Cython 3.0 is a major revision of the Cython compiler and language, not a switch that makes every Python program run at C speed. It defaults to Python 3 syntax and semantics, improves pure Python mode, and can compile Python-like source into C or C++ extension modules. Compiling code with few changes may provide a modest speed increase; larger gains depend on adding type information and using C-level operations in measured performance-critical code.
What is Cython 3.0?
Cython is a programming language and compiler that lets developers write Python-like code, add optional static types, and translate the result into C or C++. That generated code is then compiled into an extension module that Python can import. Cython 3.0 is a major revision of both the compiler and language. The project’s official migration guide describes it as “a major revision of the compiler and the language that comes with some backwards incompatible changes.” The project changelog dates the 3.0.0 release to July 17, 2023.
The key change for existing projects is that Python 3 syntax and semantics are the default, expressed as language_level=3str. That makes Cython’s default behavior closer to modern Python, but it can change how older code is interpreted or compiled. Cython’s changelog records the 3.0 release and its historical compatibility notes; those notes should not be mistaken for current support guarantees.
Does Cython make Python as fast as C?
Not automatically. Cython’s title-level promise of C speed is an optimization goal for suitable code, not a universal result. Ordinary Python operations still carry Python’s dynamic behavior when they remain dynamically typed. Cython can remove some of that overhead when the programmer supplies enough static type information and uses C-level operations, especially in hot sections such as numeric loops.
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Compiling mostly unchanged Python
The Cython project’s Pure Python Mode tutorial estimates that compiling otherwise pure Python scripts, without further optimization, usually brings a 20–50% speed gain. This is an undated typical estimate in current documentation, not a universal benchmark or guarantee for a particular application.
Adding types to hot code
For greater optimization opportunity, identify bottlenecks with profiling, then add static types and C-level operations where they matter. More explicit typing can require more code and tighter assumptions about the data being processed, so the trade-off is between development and maintenance effort and performance potential. Measure the result on the actual workload rather than assuming the compiled version is faster.
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No dated, independently reproducible Cython 3.0 benchmark establishes that it makes Python universally “as fast as C.” If publishing a performance comparison, include the workload and code, Python and Cython versions, compiler and build settings, and hardware; results from one case should not be generalized to others.
How do I use Cython with normal Python files?
Pure Python mode lets source files remain valid Python syntax while adding Cython-specific type information and declarations. You can introduce that information with Python annotations, a companion .pxd declaration file, or helpers from the cython module. This can fit into an existing Python project incrementally: source can still run in the regular Python interpreter, while a build step produces a compiled extension for use where appropriate.
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Keeping Python syntax does not itself make dynamic operations native-speed. The gains depend on which operations Cython can optimize and what type information the code provides. For code that needs Cython-specific syntax or declarations more directly, developers can use .pyx source files instead.
Compilation workflow
- Choose the source style. Keep a
.pyfile for pure Python mode, adding annotations or other Cython declarations as needed, or write Cython-specific source in a.pyxfile. - Run Cython as a build step. Cython translates the source into generated C, or C++ when using C++ mode. The documented source-file workflow is described in the Cython compilation guide.
- Compile the generated source. A suitable platform compiler and build configuration are required; Cython is not a runtime switch that changes an already-running Python interpreter.
- Import the extension module. The build creates a platform-specific extension, commonly named with a
.soor.pydsuffix. The exact filename and build setup vary by platform.
What can break when upgrading from Cython 0.29 to 3.0?
Not every project will encounter every change, but an upgrade can alter language behavior as well as compilation. Use the official migration guide as a project-specific review checklist, then test the resulting extension against the Python versions and inputs the project actually supports.
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- Python 3 behavior is the default. Among the changes are true division unless
cdivisionis enabled,printas a function, changed annotation handling, and Python-compatibleStopIterationhandling in generators. - Binding and signatures can differ. Function binding is enabled by default and can affect method binding and signature behavior.
- Annotations can influence typing more actively. Cython 3 may interpret annotations more strictly or use them differently than older projects expect.
- Other compiler and language details changed. The guide also covers arithmetic special methods, exception propagation for non-extern
cdeffunctions, NumPy C-API initialization, and namespace-package.pxdlookup. - Conditional compilation is deprecated.
DEFandIFare deprecated; depending on the purpose, alternatives include constants, enums, macros, runtime conditions, or reorganized code.
For compatibility, review the migration guide’s specific settings and use compatibility options selectively where they suit the project. Do not treat a global setting that restores older behavior as a substitute for checking affected code: exercise division, generator behavior, annotations, extension imports, and any conditional-compilation paths in tests.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Which Cython approach fits a project?
| Approach | What it involves | Best fit | Trade-off |
|---|---|---|---|
| Compile mostly unchanged Python | Use pure Python mode with little additional typing. | Exploring compiled extensions or seeking a relatively low-disruption improvement. | The project tutorial’s 20–50% figure is a typical estimate, not a workload guarantee; dynamic operations may remain costly. |
| Type selected hot paths | Add annotations or Cython declarations and use C-level operations where profiling identifies bottlenecks. | Targeted optimization of measured sections. | More typing and implementation detail can increase code complexity and maintenance. |
| Use Cython-specific source | Write code in .pyx when the implementation benefits from Cython’s own syntax and declarations. |
Code that needs more direct access to Cython features. | Source is less purely Python and may be less directly runnable in a standard interpreter. |
What Cython 3.0 does—and does not—promise
Cython 3.0 modernizes the language defaults and compiler, expands the practical use of pure Python syntax, and offers a route from Python-like code to compiled extension modules. The project’s changelog says that Cython 3.0 supported CPython 3.8–3.11 and had experimental support for in-development CPython 3.12 at that release stage, while dropping Python 2.6 support. These are historical 3.0-era statements, not a current compatibility matrix; check the documentation for the Cython version you plan to use.
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