datacube-ows | Open Data Cube Open Web Services

 by   opendatacube Python Version: 1.8.40 License: Non-SPDX

kandi X-RAY | datacube-ows Summary

kandi X-RAY | datacube-ows Summary

datacube-ows is a Python library. datacube-ows has no bugs, it has no vulnerabilities, it has build file available and it has low support. However datacube-ows has a Non-SPDX License. You can install using 'pip install datacube-ows' or download it from GitHub, PyPI.

Open Data Cube Open Web Services
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            kandi-support Support

              datacube-ows has a low active ecosystem.
              It has 48 star(s) with 32 fork(s). There are 19 watchers for this library.
              There were 4 major release(s) in the last 12 months.
              There are 21 open issues and 254 have been closed. On average issues are closed in 26 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of datacube-ows is 1.8.40

            kandi-Quality Quality

              datacube-ows has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              datacube-ows has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              datacube-ows releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed datacube-ows and discovered the below as its top functions. This is intended to give you an instant insight into datacube-ows implemented functionality, and help decide if they suit your requirements.
            • Get the coverage data for a request
            • Create a cube pool
            • Return a cube instance
            • Return a list of datacube instances
            • Parse global configuration
            • Parse metadata
            • Register a metadata property
            • Determines if we can inherit from metadata
            • Parse the WCS section
            • Convert single date data to xarray
            • Transform a single date data
            • Compile OWS command
            • Parse a rule spec
            • Parse wms section
            • Look up an OWSIndexed config entry
            • Parse the flags section
            • Check if files are valid
            • Build a list of FlagProductBands from an OWSFlag
            • Build a flag product list from a list of masks
            • Register color ramp
            • Calculate the GeoTiff
            • Parse wcs section
            • Add ranges to ODC product
            • Update a translation file
            • Return oGC env
            • Create a mask from the data
            Get all kandi verified functions for this library.

            datacube-ows Key Features

            No Key Features are available at this moment for datacube-ows.

            datacube-ows Examples and Code Snippets

            No Code Snippets are available at this moment for datacube-ows.

            Community Discussions

            No Community Discussions are available at this moment for datacube-ows.Refer to stack overflow page for discussions.

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

            Vulnerabilities

            No vulnerabilities reported

            Install datacube-ows

            You can install using 'pip install datacube-ows' or download it from GitHub, PyPI.
            You can use datacube-ows 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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            Install
          • PyPI

            pip install datacube-ows

          • CLONE
          • HTTPS

            https://github.com/opendatacube/datacube-ows.git

          • CLI

            gh repo clone opendatacube/datacube-ows

          • sshUrl

            git@github.com:opendatacube/datacube-ows.git

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