Frequently Asked Questions¶
Why have both dynamic and static typing?¶
Dynamic typing can be flexible, powerful, convenient and easy. But it’s not always the best approach; there are good reasons why many developers choose to use statically typed languages.
Here are some potential benefits of mypy-style static typing:
- Static typing can make programs easier to understand and maintain. Type declarations can serve as machine-checked documentation. This is important as code is typically read much more often than modified, and this is especially important for large and complex programs.
- Static typing can help you find bugs earlier and with less testing and debugging. Especially in large and complex projects this can be a major time-saver.
- Static typing can help you find difficult-to-find bugs before your code goes into production. This can improve reliability and reduce the number of security issues.
- Static typing makes it practical to build very useful development tools that can improve programming productivity or software quality, including IDEs with precise and reliable code completion, static analysis tools, etc.
- You can get the benefits of both dynamic and static typing in a single language. Dynamic typing can be perfect for a small project or for writing the UI of your program, for example. As your program grows, you can adapt tricky application logic to static typing to help maintenance.
See also the front page of the mypy web site.
Would my project benefit from static typing?¶
For many projects dynamic typing is perfectly fine (we think that Python is a great language). But sometimes your projects demand bigger guns, and that’s when mypy may come in handy.
If some of these ring true for your projects, mypy (and static typing) may be useful:
- Your project is large or complex.
- Your codebase must be maintained for a long time.
- Multiple developers are working on the same code.
- Running tests takes a lot of time or work (type checking may help you find errors early in development, reducing the number of testing iterations).
- Some project members (devs or management) don’t like dynamic typing, but others prefer dynamic typing and Python syntax. Mypy could be a solution that everybody finds easy to accept.
- You want to future-proof your project even if currently none of the above really apply.
Can I use mypy to type check my existing Python code?¶
It depends. Compatibility is pretty good, but some Python features are not yet implemented or fully supported. The ultimate goal is to make using mypy practical for most Python code. Code that uses complex introspection or metaprogramming may be impractical to type check, but it should still be possible to use static typing in other parts of a program.
Will static typing make my programs run faster?¶
Mypy only does static type checking and it does not improve performance. It has a minimal performance impact. In the future, there could be other tools that can compile statically typed mypy code to C modules or to efficient JVM bytecode, for example, but this is outside the scope of the mypy project. It may also be possible to modify existing Python VMs to take advantage of static type information, but whether this is feasible is still unknown. This is nontrivial since the runtime types do not necessarily correspond to the static types.
How do I type check my Python 2 code?¶
You can use a comment-based function annotation syntax
and use the
--py2 command-line option to type check your Python 2 code.
You’ll also need to install
typing for Python 2 via
pip install typing.
Is mypy free?¶
Yes. Mypy is free software, and it can also be used for commercial and proprietary projects. Mypy is available under the MIT license.
Can I use structural subtyping?¶
Mypy provides support for both nominal subtyping and
Some argue that structural subtyping is better suited for languages with duck
typing such as Python. Mypy however primarily uses nominal subtyping,
leaving structural subtyping mostly opt-in (except for built-in protocols
Iterable that always support structural subtyping). Here are some
- It is easy to generate short and informative error messages when using a nominal type system. This is especially important when using type inference.
- Python provides built-in support for nominal
isinstance()tests and they are widely used in programs. Only limited support for structural
isinstance()is available, and it’s less type safe than nominal type tests.
- Many programmers are already familiar with static, nominal subtyping and it has been successfully used in languages such as Java, C++ and C#. Fewer languages use structural subtyping.
However, structural subtyping can also be useful. For example, a “public API” may be more flexible if it is typed with protocols. Also, using protocol types removes the necessity to explicitly declare implementations of ABCs. As a rule of thumb, we recommend using nominal classes where possible, and protocols where necessary. For more details about protocol types and structural subtyping see Protocols and structural subtyping and PEP 544.
I like Python and I have no need for static typing¶
That wasn’t really a question, was it? Mypy is not aimed at replacing Python. The goal is to give more options for Python programmers, to make Python a more competitive alternative to other statically typed languages in large projects, to improve programmer productivity and to improve software quality.
How are mypy programs different from normal Python?¶
Since you use a vanilla Python implementation to run mypy programs, mypy programs are also Python programs. The type checker may give warnings for some valid Python code, but the code is still always runnable. Also, some Python features and syntax are still not supported by mypy, but this is gradually improving.
The obvious difference is the availability of static type
checking. The section Common issues mentions some
modifications to Python code that may be required to make code type
check without errors. Also, your code must make attributes explicit and
use a explicit protocol representation. For example, you may want to
subclass an Abstract Base Class such as
Mypy will support modular, efficient type checking, and this seems to rule out type checking some language features, such as arbitrary runtime addition of methods. However, it is likely that many of these features will be supported in a restricted form (for example, runtime modification is only supported for classes or methods registered as dynamic or ‘patchable’).
How is mypy different from Cython?¶
Cython is a variant of Python that supports compilation to CPython C modules. It can give major speedups to certain classes of programs compared to CPython, and it provides static typing (though this is different from mypy). Mypy differs in the following aspects, among others:
- Cython is much more focused on performance than mypy. Mypy is only about static type checking, and increasing performance is not a direct goal.
- The mypy syntax is arguably simpler and more “Pythonic” (no cdef/cpdef, etc.) for statically typed code.
- The mypy syntax is compatible with Python. Mypy programs are normal Python programs that can be run using any Python implementation. Cython has many incompatible extensions to Python syntax, and Cython programs generally cannot be run without first compiling them to CPython extension modules via C. Cython also has a pure Python mode, but it seems to support only a subset of Cython functionality, and the syntax is quite verbose.
- Mypy has a different set of type system features. For example, mypy has genericity (parametric polymorphism), function types and bidirectional type inference, which are not supported by Cython. (Cython has fused types that are different but related to mypy generics. Mypy also has a similar feature as an extension of generics.)
- The mypy type checker knows about the static types of many Python stdlib modules and can effectively type check code that uses them.
- Cython supports accessing C functions directly and many features are defined in terms of translating them to C or C++. Mypy just uses Python semantics, and mypy does not deal with accessing C library functionality.
How is mypy different from Nuitka?¶
Nuitka is a static compiler that can translate Python programs to C++. Nuitka integrates with the CPython runtime. Nuitka has additional future goals, such as using type inference and whole-program analysis to further speed up code. Here are some differences:
- Nuitka is primarily focused on speeding up Python code. Mypy focuses on static type checking and facilitating better tools.
- Whole-program analysis tends to be slow and scale poorly to large or complex programs. It is still unclear if Nuitka can solve these issues. Mypy does not use whole-program analysis and will support modular type checking (though this has not been implemented yet).
How is mypy different from RPython or Shed Skin?¶
- RPython is primarily designed for implementing virtual machines; mypy is a general-purpose tool.
- Mypy supports both static and dynamic typing. Dynamically typed and statically typed code can be freely mixed and can interact seamlessly.
- Mypy aims to support (in the future) fast and modular type checking. Both RPython and Shed Skin use whole-program type inference which is very slow, does not scale well to large programs and often produces confusing error messages. Mypy can support modularity since it only uses local type inference; static type checking depends on having type annotations for functions signatures.
- Mypy will support introspection, dynamic loading of code and many other dynamic language features (though using these may make static typing less effective). RPython and Shed Skin only support a restricted Python subset without several of these features.
- Mypy supports user-defined generic types.
Mypy is a cool project. Can I help?¶
Any help is much appreciated! Contact the developers if you would like to contribute. Any help related to development, design, publicity, documentation, testing, web site maintenance, financing, etc. can be helpful. You can learn a lot by contributing, and anybody can help, even beginners! However, some knowledge of compilers and/or type systems is essential if you want to work on mypy internals.