datakit-core | Core library for the datakit CLI framework | Application Framework library

by associatedpress Python Version: 0.3.2 License: ISC

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

kandi X-RAY | datakit-core Summary

datakit-core is a Python library typically used in Server, Application Framework, Framework applications. datakit-core has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install datakit-core' or download it from GitHub, PyPI.

Core library for the datakit CLI framework.

Support

Quality

Security

License

Reuse

Support

datakit-core has a low active ecosystem.

It has 44 star(s) with 4 fork(s). There are 11 watchers for this library.

It had no major release in the last 12 months.

There are 10 open issues and 8 have been closed. On average issues are closed in 263 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of datakit-core is 0.3.2

Quality

datakit-core has 0 bugs and 0 code smells.

Security

datakit-core has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

datakit-core code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

datakit-core is licensed under the ISC License. This license is Permissive.

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

Reuse

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

Deployable package is available in PyPI.

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

datakit-core saves you 245 person hours of effort in developing the same functionality from scratch.

It has 596 lines of code, 50 functions and 15 files.

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

Top functions reviewed by kandi - BETA

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

Return configs
Create a directory
Write configuration files
Write data to a JSON file
Read a JSON file
Return the parent directory of the plugin config
Returns the home directory
Try to find an action
Creates a list of directories

Get all kandi verified functions for this library.

datakit-core Key Features

No Key Features are available at this moment for datakit-core.

datakit-core Examples and Code Snippets

No Code Snippets are available at this moment for datakit-core.

Community Discussions

Trending Discussions on Application Framework

What is meant by required-api: param name=”#target” in config.xml file of AGL widgets?

QUESTION

What is meant by required-api: param name=”#target” in config.xml file of AGL widgets?

Asked 2020-Mar-06 at 09:53

I am trying to understand various available AGL specific options that we can give in config.xml and I am referring to the link below

https://docs.automotivelinux.org/docs/en/halibut/apis_services/reference/af-main/2.2-config.xml.html

This is the sample config.xml file

...

ANSWER

Answered 2020-Mar-06 at 09:48

I figured out why we need this

required-api: param name="#target"

OPTIONAL(not compulsory)

It declares the name of the unit(in question it is main) requiring the listed apis. Only one instance of the param “#target” is allowed. When there is not instance of this param, it behave as if the target main was specified.

Source https://stackoverflow.com/questions/60561230

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

Vulnerabilities

No vulnerabilities reported

Install datakit-core

You can install using 'pip install datakit-core' or download it from GitHub, PyPI.
You can use datakit-core 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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