面向对象编程的实践
有个产品，其有10个子产品，现在要统计每日消费数据
其中8个子产品的消费入账金额算法相同，2个不同;
拓展性差的糟糕的代码
def ConsumptionSum(product):
product_id = product.get(product)
if product == 'p1':
return p1CS()
if product == 'p2':
return p2CS()
PEP 245 -- Python Interface Syntax | Python.org https://www.python.org/dev/peps/pep-0245/
PEP 245 -- Python Interface Syntax
| PEP: | 245 |
|---|---|
| Title: | Python Interface Syntax |
| Author: | Michel Pelletier <michel at users.sourceforge.net> |
| Discussions-To: | http://www.zope.org/Wikis/Interfaces |
| Status: | Rejected |
| Type: | Standards Track |
| Created: | 11-Jan-2001 |
| Python-Version: | 2.2 |
| Post-History: | 21-Mar-2001 |
Formal Interface Syntax
Python syntax is defined in a modified BNF grammar notation described in the Python Reference Manual [8]. This section describes the proposed interface syntax using this grammar:
interfacedef: "interface" interfacename [extends] ":" suite
extends: "(" [expression_list] ")"
interfacename: identifier
This PEP also proposes an extension to Python's 'class' statement:
classdef: "class" classname [inheritance] [implements] ":" suite implements: "implements" implist implist: expression-list classname, inheritance, suite, expression-list: see the Python Reference Manual
The Problem
Interfaces are important because they solve a number of problems that arise while developing software:
- There are many implied interfaces in Python, commonly referred to as "protocols". Currently determining those protocols is based on implementation introspection, but often that also fails. For example, defining __getitem__ implies both a sequence and a mapping (the former with sequential, integer keys). There is no way for the developer to be explicit about which protocols the object intends to implement.
- Python is limited, from the developer's point of view, by the split between types and classes. When types are expected, the consumer uses code like 'type(foo) == type("")' to determine if 'foo' is a string. When instances of classes are expected, the consumer uses 'isinstance(foo, MyString)' to determine if 'foo' is an instance of the 'MyString' class. There is no unified model for determining if an object can be used in a certain, valid way.
- Python's dynamic typing is very flexible and powerful, but it does not have the advantage of static typed languages that provide type checking. Static typed languages provide you with much more type safety, but are often overly verbose because objects can only be generalized by common subclassing and used specifically with casting (for example, in Java).
There are also a number of documentation problems that interfaces try to solve.
- Developers waste a lot of time looking at the source code of your system to figure out how objects work.
- Developers who are new to your system may misunderstand how your objects work, causing, and possibly propagating, usage errors.
- Because a lack of interfaces means usage is inferred from the source, developers may end up using methods and attributes that are meant for "internal use only".
- Code inspection can be hard, and very discouraging to novice programmers trying to properly understand code written by gurus.
- A lot of time is wasted when many people try very hard to understand obscurity (like undocumented software). Effort spend up front documenting interfaces will save much of this time in the end.
Interfaces try to solve these problems by providing a way for you to specify a contractual obligation for your object, documentation on how to use an object, and a built-in mechanism for discovering the contract and the documentation.
Python has very useful introspection features. It is well known that this makes exploring concepts in the interactive interpreter easier, because Python gives you the ability to look at all kinds of information about the objects: the type, doc strings, instance dictionaries, base classes, unbound methods and more.
Many of these features are oriented toward introspecting, using and changing the implementation of software, and one of them ("doc strings") is oriented toward providing documentation. This proposal describes an extension to this natural introspection framework that describes an object's interface.
Overview of the Interface Syntax
For the most part, the syntax of interfaces is very much like the syntax of classes, but future needs, or needs brought up in discussion, may define new possibilities for interface syntax.
A formal BNF description of the syntax is givena later in the PEP, for the purposes of illustration, here is an example of two different interfaces created with the proposed syntax:
interface CountFishInterface:
"Fish counting interface"
def oneFish():
"Increments the fish count by one"
def twoFish():
"Increments the fish count by two"
def getFishCount():
"Returns the fish count"
interface ColorFishInterface:
"Fish coloring interface"
def redFish():
"Sets the current fish color to red"
def blueFish():
"Sets the current fish color to blue"
def getFishColor():
"This returns the current fish color"
This code, when evaluated, will create two interfaces called CountFishInterface and ColorFishInterface. These interfaces are defined by the interface statement.
The prose documentation for the interfaces and their methods come from doc strings. The method signature information comes from the signatures of the def statements. Notice how there is no body for the def statements. The interface does not implement a service to anything; it merely describes one. Documentation strings on interfaces and interface methods are mandatory, a 'pass' statement cannot be provided. The interface equivalent of a pass statement is an empty doc string.
You can also create interfaces that "extend" other interfaces. Here, you can see a new type of Interface that extends the CountFishInterface and ColorFishInterface:
interface FishMarketInterface(CountFishInterface, ColorFishInterface):
"This is the documentation for the FishMarketInterface"
def getFishMonger():
"Returns the fish monger you can interact with"
def hireNewFishMonger(name):
"Hire a new fish monger"
def buySomeFish(quantity=1):
"Buy some fish at the market"
The FishMarketInteface extends upon the CountFishInterface and ColorfishInterface.
Interface Assertion
The next step is to put classes and interfaces together by creating a concrete Python class that asserts that it implements an interface. Here is an example FishMarket component that might do this:
class FishError(Error):
pass
class FishMarket implements FishMarketInterface:
number = 0
color = None
monger_name = 'Crusty Barnacles'
def __init__(self, number, color):
self.number = number
self.color = color
def oneFish(self):
self.number += 1
def twoFish(self):
self.number += 2
def redFish(self):
self.color = 'red'
def blueFish(self):
self.color = 'blue'
def getFishCount(self):
return self.number
def getFishColor(self):
return self.color
def getFishMonger(self):
return self.monger_name
def hireNewFishMonger(self, name):
self.monger_name = name
def buySomeFish(self, quantity=1):
if quantity > self.count:
raise FishError("There's not enough fish")
self.count -= quantity
return quantity