Multiple statements group as suites in python
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More Detail A group of individual statements, which make a single code block are called suites in Python. Compound or complex statements, such as if, while, def, and class require a header line and a suite. Header lines begin the statement (with the keyword) and terminate with a colon (: ) and are followed by one or more lines which make up the suite. exampleif expr1==True: stmt1 stmt2 elif expr2==True: stmt3 stmt4 else: stmt5 stmt6 while expr==True: stmt1 stmt2
Jayashree Updated on 18-Jun-2020 06:31:45
Previous Page Print Page Next Page Advertisements Compound statements contain (groups of) other statements; they affect or control the execution of those other statements in some way. In general, compound statements span multiple lines, although in simple incarnations a whole compound statement may be contained in one line. The A compound statement consists of one or more ‘clauses.’ A clause consists of a header and a ‘suite.’ The clause headers of a particular compound statement are all at the same indentation level. Each clause
header begins with a uniquely identifying keyword and ends with a colon. A suite is a group of statements controlled by a clause. A suite can be one or more semicolon-separated simple statements on the same line as the header, following the header’s colon, or it can be one or more indented statements on subsequent lines. Only the latter form of a suite can contain nested compound statements; the following is illegal, mostly because it wouldn’t be clear to which
if test1: if test2: print(x) Also note that the semicolon binds tighter than the colon in this context, so that in the following example, either all or none of the
if x < y < z: print(x); print(y); print(z) Summarizing: compound_stmt ::= Note that statements always end in a The formatting of the grammar rules in the following sections places each clause on a separate line for clarity. 8.1. The if statement¶The if_stmt ::= "if" It selects exactly one of the suites by evaluating the expressions one by one until one is found to be true (see section
Boolean operations for the definition of true and false); then that suite is executed (and no other part of the 8.2. The while statement¶The while_stmt ::= "while" This repeatedly tests the expression and, if it is true, executes the first suite; if the expression is false (which may be the first time it is tested) the suite of the A 8.3. The for statement¶The
for_stmt ::= "for" The expression list is evaluated once; it should yield an iterable object. An iterator is created for the result of the A The for-loop makes assignments to the variables in the target list. This overwrites all previous assignments to those variables including those made in the suite of the for-loop: for i in range(10): print(i) i = 5 # this will not affect the for-loop # because i will be overwritten with the next # index in the range Names in the target list are not deleted when the loop is finished, but if the sequence is empty, they will not have been assigned to at all by the loop. Hint: the built-in function
8.4. The try statement¶The try_stmt ::= The If no except clause matches the exception, the search for an exception handler continues in the surrounding code and on the invocation stack. 1 If the evaluation of an expression in the header of an except clause raises an exception, the original search for a handler is canceled and a search starts for the new exception in the surrounding code and on the call stack (it is treated as if the entire
When a matching except clause is found, the exception is assigned to the target specified after the When an exception has been assigned using was translated to except E as N: try: foo finally: del N This means the exception must be assigned to a different name to be able to refer to it after the except clause. Exceptions are cleared because with the traceback attached to them, they form a reference cycle with the stack frame, keeping all locals in that frame alive until the next garbage collection occurs. Before an except clause’s suite is executed, details about the exception are stored in the >>> print(sys.exc_info()) (None, None, None) >>> try: ... raise TypeError ... except: ... print(sys.exc_info()) ... try: ... raise ValueError ... except: ... print(sys.exc_info()) ... print(sys.exc_info()) ... ( The optional If >>> def f(): ... try: ... 1/0 ... finally: ... return 42 ... >>> f() 42 The exception information is not available to the program during execution of the
When a The return value of a function is determined by the last >>> def foo(): ... try: ... return 'try' ... finally: ... return 'finally' ... >>> foo() 'finally' Additional information on exceptions can be found in section Exceptions, and information on using the
Changed in version 3.8: Prior to Python 3.8, a 8.5. The with statement¶The
with_stmt ::= "with" ( "(" The execution of the
The following code: with EXPRESSION as TARGET: SUITE is semantically equivalent to: manager = (EXPRESSION) enter = type(manager).__enter__ exit = type(manager).__exit__ value = enter(manager) hit_except = False try: TARGET = value SUITE except: hit_except = True if not exit(manager, *sys.exc_info()): raise finally: if not hit_except: exit(manager, None, None, None) With more than one item, the context managers are processed as if multiple with A() as a, B() as b: SUITE is semantically equivalent to: with A() as a: with B() as b: SUITE You can also write multi-item context managers in multiple lines if the items are surrounded by parentheses. For example: with ( A() as a, B() as b, ): SUITE Changed in version 3.1: Support for multiple context expressions. Changed in version 3.10: Support for using grouping parentheses to break the statement in multiple lines. See also PEP 343 - The “with” statementThe specification, background, and examples for the Python 8.6. The match statement¶New in version 3.10. The match statement is used for pattern matching. Syntax: match_stmt ::= 'match' Pattern matching takes a pattern as input (following
The See also
8.6.1. Overview¶Here’s an overview of the logical flow of a match statement:
Note Users should generally never rely on a pattern being evaluated. Depending on implementation, the interpreter may cache values or use other optimizations which skip repeated evaluations. A sample match statement: >>> flag = False >>> match (100, 200): ... case (100, 300): # Mismatch: 200 != 300 ... print('Case 1') ... case (100, 200) if flag: # Successful match, but guard fails ... print('Case 2') ... case (100, y): # Matches and binds y to 200 ... print(f'Case 3, y: {y}') ... case _: # Pattern not attempted ... print('Case 4, I match anything!') ... Case 3, y: 200 In this case, 8.6.2. Guards¶guard ::= "if" A The logical flow of a
Guards are allowed to have side effects as they are expressions. Guard evaluation must proceed from the first to the last case block, one at a time, skipping case blocks whose pattern(s) don’t all succeed. (I.e., guard evaluation must happen in order.) Guard evaluation must stop once a case block is selected. 8.6.3. Irrefutable Case Blocks¶An irrefutable case block is a match-all case block. A match statement may have at most one irrefutable case block, and it must be last. A case block is considered irrefutable if it has no guard and its pattern is irrefutable. A pattern is considered irrefutable if we can prove from its syntax alone that it will always succeed. Only the following patterns are irrefutable:
8.6.4. Patterns¶Note This section uses grammar notations beyond standard EBNF:
The
top-level syntax for patterns ::= The descriptions below will include a description “in simple terms” of what a pattern does for illustration purposes (credits to Raymond Hettinger for a document that inspired most of the descriptions). Note that these descriptions are purely for illustration purposes and may not reflect the underlying implementation. Furthermore, they do not cover all valid forms. 8.6.4.1. OR Patterns¶An OR pattern is two or more patterns separated by vertical bars or_pattern ::= "|". Only the final subpattern may be irrefutable, and each subpattern must bind the same set of names to avoid ambiguity. An OR pattern matches each of its subpatterns in turn to the subject value, until one succeeds. The OR pattern is then considered successful. Otherwise, if none of the subpatterns succeed, the OR pattern fails. In simple terms, 8.6.4.2. AS Patterns¶An AS pattern matches an OR pattern on the left of the as_pattern ::= If the OR pattern fails, the AS pattern fails. Otherwise, the AS pattern binds the subject to the name on the right of the as keyword and succeeds.
In simple terms 8.6.4.3. Literal Patterns¶A literal pattern corresponds to most literals in Python. Syntax: literal_pattern ::= The rule The forms In simple terms, 8.6.4.4. Capture Patterns¶A capture pattern binds the subject value to a name. Syntax: capture_pattern ::= !'_' NAME A
single underscore In a given pattern, a given name can only be bound once. E.g. Capture patterns always succeed. The binding follows scoping rules established by the assignment expression operator in
PEP 572; the name becomes a local variable in the closest containing function scope unless there’s an applicable In simple terms 8.6.4.5. Wildcard Patterns¶A wildcard pattern always succeeds (matches anything) and binds no name. Syntax: wildcard_pattern ::= '_'
In simple terms, 8.6.4.6. Value Patterns¶A value pattern represents a named value in Python. Syntax: value_pattern ::= The dotted name in the pattern is looked up using standard Python name resolution rules. The pattern succeeds if the value found compares equal to the subject value (using the In simple terms Note If the same value occurs multiple times in the same match statement, the interpreter may cache the first value found and reuse it rather than repeat the same lookup. This cache is strictly tied to a given execution of a given match statement. 8.6.4.7. Group Patterns¶A group pattern allows users to add parentheses around patterns to emphasize the intended grouping. Otherwise, it has no additional syntax. Syntax: group_pattern ::= "(" In simple terms 8.6.4.8. Sequence Patterns¶A sequence pattern contains several subpatterns to be matched against sequence elements. The syntax is similar to the unpacking of a list or tuple. sequence_pattern ::= "[" [ There is no difference if parentheses or square brackets are used for sequence patterns (i.e. Note A single pattern enclosed in parentheses without a trailing comma (e.g. At most one star subpattern may be in a sequence pattern. The star subpattern may occur in any position. If no star subpattern is present, the sequence pattern is a fixed-length sequence pattern; otherwise it is a variable-length sequence pattern. The following is the logical flow for matching a sequence pattern against a subject value:
In simple terms
8.6.4.9. Mapping Patterns¶A mapping pattern contains one or more key-value patterns. The syntax is similar to the construction of a dictionary. Syntax: mapping_pattern ::= "{" [ At most one double star pattern may be in a mapping pattern. The double star pattern must be the last subpattern in the mapping pattern. Duplicate keys in mapping patterns are disallowed. Duplicate
literal keys will raise a The following is the logical flow for matching a mapping pattern against a subject value:
Note Key-value pairs are matched using the two-argument form of the mapping subject’s In simple terms
8.6.4.10. Class Patterns¶A class pattern represents a class and its positional and keyword arguments (if any). Syntax: class_pattern ::= The same keyword should not be repeated in class patterns. The following is the logical flow for matching a class pattern against a subject value:
In simple terms
See also
8.7. Function definitions¶A function definition defines a user-defined function object (see section The standard type hierarchy): funcdef ::= [ A function definition is an executable statement. Its execution binds the function name in the current local namespace to a function object (a wrapper around the executable code for the function). This function object contains a reference to the current global namespace as the global namespace to be used when the function is called. The function definition does not execute the function body; this gets executed only when the function is called. 4 A function definition may be wrapped by one or more decorator expressions. Decorator expressions are evaluated when the function is defined, in the scope that contains the function definition. The result must be a callable, which is invoked with the function object as the only argument. The returned value is bound to the function name instead of the function object. Multiple decorators are applied in nested fashion. For example, the following code @f1(arg) @f2 def func(): pass is roughly equivalent to def func(): pass func = f1(arg)(f2(func)) except that the original function is not temporarily bound to the name Changed in version 3.9: Functions may be decorated with any valid
When one or more parameters have the form
parameter Default parameter values are evaluated from left to right when the function definition is executed. This means that the expression is evaluated once, when the function is defined, and that the same “pre-computed” value is used for each call. This is especially important to understand when a default parameter value is a mutable object, such as a list or a dictionary: if the function modifies the object (e.g. by appending an
item to a list), the default parameter value is in effect modified. This is generally not what was intended. A way around this is to use def whats_on_the_telly(penguin=None): if penguin is None: penguin = [] penguin.append("property of the zoo") return penguin Function call semantics are described in more detail in section Calls. A function call always assigns values to all parameters mentioned
in the parameter list, either from positional arguments, from keyword arguments, or from default values. If the form “ Changed in version 3.8: The Parameters may have an
annotation of the form “ It is also possible to create anonymous functions (functions not bound to a name), for immediate use in expressions. This uses lambda expressions, described in section Lambdas. Note that the lambda expression is merely a shorthand for a simplified function definition; a function defined in a
“ Programmer’s note: Functions are first-class objects. A “ See also PEP 3107 - Function AnnotationsThe original specification for function annotations. PEP 484 - Type HintsDefinition of a standard meaning for annotations: type hints. PEP 526 - Syntax for Variable AnnotationsAbility to type hint variable declarations, including class variables and instance variables PEP 563 - Postponed Evaluation of AnnotationsSupport for forward references within annotations by preserving annotations in a string form at runtime instead of eager evaluation. 8.8. Class definitions¶A class definition defines a class object (see section The standard type hierarchy): classdef ::= [ A class definition is an executable statement. The inheritance list usually gives a list of base classes (see Metaclasses for more advanced uses), so each item in the list should evaluate to a class object which allows subclassing. Classes without an inheritance list inherit, by default, from the base class is equivalent to The class’s suite is then executed in a new execution frame (see Naming and binding), using a newly created local namespace and the original global namespace. (Usually, the suite contains mostly function definitions.) When the class’s suite finishes execution, its execution frame is discarded but its local namespace is saved. 5 A class object is then created using the inheritance list for the base classes and the saved local namespace for the attribute dictionary. The class name is bound to this class object in the original local namespace. The order in which attributes are defined in the class body is preserved in the new class’s Class creation can be customized heavily using metaclasses. Classes can also be decorated: just like when decorating functions, @f1(arg) @f2 class Foo: pass is roughly equivalent to class Foo: pass Foo = f1(arg)(f2(Foo)) The evaluation rules for the decorator expressions are the same as for function decorators. The result is then bound to the class name. Changed in version 3.9: Classes may be decorated with any valid
Programmer’s note: Variables defined in the class definition are class attributes; they are shared by instances. Instance attributes can be
set in a method with See also PEP 3115 - Metaclasses in Python 3000The proposal that changed the declaration of metaclasses to the current syntax, and the semantics for how classes with metaclasses are constructed. PEP 3129 - Class DecoratorsThe proposal that added class decorators. Function and method decorators were introduced in PEP 318. 8.9. Coroutines¶New in version 3.5. 8.9.1. Coroutine function definition¶async_funcdef ::= [ Execution of Python coroutines can be suspended and resumed at many points (see coroutine). Functions defined with It is a An example of a coroutine function: async def func(param1, param2): do_stuff() await some_coroutine() Changed in version 3.7: 8.9.2. The async for statement¶async_for_stmt ::= "async" An asynchronous iterable provides an The The following code: async for TARGET in ITER: SUITE else: SUITE2 Is semantically equivalent to: iter = (ITER) iter = type(iter).__aiter__(iter) running = True while running: try: TARGET = await type(iter).__anext__(iter) except StopAsyncIteration: running = False else: SUITE else: SUITE2 See also It is a 8.9.3. The async with statement¶async_with_stmt ::= "async" An asynchronous context manager is a context manager that is able to suspend execution in its enter and exit methods. The following code: async with EXPRESSION as TARGET: SUITE is semantically equivalent to: manager = (EXPRESSION) aenter = type(manager).__aenter__ aexit = type(manager).__aexit__ value = await aenter(manager) hit_except = False try: TARGET = value SUITE except: hit_except = True if not await aexit(manager, *sys.exc_info()): raise finally: if not hit_except: await aexit(manager, None, None, None) See also It is a
See also PEP 492 - Coroutines with async and await syntaxThe proposal that made coroutines a proper standalone concept in Python, and added supporting syntax. Footnotes 1The exception is propagated to the invocation stack unless there is a In pattern matching, a sequence is defined as one of the following:
The following standard library classes are sequences:
Note Subject values of type In pattern matching, a mapping is defined as one of the following:
The standard library classes
A string literal appearing as the first statement in the function body is transformed into the
function’s A string literal appearing as the first statement in the class body is transformed into the namespace’s How do you write multiple statements in Python?How to Write Multiple Statements on a Single Line in Python?. a = 1. b = 2. c = a + b. print(c) a = 1 b = 2 c = a + b print(c). for i in range(10): c = i ** 2. print (c) for i in range(10): c = i ** 2 print (c). for i in range(3): for j in range(3): print(i, j) for i in range(3): for j in range(3): print(i, j). Can you have multiple if statements in Python?Python Nested if statements
We can have a if...elif...else statement inside another if...elif...else statement. This is called nesting in computer programming. Any number of these statements can be nested inside one another.
What is multiline statement in Python explain with example?Statements in Python typically end with a new line. Python does, however, allow the use of the line continuation character (\) to denote that the line should continue. For example − total = item_one + \ item_two + \ item_three.
What are the two statements in Python?There are mainly four types of statements in Python, print statements, Assignment statements, Conditional statements, Looping statements. The print and assignment statements are commonly used. The result of a print statement is a value.
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