如何将JSON加载的参数传入FastAPI端点函数？

First, fix the immediate issues in your code:

• Remove the redundant app.mount("/", app) line—it’s unnecessary and can cause routing conflicts.
• Unpack your parameter dictionary using ** to pass each key-value pair as individual keyword arguments to my_endpoint.
• Since my_endpoint is a synchronous function, you don’t need asyncio.run—call it directly from your async endpoint (FastAPI automatically handles sync functions in async contexts via a thread pool).

Here’s the corrected code:

from fastapi import FastAPI

app = FastAPI()

@app.get('/my-endpoint')
def my_endpoint(
   arg1: int,
   arg2: str,
   # ... include all other 68 parameters here
   arg70: str
):
  print("Doing some action with those 70 arguments...")
  # ... your business logic here
  return "Some fake response"

# Example parameters stored as a dictionary (equivalent to your JSON)
arguments_dict = {
"arg1": 12,
"arg2": "extract",
# ... match all parameters required by my_endpoint
}

@app.get('/another-endpoint')
async def another_endpoint():
  # Unpack the dictionary into individual keyword arguments
  response = my_endpoint(**arguments_dict)
  return response

Better Approach for Maintainability (With Frequent Parameter Changes) #

Having 70 individual parameters in your function signature is hard to maintain, especially when parameters are added or removed regularly. Instead, use a Pydantic BaseModel to encapsulate all parameters:

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

# Define a model that includes all your parameters
class MyEndpointParams(BaseModel):
    arg1: int
    arg2: str
    # ... add all 70 parameters here with their types

@app.get('/my-endpoint')
def my_endpoint(params: MyEndpointParams):
  # Access parameters via params.arg1, params.arg2, etc.
  print("Doing some action with parameters...")
  # ... your logic
  return "Some fake response"

# Example parameter dict (loaded from JSON or stored)
arguments_dict = {
"arg1": 12,
"arg2": "extract",
# ... all parameters matching the model
}

@app.get('/another-endpoint')
async def another_endpoint():
  # Convert the dict to the Pydantic model instance
  params = MyEndpointParams(**arguments_dict)
  response = my_endpoint(params)
  return response

This way, when you need to add or remove parameters, you only update the MyEndpointParams model instead of modifying the function signature—much cleaner and less error-prone.

内容的提问来源于stack exchange，提问作者FN_