Home > Articles > Programming > Python

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

This chapter is from the book

4.11 Inheritance As Classification

A common use for inheritance is the hierarchical classification of objects. Suppose there is one superclass that has many subclasses. Since all the subclasses have the same operations as their superclass, they can be used wherever the superclass is expected. The superclass, then, specifies what is common to all the subclasses, and the subclasses can indicate how they differ from the common characteristics. The superclass specifies the general kind of thing, and the subclasses specify variations. This fits in with how we define things. Actually, there are two common ways that we define things: using an abstract, Aristotelian definition or using a definition by reference to an example.

In an Aristotelian definition, we define a thing by the category of thing that it is and then by how it differs from the other things in that category. Using an Aristotelean definition, the superclass is the category of thing, and the methods and attributes in the subclass specify the differences from the category.

When you are using inheritance in this Aristotelian sense, the superclass is often an abstract class. An abstract class is something like a "bird," whereas the subclasses will be things like robins, penguins, and ostriches. An abstract class is not intended to be used itself to create objects, only to group together its subclasses, just as there is no instance of "bird" that is not some particular kind of bird.

When you implement an abstract class in Python, you often do not provide implementations for all the methods shared by members of the subclasses. Some methods have no behavior that is common to all instances.

AbstractSet, Figure 4–5, is an example of an abstract class. The superclass provides an interface that can have several implementations. The algorithms that use the objects don't need to know the implementation; they only need to know the interface. There are seven methods that are not defined in AbstractSet, but only in subclasses.

In other object-oriented languages like Java, AbstractSet would have to provide method signatures for the methods that are to be provided by the subclasses. Method signatures give the name of the method, the number and types of parameters, and the result type. The compiler needs this information to be able to compile calls to the methods.

In Python, there are no parameter types or result types to put in signatures, and methods are looked up at run-time. We did not have to put defs in AbstractSet for the seven methods. We did, however, put them in and made them all raise a NotImplementedError exception. If an instance of AbstractSet itself is created, a NotImplementedError will be raised when it is first used. If a subclass is coded without all the required methods, it will be raised as soon as a missing method is called. NotImplementedError was invented for precisely this purpose. It allows you to put defs for the required methods in the superclass, which is good for documentation, and it gives a more precise error message than that the attribute was not found. For an example of the error messages, here we create an instance of AbstractSet and try to call the copy() method and then to call a nonexistent remove() method.

>>> import AbstractSet
>>> x=AbstractSet.AbstractSet()
>>> x.copy()
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "AbstractSet.py", line 9, in copy
    def copy(self): raise NotImplementedError,"set.copy()"
NotImplementedError: set.copy()
>>> x.remove(1)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
AttributeError: 'AbstractSet' instance has no attribute 'remove'

So, if you are defining classes the way Aristotle suggested, you have an abstract superclass and you create concrete subclasses of it—"concrete" meaning that all the details are filled in, all the methods are defined. But that's not the way we usually understand things. Mentally, we usually use a paradigm, an example instance, and relate other things to it. For example, most people in the U.S. seem to use the robin as a paradigmatic bird. Other birds are considered birds because they resemble robins: feathers, beaks, wings, nests, eggs, flying, and soon. What about penguins and ostriches? Well, they are a lot like robins—feathers, wings, beaks—but penguins swim instead of flying and they aren't big on nests. Ostriches run.

When you program using a paradigmatic definition, you use a concrete superclass that represents the example object, and concrete subclasses that represent the related things.

Would that have worked with ListSet and DictSet?

If we made ListSet the paradigm, it would try to have its own list, and then the DictSet would override that with its own dictionary. If we used different attribute names for the data structures, then each instance of a DictSet would have both a list and a dictionary. But we programmed both of them to use the attribute name rep for their data structures. That would save space in DictSet, since it could override ListSet's list with its own dictionary.

But is that safe? ListSet contains code that assumes it's manipulating a list. If any of that code is executed, the program will crash. So DictSet would have to override all of ListSet's list manipulation code. We wrote ListSet and DictSet in such a way that that could happen. All the data structure specific code is in separate methods that can be overridden. If we had been writing ListSet in isolation, would we have done that? Would we have been so careful? Probably not. And if we weren't careful, we would have to override all the methods, rather than being able to share code for union and intersection and the others. And even if there were a few methods in ListSet that didn't need to be overridden, would it be safe to use them? If someone changed the implementation of ListSet, it could break our code. In this case, at least, where we are providing different implementations, an AbstractSet class, designed to be overridden, is much better choice.

In Python, we can get around all this discussion of whether to inherit from an abstract superclass or a concrete one. We do not have to inherit at all. All we have to do is provide classes with the proper interface, the proper collection of methods. To adapt an old saying, if it looks like a duck and walks like a duck and quacks like a duck, I don't care whether it "really" is a duck: I'll treat it like a duck.

  • + 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