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Python’s context manager protocol has only two methods, with straightforward types. But when it comes to adding accurate type hints to a context manager, we still need to combine several typing features. Let’s look at how we can do this for the two different ways of making a context manager.
A “magic number” is the anti-pattern of using a number directly rather than storing it in a descriptive variable name. In web code HTTP status codes are often used as magic numbers, perhaps because web developers memorize common codes such as 200 and 404. In Python, we can avoid such magic with descriptive references from the standard library’s http.HTTPStatus enum.
typing.Any in Python’s standard libraryWhen we add type hints, we can find our desire for strictness in tension with Python’s flexibility. In this post we’ll explore three groups of functions in the standard library that I naïvely expected to use narrow types, but due to some edge cases, instead use Any.
TypeGuardI previously covered type narrowing using isinstance(), assert, and Literal. In today’s post we’ll cover TypeGuard, a new special type that allows us to create custom type narrowing functions.
@overloadSometimes the types of several variables are related, such as “if x is type A, y is type B, else y is type C”. Basic type hints cannot describe such relationships, making type checking cumbersome or inaccurate. We can instead use @typing.overload to represent type relationships properly.
It seems inevitable that large projects need some # type: ignore comments, to work around type checking in tricky cases. I’ve found Mypy has a few options to make such ignore comments more precise and manageable.
Mypy does not allow variables to change type. I found this a little bit of a shock at first, but after I adapted, I found my code was more readable.
A couple of recent PEPs have made writing type hints easier:
NoReturn?Sometimes functions never return, for example by always raising an exception. For such functions’ return types, we can “get away” with using None, but it’s best to use the special NoReturn type). This allows Mypy to better find unreachable code (as covered previously). It also shows future readers that the lack of return is intentional.
I recently discovered Mypy has a secondary function as an unreachable code detector. This feature is a great way to highlight places bugs may be hiding, as code paths that can’t possibly run normally show a logical error.
ProtocolDuck typing says “if it quacks like a duck, treat it like a duck.” Type checking seems at odds with duck typing: we restrict variables to named types (classes), allowing only that type or subtypes. This seems like it would stop us from passing in arbitrary objects that can “quack the right way”. But since PEP 0544, we can declare “duckish” types with typing.Protocol.
isinstance(), assert, and LiteralType narrowing is the ability for a type checker to infer that inside some branch, a variable has a more specific (narrower) type than its definition. This allows us to perform type-specific operations without any explicit casting.
In a type hint, if we specify a type (class), then we mark the variable as containing an instance of that type. To specify that a variable instead contains a type, we need to use type[Cls] (or the old syntax typing.Type).
__future__.annotationsPython 3.7 added a new “postponed evaluation” mode for type hints. In this post we’ll cover how it changes the behaviour of type hints, how to activate it, and the outstanding problems.
reveal_type()When working with type hints, it’s often useful to debug the types of variables. Type checkers allow you to do this with reveal_type() and reveal_locals().
Circular imports are always annoying when they arise in Python, and type hints make them more common. Thankfully, there’s a trick to add circular imports for type hints without causing ImportErrors.
Using TypedDict is a great way to type code that passes around dictionaries. The default way to create a TypedDict is with its class-based syntax:
*args and **kwargsWhen I started writing type hints, I was a little confused about what to do with Python’s variable argument operators, * and ** (often called *args and **kwargs). Here’s what I figured out.
Take this function:
When starting out with Python type hints, it’s common to overuse typing.Any. This is dangerous, since Any entirely disables type checking for a variable, allowing any operation.
Python 3.9 introduced zoneinfo into the standard library. This module reads your operating system’s copy of the tz database. On older versions of Python, you can install the backports.zoneinfo package to use zoneinfo without upgrading.
functools.partial() in DjangoPython’s functools.partial is a great tool that I feel is underused.
Google has started rolling out FLoC, currently to 0.5% of Chrome users, and some sites are already disabling it. In this post we’ll cover what FLoC is, who’s disabling it, why, and how to do so on a Django site.
heroicons is a free SVG icon set for your websites, from the creators of tailwindcss. SVG icons are great - they’re small, they sit inline in your HTML, and you can scaled and colour them with plain HTML and CSS. And heroicons is a great icon set - minimal, clear, and consistent.
I recently upgraded my client ev.energy to PostgreSQL 13. The first feature listed in this version’s release notes is “Space savings and performance gains from de-duplication of B-tree index entries”. I reindexed all tables after the upgrade to take advantage of this deduplication and saw index storage savings of up to 90%.