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🛁 Clean Code concepts adapted for Python

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kticoder/clean-code-python

 
 

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Table of Contents

  1. Introduction
  2. Variables
  3. Functions
  4. Classes
    1. S: Single Responsibility Principle (SRP)
    2. O: Open/Closed Principle (OCP)
    3. L: Liskov Substitution Principle (LSP)
    4. I: Interface Segregation Principle (ISP)
    5. D: Dependency Inversion Principle (DIP)
  5. Don't repeat yourself (DRY)
  6. Translations

Introduction

Software engineering principles, from Robert C. Martin's bookClean Code,adapted for Python. This is not a style guide. It's a guide to producingreadable, reusable, and refactorable software in Python.

Not every principle herein has to be strictly followed, and even fewer will be universallyagreed upon. These are guidelines and nothing more, but they are ones codified over manyyears of collective experience by the authors ofClean Code.

Inspired fromclean-code-javascript

Targets Python3.7+

Variables

Use meaningful and pronounceable variable names

Bad:

importdatetimeymdstr=datetime.date.today().strftime("%y-%m-%d")

Additionally, there's no need to add the type of the variable (str) to its name.

Good:

importdatetimecurrent_date:str=datetime.date.today().strftime("%y-%m-%d")

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Use the same vocabulary for the same type of variable

Bad:Here we use three different names for the same underlying entity:

defget_user_info():passdefget_client_data():passdefget_customer_record():pass

Good:If the entity is the same, you should be consistent in referring to it in your functions:

defget_user_info():passdefget_user_data():passdefget_user_record():pass

Even betterPython is (also) an object oriented programming language. If it makes sense, package the functions together with the concrete implementationof the entity in your code, as instance attributes, property methods, or methods:

fromtypingimportUnion,DictclassRecord:passclassUser:info :str@propertydefdata(self)->Dict[str,str]:return {}defget_record(self)->Union[Record,None]:returnRecord()

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Use searchable names

We will read more code than we will ever write. It's important that the code we do write isreadable and searchable. Bynot naming variables that end up being meaningful forunderstanding our program, we hurt our readers.Make your names searchable.

Bad:

importtime# What is the number 86400 for again?time.sleep(86400)

Good:

importtime# Declare them in the global namespace for the module.SECONDS_IN_A_DAY=60*60*24time.sleep(SECONDS_IN_A_DAY)

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Use explanatory variables

Bad:

importreaddress="One Infinite Loop, Cupertino 95014"city_zip_code_regex=r"^[^,\\]+[,\\\s]+(.+?)\s*(\d{5})?$"matches=re.match(city_zip_code_regex,address)ifmatches:print(f"{matches[1]}:{matches[2]}")

Not bad:

It's better, but we are still heavily dependent on regex.

importreaddress="One Infinite Loop, Cupertino 95014"city_zip_code_regex=r"^[^,\\]+[,\\\s]+(.+?)\s*(\d{5})?$"matches=re.match(city_zip_code_regex,address)ifmatches:city,zip_code=matches.groups()print(f"{city}:{zip_code}")

Good:

Decrease dependence on regex by naming subpatterns.

importreaddress="One Infinite Loop, Cupertino 95014"city_zip_code_regex=r"^[^,\\]+[,\\\s]+(?P<city>.+?)\s*(?P<zip_code>\d{5})?$"matches=re.match(city_zip_code_regex,address)ifmatches:print(f"{matches['city']},{matches['zip_code']}")

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Avoid Mental Mapping

Don’t force the reader of your code to translate what the variable means.Explicit is better than implicit.

Bad:

seq= ("Austin","New York","San Francisco")foriteminseq:#do_stuff()#do_some_other_stuff()# Wait, what's `item` again?print(item)

Good:

locations= ("Austin","New York","San Francisco")forlocationinlocations:#do_stuff()#do_some_other_stuff()# ...print(location)

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Don't add unneeded context

If your class/object name tells you something, don't repeat that in yourvariable name.

Bad:

classCar:car_make:strcar_model:strcar_color:str

Good:

classCar:make:strmodel:strcolor:str

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Use default arguments instead of short circuiting or conditionals

Tricky

Why write:

importhashlibdefcreate_micro_brewery(name):name="Hipster Brew Co."ifnameisNoneelsenameslug=hashlib.sha1(name.encode()).hexdigest()# etc.

... when you can specify a default argument instead? This also makes it clear thatyou are expecting a string as the argument.

Good:

importhashlibdefcreate_micro_brewery(name:str="Hipster Brew Co."):slug=hashlib.sha1(name.encode()).hexdigest()# etc.

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Functions

Function arguments (2 or fewer ideally)

Limiting the amount of function parameters is incredibly important because it makestesting your function easier. Having more than three leads to a combinatorial explosionwhere you have to test tons of different cases with each separate argument.

Zero arguments is the ideal case. One or two arguments is ok, and three should be avoided.Anything more than that should be consolidated. Usually, if you have more than twoarguments then your function is trying to do too much. In cases where it's not, mostof the time a higher-level object will suffice as an argument.

Bad:

defcreate_menu(title,body,button_text,cancellable):pass

Java-esque:

classMenu:def__init__(self,config:dict):self.title=config["title"]self.body=config["body"]# ...menu=Menu(    {"title":"My Menu","body":"Something about my menu","button_text":"OK","cancellable":False    })

Also good

classMenuConfig:"""A configuration for the Menu.    Attributes:        title: The title of the Menu.        body: The body of the Menu.        button_text: The text for the button label.        cancellable: Can it be cancelled?    """title:strbody:strbutton_text:strcancellable:bool=Falsedefcreate_menu(config:MenuConfig)->None:title=config.titlebody=config.body# ...config=MenuConfig()config.title="My delicious menu"config.body="A description of the various items on the menu"config.button_text="Order now!"# The instance attribute overrides the default class attribute.config.cancellable=Truecreate_menu(config)

Fancy

fromtypingimportNamedTupleclassMenuConfig(NamedTuple):"""A configuration for the Menu.    Attributes:        title: The title of the Menu.        body: The body of the Menu.        button_text: The text for the button label.        cancellable: Can it be cancelled?    """title:strbody:strbutton_text:strcancellable:bool=Falsedefcreate_menu(config:MenuConfig):title,body,button_text,cancellable=config# ...create_menu(MenuConfig(title="My delicious menu",body="A description of the various items on the menu",button_text="Order now!"    ))

Even fancier

fromdataclassesimportastuple,dataclass@dataclassclassMenuConfig:"""A configuration for the Menu.    Attributes:        title: The title of the Menu.        body: The body of the Menu.        button_text: The text for the button label.        cancellable: Can it be cancelled?    """title:strbody:strbutton_text:strcancellable:bool=Falsedefcreate_menu(config:MenuConfig):title,body,button_text,cancellable=astuple(config)# ...create_menu(MenuConfig(title="My delicious menu",body="A description of the various items on the menu",button_text="Order now!"    ))

Even fancier, Python3.8+ only

fromtypingimportTypedDictclassMenuConfig(TypedDict):"""A configuration for the Menu.    Attributes:        title: The title of the Menu.        body: The body of the Menu.        button_text: The text for the button label.        cancellable: Can it be cancelled?    """title:strbody:strbutton_text:strcancellable:booldefcreate_menu(config:MenuConfig):title=config["title"]# ...create_menu(# You need to supply all the parametersMenuConfig(title="My delicious menu",body="A description of the various items on the menu",button_text="Order now!",cancellable=True    ))

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Functions should do one thing

This is by far the most important rule in software engineering. When functions do morethan one thing, they are harder to compose, test, and reason about. When you can isolatea function to just one action, they can be refactored easily and your code will read muchcleaner. If you take nothing else away from this guide other than this, you'll be aheadof many developers.

Bad:

fromtypingimportListclassClient:active:booldefemail(client:Client)->None:passdefemail_clients(clients:List[Client])->None:"""Filter active clients and send them an email.    """forclientinclients:ifclient.active:email(client)

Good:

fromtypingimportListclassClient:active:booldefemail(client:Client)->None:passdefget_active_clients(clients:List[Client])->List[Client]:"""Filter active clients.    """return [clientforclientinclientsifclient.active]defemail_clients(clients:List[Client])->None:"""Send an email to a given list of clients.    """forclientinget_active_clients(clients):email(client)

Do you see an opportunity for using generators now?

Even better

fromtypingimportGenerator,IteratorclassClient:active:booldefemail(client:Client):passdefactive_clients(clients:Iterator[Client])->Generator[Client,None,None]:"""Only active clients"""return (clientforclientinclientsifclient.active)defemail_client(clients:Iterator[Client])->None:"""Send an email to a given list of clients.    """forclientinactive_clients(clients):email(client)

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Function names should say what they do

Bad:

classEmail:defhandle(self)->None:passmessage=Email()# What is this supposed to do again?message.handle()

Good:

classEmail:defsend(self)->None:"""Send this message"""message=Email()message.send()

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Functions should only be one level of abstraction

When you have more than one level of abstraction, your function is usually doing toomuch. Splitting up functions leads to reusability and easier testing.

Bad:

# type: ignoredefparse_better_js_alternative(code:str)->None:regexes= [# ...    ]statements=code.split('\n')tokens= []forregexinregexes:forstatementinstatements:passast= []fortokenintokens:passfornodeinast:pass

Good:

fromtypingimportTuple,List,DictREGEXES:Tuple= (# ...)defparse_better_js_alternative(code:str)->None:tokens:List=tokenize(code)syntax_tree:List=parse(tokens)fornodeinsyntax_tree:passdeftokenize(code:str)->List:statements=code.split()tokens:List[Dict]= []forregexinREGEXES:forstatementinstatements:passreturntokensdefparse(tokens:List)->List:syntax_tree:List[Dict]= []fortokenintokens:passreturnsyntax_tree

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Don't use flags as function parameters

Flags tell your user that this function does more than one thing. Functionsshould do one thing. Split your functions if they are following different codepaths based on a boolean.

Bad:

fromtempfileimportgettempdirfrompathlibimportPathdefcreate_file(name:str,temp:bool)->None:iftemp:        (Path(gettempdir())/name).touch()else:Path(name).touch()

Good:

fromtempfileimportgettempdirfrompathlibimportPathdefcreate_file(name:str)->None:Path(name).touch()defcreate_temp_file(name:str)->None:    (Path(gettempdir())/name).touch()

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Avoid side effects

A function produces a side effect if it does anything other than take a value inand return another value or values. For example, a side effect could be writingto a file, modifying some global variable, or accidentally wiring all your moneyto a stranger.

Now, you do need to have side effects in a program on occasion - for example, likein the previous example, you might need to write to a file. In these cases, youshould centralize and indicate where you are incorporating side effects. Don't haveseveral functions and classes that write to a particular file - rather, have one(and only one) service that does it.

The main point is to avoid common pitfalls like sharing state between objectswithout any structure, using mutable data types that can be written to by anything,or using an instance of a class, and not centralizing where your side effects occur.If you can do this, you will be happier than the vast majority of other programmers.

Bad:

# type: ignore# This is a module-level name.# It's good practice to define these as immutable values, such as a string.# However...fullname="Ryan McDermott"defsplit_into_first_and_last_name()->None:# The use of the global keyword here is changing the meaning of the# the following line. This function is now mutating the module-level# state and introducing a side-effect!globalfullnamefullname=fullname.split()split_into_first_and_last_name()# MyPy will spot the problem, complaining about 'Incompatible types in# assignment: (expression has type "List[str]", variable has type "str")'print(fullname)# ["Ryan", "McDermott"]# OK. It worked the first time, but what will happen if we call the# function again?

Good:

fromtypingimportList,AnyStrdefsplit_into_first_and_last_name(name:AnyStr)->List[AnyStr]:returnname.split()fullname="Ryan McDermott"name,surname=split_into_first_and_last_name(fullname)print(name,surname)# => Ryan McDermott

Also good

fromdataclassesimportdataclass@dataclassclassPerson:name:str@propertydefname_as_first_and_last(self)->list:returnself.name.split()# The reason why we create instances of classes is to manage state!person=Person("Ryan McDermott")print(person.name)# => "Ryan McDermott"print(person.name_as_first_and_last)# => ["Ryan", "McDermott"]

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Classes

Single Responsibility Principle (SRP)

Robert C. Martin writes:

A class should have only one reason to change.

"Reasons to change" are, in essence, the responsibilities managed by a class orfunction.

In the following example, we create an HTML element that represents a comment withthe version of the document:

Bad

fromimportlibimportmetadataclassVersionCommentElement:"""An element that renders an HTML comment with the program's version number   """defget_version(self)->str:"""Get the package version"""returnmetadata.version("pip")defrender(self)->None:print(f'<!-- Version:{self.get_version()} -->')VersionCommentElement().render()

This class has two responsibilities:

  • Retrieve the version number of the Python package
  • Render itself as an HTML element

Any change to one or the other carries the risk of impacting the other.

We can rewrite the class and decouple these responsibilities:

Good

fromimportlibimportmetadatadefget_version(pkg_name:str)->str:"""Retrieve the version of a given package"""returnmetadata.version(pkg_name)classVersionCommentElement:"""An element that renders an HTML comment with the program's version number   """def__init__(self,version:str):self.version=versiondefrender(self)->None:print(f'<!-- Version:{self.version} -->')VersionCommentElement(get_version("pip")).render()

The result is that the class only needs to take care of rendering itself. Itreceives the version text during instantiation and this text is generated bycalling a separate function,get_version(). Changing the class has noimpact on the other, and vice-versa, as long as the contract between them doesnot change, i.e. the function provides a string and the class__init__ methodaccepts a string.

As an added bonus, theget_version() is now reusable elsewhere.

Open/Closed Principle (OCP)

“Incorporate new features by extending the system, not by makingmodifications (to it)”,Uncle Bob.

Objects should be open for extension, but closed to modification. It should bepossible to augment the functionality provided by an object (for example, a class)without changing its internal contracts. An object can enable this when itis designed to be extended cleanly.

In the following example, we try to implement a simple web framework thathandles HTTP requests and returns responses. TheView class has a singlemethod.get() that will be called when the HTTP server will receive a GETrequest from a client.

View is intentionally simple and returnstext/plain responses. We wouldalso like to return HTML responses based on a template file, so we subclass itusing theTemplateView class.

Bad

fromdataclassesimportdataclass@dataclassclassResponse:"""An HTTP response"""status:intcontent_type:strbody:strclassView:"""A simple view that returns plain text responses"""defget(self,request)->Response:"""Handle a GET request and return a message in the response"""returnResponse(status=200,content_type='text/plain',body="Welcome to my web site"        )classTemplateView(View):"""A view that returns HTML responses based on a template file."""defget(self,request)->Response:"""Handle a GET request and return an HTML document in the response"""withopen("index.html")asfd:returnResponse(status=200,content_type='text/html',body=fd.read()            )

TheTemplateView class has modified the internal behaviour of its parentclass in order to enable the more advanced functionality. In doing so,it now relies on theView to not change the implementation of the.get()method, which now needs to be frozen in time. We cannot introduce, for example,some additional checks in all ourView-derived classes because the behaviouris overridden in at least one subtype and we will need to update it.

Let's redesign our classes to fix this problem and let theView class beextended (not modified) cleanly:

Good

fromdataclassesimportdataclass@dataclassclassResponse:"""An HTTP response"""status:intcontent_type:strbody:strclassView:"""A simple view that returns plain text responses"""content_type="text/plain"defrender_body(self)->str:"""Render the message body of the response"""return"Welcome to my web site"defget(self,request)->Response:"""Handle a GET request and return a message in the response"""returnResponse(status=200,content_type=self.content_type,body=self.render_body()        )classTemplateView(View):"""A view that returns HTML responses based on a template file."""content_type="text/html"template_file="index.html"defrender_body(self)->str:"""Render the message body as HTML"""withopen(self.template_file)asfd:returnfd.read()

Note that we did need to override therender_body() in order to change thesource of the body, but this method has a single, well defined responsibilitythatinvites subtypes to override it. It is designed to be extended by itssubtypes.

Another good way to use the strengths of both object inheritance and objectcomposition is to useMixins.

Mixins are bare-bones classes that are meant to be used exclusively with otherrelated classes. They are "mixed-in" with the target class using multipleinheritance, in order to change the target's behaviour.

A few rules:

  • Mixins should always inherit fromobject
  • Mixins always come before the target class, e.g.class Foo(MixinA, MixinB, TargetClass): ...

Also good

fromdataclassesimportdataclass,fieldfromtypingimportProtocol@dataclassclassResponse:"""An HTTP response"""status:intcontent_type:strbody:strheaders:dict=field(default_factory=dict)classView:"""A simple view that returns plain text responses"""content_type="text/plain"defrender_body(self)->str:"""Render the message body of the response"""return"Welcome to my web site"defget(self,request)->Response:"""Handle a GET request and return a message in the response"""returnResponse(status=200,content_type=self.content_type,body=self.render_body()        )classTemplateRenderMixin:"""A mixin class for views that render HTML documents using a template file    Not to be used by itself!    """template_file:str=""defrender_body(self)->str:"""Render the message body as HTML"""ifnotself.template_file:raiseValueError("The path to a template file must be given.")withopen(self.template_file)asfd:returnfd.read()classContentLengthMixin:"""A mixin class for views that injects a Content-Length header in the    response    Not to be used by itself!    """defget(self,request)->Response:"""Introspect and amend the response to inject the new header"""response=super().get(request)# type: ignoreresponse.headers['Content-Length']=len(response.body)returnresponseclassTemplateView(TemplateRenderMixin,ContentLengthMixin,View):"""A view that returns HTML responses based on a template file."""content_type="text/html"template_file="index.html"

As you can see, Mixins make object composition easier by packaging togetherrelated functionality into a highly reusable class with a single responsibility,allowing clean decoupling. Class extension is achieved by "mixing-in" theadditional classes.

The popular Django project makes heavy use of Mixins to compose its class-basedviews.

FIXME: re-enable typechecking for the line above once it's clear how to usetyping.Protocol to make the type checker work with Mixins.

Liskov Substitution Principle (LSP)

“Functions that use pointers or references to base classesmust be able to use objects of derived classes without knowing it”,Uncle Bob.

This principle is named after Barbara Liskov, who collaborated with fellowcomputer scientist Jeannette Wing on the seminal paper*"A behavioral notion of subtyping" (1994). A core tenet of the paper is that"a subtype (must) preserve the behaviour of the supertype methods and also allinvariant and history properties of its supertype".

In essence, a function accepting a supertype should also accept all its subtypeswith no modification.

Can you spot the problem with the following code?

Bad

fromdataclassesimportdataclass@dataclassclassResponse:"""An HTTP response"""status:intcontent_type:strbody:strclassView:"""A simple view that returns plain text responses"""content_type="text/plain"defrender_body(self)->str:"""Render the message body of the response"""return"Welcome to my web site"defget(self,request)->Response:"""Handle a GET request and return a message in the response"""returnResponse(status=200,content_type=self.content_type,body=self.render_body()        )classTemplateView(View):"""A view that returns HTML responses based on a template file."""content_type="text/html"defget(self,request,template_file:str)->Response:# type: ignore"""Render the message body as HTML"""withopen(template_file)asfd:returnResponse(status=200,content_type=self.content_type,body=fd.read()            )defrender(view:View,request)->Response:"""Render a View"""returnview.get(request)

The expectation is thatrender() function will be able to work withView and itssubtypeTemplateView, but the latter has broken compatibility by modifyingthe signature of the.get() method. The function will raise aTypeErrorexception when used withTemplateView.

If we want therender() function to work with any subtype ofView, wemust pay attention not to break its public-facing protocol. But how do we knowwhat constitutes it for a given class? Type hinters likemypy will raisean error when it detects mistakes like this:

error: Signature of "get" incompatible with supertype "View"<string>:36: note:      Superclass:<string>:36: note:          def get(self, request: Any) -> Response<string>:36: note:      Subclass:<string>:36: note:          def get(self, request: Any, template_file: str) -> Response

Interface Segregation Principle (ISP)

“Keep interfaces smallso that users don’t end up depending on things they don’t need.”,Uncle Bob.

Several well known object oriented programming languages, like Java and Go,have a concept called interfaces. An interface defines the public methods andproperties of an object without implementing them. They are useful when we don'twant to couple the signature of a function to a concrete object; we'd rathersay "I don't care what object you give me, as long as it has certain methodsand attributes I expect to make use of".

Python does not have interfaces. We have Abstract Base Classes instead, whichare a little different, but can serve the same purpose.

Good

fromabcimportABCMeta,abstractmethod# Define the Abstract Class for a generic Greeter objectclassGreeter(metaclass=ABCMeta):"""An object that can perform a greeting action."""@staticmethod@abstractmethoddefgreet(name:str)->None:"""Display a greeting for the user with the given name"""classFriendlyActor(Greeter):"""An actor that greets the user with a friendly salutation"""@staticmethoddefgreet(name:str)->None:"""Greet a person by name"""print(f"Hello{name}!")defwelcome_user(user_name:str,actor:Greeter):"""Welcome a user with a given name using the provided actor"""actor.greet(user_name)welcome_user("Barbara",FriendlyActor())

Now imagine the following scenario: we have a certain number of PDF documentsthat we author and want to serve to our web site visitors. We are using aPython web framework and we might be tempted to design a class to manage thesedocuments, so we go ahead and design a comprehensive abstract base class forour document.

Error

importabcclassPersistable(metaclass=abc.ABCMeta):"""Serialize a file to data and back"""@property@abc.abstractmethoddefdata(self)->bytes:"""The raw data of the file"""@classmethod@abc.abstractmethoddefload(cls,name:str):"""Load the file from disk"""@abc.abstractmethoddefsave(self)->None:"""Save the file to disk"""# We just want to serve the documents, so our concrete PDF document# implementation just needs to implement the `.load()` method and have# a public attribute named `data`.classPDFDocument(Persistable):"""A PDF document"""@propertydefdata(self)->bytes:"""The raw bytes of the PDF document"""        ...# Code goes here - omitted for brevity@classmethoddefload(cls,name:str):"""Load the file from the local filesystem"""        ...# Code goes here - omitted for brevitydefview(request):"""A web view that handles a GET request for a document"""requested_name=request.qs['name']# We want to validate this!returnPDFDocument.load(requested_name).data

But we can't! If we don't implement the.save() method, an exception will beraised:

Can't instantiate abstract class PDFDocument with abstract method save.

That's annoying. We don't really need to implement.save() here. We couldimplement a dummy method that does nothing or raisesNotImplementedError,but that's useless code that we will need to maintain.

At the same time, if we remove.save() from the abstract class now we willneed to add it back when we will later implement a way for users to submittheir documents, bringing us back to the same situation as before.

The problem is that we have written aninterface that has features we don'tneed right now as we are not using them.

The solution is to decompose the interface into smaller and composable interfacesthat segregate each feature.

Good

importabcclassDataCarrier(metaclass=abc.ABCMeta):"""Carries a data payload"""@propertydefdata(self):        ...classLoadable(DataCarrier):"""Can load data from storage by name"""@classmethod@abc.abstractmethoddefload(cls,name:str):        ...classSaveable(DataCarrier):"""Can save data to storage"""@abc.abstractmethoddefsave(self)->None:        ...classPDFDocument(Loadable):"""A PDF document"""@propertydefdata(self)->bytes:"""The raw bytes of the PDF document"""        ...# Code goes here - omitted for brevity@classmethoddefload(cls,name:str):"""Load the file from the local filesystem"""        ...# Code goes here - omitted for brevitydefview(request):"""A web view that handles a GET request for a document"""requested_name=request.qs['name']# We want to validate this!returnPDFDocument.load(requested_name).data

Dependency Inversion Principle (DIP)

“Depend upon abstractions, not concrete details”,Uncle Bob.

Imagine we wanted to write a web view that returns an HTTP response thatstreams rows of a CSV file we create on the fly. We want to use the CSV writerthat is provided by the standard library.

Bad

importcsvfromioimportStringIOclassStreamingHttpResponse:"""A streaming HTTP response"""    ...# implementation code goes heredefsome_view(request):rows= (       ['First row','Foo','Bar','Baz'],       ['Second row','A','B','C','"Testing"',"Here's a quote"]   )# Define a generator to stream data directly to the clientdefstream():buffer_=StringIO()writer=csv.writer(buffer_,delimiter=';',quotechar='"')forrowinrows:writer.writerow(row)buffer_.seek(0)data=buffer_.read()buffer_.seek(0)buffer_.truncate()yielddata# Create the streaming response  object with the appropriate CSV header.response=StreamingHttpResponse(stream(),content_type='text/csv')response['Content-Disposition']='attachment; filename="somefilename.csv"'returnresponse

Our first implementation works around the CSV's writer interface by manipulatingaStringIO object (which is file-like) and performing several low leveloperations in order to farm out the rows from the writer. It's a lot of workand not very elegant.

A better way is to leverage the fact that the writer just needs an object witha.write() method to do our bidding. Why not pass it a dummy object thatimmediately returns the newly assembled row, so that theStreamingHttpResponseclass can immediate stream it back to the client?

Good

importcsvclassEcho:"""An object that implements just the write method of the file-like   interface.   """defwrite(self,value):"""Write the value by returning it, instead of storing in a buffer."""returnvaluedefsome_streaming_csv_view(request):"""A view that streams a large CSV file."""rows= (       ['First row','Foo','Bar','Baz'],       ['Second row','A','B','C','"Testing"',"Here's a quote"]   )writer=csv.writer(Echo(),delimiter=';',quotechar='"')returnStreamingHttpResponse(       (writer.writerow(row)forrowinrows),content_type="text/csv",headers={'Content-Disposition':'attachment; filename="somefilename.csv"'},   )

Much better, and it works like a charm! The reason it's superior to the previousimplementation should be obvious: less code (and more performant) to achievethe same result. We decided to leverage the fact that the writer class dependson the.write() abstraction of the object it receives, without caring aboutthe low level, concrete details of what the method actually does.

This example was taken froma submission made to the Django documentationby this author.

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Don't repeat yourself (DRY)

Try to observe theDRY principle.

Do your absolute best to avoid duplicate code. Duplicate code is bad becauseit means that there's more than one place to alter something if you need tochange some logic.

Imagine if you run a restaurant and you keep track of your inventory: all yourtomatoes, onions, garlic, spices, etc. If you have multiple lists thatyou keep this on, then all have to be updated when you serve a dish withtomatoes in them. If you only have one list, there's only one place to update!

Often you have duplicate code because you have two or more slightlydifferent things, that share a lot in common, but their differences force youto have two or more separate functions that do much of the same things. Removingduplicate code means creating an abstraction that can handle this set of differentthings with just one function/module/class.

Getting the abstraction right is critical. Bad abstractions can beworse than duplicate code, so be careful! Having said this, if you can makea good abstraction, do it! Don't repeat yourself, otherwise you'll find yourselfupdating multiple places any time you want to change one thing.

Bad:

fromtypingimportList,Dictfromdataclassesimportdataclass@dataclassclassDeveloper:def__init__(self,experience:float,github_link:str)->None:self._experience=experienceself._github_link=github_link@propertydefexperience(self)->float:returnself._experience@propertydefgithub_link(self)->str:returnself._github_link@dataclassclassManager:def__init__(self,experience:float,github_link:str)->None:self._experience=experienceself._github_link=github_link@propertydefexperience(self)->float:returnself._experience@propertydefgithub_link(self)->str:returnself._github_linkdefget_developer_list(developers:List[Developer])->List[Dict]:developers_list= []fordeveloperindevelopers:developers_list.append({'experience' :developer.experience,'github_link' :developer.github_link            })returndevelopers_listdefget_manager_list(managers:List[Manager])->List[Dict]:managers_list= []formanagerinmanagers:managers_list.append({'experience' :manager.experience,'github_link' :manager.github_link            })returnmanagers_list## create list objects of developerscompany_developers= [Developer(experience=2.5,github_link='https://github.com/1'),Developer(experience=1.5,github_link='https://github.com/2')]company_developers_list=get_developer_list(developers=company_developers)## create list objects of managerscompany_managers= [Manager(experience=4.5,github_link='https://github.com/3'),Manager(experience=5.7,github_link='https://github.com/4')]company_managers_list=get_manager_list(managers=company_managers)

Good:

fromtypingimportList,Dictfromdataclassesimportdataclass@dataclassclassEmployee:def__init__(self,experience:float,github_link:str)->None:self._experience=experienceself._github_link=github_link@propertydefexperience(self)->float:returnself._experience@propertydefgithub_link(self)->str:returnself._github_linkdefget_employee_list(employees:List[Employee])->List[Dict]:employees_list= []foremployeeinemployees:employees_list.append({'experience' :employee.experience,'github_link' :employee.github_link            })returnemployees_list## create list objects of developerscompany_developers= [Employee(experience=2.5,github_link='https://github.com/1'),Employee(experience=1.5,github_link='https://github.com/2')]company_developers_list=get_employee_list(employees=company_developers)## create list objects of managerscompany_managers= [Employee(experience=4.5,github_link='https://github.com/3'),Employee(experience=5.7,github_link='https://github.com/4')]company_managers_list=get_employee_list(employees=company_managers)

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