aurum-datadiscovery | Webpage version of this documentation : http : //mitdbg | Database library

by mitdbg Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | aurum-datadiscovery Summary

aurum-datadiscovery is a Python library typically used in Database applications. aurum-datadiscovery has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Webpage version of this documentation: Aurum helps users identify relevant content among multiple data sources that may consist of tabular files, such as CSV, and relational tables. These may be stored in relational database management systems (RDBMS), file systems, and they may live in cloud services, data lakes or other on-premise repositories. Aurum helps you find data through different interfaces. The most flexible one is an API of primitives that can be composed to build queries that describe the data of interest. For example, you can write a query that says "find tables that contain a column with name 'ID' and have at least one column that looks like an input column". You can also query with very simple primitives, such as "find columns that contain the keyword 'caffeine'". You can also do more complex queries, such as figuring out what tables join with a table of interest. The idea is that the API is flexible enough to allow a wide range of use cases, and that it works over all data you feed to the system, regardless where these live.

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Quality

Security

License

Reuse

Support

aurum-datadiscovery has a low active ecosystem.

It has 60 star(s) with 41 fork(s). There are 16 watchers for this library.

It had no major release in the last 6 months.

There are 29 open issues and 57 have been closed. On average issues are closed in 189 days. There are 30 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of aurum-datadiscovery is current.

Quality

aurum-datadiscovery has 0 bugs and 0 code smells.

Security

aurum-datadiscovery has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

aurum-datadiscovery code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

aurum-datadiscovery is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

aurum-datadiscovery releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

aurum-datadiscovery saves you 16047 person hours of effort in developing the same functionality from scratch.

It has 31950 lines of code, 1478 functions and 224 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Combine and report and report results
Return a list of matching source code strings
Return a list of matching formats
Compute precision recall
Create a relationship between two ontologies
Calculate matchings common to pipeline
Compute matchings for a pipeline
Find matching pipeline attributes
Local test function
Perform a virtual schema iteration
Find L1 matchings
Builds a relationship between two sites
Test for L42 language model
Find the relation class for a LSH2 network
Find relation names for LSH2
Check if a language model is supported by l6
Generate an example indexing algorithm
Find links between matchings
Loads a language model
Generate results for ontomatch
Merge groups of groups
Summarize matchings to an ancestor
Finds the relation class names for the relation class
Generate results battery parameters
Test language model
This function is used to create the engine

Get all kandi verified functions for this library.

aurum-datadiscovery Key Features

No Key Features are available at this moment for aurum-datadiscovery.

aurum-datadiscovery Examples and Code Snippets

No Code Snippets are available at this moment for aurum-datadiscovery.

Community Discussions

Trending Discussions on aurum-datadiscovery

Unable to connect neo4j and elasticsearch in docker

QUESTION

Unable to connect neo4j and elasticsearch in docker

Asked 2018-Nov-10 at 17:51

I'm trying to connect neo4j to elasticsearch in docker container with the graphaware plugin and keep getting the same error :

...

ANSWER

Answered 2018-Nov-10 at 17:51

It seems that neo4j tries to connect to elasticsearch on localhost, whereas the elasticsearch container is on a different ip.

According to https://docs.docker.com/compose/networking/ you can use the name of the service, so instead of localhost you can put elastic.

Source https://stackoverflow.com/questions/53241741

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

Vulnerabilities

No vulnerabilities reported

Install aurum-datadiscovery

You can download it from GitHub.
You can use aurum-datadiscovery like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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