Auto-Generate Java Vert.x Web Server Stub Using OpenAPI Generator

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We've added a new Java Vert.x Web server generator to OpenAPI Generator (https://github.com/OpenAPITools/openapi-generator). To generate server stubs for Java Vert.x-Web given an OpenAPI/Swagger specification file, please follow 3 simple steps below: 1. Download the Java JAR (http://central.maven.org/maven2/org/openapitools/openapi-generator-cli/4.2.0/openapi-generator-cli-4.2.0.jar) 2. Rename the JAR as "openapi-generator-cli.jar" 3. Run the following command to generate a Java Vert.x Web server stub for the Petstore API (https://raw.githubusercontent.com/OpenAPITools/openapi-generator/master/modules/openapi-generator/src/test/resources/2_0/petstore.yaml): Mac/Linux: $ java -jar openapi-generator-cli.jar generate -g java-vertx-web -i https://raw.githubusercontent.com/OpenAPITools/openapi-generator/master/modules/openapi-generator/src/test/resources/2_0/petstore.yaml -o /var/tmp/java-vertx/ Windows: $ java -jar openapi-generator-cli.jar generate -g java-vertx-web -i https://raw.githubusercontent.com/OpenAPITools/openapi-generator/master/modules/openapi-generator/src/test/resources/2_0/petstore.yaml -o C:\tmp\java-vertx If you've any feedback or question, please let us know via https://github.com/OpenAPITools/openapi-generator/issues/new

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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38%38% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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