Home > Articles > Programming > Python

  • Print
  • + Share This
This chapter is from the book

Built-in Types for Representing Program Structure

In Python, functions, classes, and modules are all objects that can be manipulated as data. Table 3.9 shows types that are used to represent various elements of a program itself.

Table 3.9 Built-in Python Types for Program Structure

Type Category

Type Name

Description

Callable

types.BuiltinFunctionType

Built-in function or method

type

Type of built-in types and classes

object

Ancestor of all types and classes

types.FunctionType

User-defined function

types.MethodType

Class method

Modules

types.ModuleType

Module

Classes

object

Ancestor of all types and classes

Types

type

Type of built-in types and classes

Note that object and type appear twice in Table 3.9 because classes and types are both callable as a function.

Callable Types

Callable types represent objects that support the function call operation. There are several flavors of objects with this property, including user-defined functions, built-in functions, instance methods, and classes.

User-Defined Functions

User-defined functions are callable objects created at the module level by using the def statement or with the lambda operator. Here’s an example:

def foo(x,y):
    return x + y

bar = lambda x,y: x + y

A user-defined function f has the following attributes:

Attribute(s)

Description

f.__doc__

Documentation string

f.__name__

Function name

f.__dict__

Dictionary containing function attributes

f.__code__

Byte-compiled code

f.__defaults__

Tuple containing the default arguments

f.__globals__

Dictionary defining the global namespace

f.__closure__

Tuple containing data related to nested scopes

In older versions of Python 2, many of the preceding attributes had names such as func_code, func_defaults, and so on. The attribute names listed are compatible with Python 2.6 and Python 3.

Methods

Methods are functions that are defined inside a class definition. There are three common types of methods—instance methods, class methods, and static methods:

class Foo(object):
    def instance_method(self,arg):
        statements
    @classmethod
    def class_method(cls,arg):
        statements
    @staticmethod
    def static_method(arg):
        statements

An instance method is a method that operates on an instance belonging to a given class. The instance is passed to the method as the first argument, which is called self by convention. A class method operates on the class itself as an object. The class object is passed to a class method in the first argument, cls. A static method is a just a function that happens to be packaged inside a class. It does not receive an instance or a class object as a first argument.

Both instance and class methods are represented by a special object of type types.MethodType. However, understanding this special type requires a careful understanding of how object attribute lookup (.) works. The process of looking something up on an object (.) is always a separate operation from that of making a function call. When you invoke a method, both operations occur, but as distinct steps. This example illustrates the process of invoking f.instance_method(arg) on an instance of Foo in the preceding listing:

f = Foo()                 # Create an instance
meth = f.instance_method  # Lookup the method and notice the lack of ()
meth(37)                  # Now call the method

In this example, meth is known as a bound method. A bound method is a callable object that wraps both a function (the method) and an associated instance. When you call a bound method, the instance is passed to the method as the first parameter (self). Thus, meth in the example can be viewed as a method call that is primed and ready to go but which has not been invoked using the function call operator ().

Method lookup can also occur on the class itself. For example:

umeth = Foo.instance_method   # Lookup instance_method on Foo
umeth(f,37)                   # Call it, but explicitly supply self

In this example, umeth is known as an unbound method. An unbound method is a callable object that wraps the method function, but which expects an instance of the proper type to be passed as the first argument. In the example, we have passed f, a an instance of Foo, as the first argument. If you pass the wrong kind of object, you get a TypeError. For example:

>>> umeth("hello",5)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: descriptor 'instance_method' requires a 'Foo' object but received a
'str'
>>>

For user-defined classes, bound and unbound methods are both represented as an object of type types.MethodType, which is nothing more than a thin wrapper around an ordinary function object. The following attributes are defined for method objects:

Attribute

Description

m.__doc__

Documentation string

m.__name__

Method name

m.__class__

Class in which this method was defined

m.__func__

Function object implementing the method

m.__self__

Instance associated with the method (None if unbound)

One subtle feature of Python 3 is that unbound methods are no longer wrapped by a types.MethodType object. If you access Foo.instance_method as shown in earlier examples, you simply obtain the raw function object that implements the method. Moreover, you’ll find that there is no longer any type checking on the self parameter.

Built-in Functions and Methods

The object types.BuiltinFunctionType is used to represent functions and methods implemented in C and C++. The following attributes are available for built-in methods:

Attribute

Description

b.__doc__

Documentation string

b.__name__

Function/method name

b.__self__

Instance associated with the method (if bound)

For built-in functions such as len(), __self__ is set to None, indicating that the function isn’t bound to any specific object. For built-in methods such as x.append, where x is a list object, __self__ is set to x.

Classes and Instances as Callables

Class objects and instances also operate as callable objects. A class object is created by the class statement and is called as a function in order to create new instances. In this case, the arguments to the function are passed to the __init__() method of the class in order to initialize the newly created instance. An instance can emulate a function if it defines a special method, __call__(). If this method is defined for an instance, x, then x(args) invokes the method x.__call__(args).

Classes, Types, and Instances

When you define a class, the class definition normally produces an object of type type. Here’s an example:

>>> class Foo(object):
...    pass
...
>>> type(Foo)
<type 'type'>

The following table shows commonly used attributes of a type object t:

Attribute

Description

t.__doc__

Documentation string

t.__name__

Class name

t.__bases__

Tuple of base classes

t.__dict__

Dictionary holding class methods and variables

t.__module__

Module name in which the class is defined

t.__abstractmethods__

Set of abstract method names (may be undefined if there aren’t any)

When an object instance is created, the type of the instance is the class that defined it. Here’s an example:

>>> f = Foo()
>>> type(f)
<class '__main__.Foo'>

The following table shows special attributes of an instance i:

Attribute

Description

i.__class__

Class to which the instance belongs

i.__dict__

Dictionary holding instance data

The __dict__ attribute is normally where all of the data associated with an instance is stored. When you make assignments such as i.attr = value, the value is stored here. However, if a user-defined class uses __slots__, a more efficient internal representation is used and instances will not have a __dict__ attribute. More details on objects and the organization of the Python object system can be found in Chapter 7.

Modules

The module type is a container that holds objects loaded with the import statement. When the statement import foo appears in a program, for example, the name foo is assigned to the corresponding module object. Modules define a namespace that’s implemented using a dictionary accessible in the attribute __dict__. Whenever an attribute of a module is referenced (using the dot operator), it’s translated into a dictionary lookup. For example, m.x is equivalent to m.__dict__["x"]. Likewise, assignment to an attribute such as m.x = y is equivalent to m.__dict__["x"] = y. The following attributes are available:

Attribute

Description

m.__dict__

Dictionary associated with the module

m.__doc__

Module documentation string

m.__name__

Name of the module

m.__file__

File from which the module was loaded

m.__path__

Fully qualified package name, only defined when the module object refers to a package

  • + Share This
  • 🔖 Save To Your Account

InformIT Promotional Mailings & Special Offers

I would like to receive exclusive offers and hear about products from InformIT and its family of brands. I can unsubscribe at any time.

Overview


Pearson Education, Inc., 221 River Street, Hoboken, New Jersey 07030, (Pearson) presents this site to provide information about products and services that can be purchased through this site.

This privacy notice provides an overview of our commitment to privacy and describes how we collect, protect, use and share personal information collected through this site. Please note that other Pearson websites and online products and services have their own separate privacy policies.

Collection and Use of Information


To conduct business and deliver products and services, Pearson collects and uses personal information in several ways in connection with this site, including:

Questions and Inquiries

For inquiries and questions, we collect the inquiry or question, together with name, contact details (email address, phone number and mailing address) and any other additional information voluntarily submitted to us through a Contact Us form or an email. We use this information to address the inquiry and respond to the question.

Online Store

For orders and purchases placed through our online store on this site, we collect order details, name, institution name and address (if applicable), email address, phone number, shipping and billing addresses, credit/debit card information, shipping options and any instructions. We use this information to complete transactions, fulfill orders, communicate with individuals placing orders or visiting the online store, and for related purposes.

Surveys

Pearson may offer opportunities to provide feedback or participate in surveys, including surveys evaluating Pearson products, services or sites. Participation is voluntary. Pearson collects information requested in the survey questions and uses the information to evaluate, support, maintain and improve products, services or sites, develop new products and services, conduct educational research and for other purposes specified in the survey.

Contests and Drawings

Occasionally, we may sponsor a contest or drawing. Participation is optional. Pearson collects name, contact information and other information specified on the entry form for the contest or drawing to conduct the contest or drawing. Pearson may collect additional personal information from the winners of a contest or drawing in order to award the prize and for tax reporting purposes, as required by law.

Newsletters

If you have elected to receive email newsletters or promotional mailings and special offers but want to unsubscribe, simply email information@informit.com.

Service Announcements

On rare occasions it is necessary to send out a strictly service related announcement. For instance, if our service is temporarily suspended for maintenance we might send users an email. Generally, users may not opt-out of these communications, though they can deactivate their account information. However, these communications are not promotional in nature.

Customer Service

We communicate with users on a regular basis to provide requested services and in regard to issues relating to their account we reply via email or phone in accordance with the users' wishes when a user submits their information through our Contact Us form.

Other Collection and Use of Information


Application and System Logs

Pearson automatically collects log data to help ensure the delivery, availability and security of this site. Log data may include technical information about how a user or visitor connected to this site, such as browser type, type of computer/device, operating system, internet service provider and IP address. We use this information for support purposes and to monitor the health of the site, identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents and appropriately scale computing resources.

Web Analytics

Pearson may use third party web trend analytical services, including Google Analytics, to collect visitor information, such as IP addresses, browser types, referring pages, pages visited and time spent on a particular site. While these analytical services collect and report information on an anonymous basis, they may use cookies to gather web trend information. The information gathered may enable Pearson (but not the third party web trend services) to link information with application and system log data. Pearson uses this information for system administration and to identify problems, improve service, detect unauthorized access and fraudulent activity, prevent and respond to security incidents, appropriately scale computing resources and otherwise support and deliver this site and its services.

Cookies and Related Technologies

This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Users can manage and block the use of cookies through their browser. Disabling or blocking certain cookies may limit the functionality of this site.

Do Not Track

This site currently does not respond to Do Not Track signals.

Security


Pearson uses appropriate physical, administrative and technical security measures to protect personal information from unauthorized access, use and disclosure.

Children


This site is not directed to children under the age of 13.

Marketing


Pearson may send or direct marketing communications to users, provided that

  • Pearson will not use personal information collected or processed as a K-12 school service provider for the purpose of directed or targeted advertising.
  • Such marketing is consistent with applicable law and Pearson's legal obligations.
  • Pearson will not knowingly direct or send marketing communications to an individual who has expressed a preference not to receive marketing.
  • Where required by applicable law, express or implied consent to marketing exists and has not been withdrawn.

Pearson may provide personal information to a third party service provider on a restricted basis to provide marketing solely on behalf of Pearson or an affiliate or customer for whom Pearson is a service provider. Marketing preferences may be changed at any time.

Correcting/Updating Personal Information


If a user's personally identifiable information changes (such as your postal address or email address), we provide a way to correct or update that user's personal data provided to us. This can be done on the Account page. If a user no longer desires our service and desires to delete his or her account, please contact us at customer-service@informit.com and we will process the deletion of a user's account.

Choice/Opt-out


Users can always make an informed choice as to whether they should proceed with certain services offered by InformIT. If you choose to remove yourself from our mailing list(s) simply visit the following page and uncheck any communication you no longer want to receive: www.informit.com/u.aspx.

Sale of Personal Information


Pearson does not rent or sell personal information in exchange for any payment of money.

While Pearson does not sell personal information, as defined in Nevada law, Nevada residents may email a request for no sale of their personal information to NevadaDesignatedRequest@pearson.com.

Supplemental Privacy Statement for California Residents


California residents should read our Supplemental privacy statement for California residents in conjunction with this Privacy Notice. The Supplemental privacy statement for California residents explains Pearson's commitment to comply with California law and applies to personal information of California residents collected in connection with this site and the Services.

Sharing and Disclosure


Pearson may disclose personal information, as follows:

  • As required by law.
  • With the consent of the individual (or their parent, if the individual is a minor)
  • In response to a subpoena, court order or legal process, to the extent permitted or required by law
  • To protect the security and safety of individuals, data, assets and systems, consistent with applicable law
  • In connection the sale, joint venture or other transfer of some or all of its company or assets, subject to the provisions of this Privacy Notice
  • To investigate or address actual or suspected fraud or other illegal activities
  • To exercise its legal rights, including enforcement of the Terms of Use for this site or another contract
  • To affiliated Pearson companies and other companies and organizations who perform work for Pearson and are obligated to protect the privacy of personal information consistent with this Privacy Notice
  • To a school, organization, company or government agency, where Pearson collects or processes the personal information in a school setting or on behalf of such organization, company or government agency.

Links


This web site contains links to other sites. Please be aware that we are not responsible for the privacy practices of such other sites. We encourage our users to be aware when they leave our site and to read the privacy statements of each and every web site that collects Personal Information. This privacy statement applies solely to information collected by this web site.

Requests and Contact


Please contact us about this Privacy Notice or if you have any requests or questions relating to the privacy of your personal information.

Changes to this Privacy Notice


We may revise this Privacy Notice through an updated posting. We will identify the effective date of the revision in the posting. Often, updates are made to provide greater clarity or to comply with changes in regulatory requirements. If the updates involve material changes to the collection, protection, use or disclosure of Personal Information, Pearson will provide notice of the change through a conspicuous notice on this site or other appropriate way. Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions.

Last Update: November 17, 2020