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🛁 Clean Code concepts adapted for Python

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ZozoCodecool/clean-code-python

 
 

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Table of Contents

  1. Introduction
  2. Variables
  3. Functions
  4. Objects and Data Structures
  5. 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)
  6. Don’t repeat yourself (DRY)

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:

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

Good:

current_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:

get_user_info()get_client_data()get_customer_record()

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

get_user_info()get_user_data()get_user_record()

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:

classUser:info :str@propertydefdata(self)->dict:# ...defget_record(self)->Union[Record,None]:# ...

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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:

# What the heck is 86400 for?time.sleep(86400);

Good:

# 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:

address='One Infinite Loop, Cupertino 95014'city_zip_code_regex=r'^[^,\\]+[,\\\s]+(.+?)\s*(\d{5})?$'matches=re.match(city_zip_code_regex,address)save_city_zip_code(matches[1],matches[2])

Not bad:

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

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

Good:

Decrease dependence on regex by naming subpatterns.

address='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)save_city_zip_code(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` for again?dispatch(item)

Good:

locations= ('Austin','New York','San Francisco')forlocationinlocations:do_stuff()do_some_other_stuff()# ...dispatch(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:

defcreate_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 ist clear thatyou are expecting a string as the argument.

Good:

defcreate_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):# ...

Good:

classMenu:def__init__(self,config:dict):title=config["title"]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):title=config.titlebody=config.body# ...config=MenuConfigconfig.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=configcreate_menu(MenuConfig(title="My delicious menu",body="A description of the various items on the menu",button_text="Order now!"    ))

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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:

defemail_clients(clients:List[Client]):"""Filter active clients and send them an email.    """forclientinclients:ifclient.active:email(client)

Good:

defget_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.    """forclientinclients:email(client)

Do you see an opportunity for using generators now?

Even better

defactive_clients(clients:List[Client])->Generator[Client]:"""Only active clients.    """return (clientforclientinclientsifclient.active)defemail_client(clients:Iterator[Client])->None:"""Send an email to a given list of clients.    """forclientinclients:email(client)

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Function names should say what they do

Bad:

classEmail:defhandle(self)->None:# Do something...message=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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