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A collection of scala and java classes for some basic character level processing for the Sanskrit and other Indic (kannada, telugu, etc..) languages, contributed by the open source sanskrit-coders projects and friends. Some notable facilities: * Transliterate text from one script or encoding scheme to another. * Some grammar simulation. Examples: see https://github.com/sanskrit-coders/indic-transliteration Contributions and suggestions are invited at https://github.com/sanskrit-coders/indic-transliteration . (Sister projects there may also be of interest.)

A collection of scala and java classes for some basic natural language processing (NLP) for the Sanskrit language, contributed by the open source SanskritNLP project and friends. Some notable facilities: * Transliterate text from one script or encoding scheme to another. * Deal with babylon dictionaries. * Use bots to write to wiki projects (wiktionary, wikisource etc..). * Basic metre identification. * Some grammar simulation. Contributions and suggestions are invited at https://github.com/sanskrit-coders/sanskritnlpjava . (Sister projects there may also be of interest.)

Kanbanery (https://kanbanery.com) is a simple but powerful Agile project management system, to be precise it focuses around the idea of Kanban, a somewhat near idea to SCRUM but with less strict rules. The heart of each Kanban flow is the Kanban board, IceBox and Archive - there are all easy accessible via this API. Janbanery wraps around the RESTful API delivered by Kanbanery while adding some more features like mass operations or filtering of results. In the end, it's very easy and pleasant to implement your own Kanbanery client be it on the desktop, mobile (android) or as for example Gradle / SBT script to take full advantage of kanbanery's features.

Kanbanery (https://kanbanery.com) is a simple but powerful Agile project management system, to be precise it focuses around the idea of Kanban, a somewhat near idea to SCRUM but with less strict rules. The heart of each Kanban flow is the Kanban board, IceBox and Archive - there are all easy accessible via this API. Janbanery wraps around the RESTful API delivered by Kanbanery while adding some more features like mass operations or filtering of results. In the end, it's very easy and pleasant to implement your own Kanbanery client be it on the desktop, mobile (android) or as for example Gradle / SBT script to take full advantage of kanbanery's features.

A tool to help visualise API differences between two different versions of a project. Jardiff takes two jar files and outputs all the public API changes as xml, html or plain text. Currently this is command line driven, though we are working on an ant plugin. It requires java 1.4 to run. <h2>Background</h2> At OSjava, we were using a shell script to work out API differences between our release versions. This unfortunately doesn't scale very well to larger projects, the main reason for jardiff was to do the same in a much shorter time (From memory it was taking minutes to get the API diff from two fairly small jars). In it's current state, jardiff can generate the api differences between rt.jar for java 1.4 and java 1.5 in under 20 seconds, so it should scale to even the largest of projects.

Idaithalam is a low code Test automation Framework, developed using Java and Cucumber. It leverages Behavior Driven Development (BDD). Tester can create test cases/scripts in simple Excel with API Spec. Excel is a simplified way to create Json based test scripts in Idaithalam. Test cases can be created quickly and tested in minutes. As a tester, you need to create Excel and pass it to Idaithalam Framework. First, generate the Json based test scripts(Virtualan Collection) from Excel. During test execution, this test script collection can be directly utilized. Then it generates Feature files from the Virtualan Collection and its executed. Lastly, It generates test report in BDD/Cucumber style. This provide complete testing support for REST APIs, GraphQL, RDBMS DB and Kafka Event messages #idaithalam #apitesting #testautomation #restapitesting #insprintautomation #rdbmstesting #graphqltesting #kafkamessagetesting #eventvalidation #messagevalidation #cucumber #bdd Virtualan Collection is a JSON based TestScripts generated from Excel API testing can be automated using Excel, POSTMAN collection and VIRTUALAN - Utilized for API testing. - Utilized Contract testing. - Utilized Production Checkout. - Agile Testing - Progressive Regression can be done for each sprint. Reduce lot of manual effects.

The IntelligentGraph SAIL offers an extended capability for embedded calculation support within any RDF graph. When enabled as an RDF4J SAIL, it offers calculation functionality as part of the RDF4J engine, on top of any RDF4J repository, using a variety of script engines including JavaScript, Jython, and Groovy. It preserves the SPARQL capability of RDF4J, but with additional capabilities for calculation debugging and tracing. IntelligentGraph includes the PathQL query language. Just as a spreadsheet cell calculation needs to access other cells, an IntelligentGraph calculation needs to access other nodes within the graph. Although full access to the underlying graph is available to any of the scripts, PathQL provides a succinct, and efficient method to access directly or indirectly related nodes. PathQL can either return just the contents of the referenced nodes, or the contents and the path to the referenced nodes. PathQL can also be used standalone to query the IntelligentGraph-enabled RDF database. This supplements, rather than replaces, SPARQL and GraphQL, as it provides graph-path querying rather than graph-pattern querying capabilities to any IntelligentGraph-enabled RDF database. The principles of IntelligentGraph are described here: https://inova8.com/bg_inova8.com/intelligent-graph-knowledge-graph-embedded-analysis/ The full PathQL syntax is described here: https://inova8.com/bg_inova8.com/pathpatternql-intelligently-finding-knowledge-as-a-path-through-a-maze-of-facts/ Using Jupyter as an IDE to IntelligentGraph and RDF4J, shown here: https://inova8.com/bg_inova8.com/intelligentgraph-getting-started/ IntelligentGraph source is here in GitHub: https://github.com/peterjohnlawrence/com.inova8.intelligentgraph IntelligentGraph Docker containers are available here: https://hub.docker.com/repository/docker/inova8/intelligentgraph

This project aims to build a command line tool that can create HTML view with syntax highlighted source code. It uses Jedit syntax highlighting engine and support all languages that are supported in JEdit. Which are currently: ActionScript, Ada 95, ANTLR, Apache HTTPD, APDL, AppleScript, ASP, Aspect-J, Assembly, AWK, B formal method, Batch, BBj, BCEL, BibTeX, C, C++, C#, CHILL, CIL, COBOL, ColdFusion, CSS, CVS Commit, D, DOxygen, DSSSL, Eiffel, EmbPerl, Erlang, Factor, Fortran, Foxpro, FreeMarker, Fortran, Gettext, Groovy, Haskell, HTML, Icon, IDL, Inform, INI, Inno Setup, Informix 4GL, Interlis, Io, Java, JavaScript, JCL, JHTML, JMK, JSP, Latex, Lilypond, Lisp, LOTOS, Lua, Makefile, Maple, ML, Modula-3, MoinMoin, MQSC, NetRexx, NQC, NSIS2, Objective C, ObjectRexx, Occam, Omnimark, Parrot, Pascal, Patch, Perl, PHP, Pike, PL-SQL, PL/I, Pop11, PostScript, Povray, PowerDynamo, Progress 4GL, Prolog, Properties, PSP, PV-WAVE, Pyrex, Python, REBOL, Redcode, Relax-NG, RelationalView, Rest, Rib, RPM spec, RTF, Ruby, Ruby-HTML, RView, S+, S#, SAS, Scheme, SDL/PL, SGML, Shell Script, SHTML, Smalltalk, SMI MIB, SQR, Squidconf, SVN Commit, Swig, TCL, TeX, Texinfo, TPL, Transact-SQL, UnrealScript, VBScript, Velocity, Verilog, VHDL, XML, XSL, ZPT

Pact server =========== The pact server is a stand-alone interactions recorder and verifier, aimed at clients that are non-JVM or non-Ruby based. The pact client for that platform will need to be implemented, but it only be responsible for generating the `JSON` interactions, running the tests and communicating with the server. The server implements a `JSON` `REST` Admin API with the following endpoints. / -&gt; For diagnostics, currently returns a list of ports of the running mock servers. /create -&gt; For initialising a test server and submitting the JSON interactions. It returns a port /complete -&gt; For finalising and verifying the interactions with the server. It writes the `JSON` pact file to disk. ## Running the server ### Versions 2.2.6+ Pact server takes the following parameters: ``` Usage: pact-jvm-server [options] [port] port port to run on (defaults to 29999) --help prints this usage text -h &lt;value&gt; | --host &lt;value&gt; host to bind to (defaults to localhost) -l &lt;value&gt; | --mock-port-lower &lt;value&gt; lower bound to allocate mock ports (defaults to 20000) -u &lt;value&gt; | --mock-port-upper &lt;value&gt; upper bound to allocate mock ports (defaults to 40000) -d | --daemon run as a daemon process -v &lt;value&gt; | --pact-version &lt;value&gt; pact version to generate for (2 or 3) -k &lt;value&gt; | --keystore-path &lt;value&gt; Path to keystore -p &lt;value&gt; | --keystore-password &lt;value&gt; Keystore password -s &lt;value&gt; | --ssl-port &lt;value&gt; Ssl port the mock server should run on. lower and upper bounds are ignored --debug run with debug logging ``` ### Using trust store 3.4.0+ Trust store can be used. However, it is limited to a single port for the time being. ### Prior to version 2.2.6 Pact server takes one optional parameter, the port number to listen on. If not provided, it will listen on 29999. It requires an active console to run. ### Using a distribution archive You can download a [distribution from maven central](http://search.maven.org/remotecontent?filepath=au/com/dius/pact-jvm-server_2.11/2.2.4/). There is both a ZIP and TAR archive. Unpack it to a directory of choice and then run the script in the bin directory. ### Building a distribution bundle You can build an application bundle with gradle by running (for 2.11 version): $ ./gradlew :pact-jvm-server_2.11:installdist This will create an app bundle in `build/2.11/install/pact-jvm-server_2.11`. You can then execute it with: $ java -jar pact-jvm-server/build/2.10/install/pact-jvm-server_2.11/lib/pact-jvm-server_2.11-3.2.11.jar or with the generated bundle script file: $ pact-jvm-server/build/2.11/install/pact-jvm-server_2.11/bin/pact-jvm-server_2.11 By default will run on port `29999` but a port number can be optionally supplied. ### Running it with docker You can use a docker image to execute the mock server as a docker container. $ docker run -d -p 8080:8080 -p 20000-20010:20000-20010 uglyog/pact-jvm-server This will run the main server on port 8080, and each created mock server on ports 20000-20010. You can map the ports to any you require. ## Life cycle The following actions are expected to occur * The client calls `/create` to initialise a server with the expected `JSON` interactions and state * The admin server will start a mock server on a random port and return the port number in the response * The client will execute its interaction tests against the mock server with the supplied port * Once finished, the client will call `/complete&apos; on the Admin API, posting the port number * The pact server will verify the interactions and write the `JSON` `pact` file to disk under `/target` * The mock server running on the supplied port will be shutdown. ## Endpoints ### /create The client will need `POST` to `/create` the generated `JSON` interactions, also providing a state as a query parameter and a path. For example: POST http://localhost:29999/create?state=NoUsers&amp;path=/sub/ref/path &apos;{ &quot;provider&quot;: { &quot;name&quot;: &quot;Animal_Service&quot;}, ... }&apos; This will create a new running mock service provider on a randomly generated port. The port will be returned in the `201` response: { &quot;port&quot; : 34423 } But you can also reference the path from `/sub/ref/path` using the server port. The service will not strip the prefix path, but instead will use it as a differentiator. If your services do not have differences in the prefix of their path, then you will have to use the port method. ### /complete Once the client has finished running its tests against the mock server on the supplied port (in this example port `34423`) the client will need to `POST` to `/complete` the port number of the mock server that was used. For example: POST http://localhost:29999/complete &apos;{ &quot;port&quot; : 34423 }&apos; This will cause the Pact server to verify the interactions, shutdown the mock server running on that port and writing the pact `JSON` file to disk under the `target` directory. ### / The `/` endpoint is for diagnostics and to check that the pact server is running. It will return all the currently running mock servers port numbers. For example: GET http://localhost:29999/ &apos;{ &quot;ports&quot;: [23443,43232] }&apos;

Pact server =========== The pact server is a stand-alone interactions recorder and verifier, aimed at clients that are non-JVM or non-Ruby based. The pact client for that platform will need to be implemented, but it only be responsible for generating the `JSON` interactions, running the tests and communicating with the server. The server implements a `JSON` `REST` Admin API with the following endpoints. / -&gt; For diagnostics, currently returns a list of ports of the running mock servers. /create -&gt; For initialising a test server and submitting the JSON interactions. It returns a port /complete -&gt; For finalising and verifying the interactions with the server. It writes the `JSON` pact file to disk. ## Running the server ### Versions 2.2.6+ Pact server takes the following parameters: ``` Usage: pact-jvm-server [options] [port] port port to run on (defaults to 29999) --help prints this usage text -h &lt;value&gt; | --host &lt;value&gt; host to bind to (defaults to localhost) -l &lt;value&gt; | --mock-port-lower &lt;value&gt; lower bound to allocate mock ports (defaults to 20000) -u &lt;value&gt; | --mock-port-upper &lt;value&gt; upper bound to allocate mock ports (defaults to 40000) -d | --daemon run as a daemon process -v &lt;value&gt; | --pact-version &lt;value&gt; pact version to generate for (2 or 3) -k &lt;value&gt; | --keystore-path &lt;value&gt; Path to keystore -p &lt;value&gt; | --keystore-password &lt;value&gt; Keystore password -s &lt;value&gt; | --ssl-port &lt;value&gt; Ssl port the mock server should run on. lower and upper bounds are ignored --debug run with debug logging ``` ### Using trust store 3.4.0+ Trust store can be used. However, it is limited to a single port for the time being. ### Prior to version 2.2.6 Pact server takes one optional parameter, the port number to listen on. If not provided, it will listen on 29999. It requires an active console to run. ### Using a distribution archive You can download a [distribution from maven central](http://search.maven.org/remotecontent?filepath=au/com/dius/pact-jvm-server_2.11/2.2.4/). There is both a ZIP and TAR archive. Unpack it to a directory of choice and then run the script in the bin directory. ### Building a distribution bundle You can build an application bundle with gradle by running (for 2.11 version): $ ./gradlew :pact-jvm-server_2.11:installdist This will create an app bundle in `build/2.11/install/pact-jvm-server_2.11`. You can then execute it with: $ java -jar pact-jvm-server/build/2.10/install/pact-jvm-server_2.11/lib/pact-jvm-server_2.11-3.2.11.jar or with the generated bundle script file: $ pact-jvm-server/build/2.11/install/pact-jvm-server_2.11/bin/pact-jvm-server_2.11 By default will run on port `29999` but a port number can be optionally supplied. ### Running it with docker You can use a docker image to execute the mock server as a docker container. $ docker run -d -p 8080:8080 -p 20000-20010:20000-20010 uglyog/pact-jvm-server This will run the main server on port 8080, and each created mock server on ports 20000-20010. You can map the ports to any you require. ## Life cycle The following actions are expected to occur * The client calls `/create` to initialise a server with the expected `JSON` interactions and state * The admin server will start a mock server on a random port and return the port number in the response * The client will execute its interaction tests against the mock server with the supplied port * Once finished, the client will call `/complete&apos; on the Admin API, posting the port number * The pact server will verify the interactions and write the `JSON` `pact` file to disk under `/target` * The mock server running on the supplied port will be shutdown. ## Endpoints ### /create The client will need `POST` to `/create` the generated `JSON` interactions, also providing a state as a query parameter and a path. For example: POST http://localhost:29999/create?state=NoUsers&amp;path=/sub/ref/path &apos;{ &quot;provider&quot;: { &quot;name&quot;: &quot;Animal_Service&quot;}, ... }&apos; This will create a new running mock service provider on a randomly generated port. The port will be returned in the `201` response: { &quot;port&quot; : 34423 } But you can also reference the path from `/sub/ref/path` using the server port. The service will not strip the prefix path, but instead will use it as a differentiator. If your services do not have differences in the prefix of their path, then you will have to use the port method. ### /complete Once the client has finished running its tests against the mock server on the supplied port (in this example port `34423`) the client will need to `POST` to `/complete` the port number of the mock server that was used. For example: POST http://localhost:29999/complete &apos;{ &quot;port&quot; : 34423 }&apos; This will cause the Pact server to verify the interactions, shutdown the mock server running on that port and writing the pact `JSON` file to disk under the `target` directory. ### / The `/` endpoint is for diagnostics and to check that the pact server is running. It will return all the currently running mock servers port numbers. For example: GET http://localhost:29999/ &apos;{ &quot;ports&quot;: [23443,43232] }&apos;