionaries (for keys) and sets support membership testing.
For the list and tuple types, x in y is true if and only if there exists an index i 这样 x == y[i] 为 True。
For the Unicode and string types, x in y 为 True 当且仅当 x is a substring of y . An equivalent test is y.find(x) != -1 . Note, x and y need not be the same type; consequently, u'ab' in 'abc' 将返回 True . Empty strings are always considered to be a substring of any other string, so "" in "abc" 将返回 True .
Changed in version 2.3: 先前, x was required to be a string of length 1 .
For user-defined classes which define the __contains__() 方法, x in y 为 True 当且仅当 y.__contains__(x) 为 True。
For user-defined classes which do not define __contains__() but do define __iter__() , x in y is true if some value z with x == z is produced while iterating over y . If an exception is raised during the iteration, it is as if in raised that exception.
Lastly, the old-style iteration protocol is tried: if a class defines __getitem__() , x in y is true if and only if there is a non-negative integer index i 这样 x == y[i] , and all lower integer indices do not raise IndexError exception. (If any other exception is raised, it is as if in raised that exception).
运算符 not in is defined to have the inverse true value of in .
运算符 is and is not test for object identity: x is y 为 True 当且仅当 x and y are the same object. x is not y yields the inverse truth value. [7]
or_test ::= and_test | or_test "or" and_test and_test ::= not_test | and_test "and" not_test not_test ::= comparison | "not" not_test
In the context of Boolean operations, and also when expressions are used by control flow statements, the following values are interpreted as false: False , None , numeric zero of all types, and empty strings and containers (including strings, tuples, lists, dictionaries, sets and frozensets). All other values are interpreted as true. (See the __nonzero__() special method for a way to change this.)
运算符 not 产生 True 若其自变量为 False, False 否则。
表达式 x and y 首先评估 x ;若 x is false, its value is returned; otherwise, y is evaluated and the resulting value is returned.
表达式 x or y 首先评估 x ;若 x is true, its value is returned; otherwise, y is evaluated and the resulting value is returned.
(Note that neither and nor or restrict the value and type they return to False and True , but rather return the last evaluated argument. This is sometimes useful, e.g., if s is a string that should be replaced by a default value if it is empty, the expression s or 'foo' yields the desired value. Because not has to invent a value anyway, it does not bother to return a value of the same type as its argument, so e.g., not 'foo' 产生 False , not '' )。
2.5 版新增。
conditional_expression ::= or_test ["if" or_test "else" expression] expression ::= conditional_expression | lambda_expr
条件表达式 (有时称为三元运算符) 在所有 Python 操作中拥有最低优先级。
表达式 x if C else y 首先评估条件, C ( not x ); if C 为 True, x is evaluated and its value is returned; otherwise, y is evaluated and its value is returned.
见 PEP 308 了解条件表达式的有关更多细节。
lambda_expr ::= "lambda" [parameter_list]: expression old_lambda_expr ::= "lambda" [parameter_list]: old_expression
Lambda expressions (sometimes called lambda forms) have the same syntactic position as expressions. They are a shorthand to create anonymous functions; the expression lambda arguments: 表达式 yields a function object. The unnamed object behaves like a function object defined with
def name(arguments): return expression
见章节 函数定义 for the syntax of parameter lists. Note that functions created with lambda expressions cannot contain statements.
expression_list ::= expression ( "," expression )* [","]
An expression list containing at least one comma yields a tuple. The length of the tuple is the number of expressions in the list. The expressions are evaluated from left to right.
The trailing comma is required only to create a single tuple (a.k.a. a singleton ); it is optional in all other cases. A single expression without a trailing comma doesn’t create a tuple, but rather yields the value of that expression. (To create an empty tuple, use an empty pair of parentheses: () )。
Python evaluates expressions from left to right. Notice that while evaluating an assignment, the right-hand side is evaluated before the left-hand side.
In the following lines, expressions will be evaluated in the arithmetic order of their suffixes:
expr1, expr2, expr3, expr4 (expr1, expr2, expr3, expr4) {expr1: expr2, expr3: expr4} expr1 + expr2 * (expr3 - expr4) expr1(expr2, expr3, *expr4, **expr5) expr3, expr4 = expr1, expr2
The following table summarizes the operator precedences in Python, from lowest precedence (least binding) to highest precedence (most binding). Operators in the same box have the same precedence. Unless the syntax is explicitly given, operators are binary. Operators in the same box group left to right (except for comparisons, including tests, which all have the same precedence and chain from left to right — see section 比较 — and exponentiation, which groups from right to left).
| 运算符 | 描述 |
|---|---|
| lambda | Lambda 表达式 |
| if – else | 条件表达式 |
| or | 布尔 OR |
| and | 布尔 AND |
| not x | 布尔 NOT |
| in , not in , is , is not , < , <= , > , >= , <> , != , == | Comparisons, including membership tests and identity tests |
| | | 按位 OR |
| ^ | 按位 XOR |
| & | 按位 AND |
| << , >> | Shifts |
| + , - | 加法和减法 |
| * , / , // , % | Multiplication, division, remainder [8] |
| +x , -x , ~x | 正、负、按位非 |
| ** | 取幂 [9] |
| x[index] , x[index:index] , x(arguments...) , x.attribute | Subscription, slicing, call, attribute reference |
| (expressions...) , [expressions...] , {key: value...} , `expressions...` | Binding or tuple display, list display, dictionary display, string conversion |
脚注
| [1] | In Python 2.3 and later releases, a list comprehension “leaks” the control variables of each for it contains into the containing scope. However, this behavior is deprecated, and relying on it will not work in Python 3. |
| [2] | While abs(x%y) < abs(y) is true mathematically, for floats it may not be true numerically due to roundoff. For example, and assuming a platform on which a Python float is an IEEE 754 double-precision number, in order that -1e-100 % 1e100 have the same sign as 1e100 , the computed result is -1e-100 + 1e100 , which is numerically exactly equal to 1e100 . The function math.fmod() returns a result whose sign matches the sign of the first argument instead, and so returns -1e-100 in this case. Which approach is more appropriate depends on the application. |
| [3] | If x is very close to an exact integer multiple of y, it’s possible for floor(x/y) to be one larger than (x-x%y)/y due to rounding. In such cases, Python returns the latter result, in order to preserve that divmod(x,y)[0] * y + x % y be very close to x . |
| [4] | While comparisons between unicode strings make sense at the byte level, they may be counter-intuitive to users. For example, the strings u"\u00C7" and u"\u0043\u0327" compare differently, even though they both represent the same unicode character (LATIN CAPITAL LETTER C WITH CEDILLA). To compare strings in a human recognizable way, compare using unicodedata.normalize() . |
| [5] | The implementation computes this efficiently, without constructing lists or sorting. |
| [6] | Earlier versions of Python used lexicographic comparison of the sorted (key, value) lists, but this was very expensive for the common case of comparing for equality. An even earlier version of Python compared dictionaries by identity only, but this caused surprises because people expected to be able to test a dictionary for emptiness by comparing it to {} . |
| [7] | Due to automatic garbage-collection, free lists, and the dynamic nature of descriptors, you may notice seemingly unusual behaviour in certain uses of the is operator, like those involving comparisons between instance methods, or constants. Check their documentation for more info. |
| [8] | The % operator is also used for string formatting; the same precedence applies. |
| [9] | 幂运算符 ** binds less tightly than an arithmetic or bitwise unary operator on its right, that is, 2**-1 is 0.5 . |