Search Results for "python-ldap" - Page 3
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Showing 59 open source projects for "python-ldap"
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Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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Cloud-based help desk software with ServoDeskWhat if You Could Automate 90% of Your Repetitive Tasks in Under 30 Days? At ServoDesk, we help businesses like yours automate operations with AI, allowing you to cut service times in half and increase productivity by 25% - without hiring more staff.
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Cover Your Asp, a Python coverage analysis tool. This coverage tool correctly traces multithreaded applications and uses deep understanding of Python syntax to provide intelligent reports.
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Windows based editor designed to allow writing extensions covering any user format of raster fonts. Supports fixed/variable character height/width, incomplete character sets, etc. Has a lot of useful character-editing functions (italicize, bold, shift...
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A suite of tools and extensions to Python to permit automatic specification-based testing with inline, incremental formal specification.
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Gathering requirements should be fun. It's the brainstorming process refined. It shouldn't get in the way of productivity or creativity. Harvest is about gathering requirements in the most intuitive, least intrusive way possible.
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This package will allow people to check, change, update the license of their projects. It will conform to all new licenses available.
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Cloud data warehouse to power your data-driven innovationBigQuery 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.
