google-cloud-datastore | based Java and Python client libraries | Database library

 by   GoogleCloudPlatform Java Version: python-5.0.0-beta License: Apache-2.0

kandi X-RAY | google-cloud-datastore Summary

kandi X-RAY | google-cloud-datastore Summary

google-cloud-datastore is a Java library typically used in Database applications. google-cloud-datastore has no bugs, it has no vulnerabilities, it has a Permissive License and it has high support. However google-cloud-datastore build file is not available. You can download it from GitHub, Maven.

Note: This repository contains low-level Java and Python client libraries for Google Cloud Datastore. For more idiomatic and usable client libraries in these languages, please visit the Google Cloud Client Libraries for Java and Google Cloud Client Libraries for Python repositories. You can also find the full list of supported client libraries in a variety of languages on the Client Libraries page of Cloud Datastore. Cloud Datastore is a highly-scalable NoSQL database for your applications. Cloud Datastore automatically handles sharding and replication, providing you with a highly available and durable database that scales automatically to handle your applications' load. Cloud Datastore provides a myriad of capabilities such as ACID transactions, SQL-like queries, indexes and much more. For more information, see the Cloud Datastore documentation. This repository contains clients that are deliberately low-level and map directly to the underlying Datastore RPC model. They're designed to provide more flexibility to developers and higher level library implementers.

            kandi-support Support

              google-cloud-datastore has a highly active ecosystem.
              It has 203 star(s) with 134 fork(s). There are 96 watchers for this library.
              It had no major release in the last 12 months.
              There are 49 open issues and 124 have been closed. On average issues are closed in 762 days. There are no pull requests.
              It has a positive sentiment in the developer community.
              The latest version of google-cloud-datastore is python-5.0.0-beta

            kandi-Quality Quality

              google-cloud-datastore has 0 bugs and 0 code smells.

            kandi-Security Security

              google-cloud-datastore has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              google-cloud-datastore code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              google-cloud-datastore 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.

            kandi-Reuse Reuse

              google-cloud-datastore releases are available to install and integrate.
              Deployable package is available in Maven.
              google-cloud-datastore has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              It has 3710 lines of code, 304 functions and 34 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

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            google-cloud-datastore Key Features

            No Key Features are available at this moment for google-cloud-datastore.

            google-cloud-datastore Examples and Code Snippets

            Read from CSV file and upload to Google Data Store Python
            Pythondot img1Lines of Code : 19dot img1License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def read_header_from_filename(filename):
              # note that depending on your newline character/file encoding, this may need to be modified
              file_handle =  
              header = file_handle.readline()
              return header.split(','
            How to update some entities in datastore by uploading a csv to datastore
            Pythondot img2Lines of Code : 60dot img2License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from import entity_pb2
            from import query_pb2
            from googledatastore import helper as datastore_helper
            import apache_beam as beam
            Apache Beam Google Datastore ReadFromDatastore entity protobuf
            Pythondot img3Lines of Code : 4dot img3License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from googledatastore import helper
            value_dict = dict((prop_name, helper.get_value(,) for prop_name in
            How to make stream pipeline pubsub to datastore with python?
            Pythondot img4Lines of Code : 9dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            pipeline_options = {
                'project': PROJECT,
                'staging_location': STAGING_LOCATION,
                'runner': 'DataflowRunner',
                'job_name': JOB_NAME,
                'temp_location': TEMP_LOCATION,
                'streaming': True,
                'save_main_session': True} # 
            Error importing cloud-spanner on apache beam 2.9
            Pythondot img5Lines of Code : 2dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            Missing required coder_id on grpc_port for -3; using deprecated fallback.
            Google Cloud Dataflow (Python) - Not installing dependencies correctly
            Pythondot img6Lines of Code : 2dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            --requirements_file requirements.txt
            error while importing WriteToDatastore (Apache Beam/Google DataFlow)
            Pythondot img7Lines of Code : 44dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import apache_beam as beam
            from import WriteToDatastore
            from import entity_pb2
            from import query_pb2
            from googledatastore import he
            Error when installing apache beam in datalab instance in GCP using python2 kernel
            Pythondot img8Lines of Code : 6dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            source activate py2env
            conda install -y pytz
            pip uninstall -y google-cloud-dataflow
            pip install --upgrade apache-beam[gcp]
            copy iconCopy
            if os.path.exists('requirements.txt'):
                with op
            ImportError phonenumbers with google cloud dataflow python
            Pythondot img10Lines of Code : 4dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            pip freeze > requirements.txt
            --requirements_file requirements.txt

            Community Discussions


            How to get the location/region of an Datastore instance
            Asked 2021-Dec-24 at 00:46

            To call the Datastore.export() API I need to provide a GCS bucket name in the same region as the Datastore I'm exporting.

            I checked with node.js' @google-cloud/datastore Datastore instances seem to have no .location property or something similar. Also, the Google provided Datastore libraries in other languages seem to lack this functionality.

            With other Google APIs you usually have a way to get the Location of the resource. E.g. in GCS: Storage().bucket('mybucket').getMetadata().location -> 'EU'.

            How to view Google Cloud Datastore Region shows to get this information in a manual way, but I'm after programmatic access.



            Answered 2021-Dec-24 at 00:46

            Firestore has a database get method (in preview as of 2021-12-23), that you can use to lookup the location of your database. This API will also tell you the mode of your database (Firestore native vs Datastore mode).



            How to get rid of call to CallCredentials2 in grpc api
            Asked 2021-Dec-01 at 19:46

            I'm writing some code for a class project that sends jobs to a dataproc cluster in GCP. I recently ran into an odd error and I'm having trouble wrapping my head around it. The error is as follows:



            Answered 2021-Dec-01 at 19:46

            Using mvn dependency:tree you can discover there's a mix of grpc-java 1.41.0 and 1.42.1 versions in your dependency tree. google-cloud-datastore:2.2.0 brings in grpc-api:1.42.1 but the other dependencies bring in grpc version 1.40.1.

            grpc-java recommends always using requireUpperBoundDeps from maven-enforcer to catch Maven silently downgrading dependencies.



            creating dataproc cluster with multiple jars
            Asked 2021-Nov-27 at 22:40

            I am trying to create a dataproc cluster that will connect dataproc to pubsub. I need to add multiple jars on cluster creation in the spark.jars flag



            Answered 2021-Nov-27 at 22:40

            The answer you linked is the correct way to do it: How can I include additional jars when starting a Google DataProc cluster to use with Jupyter notebooks?

            If you also post the command you tried with the escaping syntax and the resulting error message then others could more easily verify what you did wrong. It looks like you're specifying an additional spark property in addition to your list of jars spark:spark.driver.memory=3000m, and tried to just space-separate that from your jars flag, which isn't allowed.

            Per the linked result, you'd need to use the newly assigned separator character to separate the second spark property:



            Multipoint(df['geometry']) key error from dataframe but key exist. KeyError: 13 geopandas
            Asked 2021-Oct-11 at 14:51

            data source:

            I tried looking for a similar problem but I can't find an answer and the error does not help much. I'm kinda frustrated at this point. Thanks for the help. I'm calculating the closest distance from a point.



            Answered 2021-Oct-11 at 14:21

            geopandas 0.10.1

            • have noted that your data is on kaggle, so start by sourcing it
            • there really is only one issue shapely.geometry.MultiPoint() constructor does not work with a filtered series. Pass it a numpy array instead and it works.
            • full code below, have randomly selected a point to serve as gpdPoint



            what kind of bigtable replication do my datastore entities use?
            Asked 2021-Jan-23 at 17:11

            datastore docs say:

            the replication between Datastore servers. Replication is managed by Cloud Bigtable and Megastore, the underlying technologies for Datastore

            bigtable docs say:

            Replication for Cloud Bigtable enables you to increase the availability and durability of your data by copying it across multiple regions or multiple zones within the same region

            How can I see in the datastore UI if I'm getting any replication? If I am getting replication how can I see if I'm getting cross region or cross zone replication for my datastore entities?

            (The entities I'm looking at have been populated since 2017 if that's useful.)



            Answered 2021-Jan-23 at 13:07

            Cloud Datastore is only a regional service. You can't deploy it in multiple region in the same project.

            Its brother (or sister, I don't know), Firestore, can be deployed in multi region.

            So, Datastore is only mono region, but multi zonal in this unique region. And the BigTable replication mechanism is used to achieve this replication. You can't see this, it's serverless, transparent.



            Not able to access Datastore Resources from GKE
            Asked 2021-Jan-15 at 20:44

            I have deployed an app in GKE which makes a backend call to datastore to perform crud operations.Added cloud datastore owner role to the Service account on which gke is hosted.

            when i request any of the endpoint which makes call to the backend datastore i am getting below excpetion:



            Answered 2021-Jan-15 at 20:44

            It's a problem at node level permission. When you create your cluster, and your node pool, you can choose the security of your node. And you can explicitly allow or deny the access to some API, such as Datastore. And by default Datastore is disabled.

            You can check this in the Compute Engine that compose your GKE cluster:

            If you don't want to delete your Cluster, you need to create a new node pool, to migrate your pod and to remove the old node pool.

            Side remark. Don't you Service account key files. I recommend you to use workload identity for a better security



            ContextualVersionConflict using BigQuery in AI-Platform-Notebooks
            Asked 2021-Jan-07 at 05:46

            I am trying to use BigQuery in AI-Platform-Notebooks, but I am running into a ContextualVersionConflict. In this toy example, I am trying to pull two columns worth of data from the BigQuery database entitled bgt_all, in the project job2vec.



            Answered 2021-Jan-05 at 10:19

            In order to further contribute to the community I am posting the answer based on my comment above.

            Firstly, you should try to upgrade the packages using the command:

            pip install --upgrade pandas-gbq 'google-cloud-bigquery[bqstorage,pandas]'

            Then, instead of using the to_dataframe() method you can use the read_gbq(), which loads data from BigQuery using the environment's default project, as follows:



            Once deployed my app reports - Cannot import name 'vision' from ''
            Asked 2020-Dec-07 at 18:09

            I am working on a Google App and have an issue when I deploy it. The project contains two services website and worker. The website acts as a front page and the worker is run through a cron and has its page hit every 5 minutes.

            The issue I'm having is that when running them locally both services run fine. Once I deploy with gcloud the application returns an error in the Logs Console.

            The error is: ImportError: cannot import name 'vision' from '' (unknown location)

            It is the worker service that is not working. It's requirements.txt reads



            Answered 2020-Dec-07 at 18:09

            The issue seemed to be caused by the order of the components in the requirements file, similar to this issue. The solution is to explicitly include the grpcio module in the requirements.txt file, e.g. :



            What's the equivalent of appengine:run for the Java 11 Cloud SDK?
            Asked 2020-Aug-22 at 21:30

            tl;dr: How can I run this project locally, in a way that Datastore will work? (Zip download link here.)

            I'm migrating a Java 8 project that used App Engine and Datastore over to Java 11.

            With Java 8, I used the Cloud SDK-based App Engine plugin to run the server locally using mvn appengine:run and to deploy to the live server using mvn appengine:deploy.

            I followed this guide which told me to delete the appengine-web.xml file and use app.yaml instead..

            To deploy to the live server, I can still use mvn appengine:deploy and this works fine, with and without Datastore.

            To deploy locally, I run mvn package exec:java. This works fine for running a basic server without Datastore, but if I add some example Datastore code, then I get this error:



            Answered 2020-Aug-22 at 21:30

            Based on guillaume blaquiere's suggestion in their comment, I tried following this guide for manually running Datastore locally.

            I ran gcloud beta emulators datastore start in one command line, which seemed to run fine, and then I ran $(gcloud beta emulators datastore env-init) in another command line, and I got this error:



            Cloud Build fails to build App Engine Python 3.8 app (due to pip bug?)
            Asked 2020-Aug-22 at 16:54

            I have a number of Python 3.7 apps on Google App Engine standard, all building and deploying fine. I'm trying to upgrade some of them to the new Python 3.8 runtime, but when I try to deploy, they fail in Cloud Build.

            It looks like they're hitting this open pip bug (more background). Odd that only the Python 3.8 runtime triggers this bug, though, and 3.7 builds fine.

            Full log below. (Note that it's happening in Cloud Build, not my local machine, so I can't upgrade pip or otherwise change any of the commands or environment.) Anyone know how I can fix or work around this?



            Answered 2020-Aug-22 at 16:54

            I checked pypi page of oauth-dropins (at which it is failing) and they're mentioning there exactly this issue being caused by -e


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


            No vulnerabilities reported

            Install google-cloud-datastore

            You can download it from GitHub, Maven.
            You can use google-cloud-datastore 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 google-cloud-datastore 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 For Gradle installation, please refer .


            For more information, see the Cloud Datastore documentation.
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