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Showing 4 open source projects for "executable"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Swagger Codegen
Template-driven engine to generate documentation
Swagger-Codegen contains a template-driven engine to generate documentation, API clients and server stubs in different languages by parsing your OpenAPI / Swagger definition. Simplify API development for users, teams, and enterprises with the Swagger open source and professional toolset. Find out how Swagger can help you design and document your APIs at scale. The power of Swagger tools starts with the OpenAPI Specification, the industry standard for RESTful API design. Individual tools to... -
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Maven-Tycho-Demo
Deployment Example for Maven Tycho Builds in Eclipse
This project contains the deployed artefacts for the Maven-Tycho-Demo project. The artefacts contain p2 and binary (windows 64bit) builds for: - Daily development builds - Regular integration builds - Specific releaseb builds -
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DCTemplate is a templating system for (X)HTML and JavaScript. It allows web developers to maintain dynamic chunks of XHTML as well-formed XML templates that are "compiled" at build time to high-performance JavaScript methods. Now includes Maven sup
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action4JAVA
Simple Flexible Template Solution in Java
J-Tree is a lightweight, modular, extendible and recursive open source Java component framework with a template core. A J-Tree template is "executable" by itself. J-Tree contains some standardized actions and a data container. These actions are called when a comment tag is found. The action is controlled by the attributes within. Actions can have any purpose. Templating is just an action by itself. The template controls loading of data and storing to a file by itself. So it runs indempentently from a java development environment just from a shell call (exectutable) The website offers several examples how it works. ... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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