createSingleton | away best practice way to construct singletons | Architecture library
kandi X-RAY | createSingleton Summary
kandi X-RAY | createSingleton Summary
An abstracted-away best practice way to construct singletons in JavaScript.
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QUESTION
I would like to return only standardized error responses from my Web API (Asp.net Core 2.1), but I can't seem to figure out how to handle model binding errors.
The project is just created from the "ASP.NET Core Web Application" > "API" template. I've got a simple action defined as:
...ANSWER
Answered 2018-Jul-03 at 17:05It's worth mentioning that ASP.NET Core 2.1 added the [ApiController]
attribute, which among other things, automatically handles model validation errors by returning a BadRequestObjectResult
with ModelState
passed in. In other words, if you decorate your controllers with that attribute, you no longer need to do the if (!ModelState.IsValid)
check.
Additionally, the functionality is also extensible. In Startup
, you can add:
QUESTION
I hope somebody here can help. I've been googling this error like crazy but haven't found anything.
I have a pipeline that works perfectly when executed locally but it fails when executed on GCP. The following are the error messages that I get.
Workflow failed. Causes: S03:Write transform fn/WriteMetadata/ResolveBeamFutures/CreateSingleton/Read+Write transform fn/WriteMetadata/ResolveBeamFutures/ResolveFutures/Do+Write transform fn/WriteMetadata/WriteMetadata failed., A work item was attempted 4 times without success. Each time the worker eventually lost contact with the service. The work item was attempted on:
Traceback (most recent call last): File "preprocess.py", line 491, in main() File "preprocess.py", line 487, in main transform_data(args,pipeline_options,runner) File "preprocess.py", line 451, in transform_data eval_data |= 'Identity eval' >> beam.ParDo(Identity()) File "/Library/Python/2.7/site-packages/apache_beam/pipeline.py", line 335, in exit self.run().wait_until_finish() File "/Library/Python/2.7/site-packages/apache_beam/runners/dataflow/dataflow_runner.py", line 897, in wait_until_finish (self.state, getattr(self._runner, 'last_error_msg', None)), self) apache_beam.runners.dataflow.dataflow_runner.DataflowRuntimeException: Dataflow pipeline failed. State: FAILED, Error: Traceback (most recent call last): File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/batchworker.py", line 582, in do_work work_executor.execute() File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/executor.py", line 166, in execute op.start() File "apache_beam/runners/worker/operations.py", line 294, in apache_beam.runners.worker.operations.DoOperation.start (apache_beam/runners/worker/operations.c:10607) def start(self): File "apache_beam/runners/worker/operations.py", line 295, in apache_beam.runners.worker.operations.DoOperation.start (apache_beam/runners/worker/operations.c:10501) with self.scoped_start_state: File "apache_beam/runners/worker/operations.py", line 300, in apache_beam.runners.worker.operations.DoOperation.start (apache_beam/runners/worker/operations.c:9702) pickler.loads(self.spec.serialized_fn)) File "/usr/local/lib/python2.7/dist-packages/apache_beam/internal/pickler.py", line 225, in loads return dill.loads(s) File "/usr/local/lib/python2.7/dist-packages/dill/dill.py", line 277, in loads return load(file) File "/usr/local/lib/python2.7/dist-packages/dill/dill.py", line 266, in load obj = pik.load() File "/usr/lib/python2.7/pickle.py", line 858, in load dispatchkey File "/usr/lib/python2.7/pickle.py", line 1083, in load_newobj obj = cls.new(cls, *args) TypeError: new() takes exactly 4 arguments (1 given)
Any ideas??
Thanks,
Pedro
...ANSWER
Answered 2018-Mar-29 at 15:24If the pipeline works locally but fails on GCP it's possible that you're running into a version mismatch.
What TF, tf.Transform, beam versions are you running locally and on GCP?
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