6 High Performance packages and projects
8.7 9.4 L2 PythonOptimizing Static Compiler for Python. Uses type mixins to compile Python into C or C++ modules resulting in large performance gains.
8.3 0.7 L2A Python implementation built using LLVM and modern JIT techniques with the goal of achieving good performance.
8.1 -An implementation of Python in Python. The interpreter uses black magic to make Python very fast without having to add in additional type information.
5.8 0.4 L2 Pythonx86-64 assembler embedded in Python. Can be used as inline assembler for Python or as a stand-alone assembler for Windows, Linux, OS X, Native Client and Go.
5.8 4.0 L1 C++A JIT for Python based upon CoreCLR
0.5 -An enhanced version of the Python.
Scout APM uses tracing logic that ties bottlenecks to source code so you know the exact line of code causing performance issues and can get back to building a great product faster.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
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