#!usr/bin/env python
# -*- coding:utf-8 _*-
"""
# author: 小菠萝测试笔记
# blog: https://www.cnblogs.com/poloyy/
# time: 2021/10/9 7:25 下午
# file: 52_settings_env.py
"""
import os
import uvicorn
from fastapi import FastAPI
from pydantic import BaseSettings
class Settings(BaseSettings):
app_name: str = "Awesome API"
admin_email: str
items_per_user: int = 50
settings = Settings()
app = FastAPI()
@app.get("/info")
async def info():
return {
"app_name": settings.app_name,
"admin_email": settings.admin_email,
"items_per_user": settings.items_per_user,
}
要为单个命令设置多个环境变量,只需用空格分隔它们,并将它们全部放在命令之前
ADMIN_EMAIL="deadpool@example.com" APP_NAME="ChimichangApp" uvicorn main:app
from pydantic import BaseSettings
class Settings(BaseSettings):
app_name: str = "Awesome API"
admin_email: str
items_per_user: int = 50
settings = Settings()
from fastapi import FastAPI
from .config import settings
app = FastAPI()
@app.get("/info")
async def info():
return {
"app_name": settings.app_name,
"admin_email": settings.admin_email,
"items_per_user": settings.items_per_user,
}
from pydantic import BaseSettings
class Settings(BaseSettings):
app_name: str = "Awesome API"
admin_email: str
items_per_user: int = 50
这里不创建默认实例 settings = Settings()
from fastapi import FastAPI, Depends
from functools import lru_cache
from .config import Settings
app = FastAPI()
@lru_cache
def get_settings():
return Settings
@app.get("/info")
async def info(settings: Settings = Depends(get_settings)):
return {
"app_name": settings.app_name,
"admin_email": settings.admin_email,
"items_per_user": settings.items_per_user,
}
from fastapi.testclient import TestClient
from .config import Settings
from .main import app, get_settings
client = TestClient(app)
# 依赖覆盖,为 Settings 对象设置一个新的 admin_email 值
def get_settings_override():
return Settings(admin_email="testing_admin@example.com")
app.dependency_overrides[get_settings] = get_settings_override
def test_app():
response = client.get("/info")
data = response.json()
assert data == {
"app_name": "Awesome API",
"admin_email": "testing_admin@example.com",
"items_per_user": 50,
}
> pytest 53_settings_test.py
============================================================================================================ test session starts ============================================================================================================
platform darwin -- Python 3.9.5, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: /Users/polo/Downloads/FastAPI_project
plugins: anyio-3.3.2
collected 1 item
53_settings_test.py . [100%]
============================================================================================================= 1 passed in 0.30s =============================================================================================================
如果有会经常变化的设置项,也许在不同的环境中,将它们放在一个文件中,然后从文件中读取它们,就好像它们是环境变量一样
这些环境变量通常放在一个文件 .env 中,该文件称为“dotenv”
pip install python-doten
ADMIN_EMAIL="xiaopolo@example.com"
APP_NAME="小菠萝"
from pydantic import BaseSettings
class Settings(BaseSettings):
app_name: str = "Awesome API"
admin_email: str
items_per_user: int = 50
class Config:
# 设置需要识别的 .env 文件
env_file = ".env"
# 设置字符编码
env_file_encoding = 'utf-8'
# 创建 Settings 对象的时候指定
settings = Settings(_env_file='.env', _env_file_encoding='utf-8')
继上面的栗子,读取 .env 文件可能是一件代价高昂(缓慢)的操作
从性能角度出发,肯定希望只读取一次,后续每个请求可以重复使用同一个 Settings 对象,这样就只会读取一次 .env 文件
def get_settings():
return Settings()
上述代码,如果作为请求的依赖项,那么每次请求进来,都会创建一个 Settings 对象,然后读取一次 .env 文件,这不是我们希望的
如果加上了 @lru_cache 那么 get_settings 只会在第一次调用的时候执行一次,然后 Settings 对象也只会创建一次,.env 文件也只会读取一次
from functools import lru_cache
from fastapi import Depends, FastAPI
from . import config
app = FastAPI()
@lru_cache()
def get_settings():
return config.Settings()
@app.get("/info")
async def info(settings: config.Settings = Depends(get_settings)):
return {
"app_name": settings.app_name,
"admin_email": settings.admin_email,
"items_per_user": settings.items_per_user,
}
对于后续请求的依赖项中的 get_settings() 的任何后续调用,它不会执行 get_settings() 的内部代码并创建新的 Settings 对象,而是返回与第一次调用时返回的相同对象
@lru_cache()
def say_hi(name: str, salutation: str = "Ms."):
print(123)
return f"Hello {salutation} {name}"
print(say_hi(name="Camila"))
print(say_hi(name="Camila"))
print(say_hi(name="Rick", salutation="Mr."))
print(say_hi(name="Rick", salutation="Mr."))
print(say_hi(name="Camila"))
print(say_hi(name="Rick", salutation="Mr."))
123
Hello Ms. Camila
Hello Ms. Camila
123
Hello Mr. Rick
Hello Mr. Rick
Hello Ms. Camila
Hello Mr. Rick
使用完全相同的参数调用函数时,直接返回结果而不会执行厘米的代码