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Source channel @githubtrending · Post #14731 · May 21

#cplusplus#high_performance#interior_point_method#linear_optimization#mixed_integer_programming#parallel#quadratic_programming#simplex HiGHS is a free, high-performance software that solves large and complex optimization problems like linear, quadratic, and mixed-integer programming. It works fast on many computers, including Linux, MacOS, and Windows, without needing extra software. You can use it through various programming languages like Python, C, C#, and Fortran, making it easy to integrate into your projects. HiGHS supports both serial and parallel computing, and it is advancing GPU acceleration for even faster solutions. This helps you efficiently find the best solutions for planning, scheduling, and decision-making problems in science, engineering, and business. Installation is straightforward, and detailed documentation is available to guide you[1][2][3][4]. https://github.com/ERGO-Code/HiGHS

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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.

GitHub Trends

@githubtrending · Post #14948 · 07/11/2025, 12:30 PM

#go#logging#metrics#opentelemetry#tracing OpenTelemetry-Go is a tool for Go applications that helps you track how your software performs by collecting data like traces and metrics, then sending this information to monitoring platforms so you can see what’s happening inside your app in real time[2][3][4]. It works on many operating systems and Go versions, and you can use it by adding a few lines of code to your app and setting up an exporter. This makes it much easier to find and fix problems, understand how your app is running, and keep everything reliable and fast[2][3][4]. https://github.com/open-telemetry/opentelemetry-go

GitHub Trends

@githubtrending · Post #14846 · 06/20/2025, 12:00 PM

#go#cloudnative#grafana#hacktoberfest#logging#loki#prometheus Loki is a log aggregation system inspired by Prometheus but designed specifically for logs instead of metrics. It is cost-effective and easy to operate because it only indexes metadata (labels) about logs, not the full log content, which reduces storage and complexity. Loki works well with Kubernetes by automatically indexing pod labels and integrates natively with Grafana for easy log visualization. Its stack includes an agent (Alloy) to collect logs, Loki to store and query them, and Grafana to display them. This setup helps you efficiently manage and analyze logs with less cost and simpler operation compared to traditional logging systems[2]. https://github.com/grafana/loki