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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Use inheritance when a class is genuinely a more specific kind of another class and can honor its behavior. Use composition when an object should hold another object and delegate a responsibility to it. In Python, both patterns are available; the right choice depends on the relationship and how you expect behavior to vary.
What inheritance and composition mean
Inheritance: an “is-a” relationship
Inheritance defines a new class from one or more base classes. The derived class can use inherited attributes and methods, and it can override methods to provide specialized behavior. For example, a CsvExporter can inherit from Exporter if it is an exporter and can meet the behavior clients expect from any Exporter.
Python classes can have multiple base classes. Attribute and method lookup follows the method resolution order (MRO), which also determines how cooperative calls to super() proceed. In a multiple-inheritance design, super() does not simply mean “call my parent”; it continues to the next applicable class in the MRO. See the Python 3.14.8 Classes tutorial for the language’s inheritance and overriding mechanics.
Composition: a “has-a” relationship
Composition means a containing object keeps one or more component objects as attributes. Delegation is the act of asking a component to perform work. A Report, for instance, can have a formatter and delegate rendering to it rather than implementing every formatting strategy itself.
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Use composition to vary a responsibility
Here, Report receives a formatter object and calls its format method. Any suitable formatter can be supplied, so you do not need a subclass for each report-and-formatter combination.
class JsonFormatter:
def format(self, data):
import json
return json.dumps(data)
class Report:
def __init__(self, formatter):
self.formatter = formatter # Report has a formatter
def render(self, data):
return self.formatter.format(data) # Report delegates formatting
The caller can supply a different object with a compatible format(data) method. The object does not have to inherit from a particular formatter class for this call to work. Python’s tutorial illustrates the same general idea with file-like objects: code can work with an object that provides the expected methods, such as read() and readline(). See the Python 3.14.7 Classes tutorial.
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Use inheritance for a real, substitutable subtype
Inheritance is a good fit when the new type really is a specialized version of the base type, and code using the base type can use the subclass without being surprised by changed behavior. For example, a CsvReport could inherit from Report if it remains a report and honors the expectations established by Report.
class CsvReport(Report):
# Appropriate only if this remains usable wherever a Report is expected.
pass
Do not choose inheritance solely because it is a convenient way to reuse a method. If a subclass cannot preserve the base class’s expected behavior, the “is-a” relationship is weak even though Python allows the subclass to override methods.
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Choose between the patterns
Use these questions to make the choice for a particular design:
- Is the subtype claim true? If callers should be able to use the new class wherever they use the base class, and the new class preserves the base behavior, inheritance may express the design clearly.
- Are you varying one responsibility? If formatting, storage, or another task should be replaceable, keep a collaborator as an attribute and delegate that task to it.
- Will feature combinations multiply? If each combination would otherwise require another subclass, independent components can avoid a sprawling inheritance tree.
- Is the base class’s contract clear? Inheritance works best when its expected behavior is understood and subclasses can honor it.
- Does the design need multiple inheritance? Python supports it, but account for MRO and cooperative
super()calls before building a diamond-shaped hierarchy.
“Favor composition over inheritance” is a useful prompt to consider coupling and replaceability, not a universal Python rule. Inheritance makes subtype behavior and polymorphic overrides direct; composition makes collaborators easier to replace or combine. These are design trade-offs, not a requirement imposed by the language.
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Keep component state on the right object
With composition, an attribute such as self.formatter makes the collaborator associated with each Report instance explicit. Put per-instance mutable state, such as a list that each instance should change independently, on self in __init__. A mutable class attribute is shared by instances, so use one only when that shared state is intentional. The Python Classes tutorial explains class and instance variables.
Python does not require a formal interface for the formatter example: the relevant expectation is that the supplied object has the method the code calls. Names with leading underscores signal intended internal use by convention rather than enforcing strict data hiding. For class syntax and the rule that a class without an explicit base list inherits from object, see the Python 3.12 language reference. For the has-a relationship and delegation terminology, see Inheritance and composition.
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