Python responses.JSONResponse方法代碼示例

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def register_route(self, app):
        self.app = app
        from starlette.responses import JSONResponse, HTMLResponse

        self.app.add_route(
            self.config.spec_url,
            lambda request: JSONResponse(self.spectree.spec),
        )

        for ui in PAGES:
            self.app.add_route(
                f'/{self.config.PATH}/{ui}',
                lambda request, ui=ui: HTMLResponse(
                    PAGES[ui].format(self.config.spec_url)
                ),
            ) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def graphql_http_server(self, request: Request) -> Response:
        try:
            data = await self.extract_data_from_request(request)
        except HttpError as error:
            return PlainTextResponse(error.message or error.status, status_code=400)

        context_value = await self.get_context_for_request(request)
        extensions = await self.get_extensions_for_request(request, context_value)
        middleware = await self.get_middleware_for_request(request, context_value)

        success, response = await graphql(
            self.schema,
            data,
            context_value=context_value,
            root_value=self.root_value,
            validation_rules=self.validation_rules,
            debug=self.debug,
            introspection=self.introspection,
            logger=self.logger,
            error_formatter=self.error_formatter,
            extensions=extensions,
            middleware=middleware,
        )
        status_code = 200 if success else 400
        return JSONResponse(response, status_code=status_code) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def simulator(request: requests.Request):
    token = request.headers.get("Authorization")
    if token:
        token = token[6:]  # Drop 'token '

    data = SimulatorSchema(await request.json())
    if data["pull_request"]:
        loop = asyncio.get_running_loop()
        title, summary = await loop.run_in_executor(
            None,
            functools.partial(
                _sync_simulator,
                data["mergify.yml"]["pull_request_rules"],
                *data["pull_request"],
                token=token,
            ),
        )
    else:
        title, summary = ("The configuration is valid", None)

    return responses.JSONResponse(
        status_code=200, content={"title": title, "summary": summary}
    ) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def post(self, request: Request) -> Response:
        content_type = request.headers.get("Content-Type", "")

        if "application/json" in content_type:
            try:
                data = await request.json()
            except json.JSONDecodeError:
                return JSONResponse({"error": "Invalid JSON."}, 400)
        elif "application/graphql" in content_type:
            body = await request.body()
            data = {"query": body.decode()}
        elif "query" in request.query_params:
            data = request.query_params
        else:
            return PlainTextResponse("Unsupported Media Type", 415)

        return await self._get_response(request, data=data) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def _get_response(self, request: Request, data: QueryParams) -> Response:
        try:
            query = data["query"]
        except KeyError:
            return PlainTextResponse("No GraphQL query found in the request", 400)

        config = get_graphql_config(request)
        background = BackgroundTasks()
        context = {"req": request, "background": background, **config.context}

        engine: Engine = config.engine
        result: dict = await engine.execute(
            query,
            context=context,
            variables=data.get("variables"),
            operation_name=data.get("operationName"),
        )

        content = {"data": result["data"]}
        has_errors = "errors" in result
        if has_errors:
            content["errors"] = format_errors(result["errors"])
        status = 400 if has_errors else 200

        return JSONResponse(content=content, status_code=status, background=background) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def analyze(request):
    data = await request.body()
    instances = json.loads(data.decode('utf-8'))['instances']

    # convert from image bytes to images to tensors
    img_bytes = [b64decode(inst['image_bytes']['b64']) for inst in instances]
    tensors = [pil2tensor(Image.open(BytesIO(byts)), dtype=np.float32).div_(255) for byts in img_bytes]
    tfm_tensors = [learner.data.valid_dl.tfms[0]((tensor, torch.zeros(0)))[0] for tensor in tensors]

    # batch predict, dummy labels for the second argument
    dummy_labels = torch.zeros(len(tfm_tensors))
    tensor_stack = torch.stack(tfm_tensors)
    if torch.cuda.is_available():
        tensor_stack = tensor_stack.cuda()
    pred_tensor = learner.pred_batch(batch=(tensor_stack, dummy_labels))

    # find the maximum value along the prediction axis
    classes = np.argmax(np.array(pred_tensor), axis=1)
    return JSONResponse(dict(predictions=classes.tolist())) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def index(request: Request) -> JSONResponse:
    with incoming_trace("fetch-counter", request, tracer) as span:
        with outgoing_trace("next-count", request, tracer, span) as out:
            outgoing_span, ougoing_headers = out

            counter = await requests.get(
                'http://service2:8000/', headers=ougoing_headers, timeout=1)
            data = counter.json()

            count = data['last']
            app.counter_gauge.set({"path": request.url.path}, count)

            return JSONResponse({
                'svc': 'service1',
                'version': '2',
                'timestamp': time.time(),
                'count': count
            }) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def index(request: Request) -> JSONResponse:
    with incoming_trace("fetch-counter", request, tracer) as span:
        with outgoing_trace("next-count", request, tracer, span) as out:
            outgoing_span, ougoing_headers = out

            counter_breaker = CircuitBreaker(
                fail_max=3, timeout_duration=timedelta(seconds=30))
            counter = await counter_breaker.call_async(
                requests.get, 'http://service2:8000/', timeout=1,
                headers=ougoing_headers)
            data = counter.json()

            count = data['last']
            app.counter_gauge.set({"path": request.url.path}, count)

            return JSONResponse({
                'svc': 'service1',
                'version': '3',
                'timestamp': time.time(),
                'count': count
            }) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def predict(request):
    """
    async api

    descriptions about this function
    """
    print(request.path_params)
    print(request.context)
    return JSONResponse({'label': 5, 'score': 0.5}) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def get(self, request):
        """
        health check
        """
        return JSONResponse({'msg': 'pong'}) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def get(self, request):
        """summary
        description"""
        return JSONResponse({'msg': 'pong'}) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def user_score(request):
    score = [randint(0, request.context.json.limit) for _ in range(5)]
    score.sort(reverse=request.context.query.order)
    assert request.context.cookies.pub == 'abcdefg'
    assert request.cookies['pub'] == 'abcdefg'
    return JSONResponse({
        'name': request.context.json.name,
        'score': score
    }) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def server(model):
    app = FastAPI()

    input_features = {
        f['name'] for f in model.model_definition['input_features']
    }

    @app.get('/')
    def check_health():
        return JSONResponse({"message": "Ludwig server is up"})

    @app.post('/predict')
    async def predict(request: Request):
        form = await request.form()
        files, entry = convert_input(form)

        try:
            if (entry.keys() & input_features) != input_features:
                return JSONResponse(ALL_FEATURES_PRESENT_ERROR,
                                    status_code=400)
            try:
                resp = model.predict(data_dict=[entry]).to_dict('records')[0]
                return JSONResponse(resp)
            except Exception as e:
                logger.error("Error: {}".format(str(e)))
                return JSONResponse(COULD_NOT_RUN_INFERENCE_ERROR,
                                    status_code=500)
        finally:
            for f in files:
                os.remove(f.name)

    return app 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def http_exception_handler(request: Request, exc: HTTPException) -> JSONResponse:
    headers = getattr(exc, "headers", None)
    if headers:
        return JSONResponse(
            {"detail": exc.detail}, status_code=exc.status_code, headers=headers
        )
    else:
        return JSONResponse({"detail": exc.detail}, status_code=exc.status_code) 

# 需要導入模塊: from starlette import responses [as 別名]
# 或者: from starlette.responses import JSONResponse [as 別名]
def request_validation_exception_handler(
    request: Request, exc: RequestValidationError
) -> JSONResponse:
    return JSONResponse(
        status_code=HTTP_422_UNPROCESSABLE_ENTITY,
        content={"detail": jsonable_encoder(exc.errors())},
    )