# 5. 表达式¶

```name ::=  `othername`
```

## 5.1. 算术转换¶

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:

• 如果任一参数为复数，另一参数会被转换为复数；

• 否则，如果任一参数为浮点数，另一参数会被转换为浮点数；

• otherwise, if either argument is a long integer, the other is converted to long integer;

• otherwise, both must be plain integers and no conversion is necessary.

Some additional rules apply for certain operators (e.g., a string left argument to the ‘%’ operator). Extensions can define their own coercions.

## 5.2. 原子¶

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`
```

### 5.2.2. 字面值¶

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 字面值 for details.

### 5.2.3. 带圆括号的形式¶

```parenth_form ::=  "(" [`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).

### 5.2.4. 列表显示¶

```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.

### 5.2.5. Displays for sets and dictionaries¶

For constructing a set or a dictionary Python provides special syntax called “displays”, each of them in two flavors:

• 第一种是显式地列出容器内容

• 第二种是通过一组循环和筛选指令计算出来，称为 推导式

```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.

### 5.2.6. 生成器表达式¶

```generator_expression ::=  "(" `expression` `comp_for` ")"
```

Variables used in the generator expression are evaluated lazily when the `__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))```.

The parentheses can be omitted on calls with only one argument. See section 调用 for the detail.

### 5.2.7. 字典显示¶

```dict_display       ::=  "{" [`key_datum_list` | `dict_comprehension`] "}"
key_datum_list     ::=  `key_datum` ("," `key_datum`)* [","]
key_datum          ::=  `expression` ":" `expression`
dict_comprehension ::=  `expression` ":" `expression` `comp_for`
```

### 5.2.8. 集合显示¶

```set_display ::=  "{" (`expression_list` | `comprehension`) "}"
```

### 5.2.9. String conversions¶

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).

The built-in function `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.

### 5.2.10. yield 表达式¶

```yield_atom       ::=  "(" `yield_expression` ")"
yield_expression ::=  "yield" [`expression_list`]
```

2.5 新版功能.

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.

#### 5.2.10.1. 生成器-迭代器的方法¶

`generator.``next`()

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` exception is raised.

`generator.``send`(value)

Resumes the execution and “sends” a value into the generator function. The `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.

`generator.``throw`(type[, value[, traceback]])

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.

`generator.``close`()

Raises a `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.

```>>> 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.
```

PEP 342 - 通过增强型生成器实现协程

## 5.3. 原型¶

```primary ::=  `atom` | `attributeref` | `subscription` | `slicing` | `call`
```

### 5.3.1. 属性引用¶

```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.

### 5.3.2. 抽取¶

```subscription ::=  `primary` "[" `expression_list` "]"
```

The primary must evaluate to an object of a sequence or mapping type.

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).

### 5.3.3. 切片¶

```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 such that `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 标准类型层级结构) 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.

### 5.3.4. 调用¶

```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 parameter lists.

If the syntax `*expression` appears in the function call, `expression` 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, and `expression` 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 <module>
TypeError: f() got multiple values for keyword argument 'a'
>>> f(1, *(2,))
1 2
```

If the syntax `**expression` appears in the function call, `expression` must evaluate to a mapping, the contents of which are treated as additional keyword arguments. In the case of a keyword appearing in both `expression` and as an explicit keyword argument, a `TypeError` exception is raised.

Formal parameters using the syntax `*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.

## 5.4. 幂运算符¶

```power ::=  `primary` ["**" `u_expr`]
```

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` returns `100`, but `10**-2` returns `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).

Raising `0.0` to a negative power results in a `ZeroDivisionError`. Raising a negative number to a fractional power results in a `ValueError`.

## 5.5. 一元算术和位运算¶

```u_expr ::=  `power` | "-" `u_expr` | "+" `u_expr` | "~" `u_expr`
```

The unary `~` (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.

## 5.6. 二元算术运算符¶

```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 `/` (division) and `//` (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` exception.

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` is replaced by `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 String Formatting Operations.

2.3 版后已移除: 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.

## 5.7. 移位运算¶

```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.

A right shift by 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` exception.

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` exception is raised.

## 5.8. 二元位运算¶

```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.

## 5.9. 比较运算¶

```comparison    ::=  `or_expr` ( `comp_operator` `or_expr` )*
comp_operator ::=  "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="
| "is" ["not"] | ["not"] "in"
```

The forms `<>` and `!=` are equivalent; for consistency with C, `!=` is preferred; where `!=` is mentioned below `<>` is also accepted. The `<>` spelling is considered obsolescent.

### 5.9.1. 值比较¶

Types can customize their comparison behavior by implementing a `__cmp__()` method or rich comparison methods like `__lt__()`, described in 基本定制.

The default order comparison (`<`, `>`, `<=`, and `>=`) gives a consistent but arbitrary order.

(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.)

• 内置数值类型 (Numeric Types — int, float, long, complex) 以及标准库类型 `fractions.Fraction``decimal.Decimal` 可进行类型内部和跨类型的比较，例外限制是复数不支持次序比较。 在类型相关的限制以内，它们会按数学（算法）规则正确进行比较且不会有精度损失。

• Strings (instances of `str` or `unicode`) compare lexicographically using the numeric equivalents (the result of the built-in function `ord()`) of their characters. 4 When comparing an 8-bit string and a Unicode string, the 8-bit string is converted to Unicode. If the conversion fails, the strings are considered unequal.

• Instances of `tuple` or `list` can be compared only within each of their types. Equality comparison across these types results in unequality, and ordering comparison across these types gives an arbitrary order.

These sequences compare lexicographically using comparison of corresponding elements, whereby reflexivity of the elements is enforced.

In enforcing reflexivity of elements, the comparison of collections assumes that for a collection element `x`, `x == x` is always true. Based on that assumption, element identity is compared first, and element comparison is performed only for distinct elements. This approach yields the same result as a strict element comparison would, if the compared elements are reflexive. For non-reflexive elements, the result is different than for strict element comparison.

内置多项集间的字典序比较规则如下:

• 两个多项集若要相等，它们必须为相同类型、相同长度，并且每对相应的元素都必须相等（例如，`[1,2] == (1,2)` 为假值，因为类型不同）。

• Collections are ordered the same as their first unequal elements (for example, `cmp([1,2,x], [1,2,y])` returns the same as `cmp(x,y)`). If a corresponding element does not exist, the shorter collection is ordered first (for example, `[1,2] < [1,2,3]` is true).

• 两个映射 (`dict` 的实例) 若要相等，必须当且仅当它们具有相同的 (键, 值) 对。 键和值的一致性比较强制规定自反射性。

Outcomes other than equality are resolved consistently, but are not otherwise defined. 5

• 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.

• 相等比较应该是自反射的。 换句话说，相同的对象比较时应该相等:

`x is y` 意味着 `x == y`

• 比较应该是对称的。 换句话说，下列表达式应该有相同的结果:

`x == y``y == x`

`x != y``y != x`

`x < y``y > x`

`x <= y``y >= x`

• 比较应该是可传递的。 下列（简要的）例子显示了这一点:

`x > y and y > z` 意味着 `x > z`

`x < y and y <= z` 意味着 `x < z`

• 反向比较应该导致布尔值取反。 换句话说，下列表达式应该有相同的结果:

`x == y``not x != y`

`x < y``not x >= y` (对于完全排序)

`x > y``not x <= y` (对于完全排序)

最后两个表达式适用于完全排序的多项集（即序列而非集合或映射）。 另请参阅 `total_ordering()` 装饰器。

• `hash()` 的结果应该与是否相等一致。 相等的对象应该或者具有相同的哈希值，或者标记为不可哈希。

Python does not enforce these consistency rules.

### 5.9.2. 成员检测运算¶

The operators `in` and `not in` test for membership. ```x in s``` evaluates to `True` if x is a member of s, and `False` otherwise. `x not in s` returns the negation of `x in s`. All built-in sequences and set types support this as well as dictionary, for which `in` tests whether the dictionary has a given key. For container types such as list, tuple, set, frozenset, dict, or collections.deque, the expression `x in y` is equivalent to `any(x is e or x == e for e in y)`.

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 such that `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).

The operator `not in` is defined to have the inverse true value of `in`.

### 5.9.3. 标识号比较¶

The operators `is` and `is not` test for object identity: ```x is y``` is true if and only if x and y are the same object. `x is not y` yields the inverse truth value. 6

## 5.10. 布尔运算¶

```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.)

(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'``` yields `False`, not `''`.)

## 5.11. Conditional Expressions¶

2.5 新版功能.

```conditional_expression ::=  `or_test` ["if" `or_test` "else" `expression`]
expression             ::=  `conditional_expression` | `lambda_expr`
```

The expression `x if C else y` first evaluates the condition, C (not x); if C is true, x is evaluated and its value is returned; otherwise, y is evaluated and its value is returned.

## 5.12. lambda 表达式¶

```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 parameters: expression` yields a function object. The unnamed object behaves like a function object defined with

```def <lambda>(parameters):
return expression
```

See section 函数定义 for the syntax of parameter lists. Note that functions created with lambda expressions cannot contain statements.

## 5.13. 表达式列表¶

```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.

## 5.14. 求值顺序¶

Python evaluates expressions from left to right. Notice that while evaluating an assignment, the right-hand side is evaluated before the left-hand side.

```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
```

## 5.15. 运算符优先级¶

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 比较运算 — and exponentiation, which groups from right to left).

`lambda`

lambda 表达式

`or`

`and`

`not` `x`

`in`, `not in`, `is`, `is not`, `<`, `<=`, `>`, `>=`, `<>`, `!=`, `==`

`|`

`^`

`&`

`<<`, `>>`

`+`, `-`

`*`, `/`, `//`, `%`

Multiplication, division, remainder 7

`+x`, `-x`, `~x`

`**`

`x[index]`, `x[index:index]`, `x(arguments...)`, `x.attribute`

`(expressions...)`, `[expressions...]`, `{key: value...}`, ``expressions...``

Binding or tuple display, list display, dictionary display, string conversion

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

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) * y + x % y` be very close to `x`.

4

Unicode 标准明确区分 码位 (例如 U+0041) 和 抽象字符 (例如 “大写拉丁字母 A”)。 虽然 Unicode 中的大多数抽象字符都只用一个码位来代表，但也存在一些抽象字符可使用由多个码位组成的序列来表示。 例如，抽象字符 “带有下加符的大写拉丁字母 C” 可以用 U+00C7 码位上的单个 预设字符 来表示，也可以用一个 U+0043 码位上的 基础字符 (大写拉丁字母 C) 加上一个 U+0327 码位上的 组合字符 (组合下加符) 组成的序列来表示。

The comparison operators on unicode strings compare at the level of Unicode code points. This may be counter-intuitive to humans. For example, `u"\u00C7" == u"\u0043\u0327"` is `False`, even though both strings represent the same abstract character “LATIN CAPITAL LETTER C WITH CEDILLA”.

5

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 `{}`.

6

7

`%` 运算符也被用于字符串格式化；在此场合下会使用同样的优先级。

8