Data model

Question 1

Objects

Answer 1

Objects are Python’s abstraction for data. All data in a Python program is represented by objects or by relations between objects. (In a sense, and in conformance to Von Neumann’s model of a “stored program computer,” code is also represented by objects.)

Every object has an identity, a type and a value. An object’s identity never changes once it has been created; you may think of it as the object’s address in memory. The ‘is’ operator compares the identity of two objects; the id() function returns an integer representing its identity.

Question 2

An object’s type determines . . .

Answer 2

. . . the operations that the object supports (e.g., “does it have a length?”) and also defines the possible values for objects of that type. The type() function returns an object’s type (which is an object itself). Like its identity, an object’s type is also unchangeable.

Question 3

Value

Answer 3

The value of some objects can change. Objects whose value can change are said to be mutable; objects whose value is unchangeable once they are created are called immutable. (The value of an immutable container object that contains a reference to a mutable object can change when the latter’s value is changed; however the container is still considered immutable, because the collection of objects it contains cannot be changed. So, immutability is not strictly the same as having an unchangeable value, it is more subtle.)

An object’s mutability is determined by its type; for instance, numbers, strings and tuples are immutable, while dictionaries and lists are mutable.

Question 4

Objects are never explicitly . . .

Answer 4

Destroyed

However, when they become unreachable they may be garbage-collected. An implementation is allowed to postpone garbage collection or omit it altogether — it is a matter of implementation quality how garbage collection is implemented, as long as no objects are collected that are still reachable.

Question 5

containers

Answer 5

Some objects contain references to other objects; these are called containers. Examples of containers are tuples, lists and dictionaries. The references are part of a container’s value. In most cases, when we talk about the value of a container, we imply the values, not the identities of the contained objects; however, when we talk about the mutability of a container, only the identities of the immediately contained objects are implied.

So, if an immutable container (like a tuple) contains a reference to a mutable object, its value changes if that mutable object is changed.

Question 6

Types affect almost all aspects of object behavior.

Answer 6

Even the importance of object identity is affected in some sense: for immutable types, operations that compute new values may actually return a reference to any existing object with the same type and value, while for mutable objects this is not allowed. E.g., after a = 1; b = 1, a and b may or may not refer to the same object with the value one, depending on the implementation, but after c = []; d = [], c and d are guaranteed to refer to two different, unique, newly created empty lists. (Note that c = d = [] assigns the same object to both c and d.)

Question 7

The standard type hierarchy

Answer 7

None

NotImplemented

Ellipsis

Sequences

Set types

Mappings

Callable types

Modules

Custom classes

Class instances

I/O objects (also known as file objects)

Internal types

Question 8

None

Answer 8

This type has a single value. There is a single object with this value. This object is accessed through the built-in name None. It is used to signify the absence of a value in many situations, e.g., it is returned from functions that don’t explicitly return anything. Its truth value is false.

Question 9

NotImplemented

Answer 9

This type has a single value. There is a single object with this value. This object is accessed through the built-in name NotImplemented. Numeric methods and rich comparison methods should return this value if they do not implement the operation for the operands provided. (The interpreter will then try the reflected operation, or some other fallback, depending on the operator.) Its truth value is true.

See Implementing the arithmetic operations for more details.

Question 10

Ellipsis

Answer 10

This type has a single value. There is a single object with this value. This object is accessed through the literal … or the built-in name Ellipsis. Its truth value is true.

Question 11

numbers.Number

Answer 11

These are created by numeric literals and returned as results by arithmetic operators and arithmetic built-in functions. Numeric objects are immutable; once created their value never changes. Python numbers are of course strongly related to mathematical numbers, but subject to the limitations of numerical representation in computers.

Question 12

numbers.Integral

Answer 12

These represent elements from the mathematical set of integers (positive and negative).

There are two types of integers:

Integers (int)

These represent numbers in an unlimited range, subject to available (virtual) memory only. For the purpose of shift and mask operations, a binary representation is assumed, and negative numbers are represented in a variant of 2’s complement which gives the illusion of an infinite string of sign bits extending to the left.

Booleans (bool)

These represent the truth values False and True. The two objects representing the values False and True are the only Boolean objects. The Boolean type is a subtype of the integer type, and Boolean values behave like the values 0 and 1, respectively, in almost all contexts, the exception being that when converted to a string, the strings “False” or “True”are returned, respectively.

The rules for integer representation are intended to give the most meaningful interpretation of shift and mask operations involving negative integers.

Question 13

numbers.Real (float)

Answer 13

These represent machine-level double precision floating point numbers. You are at the mercy of the underlying machine architecture (and C or Java implementation) for the accepted range and handling of overflow. Python does not support single-precision floating point numbers; the savings in processor and memory usage that are usually the reason for using these are dwarfed by the overhead of using objects in Python, so there is no reason to complicate the language with two kinds of floating point numbers.

Question 14

numbers.Complex (complex)

Answer 14

These represent complex numbers as a pair of machine-level double precision floating point numbers. The same caveats apply as for floating point numbers. The real and imaginary parts of a complex number z can be retrieved through the read-only attributes z.real and z.imag.

Question 15

Sequences

Answer 15

These represent finite ordered sets indexed by non-negative numbers. The built-in function len() returns the number of items of a sequence. When the length of a sequence is n, the index set contains the numbers 0, 1, …, n-1. Item i of sequence a is selected by a[i].

Sequences also support slicing: a[i:j] selects all items with index k such that i <= k < j. When used as an expression, a slice is a sequence of the same type. This implies that the index set is renumbered so that it starts at 0.

Some sequences also support “extended slicing” with a third “step” parameter: a[i:j:k] selects all items of a with index x where x = i + n*k, n >= 0 and i <= x < j.

Sequences are distinguished according to their mutability

Question 16

Immutable sequences

Answer 16

An object of an immutable sequence type cannot change once it is created. (If the object contains references to other objects, these other objects may be mutable and may be changed; however, the collection of objects directly referenced by an immutable object cannot change.)

The following types are immutable sequences:

Strings

A string is a sequence of values that represent Unicode code points. All the code points in the range U+0000 - U+10FFFF can be represented in a string. Python doesn’t have a chartype; instead, every code point in the string is represented as a string object with length 1. The built-in function ord() converts a code point from its string form to an integer in the range 0 - 10FFFF; chr() converts an integer in the range 0 - 10FFFF to the corresponding length 1 string object. str.encode() can be used to convert a str to bytes using the given text encoding, and bytes.decode() can be used to achieve the opposite.

Tuples

The items of a tuple are arbitrary Python objects. Tuples of two or more items are formed by comma-separated lists of expressions. A tuple of one item (a ‘singleton’) can be formed by affixing a comma to an expression (an expression by itself does not create a tuple, since parentheses must be usable for grouping of expressions). An empty tuple can be formed by an empty pair of parentheses.

Bytes

A bytes object is an immutable array. The items are 8-bit bytes, represented by integers in the range 0 <= x < 256. Bytes literals (like b’abc’) and the built-in bytes() constructor can be used to create bytes objects. Also, bytes objects can be decoded to strings via the decode() method.

Question 17

Mutable sequences

Answer 17

Mutable sequences can be changed after they are created. The subscription and slicing notations can be used as the target of assignment and del (delete) statements.

There are currently two intrinsic mutable sequence types:

Lists

The items of a list are arbitrary Python objects. Lists are formed by placing a comma-separated list of expressions in square brackets. (Note that there are no special cases needed to form lists of length 0 or 1.)

Byte Arrays

A bytearray object is a mutable array. They are created by the built-in bytearray() constructor. Aside from being mutable (and hence unhashable), byte arrays otherwise provide the same interface and functionality as immutable bytes objects.

The extension module array provides an additional example of a mutable sequence type, as does the collections module.

Question 18

Set types

Answer 18

These represent unordered, finite sets of unique, immutable objects. As such, they cannot be indexed by any subscript. However, they can be iterated over, and the built-in function len() returns the number of items in a set. Common uses for sets are fast membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.

For set elements, the same immutability rules apply as for dictionary keys. Note that numeric types obey the normal rules for numeric comparison: if two numbers compare equal (e.g., 1 and 1.0), only one of them can be contained in a set.

There are currently two intrinsic set types:

Sets

These represent a mutable set. They are created by the built-in set() constructor and can be modified afterwards by several methods, such as add().

Frozen sets

These represent an immutable set. They are created by the built-in frozenset() constructor. As a frozenset is immutable and hashable, it can be used again as an element of another set, or as a dictionary key.

Question 19

Mappings

Answer 19

These represent finite sets of objects indexed by arbitrary index sets. The subscript notation a[k]selects the item indexed by k from the mapping a; this can be used in expressions and as the target of assignments or del statements. The built-in function len() returns the number of items in a mapping.

There is currently a single intrinsic mapping type:

Dictionaries

These represent finite sets of objects indexed by nearly arbitrary values. The only types of values not acceptable as keys are values containing lists or dictionaries or other mutable types that are compared by value rather than by object identity, the reason being that the efficient implementation of dictionaries requires a key’s hash value to remain constant. Numeric types used for keys obey the normal rules for numeric comparison: if two numbers compare equal (e.g., 1 and 1.0) then they can be used interchangeably to index the same dictionary entry.

Dictionaries are mutable; they can be created by the {…} notation (see section Dictionary displays).

The extension modules dbm.ndbm and dbm.gnu provide additional examples of mapping types, as does the collections module.

Question 20

Callable types

Answer 20

These are the types to which the function call operation (see section Calls) can be applied:

User-defined functions

Instance methods

Generator functions

Coroutine functions

Asynchronous generator functions

Built-in functions

Built-in methods

Classes

Class Instances

Question 21

User-defined functions

Answer 21

A user-defined function object is created by a function definition (see section Function definitions). It should be called with an argument list containing the same number of items as the function’s formal parameter list.

Most of the attributes labelled “Writable” check the type of the assigned value.

Function objects also support getting and setting arbitrary attributes, which can be used, for example, to attach metadata to functions. Regular attribute dot-notation is used to get and set such attributes. Note that the current implementation only supports function attributes on user-defined functions. Function attributes on built-in functions may be supported in the future.

A cell object has the attribute cell_contents. This can be used to get the value of the cell, as well as set the value.

Question 22

Instance methods

Answer 22

An instance method object combines a class, a class instance and any callable object (normally a user-defined function).

Special read-only attributes: __self__ is the class instance object, __func__ is the function object; __doc__ is the method’s documentation (same as __func__.__doc__); __name__ is the method name (same as __func__.__name__); __module__ is the name of the module the method was defined in, or None if unavailable.

Methods also support accessing (but not setting) the arbitrary function attributes on the underlying function object.

Question 23

User-defined method objects may be created

Answer 23

when getting an attribute of a class (perhaps via an instance of that class), if that attribute is a user-defined function object or a class method object.

When an instance method object is created by retrieving a user-defined function object from a class via one of its instances, its __self__ attribute is the instance, and the method object is said to be bound. The new method’s __func__ attribute is the original function object.

When a user-defined method object is created by retrieving another method object from a class or instance, the behaviour is the same as for a function object, except that the __func__attribute of the new instance is not the original method object but its __func__ attribute.

When an instance method object is created by retrieving a class method object from a class or instance, its __self__ attribute is the class itself, and its __func__ attribute is the function object underlying the class method.

Question 24

When an instance method object is called

Answer 24

the underlying function (__func__) is called, inserting the class instance (__self__) in front of the argument list. For instance, when C is a class which contains a definition for a function f(), and x is an instance of C, calling x.f(1) is equivalent to calling C.f(x, 1).

Question 25

When an instance method object is derived from a class method object

Answer 25

the “class instance” stored in \_\_self\_\_ will actually be the class itself, so that calling either x.f(1) or C.f(1) is equivalent to calling f(C,1) where f is the underlying function.

Question 26

Note that the transformation from function object to instance method object

Answer 26

happens each time the attribute is retrieved from the instance. In some cases, a fruitful optimization is to assign the attribute to a local variable and call that local variable. Also notice that this transformation only happens for user-defined functions; other callable objects (and all non-callable objects) are retrieved without transformation. It is also important to note that user-defined functions which are attributes of a class instance are not converted to bound methods; this only happens when the function is an attribute of the class.

Question 27

Generator functions

Answer 27

A function or method which uses the yield statement (see section The yield statement) is called a generator function. Such a function, when called, always returns an iterator object which can be used to execute the body of the function: calling the iterator’s iterator.\_\_next\_\_() method will cause the function to execute until it provides a value using the yield statement. When the function executes a return statement or falls off the end, a StopIteration exception is raised and the iterator will have reached the end of the set of values to be returned.

Question 28

Coroutine functions

Answer 28

A function or method which is defined using async def is called a coroutine function. Such a function, when called, returns a coroutine object. It may contain await expressions, as well as async with and async for statements. See also the Coroutine Objects section.

Question 29

Asynchronous generator functions

Answer 29

A function or method which is defined using async def and which uses the yield statement is called a asynchronous generator function. Such a function, when called, returns an asynchronous iterator object which can be used in an async for statement to execute the body of the function. Calling the asynchronous iterator’s aiterator.\_\_anext\_\_() method will return an awaitablewhich when awaited will execute until it provides a value using the yield expression. When the function executes an empty return statement or falls off the end, a StopAsyncIterationexception is raised and the asynchronous iterator will have reached the end of the set of values to be yielded.

Question 30

Built-in functions

Answer 30

A built-in function object is a wrapper around a C function. Examples of built-in functions are len() and math.sin() (math is a standard built-in module). The number and type of the arguments are determined by the C function. Special read-only attributes: \_\_doc\_\_ is the function’s documentation string, or None if unavailable; \_\_name\_\_ is the function’s name; \_\_self\_\_is set to None (but see the next item); \_\_module\_\_ is the name of the module the function was defined in or None if unavailable.

Question 31

Built-in methods

Answer 31

This is really a different disguise of a built-in function, this time containing an object passed to the C function as an implicit extra argument. An example of a built-in method is alist.append(), assuming alist is a list object. In this case, the special read-only attribute \_\_self\_\_ is set to the object denoted by alist.

Question 32

Classes

Answer 32

Classes are callable. These objects normally act as factories for new instances of themselves, but variations are possible for class types that override \_\_new\_\_(). The arguments of the call are passed to \_\_new\_\_() and, in the typical case, to \_\_init\_\_() to initialize the new instance.

Question 33

Class Instances

Answer 33

Instances of arbitrary classes can be made callable by defining a \_\_call\_\_() method in their class.

Question 34

Modules

Answer 34

Modules are a basic organizational unit of Python code, and are created by the import system as invoked either by the import statement, or by calling functions such as importlib.import\_module() and built-in \_\_import\_\_(). A module object has a namespace implemented by a dictionary object (this is the dictionary referenced by the \_\_globals\_\_ attribute of functions defined in the module). Attribute references are translated to lookups in this dictionary, e.g., m.x is equivalent to m.\_\_dict\_\_["x"]. A module object does not contain the code object used to initialize the module (since it isn’t needed once the initialization is done). Attribute assignment updates the module’s namespace dictionary, e.g., m.x = 1 is equivalent to m.\_\_dict\_\_["x"] = 1. Predefined (writable) attributes: \_\_name\_\_ is the module’s name; \_\_doc\_\_ is the module’s documentation string, or None if unavailable; \_\_annotations\_\_ (optional) is a dictionary containingvariable annotations collected during module body execution; \_\_file\_\_ is the pathname of the file from which the module was loaded, if it was loaded from a file. The \_\_file\_\_ attribute may be missing for certain types of modules, such as C modules that are statically linked into the interpreter; for extension modules loaded dynamically from a shared library, it is the pathname of the shared library file. Special read-only attribute: \_\_dict\_\_ is the module’s namespace as a dictionary object.

Question 35

Custom classes

Answer 35

Custom class types are typically created by class definitions (see section Class definitions). A class has a namespace implemented by a dictionary object. Class attribute references are translated to lookups in this dictionary, e.g., C.x is translated to C.\_\_dict\_\_["x"] (although there are a number of hooks which allow for other means of locating attributes). When the attribute name is not found there, the attribute search continues in the base classes. This search of the base classes uses the C3 method resolution order which behaves correctly even in the presence of ‘diamond’ inheritance structures where there are multiple inheritance paths leading back to a common ancestor. Additional details on the C3 MRO used by Python can be found in the documentation accompanying the 2.3 release at https://www.python.org/download/releases/2.3/mro/.

Question 36

When a class attribute reference (for class C, say) would yield a class method object

Answer 36

it is transformed into an instance method object whose \_\_self\_\_ attribute is C. When it would yield a static method object, it is transformed into the object wrapped by the static method object. See section Implementing Descriptors for another way in which attributes retrieved from a class may differ from those actually contained in its \_\_dict\_\_.

Question 37

Class attribute assignments update the class’s dictionary

Answer 37

never the dictionary of a base class.

Question 38

Custom classes Special attributes:

Answer 38

\_\_name\_\_ is the class name; \_\_module\_\_ is the module name in which the class was defined; \_\_dict\_\_ is the dictionary containing the class’s namespace; \_\_bases\_\_ is a tuple containing the base classes, in the order of their occurrence in the base class list; \_\_doc\_\_ is the class’s documentation string, or None if undefined; \_\_annotations\_\_ (optional) is a dictionary containing variable annotations collected during class body execution.

Question 39

Class instances

Answer 39

A class instance is created by calling a class object (see above). A class instance has a namespace implemented as a dictionary which is the first place in which attribute references are searched. When an attribute is not found there, and the instance’s class has an attribute by that name, the search continues with the class attributes. If a class attribute is found that is a user-defined function object, it is transformed into an instance method object whose \_\_self\_\_ attribute is the instance. Static method and class method objects are also transformed; see above under “Classes”. See section Implementing Descriptors for another way in which attributes of a class retrieved via its instances may differ from the objects actually stored in the class’s \_\_dict\_\_. If no class attribute is found, and the object’s class has a \_\_getattr\_\_() method, that is called to satisfy the lookup.

Question 40

Attribute assignments and deletions

Answer 40

update the instance’s dictionary, never a class’s dictionary. If the class has a \_\_setattr\_\_() or \_\_delattr\_\_() method, this is called instead of updating the instance dictionary directly.

Question 41

Class instances can pretend to be

Answer 41

numbers, sequences, or mappings if they have methods with certain special names. See section Special method names. Special attributes: \_\_dict\_\_ is the attribute dictionary; \_\_class\_\_ is the instance’s class.

Question 42

I/O objects (also known as file objects)

Answer 42

A file object represents an open file. Various shortcuts are available to create file objects: the open() built-in function, and also os.popen(), os.fdopen(), and the makefile() method of socket objects (and perhaps by other functions or methods provided by extension modules). The objects sys.stdin, sys.stdout and sys.stderr are initialized to file objects corresponding to the interpreter’s standard input, output and error streams; they are all open in text mode and therefore follow the interface defined by the io.TextIOBase abstract class.

Question 43

Internal types

Answer 43

A few types used internally by the interpreter are exposed to the user. Their definitions may change with future versions of the interpreter, but they are mentioned here for completeness.

Question 44

Code objects

Answer 44

Code objects represent byte-compiled executable Python code, or bytecode. The difference between a code object and a function object is that the function object contains an explicit reference to the function’s globals (the module in which it was defined), while a code object contains no context; also the default argument values are stored in the function object, not in the code object (because they represent values calculated at run-time). Unlike function objects, code objects are immutable and contain no references (directly or indirectly) to mutable objects.

Question 45

Code objects Special read-only attributes:

Answer 45

co\_name gives the function name; co\_argcount is the number of positional arguments (including arguments with default values); co\_nlocals is the number of local variables used by the function (including arguments); co\_varnames is a tuple containing the names of the local variables (starting with the argument names); co\_cellvars is a tuple containing the names of local variables that are referenced by nested functions; co\_freevarsis a tuple containing the names of free variables; co\_code is a string representing the sequence of bytecode instructions; co\_consts is a tuple containing the literals used by the bytecode; co\_names is a tuple containing the names used by the bytecode; co\_filename is the filename from which the code was compiled; co\_firstlineno is the first line number of the function; co\_lnotab is a string encoding the mapping from bytecode offsets to line numbers (for details see the source code of the interpreter); co\_stacksize is the required stack size (including local variables); co\_flags is an integer encoding a number of flags for the interpreter.

Question 46

The following flag bits are defined for co\_flags:

Answer 46

bit 0x04 is set if the function uses the \*arguments syntax to accept an arbitrary number of positional arguments; bit 0x08 is set if the function uses the \*\*keywords syntax to accept arbitrary keyword arguments; bit 0x20 is set if the function is a generator. Future feature declarations (from \_\_future\_\_ import division) also use bits in co\_flags to indicate whether a code object was compiled with a particular feature enabled: bit 0x2000 is set if the function was compiled with future division enabled; bits 0x10 and 0x1000 were used in earlier versions of Python. Other bits in co\_flags are reserved for internal use. If a code object represents a function, the first item in co\_consts is the documentation string of the function, or None if undefined.

Question 47

Frame objects

Answer 47

Frame objects represent execution frames. They may occur in traceback objects (see below), and are also passed to registered trace functions. Special read-only attributes: f\_back is to the previous stack frame (towards the caller), or None if this is the bottom stack frame; f\_code is the code object being executed in this frame; f\_locals is the dictionary used to look up local variables; f\_globals is used for global variables; f\_builtins is used for built-in (intrinsic) names; f\_lasti gives the precise instruction (this is an index into the bytecode string of the code object). Special writable attributes: f\_trace, if not None, is a function called for various events during code execution (this is used by the debugger). Normally an event is triggered for each new source line - this can be disabled by setting f\_trace\_lines to False.

Question 48

Frame objects Implementations may allow

Answer 48

per-opcode events to be requested by setting f\_trace\_opcodes to True. Note that this may lead to undefined interpreter behaviour if exceptions raised by the trace function escape to the function being traced.

Question 49

f\_lineno

Answer 49

is the current line number of the frame — writing to this from within a trace function jumps to the given line (only for the bottom-most frame). A debugger can implement a Jump command (aka Set Next Statement) by writing to f\_lineno.

Question 50

Frame objects support one method:

Answer 50

frame.clear() This method clears all references to local variables held by the frame. Also, if the frame belonged to a generator, the generator is finalized. This helps break reference cycles involving frame objects (for example when catching an exception and storing its traceback for later use). RuntimeError is raised if the frame is currently executing.

Question 51

Traceback objects

Answer 51

Traceback objects represent a stack trace of an exception. A traceback object is implicitly created when an exception occurs, and may also be explicitly created by calling types.TracebackType.

Question 52

For implicitly created tracebacks, when the search for an exception handler unwinds the execution stack . . . .

Answer 52

at each unwound level a traceback object is inserted in front of the current traceback. When an exception handler is entered, the stack trace is made available to the program. (See section The try statement.) It is accessible as the third item of the tuple returned by sys.exc\_info(), and as the \_\_traceback\_\_ attribute of the caught exception.

Question 53

When the program contains no suitable handler, the stack trace is written

Answer 53

(nicely formatted) to the standard error stream; if the interpreter is interactive, it is also made available to the user as sys.last\_traceback.

Question 54

For explicitly created tracebacks, it is up to the creator of the traceback to determine how the

Answer 54

tb\_next attributes should be linked to form a full stack trace.

Question 55

Traceback objects Special read-only attributes:

Answer 55

tb\_frame points to the execution frame of the current level;tb\_lineno gives the line number where the exception occurred; tb\_lasti indicates the precise instruction. The line number and last instruction in the traceback may differ from the line number of its frame object if the exception occurred in a try statement with no matching except clause or with a finally clause.

Question 56

Traceback objects Special read-only attributes:

Answer 56

tb\_frame points to the execution frame of the current level;tb\_lineno gives the line number where the exception occurred; tb\_lasti indicates the precise instruction. The line number and last instruction in the traceback may differ from the line number of its frame object if the exception occurred in a try statement with no matching except clause or with a finally clause.

Question 57

Traceback objects Special writable attribute:

Answer 57

tb\_next is the next level in the stack trace (towards the frame where the exception occurred), or None if there is no next level.

Question 58

Slice objects

Answer 58

Slice objects are used to represent slices for \_\_getitem\_\_() methods. They are also created by the built-in slice() function. Special read-only attributes: start is the lower bound; stop is the upper bound; step is the step value; each is None if omitted. These attributes can have any type.

Question 59

Slice objects support one method:

Answer 59

slice.indices(self, length) This method takes a single integer argument length and computes information about the slice that the slice object would describe if applied to a sequence of length items. It returns a tuple of three integers; respectively these are the start and stop indices and thestep or stride length of the slice. Missing or out-of-bounds indices are handled in a manner consistent with regular slices.

Question 60

Static method objects

Answer 60

Static method objects provide a way of defeating the transformation of function objects to method objects described above. A static method object is a wrapper around any other object, usually a user-defined method object. When a static method object is retrieved from a class or a class instance, the object actually returned is the wrapped object, which is not subject to any further transformation. Static method objects are not themselves callable, although the objects they wrap usually are. Static method objects are created by the built-in staticmethod()constructor.

Question 61

Class method objects

Answer 61

A class method object, like a static method object, is a wrapper around another object that alters the way in which that object is retrieved from classes and class instances. The behaviour of class method objects upon such retrieval is described above, under “User-defined methods”. Class method objects are created by the built-in classmethod() constructor.

Question 62

Special method names

Answer 62

A class can implement certain operations that are invoked by special syntax (such as arithmetic operations or subscripting and slicing) by defining methods with special names. This is Python’s approach to operator overloading, allowing classes to define their own behavior with respect to language operators. For instance, if a class defines a method named \_\_getitem\_\_(), and x is an instance of this class, then x[i] is roughly equivalent to type(x).\_\_getitem\_\_(x, i). Except where mentioned, attempts to execute an operation raise an exception when no appropriate method is defined (typicallyAttributeError or TypeError). Setting a special method to None indicates that the corresponding operation is not available. For example, if a class sets \_\_iter\_\_() to None, the class is not iterable, so calling iter() on its instances will raise a TypeError (without falling back to \_\_getitem\_\_()). 2 When implementing a class that emulates any built-in type, it is important that the emulation only be implemented to the degree that it makes sense for the object being modelled. For example, some sequences may work well with retrieval of individual elements, but extracting a slice may not make sense. (One example of this is the NodeList interface in the W3C’s Document Object Model.)

Question 63

object.\_\_new\_\_(cls[, ...])

Answer 63

Called to create a new instance of class cls. \_\_new\_\_() is a static method (special-cased so you need not declare it as such) that takes the class of which an instance was requested as its first argument. The remaining arguments are those passed to the object constructor expression (the call to the class). The return value of \_\_new\_\_() should be the new object instance (usually an instance of cls). Typical implementations create a new instance of the class by invoking the superclass’s \_\_new\_\_()method using super().\_\_new\_\_(cls[, ...]) with appropriate arguments and then modifying the newly-created instance as necessary before returning it. If \_\_new\_\_() returns an instance of cls, then the new instance’s \_\_init\_\_() method will be invoked like \_\_init\_\_(self[, ...]), where self is the new instance and the remaining arguments are the same as were passed to \_\_new\_\_(). If \_\_new\_\_() does not return an instance of cls, then the new instance’s \_\_init\_\_() method will not be invoked. \_\_new\_\_() is intended mainly to allow subclasses of immutable types (like int, str, or tuple) to customize instance creation. It is also commonly overridden in custom metaclasses in order to customize class creation.

Question 64

object.\_\_init\_\_(self[, ...])

Answer 64

Called after the instance has been created (by \_\_new\_\_()), but before it is returned to the caller. The arguments are those passed to the class constructor expression. If a base class has an \_\_init\_\_() method, the derived class’s \_\_init\_\_() method, if any, must explicitly call it to ensure proper initialization of the base class part of the instance; for example: super().\_\_init\_\_([args...]). Because \_\_new\_\_() and \_\_init\_\_() work together in constructing objects (\_\_new\_\_() to create it, and \_\_init\_\_() to customize it), no non-None value may be returned by \_\_init\_\_(); doing so will cause a TypeError to be raised at runtime.

Question 65

object.\_\_del\_\_(self)

Answer 65

Called when the instance is about to be destroyed. This is also called a finalizer or (improperly) a destructor. If a base class has a \_\_del\_\_() method, the derived class’s \_\_del\_\_() method, if any, must explicitly call it to ensure proper deletion of the base class part of the instance. It is possible (though not recommended!) for the \_\_del\_\_() method to postpone destruction of the instance by creating a new reference to it. This is called object resurrection. It is implementation-dependent whether \_\_del\_\_() is called a second time when a resurrected object is about to be destroyed; the current CPython implementation only calls it once. It is not guaranteed that \_\_del\_\_() methods are called for objects that still exist when the interpreter exits. Note: del x doesn’t directly call x.\_\_del\_\_() — the former decrements the reference count for x by one, and the latter is only called when x’s reference count reaches zero.

Question 66

object.\_\_repr\_\_(self)

Answer 66

Called by the repr() built-in function to compute the “official” string representation of an object. If at all possible, this should look like a valid Python expression that could be used to recreate an object with the same value (given an appropriate environment). If this is not possible, a string of the form \<...some useful description...\> should be returned. The return value must be a string object. If a class defines \_\_repr\_\_() but not \_\_str\_\_(), then \_\_repr\_\_() is also used when an “informal” string representation of instances of that class is required. This is typically used for debugging, so it is important that the representation is information-rich and unambiguous.

Question 67

object.\_\_str\_\_(self)

Answer 67

Called by str(object) and the built-in functions format() and print() to compute the “informal” or nicely printable string representation of an object. The return value must be a stringobject. This method differs from object.\_\_repr\_\_() in that there is no expectation that \_\_str\_\_() return a valid Python expression: a more convenient or concise representation can be used. The default implementation defined by the built-in type object calls object.\_\_repr\_\_().

Question 68

object.\_\_bytes\_\_(self)

Answer 68

Called by bytes to compute a byte-string representation of an object. This should return a bytesobject.

Question 69

object.\_\_format\_\_(self, format\_spec)

Answer 69

Called by the format() built-in function, and by extension, evaluation of formatted string literalsand the str.format() method, to produce a “formatted” string representation of an object. The format\_spec argument is a string that contains a description of the formatting options desired. The interpretation of the format\_spec argument is up to the type implementing \_\_format\_\_(), however most classes will either delegate formatting to one of the built-in types, or use a similar formatting option syntax. See Format Specification Mini-Language for a description of the standard formatting syntax. The return value must be a string object.

Question 70

object. \_\_lt\_\_(self, other) object. \_\_le\_\_(self, other) object. \_\_eq\_\_(self, other) object. \_\_ne\_\_(self, other) object. \_\_gt\_\_(self, other) object. \_\_ge\_\_(self, other)

Answer 70

These are the so-called “rich comparison” methods. The correspondence between operator symbols and method names is as follows: xy calls x.__gt__(y), and x>=y calls x.__ge__(y). A rich comparison method may return the singleton NotImplemented if it does not implement the operation for a given pair of arguments. By convention, False and True are returned for a successful comparison. However, these methods can return any value, so if the comparison operator is used in a Boolean context (e.g., in the condition of an if statement), Python will call bool() on the value to determine if the result is true or false.

Question 71

“rich comparison” methods

Answer 71

By default, \_\_ne\_\_() delegates to \_\_eq\_\_() and inverts the result unless it is NotImplemented. There are no other implied relationships among the comparison operators, for example, the truth of (x

See the paragraph on __hash__() for some important notes on creating hashable objects which support custom comparison operations and are usable as dictionary keys.

```

There are no swapped-argument versions of these methods (to be used when the left argument does not support the operation but the right argument does); rather, __lt__() and __gt__() are each other’s reflection, __le__() and __ge__() are each other’s reflection, and __eq__() and __ne__() are their own reflection. If the operands are of different types, and right operand’s type is a direct or indirect subclass of the left operand’s type, the reflected method of the right operand has priority, otherwise the left operand’s method has priority. Virtual subclassing is not considered.

```

Question 72

object.\_\_hash\_\_(self)

Answer 72

Called by built-in function hash() and for operations on members of hashed collections including set, frozenset, and dict. \_\_hash\_\_() should return an integer. The only required property is that objects which compare equal have the same hash value; it is advised to mix together the hash values of the components of the object that also play a part in comparison of objects by packing them into a tuple and hashing the tuple.

Question 73

If a class does not define an \_\_eq\_\_() method it should not

Answer 73

define a \_\_hash\_\_() operation either; if it defines \_\_eq\_\_() but not \_\_hash\_\_(), its instances will not be usable as items in hashable collections. If a class defines mutable objects and implements an \_\_eq\_\_() method, it should not implement \_\_hash\_\_(), since the implementation of hashable collections requires that a key’s hash value is immutable (if the object’s hash value changes, it will be in the wrong hash bucket).

Question 74

User-defined classes have \_\_eq\_\_() and \_\_hash\_\_() methods by default;

Answer 74

with them, all objects compare unequal (except with themselves) and x.\_\_hash\_\_() returns an appropriate value such that x == y implies both that x is y and hash(x) == hash(y).

Question 75

A class that overrides \_\_eq\_\_() and does not define \_\_hash\_\_() will have

Answer 75

its \_\_hash\_\_() implicitly set to None. When the \_\_hash\_\_() method of a class is None, instances of the class will raise an appropriate TypeError when a program attempts to retrieve their hash value, and will also be correctly identified as unhashable when checking isinstance(obj, collections.abc.Hashable).

Question 76

If a class that overrides \_\_eq\_\_() needs to retain the implementation of \_\_hash\_\_() from a parent class

Answer 76

the interpreter must be told this explicitly by setting \_\_hash\_\_ = .__hash__.

Question 77

If a class that does not override \_\_eq\_\_() wishes to suppress hash support

Answer 77

it should include \_\_hash\_\_ = None in the class definition. A class which defines its own \_\_hash\_\_() that explicitly raises a TypeError would be incorrectly identified as hashable by an isinstance(obj,collections.abc.Hashable) call.

Question 78

By default, the \_\_hash\_\_() values of str, bytes and datetime objects are

Answer 78

“salted” with an unpredictable random value. Although they remain constant within an individual Python process, they are not predictable between repeated invocations of Python. This is intended to provide protection against a denial-of-service caused by carefully-chosen inputs that exploit the worst case performance of a dict insertion, O(n^2) complexity. Seehttp://www.ocert.org/advisories/ocert-2011-003.html for details. Changing hash values affects the iteration order of sets. Python has never made guarantees about this ordering (and it typically varies between 32-bit and 64-bit builds). See also PYTHONHASHSEED.

Question 79

object.\_\_bool\_\_(self)

Answer 79

Called to implement truth value testing and the built-in operation bool(); should return False or True. When this method is not defined, \_\_len\_\_() is called, if it is defined, and the object is considered true if its result is nonzero. If a class defines neither \_\_len\_\_() nor \_\_bool\_\_(), all its instances are considered true.

Question 80

object.\_\_getattr\_\_(self, name)

Answer 80

Called when the default attribute access fails with an AttributeError (either \_\_getattribute\_\_()raises an AttributeError because name is not an instance attribute or an attribute in the class tree for self; or \_\_get\_\_() of a name property raises AttributeError). This method should either return the (computed) attribute value or raise an AttributeError exception. Note that if the attribute is found through the normal mechanism, \_\_getattr\_\_() is not called. (This is an intentional asymmetry between \_\_getattr\_\_() and \_\_setattr\_\_().) This is done both for efficiency reasons and because otherwise \_\_getattr\_\_() would have no way to access other attributes of the instance. Note that at least for instance variables, you can fake total control by not inserting any values in the instance attribute dictionary (but instead inserting them in another object). See the \_\_getattribute\_\_() method below for a way to actually get total control over attribute access.

Question 81

object.\_\_getattribute\_\_(self, name)

Answer 81

Called unconditionally to implement attribute accesses for instances of the class. If the class also defines \_\_getattr\_\_(), the latter will not be called unless \_\_getattribute\_\_() either calls it explicitly or raises an AttributeError. This method should return the (computed) attribute value or raise an AttributeError exception. In order to avoid infinite recursion in this method, its implementation should always call the base class method with the same name to access any attributes it needs, for example, object.\_\_getattribute\_\_(self, name). Note: This method may still be bypassed when looking up special methods as the result of implicit invocation via language syntax or built-in functions. See Special method lookup.

Question 82

object.\_\_setattr\_\_(self, name, value)

Answer 82

Called when an attribute assignment is attempted. This is called instead of the normal mechanism (i.e. store the value in the instance dictionary). name is the attribute name, value is the value to be assigned to it. If \_\_setattr\_\_() wants to assign to an instance attribute, it should call the base class method with the same name, for example, object.\_\_setattr\_\_(self, name, value).

Question 83

object.\_\_delattr\_\_(self, name)

Answer 83

Like \_\_setattr\_\_() but for attribute deletion instead of assignment. This should only be implemented if del obj.name is meaningful for the object.

Question 84

object.\_\_dir\_\_(self)

Answer 84

Called when dir() is called on the object. A sequence must be returned. dir() converts the returned sequence to a list and sorts it.

Question 85

Customizing module attribute access

Answer 85

Special names \_\_getattr\_\_ and \_\_dir\_\_ can be also used to customize access to module attributes. The \_\_getattr\_\_ function at the module level should accept one argument which is the name of an attribute and return the computed value or raise an AttributeError. If an attribute is not found on a module object through the normal lookup, i.e. object.\_\_getattribute\_\_(), then \_\_getattr\_\_ is searched in the module \_\_dict\_\_ before raising an AttributeError. If found, it is called with the attribute name and the result is returned. The \_\_dir\_\_ function should accept no arguments, and return a list of strings that represents the names accessible on module. If present, this function overrides the standard dir() search on a module. For a more fine grained customization of the module behavior (setting attributes, properties, etc.), one can set the \_\_class\_\_ attribute of a module object to a subclass of types.ModuleType. For example: