Tips and Tricks

Django REST Framework's ModelViewSet

Django REST Framework tip:

If your API endpoints map close to your models, you can save yourself quite a few lines of code by using ModelViewSet in combination with a router.

# viewsets.py
class PostModelViewSet(ModelViewSet):
    serializer_class = PostSerializer
    queryset = Post.objects.all()


# urls.py
router = routers.DefaultRouter()
router.register(r'', PostModelViewSet)

urlpatterns = [
    path('', include(router.urls)),
]


# yields:
http://127.0.0.1:8000/      # for list of posts
http://127.0.0.1:8000/1/  # for post detail

(ViewSets should be stored in a file named viewsets.py rather than views.py.)

How to create views in Django REST Framework

Django REST Framework tip:

There are three core ways to create views:

1. extending APIView class
2. Extending one of the seven concrete API views (e.g., ListCreateAPIView)
3. ViewSet (e.g., ModelViewSet)

There are also some sub-possibilities:

Django's length template filter

Django tip:

If you want to show the length of a string or list, you can use the length template filter.

{{ friends|length }}

Django's pluralize template filter

Django tip:

Sometimes you need to use the single or plural form based on the number you're displaying. You can handle this by using the pluralize filter.

{{ number_of_friends }} friend{{ number_of_friends|pluralize }}

# 1 friend
# 2 friends 

An "s" is automatically used as the suffix, but you can also provide your own suffix (for both singular and plural versions).

{{ number_of_mice }} {{ number_of_mice|pluralize:"mouse,mice" }}

# 1 mouse
# 2 mice

Selecting a random element from a list in a Django template

Django tip:

You can use the random Django template filter to return a random item from the given list.

{{ inspirational_quote|random }}

Slicing a list in a Django template

Django tip:

You can return only part of the list in a Django template by using the slice filter.

The syntax for slicing is the same as for Python’s list slicing.

{{ friends|slice:":3" }}

Django Date Template Filter

Django tip:

You can use the date filter to format a given date/time.

Example:

{{ post.datetime|date:"jS F Y" }}  # => 1st January 2022

After the colon, you can provide the desired format inside the string. If the format is not provided, the filter will use the default one, which can be specified in the settings.

Convert letter case in a Django template

Django tip:

There are four template filters you can use to change letter case:

1. title
2. capfirst
3. lower
4. upper

{{ item.name|title }}
{{ item.name|capfirst }}
{{ item.name|lower }}
{{ item.name|upper }}

Check if a For Loop Variable Is Empty in a Django Template

Django tip:

When looping through a list in a Django template, you can use the empty tag to cover cases when the list is empty:

{% for item in list %}
    {{ item }}
{% empty %}
    <p>There are no items yet.</p>
{% endfor %}

Create Custom Django Admin Actions

Django tip:

You can create custom bulk actions for the Django admin.

Example:

@admin.action(description='Mark selected items purchased')
def make_purchased(modeladmin, request, queryset):
    queryset.update(purchased=True)


@admin.register(ShoppingItem)
class ShoppingItemAdmin(admin.ModelAdmin):
    actions = [make_purchased]

How to exclude Django Modelform fields

Django tip:

You can use either exclude or fields to impact which fields will be available in the Django admin model forms.

For example:

# models.py

class Child(models.Model):
     name = models.CharField(max_length=200)
     last_name = models.CharField(max_length=200)
     grade = models.CharField(max_length=200)



# admin.py  

@admin.register(Child)
class ChildAdmin(admin.ModelAdmin):
    exclude = ('grade',)

# yields the same result as

@admin.register(Child)
class ChildAdmin(admin.ModelAdmin):
    fields = ('name', 'last_name')

How to check for first or last iteration of a for loop in a Django template

Django tip:

You can use forloop.first or forloop.last to check if the current iteration is the first or the last time through a for loop in your Django templates like so:

{% for item in item_list %}
    {{ forloop.first }}  # True if this is the first time through the loop
    {{ forloop.last }}   # True if this is the last time through the loop
{% endfor %}

Current iteration from the end of a for loop in a Django template - forloop.revcounter

Django tip:

You can use revcounter to get the number of iterations from the end of a for loop in your Django templates like so:

{% for item in item_list %}
    {{ forloop.revcounter }}  # starting index 1
    {{ forloop.revcounter0 }} # starting index 0
{% endfor %}

Current iteration of a for loop in a Django template - forloop.counter

Django tip:

You can use counter to get the current iteration of a for loop in your Django templates like so:

{% for item in item_list %}
    {{ forloop.counter }}  # starting index 1
    {{ forloop.counter0 }} # starting index 0
{% endfor %}

Django - Custom verbose plural name for admin model class

Django tip:

Django automatically creates a plural verbose name from your object by adding and "s" to the end.

child -> childs

To change the plural verbose name, you can define the verbose_name_plural property of the Meta class like so:

class Child(models.Model):

    ...

    class Meta:
        verbose_name_plural = "children"

Django - Custom Database Constraints

Django tip:

You can add custom database constraints to your Django models like so:

class Child(models.Model):  

    ....

    class Meta:
        constraints = [
            models.CheckConstraint(check=models.Q(age__lt=18))
        ]

Custom Django Management Commands

Django tip:

You can create your own custom Django management commands that you can run with manage.py. For example:

python manage.py your_command

Simply add a Python module to a "management/commands" folder in a Django app.

Example:

your_app/
    __init__.py
    models.py
    management/
        __init__.py
        commands/
            __init__.py
            your_command.py
    tests.py
    views.py

(Django will ignore any module that begins with an underscore.)

Example command:

from django.core.management.base import BaseCommand

class Command(BaseCommand):

    def handle(self, *args, **options):
        self.stdout.write('pong!')

Django Admin - custom filters with list_filter

Django tip:

With list_filter you can add custom filters to the right sidebar of the Django admin list page.

For example:

@admin.register(Child)
class ItemAdmin(admin.ModelAdmin):
    list_filter = ("grade", )

Django - reference method in the list_display tuple for the admin

Django tip:

Besides model fields, the list_display tuple can reference methods from ModelAdmin:

@admin.register(ShoppingList)
class ShoppingListAdmin(admin.ModelAdmin):
    list_display = ("title", "number_of_items")

    def number_of_items(self, obj):
        result = ShoppingItem.objects.filter(shopping_list=obj.id).count()
        return result

Customize the Django admin with list_display

Django tip:

You can make your admin list page friendlier to the user by specifying which fields should be displayed:

@admin.register(Child)
class ChildAdmin(admin.ModelAdmin):
    list_display = ("last_name", "first_name")

Custom field for search in the Django admin

Django tip:

search_fields sets which model fields will be searched when a search is performed in the Django admin.

You can also perform a related lookup on a ForeignKey or ManyToManyField with the lookup API "follow" notation (double underscore syntax):

@admin.register(Child)
class ChildAdmin(admin.ModelAdmin):
    search_fields = ['parent__name']

Registering models with the Django Admin

Django tip:

Instead of using admin.site.register for registering models with the Django admin, you can use a decorator.

https://docs.djangoproject.com/en/4.0/ref/contrib/admin/#the-register-decorator

👇

## option 1 ##

class AuthorAdmin(admin.ModelAdmin):
    fields = ('name', 'title')

admin.site.register(Author, AuthorAdmin)


## option 2 ##

# you can use a decorator instead
@admin.register(Author)
class AuthorAdmin(admin.ModelAdmin):
    fields = ('name', 'title')

Testing tip - focus testing efforts on testing private methods

Testing tip:

Focus the majority of your testing efforts on testing methods that you (or other stakeholders) intend to call from other packages/modules. Everything else is just an implementation detail.

Testing tip - use mocks only when necessary

Testing tip:

Use mocks only when necessary (like for third-party HTTP APIs). They make your test setup more complicated and your tests overall less resistant to refactoring.

Plus, they can result in false positives.

Shorten development cycles with pytest markers

Testing tip:

The faster you notice regressions, the faster you can intercept and correct them. The faster you correct them, the shorter the development cycle.

You can use pytest markers to exclude e2e and other slow tests during development. You can run them less frequently.

https://docs.pytest.org/en/6.2.x/example/markers.html

Writing Valuable Tests

Testing tip:

A test is valuable only when it protects you against regressions, allows you to refactor, and provides you with fast feedback.

Testing tip - create more loosely coupled components and modules

Testing tip:

There's no single right way to test your software.

Nonetheless, it's easier and faster to test logic when it's not coupled with your database.

Python Testing - Mocking different responses for consecutive calls

Python testing tip:

You can specify different responses for consecutive calls to your MagicMock.

It's useful when you want to mock a paginated response.

👇

from unittest.mock import MagicMock


def test_all_cars_are_fetched():
    get_cars_mock = MagicMock()
    get_cars_mock.side_effect = [
        ["Audi A3", "Renault Megane"],
        ["Nissan Micra", "Seat Arona"]
    ]

    print(get_cars_mock())
    # ['Audi A3', 'Renault Megane']
    print(get_cars_mock())
    # ['Nissan Micra', 'Seat Arona']

Type Hints - How to Use typing.cast() in Python

Python tip:

You can use cast() to signal to a type checker that the value has a designated type.

https://docs.python.org/3/library/typing.html#typing.cast

👇

from dataclasses import dataclass
from enum import Enum
from typing import cast


class BoatStatus(int, Enum):
    RESERVED = 1
    FREE = 2


@dataclass
class Boat:
    status: BoatStatus


Boat(status=2)
# example.py:16: error: Argument "status" to "Boat" has incompatible type "int"; expected "BoatStatus"
# Found 1 error in 1 file (checked 1 source file)

Boat(status=cast(BoatStatus, 2))

SQLAlchemy with_for_update

SQLAlchemy tip:

You can use with_for_update() to use SELECT FOR UPDATE. This will prevent changes in selected rows before you commit your work to the database.

https://docs.sqlalchemy.org/en/14/orm/query.html#sqlalchemy.orm.Query.with_for_update

👇

user = session.query(User).filter(User.email == email).with_for_update().first()

user.is_active = True
session.add(user)
session.commit()

Mount a Flask or Django app inside a FastAPI application

FastAPI tip:

You can use WSGIMiddleware to mount WSGI applications (like Flask and Django) to your FastAPI API.

https://fastapi.tiangolo.com/advanced/wsgi/

👇

from fastapi import FastAPI
from fastapi.middleware.wsgi import WSGIMiddleware
from flask import Flask, escape, request

flask_app = Flask(__name__)


@flask_app.route("/")
def flask_main():
    name = request.args.get("name", "World")
    return f"Hello, {escape(name)} from Flask!"


app = FastAPI()


@app.get("/v2")
def read_main():
    return {"message": "Hello World"}


app.mount("/v1", WSGIMiddleware(flask_app))

FastAPI - disable OpenAPI docs

FastAPI tip:

You can disable OpenAPI docs by setting openapi_url to an empty string.

https://fastapi.tiangolo.com/advanced/conditional-openapi/#conditional-openapi-from-settings-and-env-vars

👇

from fastapi import FastAPI
from pydantic import BaseSettings


class Settings(BaseSettings):
    openapi_url: str = ""


settings = Settings()

app = FastAPI(openapi_url=settings.openapi_url)


@app.get("/")
def root():
    return {"message": "Hello World"}

FastAPI - custom Request and APIRoute class

FastAPI tip:

You can implement custom Request and APIRoute classes.

https://fastapi.tiangolo.com/advanced/custom-request-and-route/

For example, to manipulate the request body before it's processed by your application👇

import gzip
from typing import Callable, List

from fastapi import Body, FastAPI, Request, Response
from fastapi.routing import APIRoute


class GzipRequest(Request):
    async def body(self) -> bytes:
        if not hasattr(self, "_body"):
            body = await super().body()
            if "gzip" in self.headers.getlist("Content-Encoding"):
                body = gzip.decompress(body)
            self._body = body
        return self._body


class GzipRoute(APIRoute):
    def get_route_handler(self) -> Callable:
        original_route_handler = super().get_route_handler()

        async def custom_route_handler(request: Request) -> Response:
            request = GzipRequest(request.scope, request.receive)
            return await original_route_handler(request)

        return custom_route_handler


app = FastAPI()
app.router.route_class = GzipRoute


@app.post("/sum")
async def sum_numbers(numbers: List[int] = Body(...)):
    return {"sum": sum(numbers)}

FastAPI - GraphQL with Strawberry

FastAPI tip:

You can use Strawberry to build a GraphQL API with FastAPI.

🍓

https://fastapi.tiangolo.com/fr/advanced/graphql/#graphql-with-strawberry

👇

import strawberry

from fastapi import FastAPI
from strawberry.asgi import GraphQL


@strawberry.type
class User:
    name: str
    age: int


@strawberry.type
class Query:
    @strawberry.field
    def user(self) -> User:
        return User(name="Patrick", age=100)


schema = strawberry.Schema(query=Query)


graphql_app = GraphQL(schema)

app = FastAPI()
app.add_route("/graphql", graphql_app)
app.add_websocket_route("/graphql", graphql_app)

FastAPI - Templates with Jinja2

FastAPI tip:

You can use Jinja2 as a template engine to serve HTML responses from your FastAPI application.

👇

from fastapi import FastAPI, Request
from fastapi.responses import HTMLResponse
from fastapi.staticfiles import StaticFiles
from fastapi.templating import Jinja2Templates

app = FastAPI()

app.mount("/static", StaticFiles(directory="static"), name="static")


templates = Jinja2Templates(directory="templates")


@app.get("/items/{id}", response_class=HTMLResponse)
async def read_item(request: Request, id: str):
    return templates.TemplateResponse("item.html", {"request": request, "id": id})

FastAPI Sub Applications

FastAPI tip:

You can use sub-applications when you need two separate OpenAPI schemas and Swagger UIs.

https://fastapi.tiangolo.com/advanced/sub-applications/

You can mount one or many sub-applications.

👇

from fastapi import FastAPI


app = FastAPI()


@app.get("/app")
def read_main():
    return {"message": "Hello World from main app"}


subapi = FastAPI()


@subapi.get("/sub")
def read_sub():
    return {"message": "Hello World from sub API"}


app.mount("/subapi", subapi)

FastAPI shutdown events

FastAPI tip:

You can register functions to run before the application shutdown using @app.on_event("shutdown").

https://fastapi.tiangolo.com/advanced/events/#shutdown-event

For example. to send a message to an SNS topic where you track your app health 👇

import boto3
from fastapi import FastAPI


app = FastAPI()


@app.on_event("shutdown")
def publish_message():
    client = boto3.client('sns')
    client.publish(
        TopicArn='arn:aws:sns:us-east-1:12345678910112:application-health',
        Message='Application is shutting down',
    )


@app.get("/ping")
async def ping():
    return {"message": "pong"}

FastAPI startup events

FastAPI tip:

You can register functions to run before the application start using @app.on_event("startup").

https://fastapi.tiangolo.com/advanced/events/#startup-event

For example, to send a message to an AWS SNS topic where you track your app health:

import boto3
from fastapi import FastAPI


app = FastAPI()


@app.on_event("startup")
def publish_message():
    client = boto3.client('sns')
    client.publish(
        TopicArn='arn:aws:sns:us-east-1:12345678910112:application-health',
        Message='Application is starting',
    )


@app.get("/ping")
async def ping():
    return {"message": "pong"}

FastAPI WebSockets

FastAPI tip:

You can easily add WebSockets to your app with @app.websocket().

https://fastapi.tiangolo.com/advanced/websockets/

👇

from fastapi import FastAPI, WebSocket
from fastapi.responses import HTMLResponse

app = FastAPI()

html = """
<!DOCTYPE html>
<html>
    <head>
        <title>Chat</title>
    </head>
    <body>
        <h1>WebSocket Chat</h1>
        <form action="" onsubmit="sendMessage(event)">
            <input type="text" id="messageText" autocomplete="off"/>
            <button>Send</button>
        </form>
        <ul id='messages'>
        </ul>
        <script>
            var ws = new WebSocket("ws://localhost:8000/ws");
            ws.onmessage = function(event) {
                var messages = document.getElementById('messages')
                var message = document.createElement('li')
                var content = document.createTextNode(event.data)
                message.appendChild(content)
                messages.appendChild(message)
            };
            function sendMessage(event) {
                var input = document.getElementById("messageText")
                ws.send(input.value)
                input.value = ''
                event.preventDefault()
            }
        </script>
    </body>
</html>
"""


@app.get("/")
async def get():
    return HTMLResponse(html)


@app.websocket("/ws")
async def websocket_endpoint(websocket: WebSocket):
    await websocket.accept()
    while True:
        data = await websocket.receive_text()
        await websocket.send_text(f"Message text was: {data}")

FastAPI - Using alias parameters to map fields from request to view arguments

FastAPI tip:

You can use aliases for field names to map fields from request to view arguments.

https://fastapi.tiangolo.com/tutorial/query-params-str-validations/#alias-parameters

👇

from typing import Optional

from fastapi import FastAPI, Query, Path

app = FastAPI()


@app.get("/products/")
def search_products(query: Optional[str] = Query(None, alias="q")):
    products = [{"name": "Computer"}, {"name": "HDD"}]

    return {"results": [product for product in products if query in product["name"]]}


@app.get("/users/{id}/profile/")
def user_profile(user_id: int = Path(None, alias="id")):
    return {
        "id": user_id,
        "username": "johndoe"
    }

FastAPI Middleware

FastAPI tip:

You can add custom middleware to your app to do something before or after each request.

For example, to add a header containing the version of your application for easier debugging:

from fastapi import FastAPI, Request

app = FastAPI()


@app.middleware("http")
async def add_version_header(request: Request, call_next):
    response = await call_next(request)
    response.headers["X-Version"] = "v1.2.10"
    return response


@app.get("/ping")
def ping():
    return {"message": "pong"}

FastAPI - Using "callable" instances as dependencies in your API endpoints

FastAPI tip:

You can inject instances of a class as a dependency to your API endpoints, which you can then use when you as a configurable dependency.

You need to make instances callable via __call__.

https://fastapi.tiangolo.com/advanced/advanced-dependencies/#a-callable-instance

👇

from fastapi import FastAPI, Depends, HTTPException, status
from pydantic import BaseModel


class User(BaseModel):
    username: str
    groups: set[str]


users = [
    User(username='johndoe', groups={"admin"}),
    User(username='bobbuilder', groups={"builders"}),
]

app = FastAPI()


class AuthorizeUser:
    def __init__(self, allowed_groups: set[str]):
        self._allowed_groups = allowed_groups

    def __call__(self, username: str):
        try:
            user = next(user for user in users if user.username == username)
        except StopIteration:
            raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED)

        if user.groups.isdisjoint(self._allowed_groups):
            raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED)

        return user


@app.get("/only-admins")
def only_admins(user: User = Depends(AuthorizeUser(allowed_groups={"admin"}))):
    return {"message": f"User: {user.username} is in admin group."}


@app.get("/only-builders")
def only_admins(user: User = Depends(AuthorizeUser(allowed_groups={"builders"}))):
    return {"message": f"User: {user.username} is in builders group."}

FastAPI - API key authentication

FastAPI Tip:

You can protect API endpoints with an API key like so:

from fastapi import FastAPI, Body, Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer

api_keys = [
    "akljnv13bvi2vfo0b0bw"
]  # This is encrypted in the database

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")  # use token authentication


def api_key_auth(api_key: str = Depends(oauth2_scheme)):
    if api_key not in api_keys:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail="Forbidden"
        )


app = FastAPI()


@app.get("/protected", dependencies=[Depends(api_key_auth)])
def add_post() -> dict:
    return {
        "data": "You used a valid API key."
    }


####################################


# call API
import requests

url = "http://localhost:8000/protected"

# The client should pass the API key in the headers
headers = {
  'Content-Type': 'application/json',
  'Authorization': 'Bearer akljnv13bvi2vfo0b0bw'
}

response = requests.get(url, headers=headers)
print(response.text)  # => "You used a valid API key."

FastAPI - set cookie when returning a response

FastAPI tip:

You can set a cookie on the response by using .set_cookie(). Response must be added as a view argument.

https://fastapi.tiangolo.com/advanced/response-cookies/

👇

from fastapi import FastAPI, Response

app = FastAPI()


@app.post("/session/")
def cookie(response: Response):
    response.set_cookie(key="mysession", value="1242r")
    return {"message": "Wanna cookie?"}

FastAPI - Overriding dependencies while running tests

FastAPI tip:

You can override a dependency of your app while running tests with dependency_overrides.

https://fastapi.tiangolo.com/advanced/testing-dependencies/#use-the-appdependency_overrides-attribute

For example, to connect to a test database:

from fastapi import Depends, FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel
from sqlalchemy.orm import Session, sessionmaker, declarative_base
from sqlalchemy import create_engine, Column, Integer, String


SQLALCHEMY_DATABASE_URL = "sqlite:///./sql_app.db"

engine = create_engine(
    SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False}
)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)

Base = declarative_base()


class User(Base):
    __tablename__ = "users"

    id = Column(Integer, primary_key=True, index=True)
    email = Column(String, unique=True, index=True)


Base.metadata.create_all(bind=engine)


class UserSchema(BaseModel):
    email: str

    class Config:
        orm_mode = True


app = FastAPI()


# Dependency
def get_db():
    db = SessionLocal()
    try:
        yield db
    finally:
        db.close()


@app.post("/users/", response_model=UserSchema)
def create_user(user_data: UserSchema, database_session: Session = Depends(get_db)):
    db_user = User(email=user_data.email)
    database_session.add(db_user)
    database_session.commit()

    return db_user


SQLALCHEMY_DATABASE_URL = "sqlite:///./test.db"

engine = create_engine(
    SQLALCHEMY_DATABASE_URL, connect_args={"check_same_thread": False}
)
TestingSessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Base.metadata.create_all(bind=engine)


def override_get_db():
    db = TestingSessionLocal()
    try:
        yield db
    finally:
        db.close()


# THIS
app.dependency_overrides[get_db] = override_get_db
# THIS

client = TestClient(app)


def test_create_user():
    response = client.post(
        "/users/",
        json={"email": "[email protected]"},
    )
    assert response.status_code == 200

Python - set isdisjoint()

Python tip:

You can use .isdisjoint() to check whether the intersection of two sets is empty -- i.e., there are not elements that are in the first and second sets.

👇

winners = {"Carl", "Dan"}
players = {"Daisy", "John", "Bob"}

print(players.isdisjoint(winners))
# => True

Python - set symmetric_difference()

Python tip:

You can use .symmetric_difference() to get a new set containing elements that are either in the first or second set but not in both.

For example:

winners = {"John", "Marry"}
players = {"Daisy", "John", "Bob"}

print(players.symmetric_difference(winners))
# => {'Bob', 'Daisy', 'Marry'}

Python - set issubset()

Python tip:

You can use .issubset() to check whether the second set contains the first one.

👇

winners = {"John", "Marry"}
players = {"Daisy", "John", "Bob", "Marry"}

print(winners.issubset(players))
# => True

How to get the difference between two sets in Python

Python tip:

You can use .difference() to get a new set that contains unique elements that are in the first set but not in the second one.

For example:

winners = {"John", "Marry"}
players = {"Daisy", "John", "Bob", "Marry"}

print(players.difference(winners))
# => {'Bob', 'Daisy'}

Python Set Intersection

Python tip:

You can use .intersection() to get a new set containing unique elements that are present inside two sets.

👇

winners = {"John", "Marry"}
players = {"Daisy", "John", "Bob", "Marry"}

print(winners.intersection(players))
# => {'John', 'Marry'}

Union multiple sets in Python

Python tip:

You can use .union() to create a new set containing unique elements that are either in the first set, the second set, or in both of them.

👇

winners = {"John", "Marry"}
players = {"Daisy", "John", "Bob", "Marry"}

print(winners.union(players))
# => {'John', 'Marry', 'Bob', 'Daisy'}

Using a Python dictionary as a switch statement

Python tip:

You can use a dictionary to implement switch-like behavior.

For example:

class ProductionConfig:
    ELASTICSEARCH_URL = "https://elasticsearch.example.com"


class DevelopmentConfig:
    ELASTICSEARCH_URL = "https://development-elasticsearch.example.com"


class TestConfig:
    ELASTICSEARCH_URL = "http://test-in-docker:9200"


CONFIGS = {
    "production": ProductionConfig,
    "development": DevelopmentConfig,
    "test": TestConfig,
}


def load_config(environment):
    return CONFIGS.get(environment, ProductionConfig)


print(load_config("production"))
# <class '__main__.ProductionConfig'>
print(load_config("test"))
# <class '__main__.TestConfig'>
print(load_config("unknown"))
# <class '__main__.ProductionConfig'>

Passing a dictionary as keyword arguments to a function in Python

Python tip:

You can use ** to unpack a dictionary as keyword arguments (kwargs) for a function.

👇

user = {"name": "Jan", "surname": "Giacomelli"}


def print_full_name(name, surname):
    print(f"{name} {surname}")


print_full_name(**user)
# => Jan Giacomelli

Remove duplicates from a Python list while preserving order

Python tip:

You can use a dictionary to remove duplicates from a list while preserving the order of elements:

users = ["Jan", "Mike", "Marry", "Mike"]

print(list({user: user for user in users}))
# => ['Jan', 'Mike', 'Marry']

A dictionary preserves the insertion order.

How do I join dictionaries together in Python?

Python tip:

You can join two dictionaries using ** or | (for Python >= 3.9, works for all subclasses).

If there are any duplicate keys, the second (rightmost) key-value pair is used.

user = {"name": "Jan", "surname": "Giacomelli"}
address = {"address1": "Best street 42", "city": "Best city"}


user_with_city = {**user, **address}
print(user_with_city)
# {'name': 'Jan', 'surname': 'Giacomelli', 'address1': 'Best street 42', 'city': 'Best city'}


user_with_city = user | address
print(user_with_city)
# {'name': 'Jan', 'surname': 'Giacomelli', 'address1': 'Best street 42', 'city': 'Best city'}


user_with_city = {"address": "Best street"} | {"address": "Almost best street"}
print(user_with_city)
# {'address': 'Almost best street'}

Prevent KeyError when working with dictionaries in Python

Python tip:

You can use .get() to avoid a KeyError when accessing non-existing keys inside a dictionary:

user = {"name": "Jan", "surname": "Giacomelli"}

print(user.get("address", "Best street 42"))
# => Best street 42

print(user["address"])
# => KeyError: 'address'

If you don't provide a default value, .get() will return None if the key doesn't exist.

If you're just trying to see if the key exists, it's better to use the in operator like so due to performance reasons:

# good
if "address" in user:
    print("yay")
else:
    print("nay")

# bad
if user.get("address"):
    print("yay")
else:
    print("nay")

Unpacking a list in Python

Python tip:

You can unpack list elements to variables. You can also ignore some of the elements.

👇

tournament_results = ["Jan", "Mike", "Marry", "Bob"]

first_player, *_, last_player = tournament_results
print(first_player, last_player)
# => Jan Bob

*_, last_player = tournament_results
print(last_player)
# => Bob

first_player, *_ = tournament_results
print(first_player)
# => Jan

first_player, second_player, third_player, fourth_player = tournament_results
print(first_player, second_player, third_player, fourth_player)
# => Jan Mike Marry Bob

Python - Iterate over multiple lists simultaneously with zip

Python tip:

You can use zip to iterate through multiple lists of equal length in a single loop.

👇

users = ["Jan", "Mike", "Marry", "Mike"]
user_visits = [10, 31, 10, 1]

for user, visits in zip(users, user_visits):
    print(f"{user}: {visits}")

# Jan: 10
# Mike: 31
# Marry: 10
# Mike: 1

Count the number of occurrences of an element in a list in Python

Python tip:

You can count occurrences of an element in a list with .count().

For example:

users = ["Jan", "Mike", "Marry", "Mike"]
print(users.count("Mike"))
# => 2

How do I concatenate two lists in Python?

Python tip:

You can use + to join two lists into a new list.

a = [10, 2]
b = [6, 3]

print(a + b)
# => [10, 2, 6, 3]

Python - create a list from a list repeated N times

Python tip:

You can create a new list with elements from the first list that are repeated as many times as you want by multiplying.

Fo example:

users = ["johndoe", "marry", "bob"]
print(3 * users)
# => ['johndoe', 'marry', 'bob', 'johndoe', 'marry', 'bob', 'johndoe', 'marry', 'bob']

Execute raw SQL queries in SQLAlchemy

Python SQLAlchemy tip:

You can use raw queries while still using SQLAlchemy models.

For example

user = session.query(Course).from_statement(
    text("""SELECT * FROM courses where title=:title""")
).params(title="Scalable FastAPI Applications on AWS").all()

Python - sep parameter in print()

Python tip:

You can pass as many values to print to the print() function as you want. You can also specify a custom separator.

print("123", "456", "789")
# => 123 456 789

print("123", "456", "789", sep="-")
# => 123-456-789

How to flush output of print in Python?

Python tip:

You can set flush=True for the print() function to avoid buffering the output data and forcibly flush it:

print("I'm awesome", flush=True)

Python - find the last occurrence of an item in a list with rindex()

Python tip:

You can use .rindex() to find the highest index in a string where a substring is found.

👇

print("2021 was awesome. 2022 is going to be even more awesome.".rindex("awesome"))
# => 48

Python - string ljust() method

Python tip:

You can use .ljust() to create a left-justified string of given width.

string.ljust(width, fillchar)

Padding is a space, " ", by default.

print("Mike".ljust(10, "*"))
# => Mike******

Python - string center() method

Python tip:

You can use .center() to create a centered string of given width.

string.center(width, fillchar)

Padding on each side is a space, " ", by default.

print("Mike".center(10, "*"))
# => ***Mike***

Python - lower() vs. casefold() for string matching and converting to lowercase

Python tip:

Use .casfolde() instead of .lower() when you want to perform caseless operations when working with Unicode strings (for ASCII only strings they work the same) -- e.g., check if two strings are equal.

# In German ß == ss
print("straße".lower() == "strasse")
# False
print("straße".casefold() == "strasse")
# True

Python - remove a prefix from a string

Python tip (>=3.9):

You can use .removeprefix() to remove the prefix from a string.

For example, to remove a filename prefix:

invoice_filenames = ("INV_123.pdf", "INV_234.pdf", "INV_345.pdf")

for invoice_filename in invoice_filenames:
    print(invoice_filename.removeprefix("INV_"))

# 123.pdf
# 234.pdf
# 345.pdf

Python - remove a suffix from a string

Python tip (>=3.9):

You can remove the suffix of a string with .removesuffix().

For example, to remove the file type from a filename:

import pathlib

filename = "cv.pdf"

file_type_suffix = pathlib.Path(filename).suffix
print(filename.removesuffix(file_type_suffix))
# => cv

Pytest - Only run tests that match a substring expression

Pytest tip:

You can filter and run only tests that contain or do not contain some substring in their name.

Examples:

# run all tests that contain login in their name
$ pytest -k login

# run all tests that do not contain login in their name
$ pytest -k 'not login'

CSRF Protection in Flask with Flask-WTF

Flask tip:

You can use Flask-WTF to implement CSRF protection for your application.

Example:

from flask import Flask, Response, abort, redirect, render_template, request, url_for
from flask_login import (
    LoginManager,
    UserMixin,
    current_user,
    login_required,
    login_user,
    logout_user,
)
from flask_wtf.csrf import CSRFProtect

app = Flask(__name__)
app.config.update(
    DEBUG=True,
    SECRET_KEY="secret_sauce",
)

login_manager = LoginManager()
login_manager.init_app(app)

csrf = CSRFProtect()
csrf.init_app(app)

...

You can read more here: https://testdriven.io/blog/csrf-flask/.

Contract Testing in Python

Python clean code tip:

Use contract testing when you want to verify the same behavior for different implementations.

Example:

import json
import pathlib
from dataclasses import dataclass

import pytest


@dataclass
class User:
    username: str


class InMemoryUserRepository:
    def __init__(self):
        self._users = []

    def add(self, user):
        self._users.append(user)

    def get_by_username(self, username):
        return next(user for user in self._users if user.username == username)


class JSONUserRepository:
    def __init__(self, file_path):
        self._users = json.load(pathlib.Path(file_path).open())

    def add(self, user):
        self._users.append(user)

    def get_by_username(self, username):
        return next(user for user in self._users if user.username == username)


class UserRepositoryContract:
    @pytest.fixture
    def repository(self):
        raise NotImplementedError('Not Implemented Yet')

    @pytest.fixture
    def username(self):
        return 'johndoe'

    @pytest.fixture
    def user(self, username):
        return User(username=username)

    def test_added_user_is_retrieved_by_username(self, username, user, repository):
        repository.add(user)

        assert repository.get_by_username(user.username).username == username


class TestInMemoryUserRepository(UserRepositoryContract):
    @pytest.fixture
    def repository(self):
        return InMemoryUserRepository()


class TestInJSONUserRepository(UserRepositoryContract):
    @pytest.fixture
    def repository(self, tmp_path):
        users_file = tmp_path/"user.json"
        users_file.write_text(json.dumps([]))
        return JSONUserRepository(users_file)

Simplify Testing with Dependency Injection

Python clean code tip:

Use dependency injection to simplify testing

Example:

from dataclasses import dataclass

from fastapi import FastAPI


@dataclass
class User:
    username: str


class StartUserOnboarding:
    def __init__(self, user_repository):
        self._user_repository = user_repository

    def execute(self, username):
        user = User(username=username)
        self._user_repository.add(user)


class InMemoryUserRepository:
    def __init__(self):
        self._users = []

    def add(self, user):
        self._users.append(user)

    def get_by_username(self, username):
        return next(user for user in self._users if user.username == username)


class SQLiteUserRepository:
    def __init__(self, config):
        self._config = config

    def add(self, user):
        print(f"Running some SQL statements for insert DATABASE_PATH")

    def get_by_username(self, username):
        print(f"Running some SQL statements for fetch from {self._config.DATABASE_PATH}")


def test_user_is_added_to_repository():
    username = "[email protected]"
    repository = InMemoryUserRepository()
    use_case = StartUserOnboarding(user_repository=repository)

    use_case.execute(username)

    assert repository.get_by_username(username).username


class ApplicationConfig:
    DATABASE_PATH = "db"


app = FastAPI()


@app.post("/users/start-onboarding", status_code=202)
async def start_user_onboarding(username: str):
    StartUserOnboarding(SQLiteUserRepository(ApplicationConfig())).execute(username)

    return "OK"

Python - use enums to group related constants

Python clean code tip:

Use enums to group related constants.

Why?

1. Autocomplete
2. Static type checking

Example:

from dataclasses import dataclass
from enum import Enum

# bad
ORDER_PLACED = "PLACED"
ORDER_CANCELED = "CANCELED"
ORDER_FULFILLED = "FULFILLED"


@dataclass
class Order:
    status: str


order = Order(ORDER_PLACED)
print(order)


# better
class OrderStatus(str, Enum):
    PLACED = "PLACED"
    CANCELED = "CANCELED"
    FULFILLED = "FULFILLED"


@dataclass
class Order:
    status: OrderStatus


order = Order(OrderStatus.PLACED)
print(order)

Interfaces in Python with Protocol Classes

Python clean code tip:

Use Protocol to define the interface required by your function/method instead of using real objects. This way your function/method defines what it needs.

from typing import Protocol


class ApplicationConfig:
    DEBUG = False
    SECRET_KEY = "secret-key"
    EMAIL_API_KEY = "api-key"


# bad
def send_email(config: ApplicationConfig):
    print(f"Send email using API key: {config.EMAIL_API_KEY}")


# better
class EmailConfig(Protocol):
    EMAIL_API_KEY: str


def send_email_(config: EmailConfig):
    print(f"Send email using API key: {config.EMAIL_API_KEY}")

Python - Property-based Testing with Hypothesis

Python testing tip:

Rather than having to write different test cases for every argument you want to test, property-based testing generates a wide-range of random test data that's dependent on previous tests runs.

Use Hypothesis for this:

def increment(num: int) -> int:
    return num + 1


# regular test
import pytest


@pytest.mark.parametrize(
    'number, result',
    [
        (-2, -1),
        (0, 1),
        (3, 4),
        (101234, 101235),
    ]
)
def test_increment(number, result):
    assert increment(number) == result

# property-based test
from hypothesis import given
import hypothesis.strategies as st


@given(st.integers())
def test_add_one(num):
    assert increment(num) == num - 1

Python - mock.create_autospec()

Python tip:

Use mock.create_autospec() to create a mock object with methods that have the same interface as the ones inside the original object.

Example:

from unittest import mock

import requests
from requests import Response


def get_my_ip():
    response = requests.get(
        'http://ipinfo.io/json'
    )
    return response.json()['ip']


def test_get_my_ip(monkeypatch):
    my_ip = '123.123.123.123'
    response = mock.create_autospec(Response)
    response.json.return_value = {'ip': my_ip}

    monkeypatch.setattr(
        requests,
        'get',
        lambda *args, **kwargs: response
    )

    assert get_my_ip() == my_ip

Pytest - clean up resources at the end of a test session

Python clean test tip:

Clean up resources needed for test after the pytest session is finished -- i.e., drop test database, remove files added to the file system.

Example:

import csv
import os
import pathlib

import pytest


def list_users_from_csv(file_path):
    return [
        {field_name: field_value for field_name, field_value in row.items()}
        for row in csv.DictReader(
            file_path.open(),
            skipinitialspace=True,
            fieldnames=["first_name", "last_name"],
        )
    ]


@pytest.fixture
def users_csv_path():
    # before test - create resource
    file_path = pathlib.Path("users.csv")
    file_path.write_text("Jan,Giacomelli")
    yield file_path
    # after test - remove resource
    file_path.unlink()


def test_all_users_are_listed(users_csv_path):
    assert list_users_from_csv(users_csv_path) == [
        {"first_name": "Jan", "last_name": "Giacomelli"}
    ]

Arrange-Act-Assert - testing pattern

Python clean test tip:

Structure your tests in an Arrange-Act-Assert way:

• Arrange - set-up logic
• Act - invokes the system you're about to test
• Assert - verifies that the action of the system under test behaves as expected

Example:

from dataclasses import dataclass


@dataclass
class User:
    first_name: str
    last_name: str

    def full_name(self):
        return f"{self.first_name} {self.last_name}"


def test_full_name_consists_of_first_name_and_last_name():
    # arrange
    first_name = "John"
    last_name = "Doe"
    user = User(first_name=first_name, last_name=last_name)

    # act
    full_name = user.full_name()

    # assert
    assert full_name == "John Doe"

Pytest - Parameterizing Tests

Python clean test tip:

Use pytest parametrize when you need multiple cases to prove a single behavior.

Example:

import difflib
import pytest


def names_are_almost_equal(first, second):
    return difflib.SequenceMatcher(None, first, second).ratio() > 0.7


@pytest.mark.parametrize(
    "first,second",
    [
        ("John", "Johny"),
        ("Many", "Mary"),
    ]
)
def test_names_are_almost_equal(first, second):
    assert names_are_almost_equal(first, second)


@pytest.mark.parametrize(
    "first,second",
    [
        ("John", "Joe"),
        ("Daisy", "Serena"),
    ]
)
def test_names_are_not_almost_equal(first, second):
    assert not names_are_almost_equal(first, second)

Hide irrelevant test data

Python clean test tip:

You should hide irrelevant data for the test.

Such information just increases the cognitive mental load, resulting in bloated tests.

Example:

import uuid
from dataclasses import dataclass
from enum import Enum
from uuid import UUID
import pytest


class ProductCategory(str, Enum):
    BOOK = "BOOK"
    ELECTRONIC = "ELECTRONIC"


@dataclass
class Product:
    id: UUID
    price: int
    name: str
    category: ProductCategory


class ShoppingCart:
    def __init__(self):
        self._products = []

    def add(self, product):
        self._products.append(product)

    def calculate_total_price(self):
        return sum(product.price for product in self._products)


# BAD - category, id, and name are irrelevant for this test
def test_given_products_with_total_price_50_when_calculate_total_price_then_total_price_is_50_():
    shopping_cart = ShoppingCart()
    shopping_cart.add(Product(uuid.uuid4(), 10, "Mobile phone case", ProductCategory.ELECTRONIC))
    shopping_cart.add(Product(uuid.uuid4(), 20, "Never enough", ProductCategory.BOOK))
    shopping_cart.add(Product(uuid.uuid4(), 20, "Mobile phone charger", ProductCategory.ELECTRONIC))

    assert shopping_cart.calculate_total_price() == 50


# GOOD
@pytest.fixture
def product_with_price():
    def _product_with_price(price):
        return Product(uuid.uuid4(), price, "Mobile phone case", ProductCategory.ELECTRONIC)
    return _product_with_price


def test_given_products_with_total_price_50_when_calculate_total_price_then_total_price_is_50(product_with_price):
    shopping_cart = ShoppingCart()
    shopping_cart.add(product_with_price(10))
    shopping_cart.add(product_with_price(20))
    shopping_cart.add(product_with_price(20))

    assert shopping_cart.calculate_total_price() == 50

Tests should use meaningful data

Python clean test tip:

Your tests should use meaningful data in order to provide examples of how to use your code.

Examples:

from dataclasses import dataclass


@dataclass
class Car:
    manufacture: str
    model: str
    vin_number: str
    top_speed: int


class InMemoryCarRepository:
    def __init__(self):
        self._cars = []

    def add(self, car):
        self._cars.append(car)

    def get_by_vin_number(self, vin_number):
        return next(car for car in self._cars if car.vin_number == vin_number)


# BAD - non-existing manufacture and model, VIN number not matching manufacture and model, impossible to reach top speed
def test_added_car_can_be_retrieved_by_vin_number_():
    car = Car(manufacture="AAAA", model="BBB+", vin_number="2FTJW36M6LCA90573", top_speed=1600)
    repository = InMemoryCarRepository()
    repository.add(car)

    assert car == repository.get_by_vin_number(car.vin_number)


# GOOD
def test_added_car_can_be_retrieved_by_vin_number():
    car = Car(manufacture="Jeep", model="Wrangler", vin_number="1J4FA29P4YP728937", top_speed=160)
    repository = InMemoryCarRepository()
    repository.add(car)

    assert car == repository.get_by_vin_number(car.vin_number)

What should tests cover?

Python clean test tip:

For the most part, the tests you write should cover:

• all happy paths
• edge/corner/boundary cases
• negative test cases
• security and illegal issues

👇

import uuid
from dataclasses import dataclass
from typing import Optional


@dataclass
class User:
    username: str


class InMemoryUserRepository:
    def __init__(self):
        self._users = []

    def add(self, user: User) -> None:
        self._users.append(user)

    def search(self, query: Optional[str] = None) -> list[User]:
        if query is None:
            return self._users
        else:
            return [
                user
                for user in self._users
                if query in user.username
            ]


# happy path
def test_search_users_without_query_lists_all_users():
    user1 = User(username="[email protected]")
    user2 = User(username="[email protected]")
    repository = InMemoryUserRepository()
    repository.add(user1)
    repository.add(user2)

    assert repository.search() == [user1, user2]


# happy path
def test_search_users_with_email_part_lists_all_matching_users():
    user1 = User(username="[email protected]")
    user2 = User(username="[email protected]")
    user3 = User(username="[email protected]")
    repository = InMemoryUserRepository()
    repository.add(user1)
    repository.add(user2)
    repository.add(user3)

    assert repository.search("doe") == [user1, user3]


# edge test case
def test_search_users_with_empty_query_lists_all_users():
    user1 = User(username="[email protected]")
    user2 = User(username="[email protected]")
    repository = InMemoryUserRepository()
    repository.add(user1)
    repository.add(user2)

    assert repository.search("") == [user1, user2]


# negative test case
def test_search_users_with_random_query_lists_zero_users():
    user1 = User(username="[email protected]")
    repository = InMemoryUserRepository()
    repository.add(user1)

    assert repository.search(str(uuid.uuid4())) == []


# security test
def test_search_users_with_sql_injection_has_no_effect():
    user1 = User(username="[email protected]")
    repository = InMemoryUserRepository()
    repository.add(user1)

    repository.search("DELETE FROM USERS;")
    assert repository.search() == [user1]

Tests should validate themselves regardless of whether the test execution passes or fails

Python clean test tip:

A test should validate itself whether the test execution is passed or failed.

The self-validating test can avoid the need to do an evaluation manually by us.

Example:

from dataclasses import dataclass


@dataclass
class User:
    first_name: str
    last_name: str

    def fullname(self):
        return f"{self.first_name} {self.last_name}"


# BAD
def test_full_name_consists_of_first_name_and_last_name_manual():
    first_name = "John"
    last_name = "Doe"
    user = User(first_name=first_name, last_name=last_name)

    print(user.fullname())
    assert input("Is result correct? (Y/n)") == "Y"


# GOOD
def test_full_name_consists_of_first_name_and_last_name():
    first_name = "John"
    last_name = "Doe"
    full_name = "John Doe"
    user = User(first_name=first_name, last_name=last_name)

    assert user.fullname() == full_name

Tests should be independent

Python clean test tip:

A test should not depend on the state of any other tests or external services.

👇

from dataclasses import dataclass

import pytest


@dataclass
class User:
    username: str


class InMemoryUserRepository:
    def __init__(self):
        self._users = []

    def add(self, user: User) -> None:
        self._users.append(user)

    def get_by_username(self, username: str) -> User:
        return next(
            user
            for user in self._users
            if user.username == username
        )


# BAD - depends on persistence layer having user record at test time
def test_get_by_username():
    user = User(username="[email protected]")
    repository = InMemoryUserRepository()
    assert repository.get_by_username(user.username) == user


# BAD - test_user_is_fetched_by_username will succeed only when running after test_added_user
@pytest.fixture(scope="module")
def repository():
    return InMemoryUserRepository()


def test_added_user(repository):
    user = User(username="[email protected]")
    assert repository.add(user) is None


def test_user_is_fetched_by_username(repository):
    user = User(username="[email protected]")
    assert repository.get_by_username(user.username) == user


# GOOD - makes sure it has all the needed data
def test_added_user_is_fetched_by_username():
    user = User(username="[email protected]")
    repository = InMemoryUserRepository()

    repository.add(user)

    assert repository.get_by_username(user.username) == user

Tests should be repeatable and deterministic

Python clean test tip:

Your tests should be repeatable in any environment.

They should be deterministic, always result in the same tests succeeding.

Example:

import random

LOTTO_COMBINATION_LENGTH = 5
MIN_LOTTO_NUMBER = 1
MAX_LOTTO_NUMBER = 42


def lotto_combination():
    combination = []
    while len(combination) < LOTTO_COMBINATION_LENGTH:
        number = random.randint(MIN_LOTTO_NUMBER, MAX_LOTTO_NUMBER)
        if number not in combination:
            combination.append(number)

    return combination


# BAD
def test_lotto_combination():
    assert lotto_combination() == [10, 33, 5, 7, 2]


# GOOD
def test_all_numbers_are_between_min_max_range():
    assert all(MIN_LOTTO_NUMBER <= number <= MAX_LOTTO_NUMBER for number in lotto_combination())


def test_length_of_lotto_combination_has_expected_number_of_elements():
    assert len(lotto_combination()) == LOTTO_COMBINATION_LENGTH

Shorten your feedback loops by increasing the speed of your test suite

Python clean test tip:

Your tests should be fast. The faster the tests the faster the feedback loop.

Consider using mocks or test doubles when dealing with third-party APIs and other slow things.

Example:

import time


def fetch_articles():
    print("I'm fetching articles from slow API")
    time.sleep(10)
    return {"articles": [{"title": "Facebook is Meta now."}]}


# BAD
def test_fetch_articles_slow():
    assert fetch_articles() == {"articles": [{"title": "Facebook is Meta now."}]}


# GOOD
def test_fetch_articles_fast(monkeypatch):
    monkeypatch.setattr(time, "sleep", lambda timeout: None)
    assert fetch_articles() == {"articles": [{"title": "Facebook is Meta now."}]}

Tests should be useful

Python clean test tip:

Tests should protect you against regressions. They shouldn't just increase your code coverage percentage. Make sure they are useful! Don't just write tests for the sake of writing tests. They are code too, so they need to be maintained.

Example:

from dataclasses import dataclass


@dataclass
class User:
    first_name: str
    last_name: str

    def fullname(self):
        return f"{self.first_name} {self.last_name}"


# BAD
def test_full_name():
    user = User(first_name="John", last_name="Doe")
    assert user.fullname() is not None


# GOOD
def test_full_name_consists_of_first_name_and_last_name():
    first_name = "John"
    last_name = "Doe"
    full_name = "John Doe"
    user = User(first_name=first_name, last_name=last_name)

    assert user.fullname() == full_name

Test behavior, not implementation

Python clean test tip:

Tests should check the behavior rather than the underlying implementation details.

Such tests are easier to understand and maintain. They're also more resistant to refactoring (helps prevent false negatives).

👇

from dataclasses import dataclass


@dataclass
class User:
    username: str


class InMemoryUserRepository:
    def __init__(self):
        self._users = []

    def add(self, user):
        self._users.append(user)

    def get_by_username(self, username):
        return next(user for user in self._users if user.username == username)


# BAD
def test_add():
    user = User(username="johndoe")
    repository = InMemoryUserRepository()
    repository.add(user)

    assert user in repository._users


def test_get_by_username():
    user = User(username="johndoe")
    repository = InMemoryUserRepository()
    repository._users = [user]

    user_from_repository = repository.get_by_username(user.username)

    assert user_from_repository == user


# GOOD
def test_added_user_can_be_retrieved_by_username():
    user = User(username="johndoe")
    repository = InMemoryUserRepository()
    repository.add(user)

    assert user == repository.get_by_username(user.username)

Tests should fail for exactly one reason - aim for a single assert per test

Python clean test tip:

Aim for a single assert per test. Tests will be more readable and it's easier to locate a defect when a test is failing.

Example:

import pytest


class User:
    def __init__(self, username):
        if len(username) < 1:
            raise Exception("Username must not be empty.")
        self._username = username

    @property
    def username(self):
        return self._username


# BAD
def test_user():
    username = "johndoe"
    assert User(username).username == username

    username = ""
    with pytest.raises(Exception):
        User(username)


# GOOD
def test_user_with_valid_username_can_be_initialized():
    username = "johndoe"
    assert User(username).username == username


def test_user_with_empty_username_cannot_be_initialized():
    username = ""
    with pytest.raises(Exception):
        User(username)

It's fine to deviate from this, to include multiple asserts per test as long as you're testing the same concept.

Testing Naming Conventions - GIVEN-WHEN-THEN

Python clean test tip:

Tests should have descriptive names to reveal their intention. For example, you could follow GIVEN-WHEN-THEN or SHOULD-WHEN naming conventions:

import pytest
from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class LoginRequest(BaseModel):
    username: str
    password: str


@app.post("/login")
def login(data: LoginRequest):
    return {"access_token": "1234"}


@pytest.fixture()
def client():
    yield TestClient(app)


# BAD
def test_login(client):
    response = client.post("/login", json={"username": "johndoe", "password": "correct_password"})
    assert response.status_code == 200
    assert response.json()["access_token"] == "1234"


# GOOD
def test_valid_username_and_password_combination_can_be_exchanged_for_access_token(client):
    response = client.post("/login", json={"username": "johndoe", "password": "correct_password"})
    assert response.status_code == 200
    assert response.json()["access_token"] == "1234"


def test_given_valid_username_and_password_combination_when_user_calls_login_then_access_token_is_returned(client):
    response = client.post("/login", json={"username": "johndoe", "password": "correct_password"})
    assert response.status_code == 200
    assert response.json()["access_token"] == "1234"


def test_access_token_should_be_returned_when_valid_username_and_password_combination_is_provided(client):
    response = client.post("/login", json={"username": "johndoe", "password": "correct_password"})
    assert response.status_code == 200
    assert response.json()["access_token"] == "1234"

Docker - Use COPY --chown instead of RUN chown after COPY in Dockerfile

Docker best practice:

Use --chown option of Docker's COPY command instead of doing it manually to reduce build time.

 # manually changing owner
 COPY . $APP_HOME
 RUN chown -r app:app $APP_HOME

 # using --chown option
 COPY --chown=app:app . $APP_HOME

Docker and Python Virtual Environments

Docker tip:

You can use a virtual environment instead of building wheels in multi-stage builds.

For example:

# temp stage
FROM python:3.9-slim as builder

WORKDIR /app

ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1

RUN apt-get update && \
    apt-get install -y --no-install-recommends gcc

RUN python -m venv /opt/venv
ENV PATH="/opt/venv/bin:$PATH"

COPY requirements.txt .
RUN pip install -r requirements.txt


# final stage
FROM python:3.9-slim

COPY --from=builder /opt/venv /opt/venv

WORKDIR /app

ENV PATH="/opt/venv/bin:$PATH"

Note: This is one of the only use cases for using a Python virtual environment with Docker.

1. Install the dependencies in the builder image within a virtual environment.
2. Copy over the dependencies to the final image

This reduces the size of the final image significantly.

Docker Logging Best Practices - stdout and stderr

Docker best practice:

Your Docker applications should log to standard output (stdout) and standard error (stderr) rather than to a file.

You can then configure the Docker daemon to send your log messages to a centralized logging solution (like CloudWatch or Papertrail).

Set Docker Memory and CPU Limits

Docker best practice:

Limit CPU and memory for your containers to prevent crippling the rest of the containers on the machine.

Examples:

# using docker run
$ docker run --cpus=2 -m 512m nginx


# using docker-compose
version: "3.9"
services:
  redis:
    image: redis:alpine
    deploy:
      resources:
        limits:
          cpus: 2
          memory: 512M
        reservations:
          cpus: 1
          memory: 256M

Sign and Verify Docker Images

Docker best practice:

Sign and verify your Docker images to prevent running images that have been tampered with.

To verify the integrity and authenticity of an image, set the DOCKER_CONTENT_TRUST environment variable:

DOCKER_CONTENT_TRUST=1

Lint and Scan Your Dockerfiles and Images

Docker best practice:

Lint and scan your Dockerfiles and images to check your code for programmatic and stylistic errors and bad practices that could lead to potential flaws.

Some options:

• hadolint
• Synk
• Trivy
• Claire
• Anchore

👇

hadolint Dockerfile

Dockerfile:1 DL3006 warning: Always tag the version of an image explicitly
Dockerfile:7 DL3042 warning: Avoid the use of cache directory with pip. Use `pip install --no-cache-dir <package>`
Dockerfile:9 DL3059 info: Multiple consecutive `RUN` instructions. Consider consolidation.
Dockerfile:17 DL3025 warning: Use arguments JSON notation for CMD and ENTRYPOINT arguments

Use a .dockerignore File

A properly structured .dockerignore file can help:

1. Decrease the size of the Docker image
2. Speed up the build process
3. Prevent unnecessary cache invalidation
4. Prevent leaking secrets

Example:

**/.git
**/.gitignore
**/.vscode
**/coverage
**/.env
**/.aws
**/.ssh
Dockerfile
README.md
docker-compose.yml
**/.DS_Store
**/venv
**/env

Don't Embed Secrets in Docker Images

Docker best practice:

Don't store secrets in Docker images.

Instead, they should be injected via:

1. Environment variables (at run-time)
2. Build-time arguments (at build-time)
3. An orchestration tool like Docker Swarm (via Docker secrets) or Kubernetes (via Kubernetes secrets)

For more along with examples, check out Don't Store Secrets in Images.