Dependencies - First Steps
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FastAPI has a very powerful but intuitive Dependency Injection system.
It is designed to be very simple to use, and to make it very easy for any developer to integrate other components with FastAPI.
What is “Dependency Injection”
“Dependency Injection” means, in programming, that there is a way for your code (in this case, your path operation functions) to declare things that it requires to work and use: “dependencies”.
And then, that system (in this case FastAPI) will take care of doing whatever is needed to provide your code with those needed dependencies (“inject” the dependencies).
This is very useful when you need to:
- Have shared logic (the same code logic again and again).
- Share database connections.
- Enforce security, authentication, role requirements, etc.
- And many other things…
All these, while minimizing code repetition.
First Steps
Let’s see a very simple example. It will be so simple that it is not very useful, for now.
But this way we can focus on how the Dependency Injection system works.
Create a dependency, or “dependable”
Let’s first focus on the dependency.
It is just a function that can take all the same parameters that a path operation function can take:
from typing import Optional
from fastapi import Depends, FastAPI
app = FastAPI()
async def common_parameters(q: Optional[str] = None, skip: int = 0, limit: int = 100):
return {"q": q, "skip": skip, "limit": limit}
@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
return commons
@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):
return commons
That’s it.
2 lines.
And it has the same shape and structure that all your path operation functions have.
You can think of it as a path operation function without the “decorator” (without the @app.get("/some-path")
).
And it can return anything you want.
In this case, this dependency expects:
- An optional query parameter
q
that is astr
. - An optional query parameter
skip
that is anint
, and by default is0
. - An optional query parameter
limit
that is anint
, and by default is100
.
And then it just returns a dict
containing those values.
Import Depends
from typing import Optional
from fastapi import Depends, FastAPI
app = FastAPI()
async def common_parameters(q: Optional[str] = None, skip: int = 0, limit: int = 100):
return {"q": q, "skip": skip, "limit": limit}
@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
return commons
@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):
return commons
Declare the dependency, in the “dependant”
The same way you use Body
, Query
, etc. with your path operation function parameters, use Depends
with a new parameter:
from typing import Optional
from fastapi import Depends, FastAPI
app = FastAPI()
async def common_parameters(q: Optional[str] = None, skip: int = 0, limit: int = 100):
return {"q": q, "skip": skip, "limit": limit}
@app.get("/items/")
async def read_items(commons: dict = Depends(common_parameters)):
return commons
@app.get("/users/")
async def read_users(commons: dict = Depends(common_parameters)):
return commons
Although you use Depends
in the parameters of your function the same way you use Body
, Query
, etc, Depends
works a bit differently.
You only give Depends
a single parameter.
This parameter must be something like a function.
And that function takes parameters in the same way that path operation functions do.
Tip
You’ll see what other “things”, apart from functions, can be used as dependencies in the next chapter.
Whenever a new request arrives, FastAPI will take care of:
- Calling your dependency (“dependable”) function with the correct parameters.
- Get the result from your function.
- Assign that result to the parameter in your path operation function.
graph TB common_parameters([“common_parameters”]) read_items[“/items/“] read_users[“/users/“] common_parameters —> read_items common_parameters —> read_users
This way you write shared code once and FastAPI takes care of calling it for your path operations.
Check
Notice that you don’t have to create a special class and pass it somewhere to FastAPI to “register” it or anything similar.
You just pass it to Depends
and FastAPI knows how to do the rest.
To async
or not to async
As dependencies will also be called by FastAPI (the same as your path operation functions), the same rules apply while defining your functions.
You can use async def
or normal def
.
And you can declare dependencies with async def
inside of normal def
path operation functions, or def
dependencies inside of async def
path operation functions, etc.
It doesn’t matter. FastAPI will know what to do.
Note
If you don’t know, check the Async: “In a hurry?” section about async
and await
in the docs.
Integrated with OpenAPI
All the request declarations, validations and requirements of your dependencies (and sub-dependencies) will be integrated in the same OpenAPI schema.
So, the interactive docs will have all the information from these dependencies too:
Simple usage
If you look at it, path operation functions are declared to be used whenever a path and operation matches, and then FastAPI takes care of calling the function with the correct parameters, extracting the data from the request.
Actually, all (or most) of the web frameworks work in this same way.
You never call those functions directly. They are called by your framework (in this case, FastAPI).
With the Dependency Injection system, you can also tell FastAPI that your path operation function also “depends” on something else that should be executed before your path operation function, and FastAPI will take care of executing it and “injecting” the results.
Other common terms for this same idea of “dependency injection” are:
- resources
- providers
- services
- injectables
- components
FastAPI plug-ins
Integrations and “plug-in”s can be built using the Dependency Injection system. But in fact, there is actually no need to create “plug-ins”, as by using dependencies it’s possible to declare an infinite number of integrations and interactions that become available to your path operation functions.
And dependencies can be created in a very simple and intuitive way that allow you to just import the Python packages you need, and integrate them with your API functions in a couple of lines of code, literally.
You will see examples of this in the next chapters, about relational and NoSQL databases, security, etc.
FastAPI compatibility
The simplicity of the dependency injection system makes FastAPI compatible with:
- all the relational databases
- NoSQL databases
- external packages
- external APIs
- authentication and authorization systems
- API usage monitoring systems
- response data injection systems
- etc.
Simple and Powerful
Although the hierarchical dependency injection system is very simple to define and use, it’s still very powerful.
You can define dependencies that in turn can define dependencies themselves.
In the end, a hierarchical tree of dependencies is built, and the Dependency Injection system takes care of solving all these dependencies for you (and their sub-dependencies) and providing (injecting) the results at each step.
For example, let’s say you have 4 API endpoints (path operations):
/items/public/
/items/private/
/users/{user_id}/activate
/items/pro/
then you could add different permission requirements for each of them just with dependencies and sub-dependencies:
graph TB current_user([“current_user”]) active_user([“active_user”]) admin_user([“admin_user”]) paying_user([“paying_user”]) public[“/items/public/“] private[“/items/private/“] activate_user[“/users/{user_id}/activate”] pro_items[“/items/pro/“] current_user —> active_user active_user —> admin_user active_user —> paying_user current_user —> public active_user —> private admin_user —> activate_user paying_user —> pro_items
Integrated with OpenAPI
All these dependencies, while declaring their requirements, also add parameters, validations, etc. to your path operations.
FastAPI will take care of adding it all to the OpenAPI schema, so that it is shown in the interactive documentation systems.