Search Results for "python-ldap"
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Showing 6 open source projects for "python-ldap"
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
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Teradata VantageCloud Enterprise is a data analytics platform for performing advanced analytics on AWS, Azure, and Google Cloud.VantageCloud is the complete cloud analytics and data platform, delivering harmonized data and Trusted AI for all. Built for performance, flexibility, and openness, VantageCloud enables organizations to unify diverse data sources, run complex analytics, and deploy AI models—all within a single, scalable platform.
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GeographicLib
Geographic library
GeographicLib is a small C++ library for: geodesic and rhumb line calculations; conversions between geographic, UTM, UPS, MGRS, geocentric, and local cartesian coordinates; gravity (e.g., EGM2008) and geomagnetic field (e.g., WMM2020) calculations. -
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A web based Metadata Catalog Server for data description and discovery. Supports both generic and geospatial data discovery. It implements international standards (e.g. ISO19115/19139/19119, ISO19115-3, DCAT-AP, CSW 2.0, OGC API Records). It originates from the United Nations and is used by many governments as geoportal software. Active development and discussion takes place on GitHub and OSGeo Discourse. You can also connect directly with the companies supporting the...
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Platform providing the support for Wireless Sensor Networks in the domain of Natural Hazards as a Service. The objective of the WSN platform is monitoring the behaviour of rockfall barriers, rockfall netting, rock sheds and other protection systems
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Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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This project aims to provide an open source fleet management system with special focus on modularity and integration.
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This project exists as a central meeting place for those wishing to share in-house developed applications and tools for local government (and related industries) in Australia.
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