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Source channel @githubtrending · Post #14923 · Jul 7

#rust#ai_agent#developer_tools#enterprise#fine_tuning#on_prem#open_source#rag#self_hosted#swe_bench#vscode Refact.ai is a free, open-source AI software development agent that helps you code faster and smarter by deeply understanding your code and integrating with tools like GitHub, databases, Docker, and debuggers. It offers unlimited, context-aware code auto-completion, can generate, refactor, explain, debug code, and create tests and documentation across 25+ programming languages. You can run it securely on your own servers, use top AI models like GPT-4o, and connect your own API keys. This means you save time on repetitive tasks, improve code quality, and collaborate better, making your development workflow much more efficient and productive[1][3][5]. https://github.com/smallcloudai/refact

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djangoproject

@djangoproject · Post #77 · 07/05/2016, 07:46 AM

https://docs.python.org/2/library/logging.html This module defines functions and classes which implement a flexible event logging system for applications and libraries. The key benefit of having the #logging_API provided by a standard library module is that all Python modules can participate in logging, so your application log can include your own messages integrated with messages from third-party modules. The module provides a lot of functionality and flexibility. If you are unfamiliar with #logging, the best way to get to grips with it is to see the tutorials (see the links on the right). The basic classes defined by the module, together with their functions, are listed below. #Loggers expose the interface that application code directly uses. Handlers send the log records (created by loggers) to the appropriate destination. Filters provide a finer grained facility for determining which log records to output. Formatters specify the layout of log records in the final output.