Mypy 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 staticaly 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.
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
- 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 several Python features are
not yet implemented. 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 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.
All of my code is still in Python 2. What are my options?
Mypy currently supports Python 3 syntax. Python 2 support is still in early stages
of development. However, Python 2 support will be improving. Mypy includes a
custom codec that lets you use Python 3 function annotations in Python 2 code.
The codec just removes the annotations before bytecode compilation.
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.
Why not use structural subtyping?
Mypy primarily uses
. Some argue that structural subtyping is better suited for
languages with duck typing such as Python. Here are some reasons why
mypy uses nominal subtyping:
- 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 supports basically nominal isinstance tests and they are
widely used in programs. It is not clear how to support isinstance in
a purely structural type system while remaining compatible with Python
- Many programmers are already familiar with nominal subtyping and it has
been successfully used in languages such as Java, C++ and C#. Only
few languages use structural subtyping.
However, structural subtyping can also be useful.
Structural subtyping is a likely feature to be added to mypy in the
future, even though we expect that most mypy programs will still primarily use
I like Python as it is. I don't need 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 mypy tutorial mentions some modifications
to Python code that may be required to make code type check without
errors, such as the
need to make attributes explicit and more explicit protocol representation.
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 PyPy?
This answer relates to PyPy as a Python implementation. See also the
answer related to RPython below.
Mypy and PyPy are orthogonal. Mypy does static type checking, i.e.
it is basically a linter, but static typing has no runtime effect, whereas the
PyPy is an Python implementation. You can use PyPy to run mypy programs.
How is mypy different from 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
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
- 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?
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
- 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?
basically statically typed subsets of Python. Mypy does the following
important things differently:
- 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
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 annotatations for functions
- 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
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.