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prediction-try-java-python | Sample application illustrating use of the Google | GCP library

 by   GoogleCloudPlatform Java Version: Current License: Apache-2.0

 by   GoogleCloudPlatform Java Version: Current License: Apache-2.0

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kandi X-RAY | prediction-try-java-python Summary

prediction-try-java-python is a Java library typically used in Cloud, GCP applications. prediction-try-java-python has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However prediction-try-java-python build file is not available. You can download it from GitHub.
sample application illustrating use of the google prediction api within the google app engine environmenttry prediction (v1.0). this project provides a complete application illustrating use of the google prediction api within the google app engine environment. sample code is provided for both the java and python app engine runtimes, along with resources for css, javascript, images and config data files, all of which are shared across the two runtime environments. the application presents a simple interactive user experience: select a prediction model, enter a corresponding set of input text and submit your prediction request. for classification models, a graphical response is provided showing the confidence level for each category in the selected model. for regression models, a numerical result is presented. the set of models supported and the corresponding input fields are entirely dynamic and controlled by a
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kandi-support Support

  • prediction-try-java-python has a low active ecosystem.
  • It has 59 star(s) with 36 fork(s). There are 86 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 6 open issues and 2 have been closed. On average issues are closed in 49 days. There are 1 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of prediction-try-java-python is current.
This Library - Support
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This Library - Support
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quality kandi Quality

  • prediction-try-java-python has 0 bugs and 0 code smells.
This Library - Quality
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This Library - Quality
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securitySecurity

  • prediction-try-java-python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • prediction-try-java-python code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
This Library - Security
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This Library - Security
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license License

  • prediction-try-java-python is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
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This Library - License
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buildReuse

  • prediction-try-java-python releases are not available. You will need to build from source code and install.
  • prediction-try-java-python has no build file. You will be need to create the build yourself to build the component from source.
  • It has 2811 lines of code, 15 functions and 22 files.
  • It has low code complexity. Code complexity directly impacts maintainability of the code.
This Library - Reuse
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This Library - Reuse
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Top functions reviewed by kandi - BETA

kandi has reviewed prediction-try-java-python and discovered the below as its top functions. This is intended to give you an instant insight into prediction-try-java-python implemented functionality, and help decide if they suit your requirements.

  • HTTP GET request .
    • Parses a JsonFile .
      • Forward to the request .
        • Handle GET operation .

          Get all kandi verified functions for this library.

          Get all kandi verified functions for this library.

          prediction-try-java-python Key Features

          Python 2.5 or later

          Google App Engine

          Google Python API Client

          Command line flags modules for Python

          HTTP Client Library for Python

          Google OAuth 2.0 Client Library for Python

          URI Templates for Python

          Java 5 (or higher) standard (SE) and enterprise (EE)

          Google App Engine

          Maven

          Maven Plugin for App Engine

          Clone this repo into a new directory.

          Customize the following files: In shared/rc/client_secrets.json, replace the placeholder strings with your actual client id and client secret from the Google APIs console. In shared/rc/models.json, enter information about the model(s) you would like to use, following the format shown for the two sample models. Java only: edit the file gae-java/src/main/java/com/google/tryPredictionJava/web/IndexServlet.java to specify your redirect URI, which should be your app’s base URI /auth_return, e.g. http://your-app-name.appspot.com/auth_return. Add your redirect URI (defined in previous step) to the list of valid redirect URIs in the "API Access" tab of the APIs Console. If you miss this step, you’ll get a redirect_uri_mismatch error during initial authorization of the shared server credentials.

          Build and deploy your app: For Python: Modify the "application:" line in your app.yaml file to reflect your chosen app name and use the Google App Engine tools to deploy your app. Install google-api-python-client library to your project vendor dir via pip: pip install -t vendor -r requirements.txt Note: this is only required for dev. On production this is done upon deployment For Java: modify the contents of the "application" XML element in your gae-java/src/main/webapp/WEB-INF/appengine-web.xml file to reflect your chosen app name and use the Maven plugin for Google App Engine to deploy your app (you need to run "mvn gae:unpack" once and then you can subsequently deploy your app repeatedly with "mvn gae:deploy").

          The first time you access your app, it will step you through the login and OAuth 2.0 sequence, however, all access thereafter, by you or anyone else, will reuse your initially established security credentials. If you ever wish to change or re-establish the shared server credentials, simply visit your service’s URI with the "/reset" suffix (note that the reset service can only be invoked by the application administrator).

          Community Discussions

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          QUESTION

          Submit command line arguments to a pyspark job on airflow

          Asked 2022-Mar-29 at 10:37

          I have a pyspark job available on GCP Dataproc to be triggered on airflow as shown below:

          config = help.loadJSON("batch/config_file")
          
          MY_PYSPARK_JOB = {
              "reference": {"project_id": "my_project_id"},
              "placement": {"cluster_name": "my_cluster_name"},
              "pyspark_job": {
                  "main_python_file_uri": "gs://file/loc/my_spark_file.py"]
                  "properties": config["spark_properties"]
                  "args": <TO_BE_ADDED>
              },
          }
          
          

          I need to supply command line arguments to this pyspark job as show below [this is how I am running my pyspark job from command line]:

          spark-submit gs://file/loc/my_spark_file.py --arg1 val1 --arg2 val2
          

          I am providing the arguments to my pyspark job using "configparser". Therefore, arg1 is the key and val1 is the value from my spark-submit commant above.

          How do I define the "args" param in the "MY_PYSPARK_JOB" defined above [equivalent to my command line arguments]?

          ANSWER

          Answered 2022-Mar-28 at 08:18

          You have to pass a Sequence[str]. If you check DataprocSubmitJobOperator you will see that the params job implements a class google.cloud.dataproc_v1.types.Job.

          class DataprocSubmitJobOperator(BaseOperator):
          ...
              :param job: Required. The job resource. If a dict is provided, it must be of the same form as the protobuf message.
              :class:`~google.cloud.dataproc_v1.types.Job` 
          

          So, on the section about job type pySpark which is google.cloud.dataproc_v1.types.PySparkJob:

          args Sequence[str] Optional. The arguments to pass to the driver. Do not include arguments, such as --conf, that can be set as job properties, since a collision may occur that causes an incorrect job submission.

          Source https://stackoverflow.com/questions/71616491

          Community Discussions, Code Snippets contain sources that include Stack Exchange Network

          Vulnerabilities

          No vulnerabilities reported

          Install prediction-try-java-python

          You can download it from GitHub.
          You can use prediction-try-java-python like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the prediction-try-java-python component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

          Support

          For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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