What is assignment in Python with example?

What is assignment in Python with example? : 1) Assign: This operator is used to transfer the value from the right side of the expression to the operand on the left . Assignment Operators in Python. OperatorDescriptionSyntax=Add and Assign: Add the right side operand and the left side operand , then assign to the left operanda = b. This means adding the right side operand with the left side operand.

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When programming, it is useful to be able to store information in variables. A variable is a string of characters and numbers associated with a piece of information. Theassignment operator, denoted by the “=” symbol, is the operator that is used to assign values to variables in Python. The line x=1 takes the known value, 1, and assigns that value to the variable with name “x”. After executing this line, this number will be stored into this variable. Until the value is changed or the variable deleted, the character x behaves like the value 1.

A variable is more like a container to store the data in the computer’s memory, the name of the variable tells the computer where to find this value in the memory. For now, it is sufficient to know that the notebook has its own memory space to store all the variables in the notebook. As a result of the previous example, you will see the variable “x” and “y” in the memory. You can view a list of all the variables in the notebook using the magiccommand %whos.

Note that the equal sign in programming is not the same as a truth statement in mathematics. In math, the statement x = 2 declares the universal truth within the given framework, x is 2. In programming, the statement x=2 means a known value is being associated with a variable name, store 2 in x. Although it is perfectly valid to say 1 =x in mathematics, assignments in Python always go left: meaning the value to the right of the equal sign is assigned to the variable on the left of the equal sign. Therefore, 1=x will generate an error in Python. The assignment operator is always last in the order of operations relative to mathematical, logical, and comparison operators.

TRY IT! The mathematical statement x=x+1 has no solution for any value of x. In programming, if weinitialize the value of x to be 1, then the statement makes perfect sense. It means, “Add x and 1, which is 2, then assign that value to the variable x”. Note that this operation overwrites the previous value stored in x.

The names that variables can have are subject to some limitations. Only alphanumeric (letters and numbers) and underscore characters are permitted in variables. Although a variable name must begin with a letter or an underscore, it is not required. The variable names are case-sensitive and cannot contain any spaces. g. , x and X are going to be viewed as different variables).

TIP! Unlike in pure mathematics, variables in programming almost always represent something tangible. It may be the distance between two points in space or the number of rabbits in a population. Therefore, as your code becomes increasingly complicated, it is very important that your variables carry a name that caneasily be associated with what they represent. For example, the distance between two points in space is better represented by the variable dist than x, and the number of rabbits in a population is better represented by nRabbits than y.

Notably, a variable has no memory of the assignment process once it has been set. In other words, changing the value of x won’t change the value of y if y is created from other variables, like x.

EXAMPLE: What value will y have after the following lines of code are executed?

WARNING! You can overwrite variables or functions that have been stored in Python. For example, the command help = 2 will store the value 2 in the variable with name help. After this assignment help will behave like the value 2 instead of the function help. Therefore, youshould always be careful not to give your variables the same name as built-in functions or values.

TIP! Now that you know how to assign variables, it is important that you learn to never leave unassigned commands. An unassigned command is an operation that has a result, but that result is not assigned to a variable. For example, you should never use 2+2. You should instead assign it to some variable x=2+2. This allows you to “hold on”to the results of previous commands and will make your interaction with Python must less confusing.

You can clear a variable from the notebook using the del function. Typing del x will clear the variable x from the workspace. If you want to remove all the variables in the notebook, you can use the magic command %reset.

In mathematics, variables are usually associated with unknown numbers; in programming, variables are associated with a value ofa certain type. There are many data types that can be assigned to variables. A data type is a classification of the type of information that is being stored in a variable. The basic data types that you will utilize throughout this book are boolean, int, float, string, list, tuple, dictionary, set. A formal description of these data types is given in the following sections.

<2.0 Variables and Basic Data Structures | Contents | 2.2 Data Structure – Strings >

What is assignment statement explain with example? : For instance, int a = 50, float b, a = 25, and b = 34. Variable ‘a’ is given a value in the same statement in the examples above in accordance with its specified data type, as shown in line 25f. Only Variable “b” has a data type declared. Variable ‘a’ is given the new value of 25 in the third line of code.
What do you mean by assignment statement? : A variable, field, parameter, or element is given its current value by an assignment statement. The assignment operator, an expression, and an assignment target are all parts of the statement. The expression is assessed when the statement is run, and the outcome is then saved in the target.
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A simple statement is comprised within a single logical line. Several simple statements may occur on a single line separated by semicolons. The syntax for simple statements is:

simple_stmt ::=  expression_stmt                 | assert_stmt                 | assignment_stmt                 | augmented_assignment_stmt                 | annotated_assignment_stmt                 | pass_stmt                 | del_stmt                 | return_stmt                 | yield_stmt                 | raise_stmt                 | break_stmt                 | continue_stmt                 | import_stmt                 | future_stmt                 | global_stmt                 | nonlocal_stmt

7.1. Expression statements¶

Expression statements are used (mostly interactively) to compute and write a value, or (usually) to call a procedure (a function that returns no meaningful result; in Python, procedures return the value None). Other uses of expression statements are allowed and occasionally useful. The syntax for an expression statement is:

expression_stmt ::=  starred_expression

In interactive mode, if the value is not None, it is converted to a string using the built-in repr() function and the resulting string is written to standard output on a line by itself (except if the result is None, so that procedure calls do not cause any output.)

7.2.Assignment statements¶

Assignment statements are used to (re)bind names to values and to modify attributes or items of mutable objects:

assignment_stmt ::=  (target_list "=")+ (starred_expression | yield_expression)target_list     ::=  target ("," target)* [","]target          ::=  identifier                     | "(" [target_list] ")"                     | "[" [target_list] "]"                     | attributeref                     | subscription                     | slicing                     | "*" target

(See section Primaries for the syntax definitions for attributeref,subscription, and slicing.)

The single object that results from evaluating the expression list—which can either be a single expression or a comma-separated list that produces a tuple—is then assigned to each of the target lists, going from left to right.

Assignment is defined recursively depending on the form of the target (list). When a target is part of a mutable object (an attribute reference, subscription or slicing), the mutableobject must ultimately perform the assignment and decide about its validity, and may raise an exception if the assignment is unacceptable. The rules observed by various types and the exceptions raised are given with the definition of the object types (see section The standard type hierarchy).

Assignment of an object to a target list, optionally enclosed in parentheses or squarebrackets, is recursively defined as follows.

  • If the target list is a single target with no trailing comma, optionally in parentheses, the object is assigned to that target.

  • Else:

    • If the target list contains one target prefixed with an asterisk, called a “starred” target: The object must be an iterable with at least as many items as there are targets in the target list, minus one. The first items of the iterable are assigned, from left to right, to thetargets before the starred target. The final items of the iterable are assigned to the targets after the starred target. A list of the remaining items in the iterable is then assigned to the starred target (the list can be empty).

    • Else: The object must be an iterable with the same number of items as there are targets in the target list, and the items are assigned, from left to right, to the corresponding targets.

Assignment of an object to a single targetis recursively defined as follows.

  • If the target is an identifier (name):

    • If the name does not occur in a global or nonlocal statement in the current code block: the name is bound to the object in the current local namespace.

    • Otherwise: the name is bound to the object inthe global namespace or the outer namespace determined by nonlocal, respectively.

    The name is rebound if it was already bound. This may cause the reference count for the object previously bound to the name to reach zero, causing the object to be deallocated and its destructor (if it has one) to be called.

  • If the target is an attribute reference:The primary expression in the reference is evaluated. It should yield an object with assignable attributes; if this is not the case, TypeError is raised. That object is then asked to assign the assigned object to the given attribute; if it cannot perform the assignment, it raises an exception (usually but not necessarilyAttributeError).

    Note: If the object is a class instance and the attribute reference occurs on both sides of the assignment operator, the right-hand side expression, a.x can access either an instance attribute or (if no instance attribute exists) a class attribute. The left-hand side target a.x is always set as an instance attribute, creating it ifnecessary. Thus, the two occurrences of a.x do not necessarily refer to the same attribute: if the right-hand side expression refers to a class attribute, the left-hand side creates a new instance attribute as the target of the assignment:

    class Cls:    x = 3             # class variableinst = Cls()inst.x = inst.x + 1   # writes inst.x as 4 leaving Cls.x as 3

    This description does not necessarily apply to descriptor attributes, such as properties created with property().

  • If the target is a subscription: The primary expression in the reference is evaluated. It should yield either a mutable sequence object (such as a list) or a mapping object (such as a dictionary). Next, the subscript expression is evaluated.

    If the primary is a mutable sequence object (such as a list), the subscript must yield an integer. If it is negative, the sequence’s length is added to it. The resulting value must be a nonnegative integer less than thesequence’s length, and the sequence is asked to assign the assigned object to its item with that index. If the index is out of range, IndexError is raised (assignment to a subscripted sequence cannot add new items to a list).

    If the primary is a mapping object (such as a dictionary), the subscript must have a type compatible with the mapping’s key type, and the mappingis then asked to create a key/datum pair which maps the subscript to the assigned object. This can either replace an existing key/value pair with the same key value, or insert a new key/value pair (if no key with the same value existed).

    For user-defined objects, the __setitem__() method is called with appropriate arguments.

  • If the target is a slicing: The primary expression in the reference is evaluated. It should yield a mutable sequence object (such as a list).The assigned object should be a sequence object of the same type. Next, the lower and upper bound expressions are evaluated, insofar they are present; defaults are zero and the sequence’s length. The bounds should evaluate to integers. If either bound is negative, the sequence’s length is added to it. The resulting bounds are clipped to lie between zero and the sequence’s length, inclusive. Finally, the sequence object is asked to replace the slice with the items of the assigned sequence. Thelength of the slice may be different from the length of the assigned sequence, thus changing the length of the target sequence, if the target sequence allows it.

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CPython implementation detail: In the current implementation, the syntax for targets is taken to be the same as for expressions, and invalid syntax is rejected during the code generation phase, causing less detailed error messages.

Although the definition of assignment implies that overlaps betweenthe left-hand side and the right-hand side are ‘simultaneous’ (for example a, b =b, a swaps two variables), overlaps within the collection of assigned-to variables occur left-to-right, sometimes resulting in confusion. For instance, the following program prints [0, 2]:

x = [, 1]i = i, x[i] = 1, 2         # i is updated, then x[i] is updatedprint(x)

See also

PEP 3132 – Extended Iterable Unpacking

Thespecification for the *target feature.

7.2.1. Augmented assignment statements¶

Augmented assignment is the combination, in a single statement, of a binary operation and an assignment statement:

augmented_assignment_stmt ::=  augtarget augop (expression_list | yield_expression)augtarget                 ::=  identifier | attributeref | subscription | slicingaugop                     ::=  "+=" | "-=" | "*=" | "@=" | "/=" | "//=" | "%=" | "**="                               | ">>=" | "<<=" | "&=" | "^=" | "|="

(Seesection Primaries for the syntax definitions of the last three symbols.)

Unlike regular assignment statements, an augmented assignment evaluates the target and the expression list, applies the appropriate binary operation to the two operands, and then returns the result to the original target. Only one evaluation of the target is performed.

Anaugmented assignment expression like x += 1 can be rewritten as x = x +1 to achieve a similar, but not exactly equal effect. In the augmented version, x is only evaluated once. Also, when possible, the actual operation is performed in-place, meaning that rather than creating a new object and assigning that to the target, the old object is modified instead.

Unlike normal assignments, augmented assignments evaluate the left-hand side before evaluating theright-hand side. For example, a[i] += f(x) first looks-up a[i], then it evaluates f(x) and performs the addition, and lastly, it writes the result back to a[i].

The assignment carried out by augmented assignment statements is handled in the same way as regular assignments, with the exception of assigning to tuples and multiple targets in a single statement. Similar to how the binary operation carried out by augmented assignment is the same as the standard binary operations, with the possible exception of in-place behavior.

For targets which are attribute references, the same caveat about class and instance attributes applies as for regular assignments.

7.2.2. Annotated assignmentstatements¶

Annotation assignment is the combination, in a single statement, of a variable or attribute annotation and an optional assignment statement:

annotated_assignment_stmt ::=  augtarget ":" expression                               ["=" (starred_expression | yield_expression)]

The difference from normalAssignment statements is that only single target is allowed.

For simple names as assignment targets, if in class or module scope, the annotations are evaluated and stored in a special class or module attribute __annotations__ that is a dictionary mapping from variable names (mangled if private) to evaluated annotations. This attribute is writable and is automatically created at the start ofclass or module body execution, if annotations are found statically.

The annotations are evaluated for class or module scope when using expressions as assignment targets, but they are not stored.

A name is local to a function scope if it is annotated in that scope. When stored in function scopes, annotations are never evaluated.

If the right hand side is present, an annotated assignment performs the actual assignment before evaluating annotations (where applicable). If the righthand side is not present for an expression target, then the interpreter evaluates the target except for the last __setitem__() or __setattr__() call.

See also

PEP 526 – Syntax for Variable Annotations

The proposal that added syntax for annotating the types of variables (including class variables and instance variables), instead of expressing them throughcomments.

PEP 484 – Type hints

The proposal that added the typing module to provide a standard syntax for type annotations that can be used in static analysis tools and IDEs.

Changed inversion 3.8: Now annotated assignments allow same expressions in the right hand side as the regular assignments. Previously, some expressions (like un-parenthesized tuple expressions) caused a syntax error.

7.3. The assert statement¶

Assert statements are a convenient way to insert debugging assertions into a program:

assert_stmt ::=  "assert" expression ["," expression]

The simple form, assert expression, is equivalent to

if __debug__:    if not expression: raise AssertionError

The extended form, assert expression1, expression2, is equivalent to

if __debug__:    if not expression1: raise AssertionError(expression2)

These equivalences assume that __debug__ andAssertionError refer to the built-in variables with those names. In the current implementation, the built-in variable __debug__ is True under normal circumstances, False when optimization is requested (command line option-O). The current code generator emits no code for an assert statement when optimization is requested at compile time. Note that it is unnecessary to include the source code for the expression that failed in the error message; it will be displayed as part of the stack trace.

Assignments to__debug__ are illegal. The value for the built-in variable is determined when the interpreter starts.

7.4. The pass statement¶

pass_stmt ::=  "pass"

pass is a null operation — when it is executed, nothing happens. It is useful as a placeholder when a statement is required syntactically, but no code needs to be executed, for example:

def f(arg): pass    # a function that does nothing (yet)class C: pass       # a class with no methods (yet)

7.5. The delstatement¶

del_stmt ::=  "del" target_list

Similar to how assignment is defined, deletion is also defined in a recursive manner. I’ll give you a few hints instead of going into great detail.

Each target in a target list is deleted from left to right when the target list is deleted.

Deletion of a name removes the binding of that name from the local or global namespace,depending on whether the name occurs in a global statement in the same code block. If the name is unbound, a NameError exception will be raised.

Removal of attribute references, subscriptions, and slicings is passed to the primary object concerned; removal of a slicing generally entails assigning an empty slice of the appropriate type (though even this is determined by the sliced object).

Changed in version 3.2: Previously it was illegal to delete a name from the local namespace if it occurs as a free variable in a nested block.

7.6. The returnstatement¶

return_stmt ::=  "return" [expression_list]

return may only occur syntactically nested in a function definition, not within a nested class definition.

If an expression list is present, it is evaluated, else None is substituted.

return leaves the current function call with the expression list (or None) as return value.

When return passes control out of a try statement with afinally clause, that finally clause is executed before really leaving the function.

In a generator function, the return statement indicates that the generator is done and will causeStopIteration to be raised. The returned value (if any) is used as an argument to construct StopIteration and becomes the StopIteration.value attribute.

In an asynchronous generator function, an emptyreturn statement indicates that the asynchronous generator is done and will cause StopAsyncIteration to be raised. A non-empty return statement is a syntax error in an asynchronous generator function.

7.7.The yield statement¶

yield_stmt ::=  yield_expression

A yield statement is semantically equivalent to a yield expression. The yield statement can be used to omit theparentheses that would otherwise be required in the equivalent yield expression statement. For example, the yield statements

yield <expr>yield from <expr>

are equivalent to the yield expression statements

(yield <expr>)(yield from <expr>)

Yield expressions and statements are only used when defining a generator function, and are only used in the body of the generator function. Using yield in a function definition issufficient to cause that definition to create a generator function instead of a normal function.

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For full details of yield semantics, refer to the Yield expressions section.

7.8. The raisestatement¶

raise_stmt ::=  "raise" [expression ["from" expression]]

If no expressions are present, raise re-raises the exception that is currently being handled, which is also known as the active exception. If there isn’t currently an active exception, aRuntimeError exception is raised indicating that this is an error.

Otherwise, raise evaluates the first expression as the exception object. It must be either a subclass or an instance ofBaseException. If it is a class, the exception instance will be obtained when needed by instantiating the class with no arguments.

The class of the exception instance serves as both the exception’s type and its value.

A traceback object is normally created automatically when an exception is raised and attached to it as the __traceback__attribute, which is writable. You can create an exception and set your own traceback in one step using the with_traceback() exception method (which returns the same exception instance, with its traceback set to its argument), like so:

raise Exception("foo occurred").with_traceback(tracebackobj)

The from clause is used for exception chaining: if given, the secondexpression must be another exception class or instance. If the second expression is an exception instance, it will be attached to the raised exception as the __cause__ attribute (which is writable). If the expression is an exception class, the class will be instantiated and the resulting exception instance will be attached to the raised exception as the __cause__ attribute. If the raised exception is not handled, both exceptions will be printed:

>>> try:...     print(1 / )... except Exception as exc:...     raise RuntimeError("Something bad happened") from exc...Traceback (most recent call last):  File "<stdin>", line 2, in <module>ZeroDivisionError: division by zeroThe above exception was the direct cause of the following exception:Traceback (most recent call last):  File "<stdin>", line 4, in <module>RuntimeError: Something bad happened

A similar mechanismworks implicitly if a new exception is raised when an exception is already being handled. An exception may be handled when an except or finally clause, or a with statement, is used. The previous exception is thenattached as the new exception’s __context__ attribute:

>>> try:...     print(1 / )... except:...     raise RuntimeError("Something bad happened")...Traceback (most recent call last):  File "<stdin>", line 2, in <module>ZeroDivisionError: division by zeroDuring handling of the above exception, another exception occurred:Traceback (most recent call last):  File "<stdin>", line 4, in <module>RuntimeError: Something bad happened

Exception chaining can be explicitly suppressed by specifying None in the from clause:

>>> try:...     print(1 / )... except:...     raise RuntimeError("Something bad happened") from None...Traceback (most recent call last):  File "<stdin>", line 4, in <module>RuntimeError: Something bad happened

Additional information on exceptions can be found in section Exceptions, and information abouthandling exceptions is in section The try statement.

Changed in version 3.3: None is now permitted as Y in raise X from Y.

New in version 3.3: The __suppress_context__ attribute to suppress automatic display of the exception context.

7.9. The break statement¶

break_stmt ::=  "break"

break may only occur syntactically nested in a for orwhile loop, but not nested in a function or class definition within that loop.

It terminates the nearest enclosing loop, skipping the optional else clause if the loop has one.

If a for loop is terminated bybreak, the loop control target keeps its current value.

When break passes control out of a try statement with afinally clause, that finally clause is executed before really leaving the loop.

7.10. The continue statement¶

continue_stmt ::=  "continue"

continue may only occur syntactically nested in a for or while loop, but not nested in a function or class definition within that loop. It continues with the next cycle of the nearest enclosing loop.

Whencontinue passes control out of a try statement with a finally clause, that finally clause is executed before really starting the next loop cycle.

7.11. The import statement¶

import_stmt     ::=  "import" module ["as" identifier] ("," module ["as" identifier])*                     | "from" relative_module "import" identifier ["as" identifier]                     ("," identifier ["as" identifier])*                     | "from" relative_module "import" "(" identifier ["as" identifier]                     ("," identifier ["as" identifier])* [","] ")"                     | "from" relative_module "import" "*"module          ::=  (identifier ".")* identifierrelative_module ::=  "."* module | "."+

The basic import statement (no from clause) is executed in two steps:

  • find a module, loading and initializing it if necessary

  • definea name or names in the local namespace for the scope where the import statement occurs.

  • The two steps are performed separately for each clause when the statement contains multiple clauses (separated by commas), just as if the clauses had been broken out into separate import statements.

    The details of the first step, finding and loading modules are described in greaterdetail in the section on the import system, which also describes the various types of packages and modules that can be imported, as well as all the hooks that can be used to customize the import system. Note that failures in this step may indicate either that the module could not be located, or that an error occurred while initializing the module, which includes execution of themodule’s code.

    If the requested module is retrieved successfully, it will be made available in the local namespace in one of three ways:

    • If the module name is followed by as, then the name following as is bound directly to the imported module.

    • If no other name is specified, and the module being imported is a top level module, the module’s name is bound in the local namespace as a reference to the imported module

    • If themodule being imported is not a top level module, then the name of the top level package that contains the module is bound in the local namespace as a reference to the top level package. The imported module must be accessed using its full qualified name rather than directly

    The from form uses a slightly more complex process:

  • find the module specified inthe from clause, loading and initializing it if necessary;

  • for each of the identifiers specified in the import clauses:

  • check if the imported module has an attribute by that name

  • if not, attempt to import a submodule with that name and then check the imported moduleagain for that attribute

  • if the attribute is not found, ImportError is raised.

  • otherwise, a reference to that value is stored in the local namespace, using the name in the as clause if it is present, otherwise using the attribute name

  • Examples:

    import foo                 # foo imported and bound locallyimport foo.bar.baz         # foo, foo.bar, and foo.bar.baz imported, foo bound locallyimport foo.bar.baz as fbb  # foo, foo.bar, and foo.bar.baz imported, foo.bar.baz bound as fbbfrom foo.bar import baz    # foo, foo.bar, and foo.bar.baz imported, foo.bar.baz bound as bazfrom foo import attr       # foo imported and foo.attr bound as attr

    If the list of identifiers is replaced by astar ('*'), all public names defined in the module are bound in the local namespace for the scope where the import statement occurs.

    The public names defined by a module are determined by checking the module’s namespace for a variable named __all__; if defined, it must be a sequence of strings which are names defined or imported by that module. The names given in__all__ are all considered public and are required to exist. If __all__ is not defined, the set of public names includes all names found in the module’s namespace which do not begin with an underscore character ('_'). __all__ should contain the entire public API. It is intended to avoid accidentally exporting items that are not part of the API (such as library modules which were imported and used within the module).

    The wild card form of import — from module import * —is only allowed at the module level. Attempting to use it in class or function definitions will raise a SyntaxError.

    When specifying what module to import you do not have to specify the absolute name of the module. When a module or package is contained within another package it is possible to make a relative import within the same top package without having to mentionthe package name. By using leading dots in the specified module or package after from you can specify how high to traverse up the current package hierarchy without specifying exact names. One leading dot means the current package where the module making the import exists. Two dots means up one package level. Three dots is up two levels, etc. So if you execute from . import mod from a module in the pkgpackage then you will end up importing pkg.mod. If you execute from ..subpkg2import mod from within pkg.subpkg1 you will import pkg.subpkg2.mod. The specification for relative imports is contained in the Package Relative Imports section.

    importlib.import_module() is provided to supportapplications that determine dynamically the modules to be loaded.

    Raises an auditing event import with arguments module, filename, sys.path, sys.meta_path, sys.path_hooks.

    7.11.1. Futurestatements¶

    A future statement instructs the compiler to compile a particular module using syntax or semantics that will be included in a specific future Python release when the feature is made standard.

    The future statement is intended to ease migration to future versions of Python that introduceincompatible changes to the language. It allows use of the new features on a per-module basis before the release in which the feature becomes standard.

    future_stmt ::=  "from" "__future__" "import" feature ["as" identifier]                 ("," feature ["as" identifier])*                 | "from" "__future__" "import" "(" feature ["as" identifier]                 ("," feature ["as" identifier])* [","] ")"feature     ::=  identifier

    A future statement must appear near the top of the module. The only lines that can appear before a future statement are:

    • the module docstring (if any),

    • comments,

    • blank lines, and

    • other future statements.

    The only feature that requires using the futurestatement is annotations (see PEP 563).

    All historical features enabled by the future statement are still recognized by Python 3. The list includes absolute_import, division, generators, generator_stop, unicode_literals, print_function, nested_scopes and with_statement. They are all redundant because they are always enabled, and only kept for backwards compatibility.

    A future statement is recognized and treatedspecially at compile time: Changes to the semantics of core constructs are often implemented by generating different code. It may even be the case that a new feature introduces new incompatible syntax (such as a new reserved word), in which case the compiler may need to parse the module differently. Such decisions cannot be pushed off until runtime.

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    For any given release, the compiler knows which feature names have been defined, and raises a compile-time error if a future statementcontains a feature not known to it.

    The direct runtime semantics are the same as for any import statement: there is a standard module __future__, described later, and it will be imported in the usual way at the time the future statement is executed.

    The interesting runtime semantics depend on the specific feature enabled by the futurestatement.

    Note that there is nothing special about the statement:

    import __future__ [as name]

    That sentence lacks any special syntax or semantic constraints and is not a future statement.

    Code compiled by calls to the built-in functions exec() and compile() that occurin a module M containing a future statement will, by default, use the new syntax or semantics associated with the future statement. This can be controlled by optional arguments to compile() — see the documentation of that function for details.

    A future statement typed at an interactive interpreter prompt will take effect for the rest of the interpreter session. If an interpreter isstarted with the -i option, is passed a script name to execute, and the script includes a future statement, it will be in effect in the interactive session started after the script is executed.

    See also

    PEP 236 – Back to the __future__

    The original proposalfor the __future__ mechanism.

    7.12. The global statement¶

    global_stmt ::=  "global" identifier ("," identifier)*

    The global statement is a declaration which holds for the entire currentcode block. It means that the listed identifiers are to be interpreted as globals. It would be impossible to assign to a global variable without global, although free variables may refer to globals without being declared global.

    Names listed in a global statement must not be used in the same code block textually preceding that global statement.

    Names listed in aglobal statement must not be defined as formal parameters, or as targets in with statements or except clauses, or in a fortarget list, class definition, function definition, import statement, or variable annotation.

    CPython implementation detail: The current implementation does not enforce some of these restrictions, but programs should not abuse this freedom, as future implementations may enforce them orsilently change the meaning of the program.

    Programmer’s note: global is a directive to the parser. It applies only to code parsed at the same time as the global statement. In particular, a global statement contained in a string or code object supplied to the built-inexec() function does not affect the code block containing the function call, and code contained in such a string is unaffected by global statements in the code containing the function call. The same applies to the eval() andcompile() functions.

    7.13. The nonlocal statement¶

    nonlocal_stmt ::=  "nonlocal" identifier ("," identifier)*

    Thenonlocal statement causes the listed identifiers to refer to previously bound variables in the nearest enclosing scope excluding globals. This is important because the default behavior for binding is to search the local namespace first. The statement allows encapsulated code to rebind variables outside of the local scope besides the global (module) scope.

    Names listed in anonlocal statement, unlike those listed in a global statement, must refer to pre-existing bindings in an enclosing scope (the scope in which a new binding should be created cannot be determined unambiguously).

    Names listed in anonlocal statement must not collide with pre-existing bindings in the local scope.

    See also

    PEP 3104 – Access to Names in Outer Scopes

    The specification for thenonlocal statement.

    Is == an assignment operator in Python? : Assignment operators are used in Python to assign values to variables. a = 5 is a simple assignment operator that assigns the value 5 on the right to the variable a on the left. Assignment operators.
    Equivalent to

    x %= 5
    x = x % 5

    x //= 5
    x = x // 5

    x **= 5
    x = x ** 5

    x &= 5
    x = x & 5

    Read Detail Answer On Is == an assignment operator in Python?

    Arithmetic operators are used with numeric values to perform common mathematical operations:

    OperatorNameExampleTry it

    + Addition x + y Try it »
    Subtraction x – y Try it »
    * Multiplication x * y Try it »
    / Division x / y Try it »
    % Modulus x % y Try it »
    ** Exponentiation x ** y Try it »
    // Floor division x // y Try it »

    Python Assignment Operators

    Assignment operators are used to assign values to variables:

    OperatorExampleSame AsTry it

    = x = 5 x = 5 Try it »
    += x += 3 x = x + 3 Try it »
    -= x -= 3 x = x – 3 Try it »
    *= x *= 3 x = x * 3 Try it »
    /= x /= 3 x = x / 3 Try it »
    %= x %= 3 x = x % 3 Try it »
    //= x //= 3 x = x // 3 Try it »
    **= x **= 3 x = x ** 3 Try it »
    &= x &= 3 x = x & 3 Try it »
    |= x |= 3 x = x | 3 Try it »
    ^= x ^= 3 x = x ^ 3 Try it »
    >>= x >>= 3 x = x >> 3 Try it »
    <<= x <<= 3 x = x << 3 Try it »

    Python Comparison Operators

    Comparison operators are used to compare two values:

    OperatorNameExampleTry it

    == Equal x == y Try it »
    != Not equal x != y Try it »
    > Greater than x > y Try it »
    < Less than x < y Try it »
    >= Greater than or equal to x >= y Try it »
    <= Less than or equal to x <= y Try it »

    Python Logical Operators

    Logical operators are used to combine conditional statements:

    OperatorDescriptionExampleTry it

    and  Returns True if both statements are true x < 5 and  x < 10 Try it »
    or Returns True if one of the statements is true x < 5 or x < 4 Try it »
    not Reverse the result, returns False if the result is true not(x < 5 and x < 10) Try it »

    Python Identity Operators

    Identity operators are used to compare the objects, not if they are equal, but if they are actually the same object, with the same memory location:

    OperatorDescriptionExampleTry it

    is  Returns True if both variables are the same object x is y Try it »
    is not Returns True if both variables are not the same object x is not y Try it »

    Python Membership Operators

    Membership operators are used to test if a sequence is presented in an object:

    OperatorDescriptionExampleTry it

    in  Returns True if a sequence with the specified value is present in the object x in y Try it »
    not in Returns True if a sequence with the specified value is not present in the object x not in y Try it »

    Python Bitwise Operators

    Bitwise operators are used to compare (binary) numbers:


    AND Sets each bit to 1 if both bits are 1
    | OR Sets each bit to 1 if one of two bits is 1
     ^ XOR Sets each bit to 1 if only one of two bits is 1
    NOT Inverts all the bits
    << Zero fill left shift Shift left by pushing zeros in from the right and let the leftmost bits fall off
    >> Signed right shift Shift right by pushing copies of the leftmost bit in from the left, and let the rightmost bits fall off

    Test Yourself With Exercises

    Additional Question — What is assignment in Python with example?

    What are assignments in Python?

    The assignment operator, denoted by the = symbol, is the operator that is used to assign values to variables in Python The statement x=1 assigns the known value of 1 to the x variable.

    How do you use assignment operators?

    In an assignment operation, the value of the right-hand operand is assigned to the storage location specified by the left-hand operand. A modifiable l-value must therefore be the left-hand operand of an assignment operation. After the assignment, an assignment expression has the value of the left operand but is not an l-value.

    Is an assignment operator?

    The assignment operator = assigns the value of its right-hand operand to a variable, a property, or an indexer element given by its left-hand operand. The result of an assignment expression is the value assigned to the left-hand operand.

    Which of the following is an assignment operator in Python a == b === C >>> D?

    Answer one. Assignment operators: The = assignment operator in Python makes it easy to assign values to variables. The assignment statement “Let a = 5 and b = 10” can also be written as “a, b = 5, 10,” which assigns the values 5 and 10 to the variables a and b, respectively, on the right.

    Which one is the assignment operator?

    Assignment Operators in C


    Simple assignment operator. Assigns values from right side operands to left side operand

    Add AND assignment operator. It adds the right operand to the left operand and assign the result to the left operand.

    What are the assignment operators in Python Mcq?

    The following operators are used in assignments: =, -=, *=, /=, and **=.

    Which is not assignment operator?

    Which of the following is not an assignment operator? Explanation: Assignment operators are used to assign some value to a data object. := operator is used to assign values to VARIABLE, CONSTANTS and GENERICS; this operator is also used for assigning initial values.

    What is -= mean in Python?

    -= Subtraction Assignment Subtracts a value from the variable and assigns the result to that variable.

    What is += used for in Python?

    = assigns the new value to the variable and adds it along with the value of the original variable. Similar operations are performed for addition, subtraction, multiplication, and division by -=, *=, /=.

    Is Python or C++ better?

    Python is slower than C because Python is dynamically typed, which causes slower code compilation. Python is slower than C because it uses the interpreter and supports dynamic typing, which slows down compilation.

    What is == in Python?

    The Python is operator determines whether two variables point to the same memory object as opposed to the == operator, which compares the value or equality of two objects. Use the equality operators == and!= in the vast majority of circumstances, according to this rule.

    Dannie Jarrod

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