Embedded Profiler is low-overhead C++ profiler based on automatic instrumentation of functions done by the compiler (GCC, MinGW, or MSVC). Profiling can be done either automatically or manually. Automatic profiling generates a complete call tree and needs no modification of code. Manual profiling requires using the EProfiler API to specify the parts of code to be profiled. The resulting log can be opened in Performance Analyzer, a GUI application with several views designed for comfortable log analysis.
Django-live-profiler is a low-overhead data access and code profiler for Django-based applications. Profiling Web applications on a development environment often produces misleading results due to different patterns in the data, different patterns in user behavior, and differences in infrastructure. All existing DB access profiling solutions for Django seem to focus on a single request, but in the real world certain queries might be negligible in a single request while still putting a considerable strain the database across all requests. Django-live-profiler aims to solve these issues by collecting database usage data from a live application.