<metapackage xmlns:os="http://opensuse.org/Standards/One_Click_Install" xmlns="http://opensuse.org/Standards/One_Click_Install">
  <group distversion="openSUSE Tumbleweed">
    <repositories>
      <repository recommended="true">
        <name>devel:languages:R:autoCRAN</name>
        <summary>Large parts of CRAN (cran.r-project.org) mirrored to OBS in a fully automatic way.</summary>
        <description>This repo contains a large part of CRAN automatically converted to rpm packages.
*ALL* packages in the repo are created and kept uptodate(!) in a fully automatic way using the R package CRAN2OBS (gitlab.com/dsteuer/CRAN2OBS).
At the moment CRAN2OBS is still subject to many changes, but it already works well enough to bring about 15k packages from CRAN to Suse.
If you find packages not working, please contact me. Do not push packages here by hand after manually altering anything in a spec file, please. If you find an important package still missing, send a note, please. May be it is easy to add fitting rules to the scripts. 

Attention: there are Prefer: lines in the project config. Should be rechecked from time to time.</description>
        <url>https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/</url>
      </repository>
      <repository recommended="true">
        <name>devel:languages:R:autoCRANsupp</name>
        <summary>Supplements for the autoCRAN project</summary>
        <description>autoCRANsupp contains *only* 
- libraries needed to build a worthy number of R packages that are not in factory/tumbleweed, i.e. udunits2-1 
- a link to d:l:R:released/R-base to provide newer versions for older SuSE releases. A lot of packages need the latest R.

This project will be as small as possible. 
In a best case scenario only R-base will remain here to be included for building autoCRAN.

</description>
        <url>https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRANsupp/openSUSE_Tumbleweed/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Factory</name>
        <summary>The next openSUSE distribution</summary>
        <description>openSUSE Tumbleweed: The Bleeding Edge, Perfected.
Tumbleweed is the ultimate rolling release distribution, providing the latest software as it’s released, built upon a foundation of world-class stability and testing.

* Always Current: Get the newest kernel, IDEs, desktops, and applications automatically.

* Powerfully Stable: Experience the velocity of a rolling release without sacrificing the reliability you depend on.

* Engineered for Professionals: The top choice for Developers, Power Users, and openSUSE Contributors who need the best tools for the job.

If you demand the latest stable software, your choice is Tumbleweed.

Staging dashboard is located at: https://build.opensuse.org/staging_workflows/openSUSE:Factory 

List of known devel projects: https://build.opensuse.org/package/view_file/openSUSE:Factory:Staging/dashboard/devel_projects

Have a look at http://en.opensuse.org/Portal:Factory for more details.</description>
        <url>https://download.opensuse.org/tumbleweed/repo/oss/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Tumbleweed</name>
        <summary>Tumbleweed</summary>
        <description>Tumbleweed is the openSUSE Rolling Release

This OBS Project represents the content of the currently published
snapshot. The newer repository for next publish can be found in openSUSE:Factory standard repository.
</description>
        <url>https://download.opensuse.org/repositories/openSUSE:/Tumbleweed/standard/</url>
      </repository>
      <repository recommended="true">
        <name>openSUSE:Tumbleweed</name>
        <summary>Tumbleweed</summary>
        <description>Tumbleweed is the openSUSE Rolling Release

This OBS Project represents the content of the currently published
snapshot. The newer repository for next publish can be found in openSUSE:Factory standard repository.
</description>
        <url>https://download.opensuse.org/tumbleweed/repo/oss/</url>
      </repository>
      <repository recommended="false">
        <name>openSUSE:Factory</name>
        <summary>The next openSUSE distribution</summary>
        <description>openSUSE Tumbleweed: The Bleeding Edge, Perfected.
Tumbleweed is the ultimate rolling release distribution, providing the latest software as it’s released, built upon a foundation of world-class stability and testing.

* Always Current: Get the newest kernel, IDEs, desktops, and applications automatically.

* Powerfully Stable: Experience the velocity of a rolling release without sacrificing the reliability you depend on.

* Engineered for Professionals: The top choice for Developers, Power Users, and openSUSE Contributors who need the best tools for the job.

If you demand the latest stable software, your choice is Tumbleweed.

Staging dashboard is located at: https://build.opensuse.org/staging_workflows/openSUSE:Factory 

List of known devel projects: https://build.opensuse.org/package/view_file/openSUSE:Factory:Staging/dashboard/devel_projects

Have a look at http://en.opensuse.org/Portal:Factory for more details.</description>
        <url>https://download.opensuse.org/repositories/openSUSE:/Factory/ports/</url>
      </repository>
    </repositories>
    <software>
      <item>
        <name>R-adheRenceRX</name>
        <summary>Assess Medication Adherence from Pharmaceutical Claims Data</summary>
        <description>A (mildly) opinionated set of functions to help assess medication
adherence for researchers working with medication claims data.
Medication adherence analyses have several complex steps that are often
convoluted and can be time-intensive. The focus is to create a set of
functions using &quot;tidy principles&quot; geared towards transparency, speed,
and flexibility while working with adherence metrics. All functions
perform exactly one task with an intuitive name so that a researcher
can handle details (often achieved with vectorized solutions) while we
handle non-vectorized tasks common to most adherence calculations such
as adjusting fill dates and determining episodes of care. The
methodologies in referenced in this package come from Canfield SL, et
al (2019) &quot;Navigating the Wild West of Medication Adherence Reporting
in Specialty Pharmacy&quot; &lt;doi:10.18553/jmcp.2019.25.10.1073&gt;.</description>
      </item>
    </software>
  </group>
</metapackage>
