createSingleton | away best practice way to construct singletons | Architecture library

 by   tarunc JavaScript Version: Current License: MIT

kandi X-RAY | createSingleton Summary

kandi X-RAY | createSingleton Summary

createSingleton is a JavaScript library typically used in Architecture applications. createSingleton has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can install using 'npm i create-singleton' or download it from GitHub, npm.

An abstracted-away best practice way to construct singletons in JavaScript.
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            kandi-support Support

              createSingleton has a low active ecosystem.
              It has 8 star(s) with 1 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 0 open issues and 1 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of createSingleton is current.

            kandi-Quality Quality

              createSingleton has no bugs reported.

            kandi-Security Security

              createSingleton has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              createSingleton is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              createSingleton releases are not available. You will need to build from source code and install.
              Deployable package is available in npm.

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            createSingleton Key Features

            No Key Features are available at this moment for createSingleton.

            createSingleton Examples and Code Snippets

            No Code Snippets are available at this moment for createSingleton.

            Community Discussions

            QUESTION

            How do I customize ASP.Net Core model binding errors?
            Asked 2018-Jul-03 at 17:05

            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 17:05

            It'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:

            Source https://stackoverflow.com/questions/51145243

            QUESTION

            Pipeline will fail on GCP when writing tensorflow transform metadata
            Asked 2018-Mar-29 at 15:24

            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 15:24

            If 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?

            Source https://stackoverflow.com/questions/49546141

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            Vulnerabilities

            No vulnerabilities reported

            Install createSingleton

            You can install using 'npm i create-singleton' or download it from GitHub, npm.

            Support

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            gh repo clone tarunc/createSingleton

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