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Showing 4 open source projects for "os windows"
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Deploy Red Hat Ansible Automation Platform on Microsoft Azure for a strategic automation solution that allows you to orchestrate, govern and operationalize your Azure environment.
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Don’t let unpaid invoices limit your business’s growth. EBizCharge plugs directly into the tools your business already uses to speed up payment collection.
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QxOrm library
C++ Qt ORM (Object Relational Mapping) and ODM library
QxOrm library is an Object Relational Mapping (ORM) and Object Document Mapper (ODM) database library for C++ Qt developers. QxEntityEditor is a graphic editor for QxOrm library : QxEntityEditor provides a graphic way to manage the data model. QxEntityEditor is multi-platform (available for Windows, Linux, and Mac OS X) and generates native code for all environments, desktop (Windows, Linux, Mac OS X), embedded and mobile (Android, iOS, Windows Phone, Raspberry Pi, etc.). A user manual... -
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gSOAP Toolkit
Development toolkit for Web Services and XML data bindings for C & C++
The gSOAP toolkit is an extensive suite of portable C and C++ software to develop XML Web services with powerful type-safe XML data bindings. Easy-to-use code-generator tools allow you to directly integrate XML data in C and C++. Serializes native application data in XML. Includes WSDL/XSD schema binding and auto-coding tools, stub/skeleton compiler, Web server integration with Apache module and IIS extension, high-performance XML processing with schema validation, fast MIME/MTOM streaming,... -
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libjson-rpc-cpp
C++ framework for json-rpc (json remote procedure call)
This framework provides cross-platform JSON-RPC (remote procedure call) support for C++. It is fully JSON-RPC 2.0 & 1.0 compatible. -
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JSON is a lightweight data-interchange format. It can represents integer, real number, string, an ordered sequence of value, and a collection of name/value pairs. QJson is a qt-based library that maps JSON data to QVariant objects.
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BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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