incubator-superset | Apache Superset is a Data Visualization | Data Visualization library

 by   apache Python Version: 0.38.0 License: Apache-2.0

kandi X-RAY | incubator-superset Summary

kandi X-RAY | incubator-superset Summary

incubator-superset is a Python library typically used in Analytics, Data Visualization applications. incubator-superset has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install incubator-superset' or download it from GitHub, PyPI.

Apache Superset is a Data Visualization and Data Exploration Platform

            kandi-support Support

              incubator-superset has a medium active ecosystem.
              It has 31662 star(s) with 6530 fork(s). There are 1312 watchers for this library.
              It had no major release in the last 12 months.
              There are 393 open issues and 4913 have been closed. On average issues are closed in 103 days. There are 82 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of incubator-superset is 0.38.0

            kandi-Quality Quality

              incubator-superset has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              incubator-superset 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

              incubator-superset releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              incubator-superset saves you 62371 person hours of effort in developing the same functionality from scratch.
              It has 70846 lines of code, 3283 functions and 1365 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

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            incubator-superset Key Features

            No Key Features are available at this moment for incubator-superset.

            incubator-superset Examples and Code Snippets

            incubator-superset - data
            JavaScriptdot img1Lines of Code : 137dot img1License : Non-SPDX (Apache License 2.0)
            copy iconCopy
             * Licensed to the Apache Software Foundation (ASF) under one
             * or more contributor license agreements.  See the NOTICE file
             * distributed with this work for additional information
             * regarding copyright ownership.  The ASF licenses this file
            incubator-superset - sidebars
            JavaScriptdot img2Lines of Code : 16dot img2License : Non-SPDX (Apache License 2.0)
            copy iconCopy
             * Licensed to the Apache Software Foundation (ASF) under one
             * or more contributor license agreements.  See the NOTICE file
             * distributed with this work for additional information
             * regarding copyright ownership.  The ASF licenses this file
            incubator-superset - matomo
            JavaScriptdot img3Lines of Code : 15dot img3License : Non-SPDX (Apache License 2.0)
            copy iconCopy
             * Licensed to the Apache Software Foundation (ASF) under one
             * or more contributor license agreements.  See the NOTICE file
             * distributed with this work for additional information
             * regarding copyright ownership.  The ASF licenses this file

            Community Discussions


            No package metadata was found for apache-superset
            Asked 2022-Jan-14 at 00:53
            (superset) cwj0@ubuntu:~/anaconda3/envs/superset/lib/python3.7/site-packages/incubator-superset$ superset init
            Traceback (most recent call last):
              File "/home/cwj0/anaconda3/envs/superset/bin/superset", line 33, in 
                sys.exit(load_entry_point('apache-superset', 'console_scripts', 'superset')())
              File "/home/cwj0/anaconda3/envs/superset/bin/superset", line 22, in importlib_load_entry_point
                for entry_point in distribution(dist_name).entry_points
              File "/home/cwj0/anaconda3/envs/superset/lib/python3.7/site-packages/importlib_metadata/", line 951, in distribution
                return Distribution.from_name(distribution_name)
              File "/home/cwj0/anaconda3/envs/superset/lib/python3.7/site-packages/importlib_metadata/", line 542, in from_name
                raise PackageNotFoundError(name)
            importlib_metadata.PackageNotFoundError: No package metadata was found for apache-superset


            Answered 2022-Jan-14 at 00:53

            Solved. Because this is the need to refresh the permissions after I add a new page, I don't know why the dependencies are missing, and the installation is solved.

            pip install -r requirements/local.txtpip install -e .



            I have mysql and apache superset setup on dockers and connected by a bridge network, what will theSQLAlchemy URI be?
            Asked 2020-Dec-11 at 10:09

            I pulled the official superset image:



            Answered 2020-Dec-08 at 18:54

            I don't have a lot of experience with Docker, but I don't think you should use 8088 as the host for your MySQL database.

            Try using mysql://user:password@ as the URI.



            Has anyone tried making custom charts with Superset as per blog?
            Asked 2020-Aug-09 at 12:15

            So I have followed: for creating a simple hello-world plugin and also followed this video:

            It worked really smooth in there but when I try it at my end, I run into a lot of issues. I tried running it on docker as well, still it didn't work. Pypi version seems to be outdated. Here's the error i get when I try to run npm run prod:

            ERROR in ./src/visualizations/presets/MainPreset.js Module not found: Error: Can't resolve '@superset-ui/plugin-chart-hello-world' in '/home/spidey/apache_superset/superset-dev/incubator-superset/superset-frontend/src/visualizations/presets'

            When I open the MainPreset.js file:

            Here is how it looks: And the bottom configuration:

            Going back to superset-frontend/node-modules/@superset-ui/ I have:

            When I run npm run dev-server: But since I am running it on Virtual Instance so I can't open up the browser and check, whereas when I try npm run prod the error still persists:



            Answered 2020-Jul-29 at 16:17

            I have a suspicion of what's happening here. Is it possible that your plugin is not in superset-frontend/package.json?

            Note that if you put your hello-world plugin in package.json, and THEN do npm install, the npm install won't work. It's frustrating, but you need to do these things in the correct order:

            1. npm install (this nukes any npm links)
            2. add the plugin to your package.json (version number doesn't really matter)
            3. do the npm link ../../...... routine
            4. npm run dev-server

            Hope that helps, but I'll continue to try to help wherever I'm able.



            How to configure Celery Worker and Beat for Email Reporting in Apache Superset running on Docker?
            Asked 2020-May-12 at 11:32

            I am running Superset via Docker. I enabled the Email Report feature and tried it:

            However, I only receive the test email report. I don't receive any emails after.

            This is my CeleryConfig in



            Answered 2020-Apr-21 at 14:06

            I believe Celery needs to run inside your superset container - so you'll need to modify your dockerfile and entrypoint.
            BUT you should really first daemonize celery so you don't have to monitor and restart celery [see how to detect failure and auto restart celery worker and].
            See an example here for how to run a daemonized celery process in docker: Docker - Celery as a daemon - no pidfiles found



            Terraform: Deploying a Docker Compose app on EKS/ECS
            Asked 2020-Apr-21 at 15:31

            I use an open-source server application running on Docker Compose. It has a few services, including PostgreSQL DB and Redis.

            How can I best deploy this application to AWS in full IaC with Terraform?

            Solutions so far 1. AWS ecs-cli

            ecs-cli now supports sending docker compose configs in Amazon ECS.

            However, I do not think it could be integrated with the Terraform workflow (which is maybe not a big fuss). What I know for sure is that ecs-cli is not supported in CloudFormation, as per this issue, still open at this time. So I assume it cannot easily be added to Terraform either.

            2. The hard EKS way
            • Take your docker-compose.yml file, translate it to kubectl YAML.
            • (Prepare to doing so every time the package upgrades).
            • Deploy using Terraform's + EKS APIs (minimal example).

            But that is not fully IaC yet. And you have to retranslate your config each time the docker-compose changes in the source repository. And it sounds like a lot of work.

            3. Using a Helm chart
            • Write a Helm chart for the application.
            • Run Terraform to start a cluster.
            • Still run Terraform with a helm provider to install the application with Helm on the cluster.
            4. [Not OK] k8s Kompose

            I read Kompose can automagically translate a Docker Compose configuration to a k8s configuration, but they don't appear to be ported on AWS, not to talk about Terraform.

            5. [Not OK] The dirty AMI solution
            • Build a custom EC2 AMI with Packer.
            • Using Terraform, set up the DB, Redis and all permissions / network / etc.
            • Start an EC2 instance with the custom AMI.
            • The AMI contains (customized) application code, especially the docker-compose.yml. And the Docker images.
            • The AMI starts a Docker Compose systemctl service.

            That would kind of hurt: long builds, difficult monitoring, no scaling.

            Side notes
            • I mentioned I need full IaC. What I mean by it is:
              1. The written config (and it only) on master tells you what is deployed.
              2. The deploy will complete without my team having to run any other command. It basically works either on CI/CD or on single-push'n'go.
              3. Monitoring and alerting are easily configured in the IaC.
            • I wish to replace some services with AWS components (namely, the PostgreSQL service by an RDS, and the Redis service with an ElastiCache).
            • The application happens to be Apache Superset. However I am also wondering what is considered the best general approach to this Docker Compose problem.


            Answered 2020-Apr-20 at 14:22
            1. Wait and See

            Who knows, ecs-cli-v2 might be better integrated with CloudFormation and/or Terraform.

            2. Use a Helm chart

            As mentioned in the question. Probably the best solution, albeit requiring a (little) effort to parametrize Helm.

            See also: Getting started with Helm.

            3. Docker Swarm + CloudFormation + Terraform

            Docker Swarm now accepts inputs from a docker-compose.yml file. The template can be found and configured here. Once configured, it may be integrated to a Terraform infrastructure.

            This (3-year old) tutorial explains how to use Docker Swarm mode on AWS.

            To launch the container, if necessary (not fully investigated, feedback is welcome), you could use Terraform's local-exec. This way you can SSH into the master node and run docker stack deploy and other similar commands, while still having all written down in IaC style.



            how to give individual schema access to users in apache-superset?
            Asked 2020-Jan-29 at 11:12

            I have searched a lot about this question, there are no concrete answers to this. I have a AWS Redshift DB, has around 6-7 schema' with 10-12 tables in each. and dashboards are made within schema level as well as across schema.

            here's the use case:

            • I have some users who needs to see only dashboards related to "schema 1" but not "schema 2"
            • I have some other users who are looking at dashboards which are connected to "schema 1" and as well as "schema 2", but m not able to find any workaround to this.

            I have seen a thread saying that it's possible to give access to schema but they haven't mentioned that How.




            Answered 2020-Jan-29 at 11:12

            As per the Superset documentation, you can not create access level on the schema but you can create access on data source level. Or you can create custom data sources and can create desired roles as per your need.



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


            No vulnerabilities reported

            Install incubator-superset

            [See in the documentation](


            Superset speaks many SQL dialects through SQLAlchemy - a Python SQL toolkit that is compatible with most databases. Here are some of the major database solutions that are supported:. <p align="center"> <img src="superset-frontend/images/redshift.png" alt="redshift" border="0" width="106" height="41"/> <img src="superset-frontend/images/google-biquery.png" alt="google-biquery" border="0" width="114" height="43"/> <img src="superset-frontend/images/snowflake.png" alt="snowflake" border="0" width="152" height="46"/> <img src="superset-frontend/images/presto.png" alt="presto" border="0" width="152" height="46"/> <img src="superset-frontend/images/druid.png" alt="druid" border="0" width="135" height="37" /> <img src="superset-frontend/images/postgresql.png" alt="postgresql" border="0" width="132" height="81" /> <img src="superset-frontend/images/mysql.png" alt="mysql" border="0" width="119" height="62" /> <img src="superset-frontend/images/mssql-server.png" alt="mssql-server" border="0" width="93" height="74" /> <img src="superset-frontend/images/db2.png" alt="db2" border="0" width="62" height="62" /> <img src="superset-frontend/images/sqlite.png" alt="sqlite" border="0" width="102" height="45" /> <img src="superset-frontend/images/sybase.png" alt="sybase" border="0" width="128" height="47" /> <img src="superset-frontend/images/mariadb.png" alt="mariadb" border="0" width="83" height="63" /> <img src="superset-frontend/images/vertica.png" alt="vertica" border="0" width="128" height="40" /> <img src="superset-frontend/images/oracle.png" alt="oracle" border="0" width="121" height="66" /> <img src="superset-frontend/images/firebird.png" alt="firebird" border="0" width="86" height="56" /> <img src="superset-frontend/images/greenplum.png" alt="greenplum" border="0" width="140" height="45" /> <img src="superset-frontend/images/clickhouse.png" alt="clickhouse" border="0" width="133" height="34" /> <img src="superset-frontend/images/exasol.png" alt="exasol" border="0" width="106" height="59" /> <img src="superset-frontend/images/monet-db.png" alt="monet-db" border="0" width="106" height="46" /> <img src="superset-frontend/images/apache-kylin.png" alt="apache-kylin" border="0" width="56" height="64"/> </p>. A complete list of supported databases can be found [here](
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