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Manual
Use this section if sapi.py is not avialable in your distribution
1) Create the Endpoint package
- Create a folder in app/api/v1
Inside the folder create the __init__.py and the endpoint file
Tip A descriptive name works the best
On the endpoint file
2) Add the imports
Special attention to APIRouter
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from fastapi import APIRouter, Body from fastapi.requests import Request |
3) Declare the endpoint Router
- This is essentially a small branch of the app, which will hold all our related routes
The prefix indicates the prefix of the endpoint
Info All endpoint have the same base path, /es/api/v1, from here we attach the prefix, in this case being /Simple, so /es/api/v1/Simple
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router = APIRouter(prefix='/Simple', tags=['Simple']) |
4) Declare the routes
- At this point, all the routes are pure FastAPI
- The content of each route depends entirely on the one implementing the endpoint
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If you want more information on how to build routes, and what features are available please go to the FastAPI tutorial, whenever you see @app, just replace that with @router |
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@router.post('/post')
async def post_request(req: Request, body: dict = Body()):
return body
@router.post('/put/{name}')
async def post_request(req: Request, name: str):
return {"name": name}
@router.post('/get/{id}')
async def post_request(req: Request, id: int, param_a: int = 0):
return f'GET Request for id {id}, with number {param_a}' |
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In this scenario the path for each route is: /es/api/v1/Simple/post /es/api/v1/Simple/put/lincon /es/api/v1/Simple/get/42 |
on the __init__ file
5) Add the import for your router
- Go to the __init__.py file
- Import the router from the API file
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If you don’t import the router in the __init__.py, Search API won’t load it |
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from .simple import router |
6) Verify Endpoint Status
- Starting the server check the logs for the entry loading the endpoint
- In case of error, the logs will show the issue
- Either unable to load the endpoint or unable to initialize it
- Otherwise you should see Endpoint <endpoint path> added
You can go to /es/docs or /es/redocand check the
API documentation
Swagger (/es/docs)
ReDoc (/es/redoc)
Endpoint as a Pipeline Wrapper
Using an endpoint to wrap a pipeline gives some advantages when working on a project, specially if a separate team is needs to consume said endpoint, specially when compared to use the provided Pipeline endpoint
General Pipeline Endpoint
- Pipeline endpoint only accepts POST, without restriction of what parameters can accept
- User needs to know the parameters each pipeline accepts
- Proneto data input errors
Specific Pipeline Endpoint
- FastAPI allow to pass a Pydantic model as the Body, meaning all data validation
- Multiple methods (GET, PUT, POST, DELET) can apply to same pipeline
- Can add query parameters or path Parameters
- Customize pipeline response
- API documentation & User guidance for data input
How To Use The Pipeline In An API
We will use the Search Endpoint for this example
1) Create a Model
Create a file for the model in models/api
Info The __init__.py is already included in this package
on the model file
2) Add the imports
Since we are making a model from scratch we need to import BaseModel
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from typing import Optional from pydantic import BaseModel, Field, Extra from framework.aggregations.utils import SelectionAgg from models.engines import SortEntry from models.utils import BoolOperation |
3) Declare the model class
All models must inherit from BaseModel or from another model
Declare parameters as we did for Stages
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class ApiSearchRequest(BaseModel):
q: Optional[str] = Field(default='*', description='Query string')
query: Optional[dict] = Field(default=None, description='Specific query object for search engine')
knn: Optional[dict] = Field(default=None, description='Specific knn query object for search engine')
size: Optional[int] = Field(default=25, description='Number of hits to return per request')
sort: Optional[SortEntry] = Field(description='Sort field and order')
start: Optional[int] = Field(alias='from', description='Start position for retrieving hits', ge=0)
page: Optional[int] = Field(description='Start page for retrieving hits. Minimum page is 1. Not applicable when start, is being used', ge=1)
fetch_fields: Optional[list[str]] = Field(
description='List of fields to return in the response based on field values', title='Fetch Fields')
scroll: Optional[str] = Field(default=None, description='Period to retain the search context for scrolling')
default_operator: BoolOperation = Field(BoolOperation.OR,
description='The default operator for query string query: AND or OR',
title='Default Operator')
exclude_fields: Optional[list[str]] = Field(
description='List of fields to exclude in the response based on field values.', title='Exclude Fields')
aggs: Optional[list[SelectionAgg]] = Field(
description='List of selected aggregations. Usable only when a DynamicAggStage exist in the pipeline',
title='Aggregations') |
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We will not import the model in the __init__, because we want the route to be import like this
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