cython/cython
Cython
Cython is a compiler that translates Python code into C or C++ to create high-performance extension modules. It functions as a static typing optimizer and a C extension generator, allowing developers to declare C types within Python code to reduce interpreter overhead and increase execution speed.
The project enables the wrapping of external C libraries to provide high-level interfaces to low-level system capabilities. It also serves as a native binary packager, capable of freezing scripts and their dependencies into standalone executable binaries for distribution.
The system covers a broad range of capabilities including native library wrapping, C extension development, and the embedding of a Python runtime environment into native C applications. It provides tools for loop execution optimization, memory reference control, and the packaging of compiled extensions into platform-specific wheels.
Build automation is supported through standard setup scripts and on-demand module compilation during import.
Features
- C-Extensions - Provides tools for compiling Python code into C extensions to increase execution speed and memory efficiency.
- Source-to-C Transpilers - Converts a Python-like source language into C or C++ code that interfaces directly with the Python C API.
- Native Glue Code Generators - Automatically generates the boilerplate code required to map Python objects and functions to native C structures and calls.
- Compiled Type Optimizations - Enables the declaration of specific C types for variables to generate more efficient machine code.
- Native Library Integrations - Builds high-level Python interfaces for existing C libraries to access low-level system capabilities and external functions.
- C Function Bindings - Allows the declaration of C types, functions, and structs within modules to enable direct integration with external C libraries.
- Native Library Wrappers - Cython enables interfacing with existing C functions to provide a high-level bridge to low-level system capabilities.
- Execution Performance Optimizers - Converts Python code into C extensions to increase execution speed and reduce runtime overhead for compute-intensive tasks.
- Type Annotations - Translates high-level type declarations into C-level types to generate optimized machine code and bypass Python dynamic lookup.
- Type-Based Performance Optimization - Allows declaring C types within Python code to reduce interpreter overhead and increase execution speed.
- Standalone Binary Generators - Packages a script and its dependencies into a standalone executable binary for distribution to end users.
- Native Binary Packagers - Allows freezing scripts and their dependencies into standalone executable binaries for platform-specific distribution.
- Runtime Embedding - Integrates a script execution environment into a native binary to run scripts from within a C application.
- Reference Counting - Controls the lifecycle of Python objects using explicit rules for borrowed and new references within generated C code.
- Native Memory Lifecycle Management - Provides mechanisms to manage the memory lifecycle of native objects using explicit reference counting control.
- Loop Optimizations - Transforms integer loops into efficient C implementations to reduce runtime overhead and execution time.
- Loop Vectorization - Transforms Python loops into efficient C implementations to remove interpreter overhead and increase execution speed.
- Wheel Binary Compilation - Packages compiled extensions into platform-specific wheels to support distribution across various hardware architectures.
- Code Quality and Analysis - Compiler for high-performance Python and C interoperability.
- Language Implementations - Compiles Python code into C for performance optimization.
- Language Interop - Compiler for writing Python extensions in C-like syntax.
- Scripting and Bindings - Optimizing compiler for Python and C-extended Python code.
