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rsine | Resource SubscrIption and Notification sErvice | Data Manipulation library

 by   rsine Java Version: 1.0.0-rc1 License: Non-SPDX

 by   rsine Java Version: 1.0.0-rc1 License: Non-SPDX

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kandi X-RAY | rsine Summary

rsine is a Java library typically used in Manufacturing, Utilities, Automotive, Utilities, Data Manipulation applications. rsine has no bugs, it has no vulnerabilities, it has build file available and it has low support. However rsine has a Non-SPDX License. You can download it from GitHub.
Rsine (Resource SubscrIption and Notification sErvice) is a service that allows users to subscribe for notification on specific changes to triples in an RDF dataset. It is developed as part of work package 5 in the LOD2 project by Semantic Web Company. Rsine is implemented as a service that listens for changes of triples (additions/removals) stored in an RDF triple store (the managed store) which is accessibly by a SPARQL endpoint. Users can express their interest in data changes as subscriptions which are essentially SPARQL queries that are run against the history of changes and the managed store. A subscription consists of.
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kandi-support Support

  • rsine has a low active ecosystem.
  • It has 14 star(s) with 1 fork(s). There are 6 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 1 open issues and 0 have been closed. On average issues are closed in 2217 days. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of rsine is 1.0.0-rc1
rsine Support
Best in #Data Manipulation
Average in #Data Manipulation
rsine Support
Best in #Data Manipulation
Average in #Data Manipulation

quality kandi Quality

  • rsine has 0 bugs and 0 code smells.
rsine Quality
Best in #Data Manipulation
Average in #Data Manipulation
rsine Quality
Best in #Data Manipulation
Average in #Data Manipulation

securitySecurity

  • rsine has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • rsine code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
rsine Security
Best in #Data Manipulation
Average in #Data Manipulation
rsine Security
Best in #Data Manipulation
Average in #Data Manipulation

license License

  • rsine 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.
rsine License
Best in #Data Manipulation
Average in #Data Manipulation
rsine License
Best in #Data Manipulation
Average in #Data Manipulation

buildReuse

  • rsine releases are available to install and integrate.
  • Build file is available. You can build the component from source.
  • Installation instructions, examples and code snippets are available.
  • rsine saves you 1045 person hours of effort in developing the same functionality from scratch.
  • It has 2371 lines of code, 213 functions and 46 files.
  • It has low code complexity. Code complexity directly impacts maintainability of the code.
rsine Reuse
Best in #Data Manipulation
Average in #Data Manipulation
rsine Reuse
Best in #Data Manipulation
Average in #Data Manipulation
Top functions reviewed by kandi - BETA

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

  • Assemble a change set .
    • Creates a collection of NotificationQuery from the RDF
      • Evaluates a query and sends a notification .
        • Read the settings from the properties file .
          • Evaluates the notification set .
            • Evaluate a SPARQL query .
              • Handle a specific feedback file .
                • Initialize unset values from properties .
                  • Extract statements from the post - triples .
                    • Starts the server .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      rsine Key Features

                      definition of the type of change (e.g., addition of a triple with property skos:broader)

                      an optional condition that must be fulfilled for receiving the notification

                      a pattern that defines the text and data values contained in the notification message

                      a notifier that specifies the way the notification is disseminated to the subscriber (e.g, by email)

                      Virtuoso: To establish interoperability with rsine, the provided vad package must installed. It has been tested and works with Virtuoso 6.1, however there are currently issues with Virtuoso 7.x. An alternative way for getting triple changes from Virtuoso is the Transaction Log Parser developed in the course of the GeoKnow project

                      openRDF: We developed a reference implementation of a RepositoryConnectionListener that forwards triple changes to rsine. The implementation is not published yet.

                      rsine Examples and Code Snippets

                      See all related Code Snippets

                      Changeset Selection

                      copy iconCopydownload iconDownload
                      rsine:query [
                          spin:text "PREFIX cs:<http://purl.org/vocab/changeset/schema#>
                              PREFIX spin:<http://spinrdf.org/sp/>
                              PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
                              PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
                              SELECT ?concept ?newLabel WHERE {
                                  ?cs a cs:ChangeSet .
                                  ?cs cs:addition ?addition .
                                  ?addition rdf:subject ?concept .
                                  ?addition rdf:predicate skos:prefLabel .
                                  ?addition rdf:object ?newLabel
                              }";
                          ];
                      

                      Condition

                      copy iconCopydownload iconDownload
                      rsine:condition [
                          spin:text "PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
                              ASK {
                                  ?concept skos:broader+ ?otherConcept .
                                  ?otherConcept skos:broader+ ?concept
                              }";
                          rsine:expect true;
                      ];
                      

                      Auxiliary Query

                      copy iconCopydownload iconDownload
                      rsine:auxiliary [
                          spin:text "PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
                              SELECT ?conceptLabel WHERE {
                                  ?concept skos:prefLabel ?conceptLabel .
                                  FILTER(langMatches(lang(?conceptLabel), 'en'))
                              }";
                          spin:text "PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
                              SELECT ?otherConceptLabel WHERE {
                                  ?otherConcept skos:prefLabel ?otherConceptLabel .
                                  FILTER(langMatches(lang(?otherConceptLabel), 'en'))
                              }";
                      ];
                      

                      Formatter

                      copy iconCopydownload iconDownload
                      rsine:formatter [
                          a rsine:vtlFormatter;
                          rsine:message "The concepts <a href='$bindingSet.getValue('concept')'>$bindingSet.getValue('conceptLabel').getLabel()</a> and
                              <a href='$bindingSet.getValue('otherConcept')'>$bindingSet.getValue('otherConceptLabel').getLabel()</a> form a hierarchical cycle";
                      ];
                      

                      Notifier

                      copy iconCopydownload iconDownload
                      rsine:notifier [
                          a rsine:loggingNotifier;
                      ];
                      

                      See all related Code Snippets

                      Community Discussions

                      Trending Discussions on Data Manipulation
                      • R: Is there a "Un-Character" Command in R?
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                      • How to return the column title wherein the row contains the greatest value in Pandas Dataframe
                      • Split large csv file into multiple files based on column(s)
                      • Get the first non-null value from selected cells in a row
                      • pivot_longer with column pairs
                      • Simulating Random Draws From a "Hat"
                      • Break Apart a String into Separate Columns R
                      Trending Discussions on Data Manipulation

                      QUESTION

                      R: Is there a "Un-Character" Command in R?

                      Asked 2022-Apr-10 at 17:37

                      I am working with the R programming language.

                      I have the following dataset:

                      v <- c(1,2,3,4,5,6,7,8,9,10)
                      
                      var_1 <- as.factor(sample(v, 10000, replace=TRUE, prob=c(0.1,0.1,0.1,0.1,0.1, 0.1,0.1,0.1,0.1,0.1)))
                      
                      var_2 <- as.factor(sample(v, 10000, replace=TRUE, prob=c(0.1,0.1,0.1,0.1,0.1, 0.1,0.1,0.1,0.1,0.1)))
                      
                      var_3 <- as.factor(sample(v, 10000, replace=TRUE, prob=c(0.1,0.1,0.1,0.1,0.1, 0.1,0.1,0.1,0.1,0.1)))
                      
                      var_4 <- as.factor(sample(v, 10000, replace=TRUE, prob=c(0.1,0.1,0.1,0.1,0.1, 0.1,0.1,0.1,0.1,0.1)))
                      
                      var_5 <- as.factor(sample(v, 10000, replace=TRUE, prob=c(0.1,0.1,0.1,0.1,0.1, 0.1,0.1,0.1,0.1,0.1)))
                      
                      my_data = data.frame(var_1, var_2, var_3, var_4, var_5)
                      

                      I also have another dataset of "conditions" that will be used for querying this data frame:

                      conditions = data.frame(cond_1 = c("1,3,4", "4,5,6"), cond_2 = c("5,6", "7,8,9"))
                      

                      My Question: I tried to run the following command to select rows from "my_data" based on the first row of "conditions" - but this returns an empty result:

                      my_data[my_data$var_1 %in% unlist(conditions[1,1]) &
                                  my_data$var_2 %in% unlist(conditions[1,2]), ]
                      
                      [1] var_1 var_2 var_3 var_4 var_5
                      <0 rows> (or 0-length row.names)
                      

                      I tried to look more into this by "inspecting" these conditions:

                      class(conditions[1,1])
                      [1] "character"
                      

                      This makes me think that the "unlist()" command is not working because the conditions themselves are a "character" instead of a "list".

                      Is there an equivalent command that can be used here that plays the same role as the "unlist()" command so that the above statement can be run?

                      In general, I am trying to produce the same results as I would have gotten from this code - but keeping the format I was using above:

                      my_data[my_data$var_1 %in% c("1", "3", "4") &
                                  my_data$var_2 %in% c("5", "6"), ]
                      

                      ANSWER

                      Answered 2022-Apr-10 at 05:36

                      Up front, "1,3,4" != 1. It seems you should look to split the strings using strsplit(., ",").

                      expected <- my_data[my_data$var_1 %in% c("1", "3", "4") & my_data$var_2 %in% c("5", "6"), ]
                      head(expected)
                      #     var_1 var_2 var_3 var_4 var_5
                      # 18      3     6     2     2     9
                      # 129     3     5     3     2     8
                      # 133     4     5     6     5     8
                      # 186     1     6     6    10    10
                      # 204     4     6     4     2     6
                      # 207     1     5     3     2     9
                      
                      out <- my_data[do.call(`&`, 
                        Map(`%in%`,
                            lapply(my_data[,1:2], as.character), 
                            lapply(conditions, function(z) strsplit(z, ",")[[1]]))),]
                      head(out)
                      #     var_1 var_2 var_3 var_4 var_5
                      # 18      3     6     2     2     9
                      # 129     3     5     3     2     8
                      # 133     4     5     6     5     8
                      # 186     1     6     6    10    10
                      # 204     4     6     4     2     6
                      # 207     1     5     3     2     9
                      

                      Edit: update for new conditions: change do.call to Reduce:

                      conditions = data.frame(cond_1 = c("1,3,4", "4,5,6"), cond_2 = c("5,6", "7,8,9"), cond_3 = c("4,6", "9"))
                      out <- my_data[Reduce(`&`,
                        Map(`%in%`,
                            lapply(my_data[,1:3], as.character),
                            lapply(conditions, function(z) strsplit(z, ",")[[1]]))),]
                      head(out)
                      #     var_1 var_2 var_3 var_4 var_5
                      # 133     4     5     6     5     8
                      # 186     1     6     6    10    10
                      # 204     4     6     4     2     6
                      # 232     1     5     6     5     8
                      # 332     3     6     6     5    10
                      # 338     1     5     6     3     6
                      

                      Source https://stackoverflow.com/questions/71813866

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

                      Vulnerabilities

                      No vulnerabilities reported

                      Install rsine

                      Verify that Java version 1.7 or greater is installed: javac -version
                      Make sure Maven version 3.0 or greater is installed: mvn -v
                      Make sure you have the current version of the git version control system installed on your system
                      If you know in advance for what SPARQL endpoint you want to configure rsine, you can set this information in the application.properties file, located in the rsine/src/main/resources directory. However, you can also skip this step and set the relevant parameters at runtime (i.e. when starting the rsine service). The file rsine-cmd.jar is now available in the directory rsine/target.
                      Get the sourcecode by cloning the rsine repository: git clone https://github.com/rsine/rsine.git)
                      Change into the newly created rsine directory and build the application: mvn -DskipTests=true package
                      When building rsine with tests enabled (i.e. without the -DskipTests=true switch) it can happen that the build fails due to non-successful tests. This happens when all tests are run consecutively and seems to be caused by some concurrency issue in the test setup. As far as we know, these failing tests do not affect the functionality of the rsine application.

                      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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