My experiences with static type checking. More specifically, I try to argue how a dynamic typed language can get help from optional (gradual) typing using mypy as example.

I recently tried TypeScript for a project. Essentially, it is a gradually typed superset of JavaScript. Originally intended for learning, the switch immediately felt empowering. Not that TypeScript is necessarily better (haven't used it enough to say that) but for a long time python user like me, (pushed) optional type annotations is refreshing.

Python is one of the popular dynamic typed languages. Not specifying data types like int, string allows for simpler programming and faster prototyping, making it easy to learn. Its not just about being simple though, duck typed languages have their share of benefits which are regularly exploited by the users.

Recent python versions have been pushing through a new change. Python now provides type hinting support using a now stable typing module. I never really cared about types in Python because, well, thats what I probably have been avoiding by using Python all along. But this is slowly changing as I use static typing more and more.

I enjoy cricket and Emacs. So wrote up a package, cricbuzz.el, for displaying cricket scores in Emacs. It basically is a web scraper for cricbuzz.com. Occasionally, there are changes to the web page structure and I have to do a little bit of tweaking. It was broken recently and I had to fix it a few months back. Here is one of the changes I did

-  (let* ((header-node (first data-nodes))
-         (row-nodes (cdr data-nodes))
+         (col-size (length (-remove-item " " header-node)))
+         (row-nodes (cdr (cdr data-nodes)))


I don't know what changed in the variable data-nodes. Don't even know what it holds. The only thing I know is that it contains html elements parsed to form S-expressions and contains structured data scraped from the website. The fix works for now but this thing will bug me badly again when something changes. Knowing that enforcing a structure in html is hard, the point here is that it is important to know what the symbols contain in your code. This is really helpful for maintaining the code over a long period of time, or when there are too many pieces to keep track of.

There are two things really that are usually done to solve these issues:

• Documenting functions, variables

Helpful names are helpful. But they can get weird. There are understandable limits to them. Documentations, specially function docs are more helpful. Usually you add data types for the arguments in the docstring too. Like this (numpy style):

def noot_noot(pingu, n_noots):
"""

Parameters
----------
pingu : Pingu
A pingu object
n_noots : int
Number of times to noot
"""

pass


This helps in knowing what is going to happen in the function. This also gets parsed by a documentation generator like sphinx so the types specified in here end up being useful. But they still are pretty passive. There is no way anyone could stop you from writing this

noot_noot(Pingu(), 1.3)


Not until runtime that is.

Notice the function again. The definition line itself is pretty much self explanatory (thanks to variable naming). There are many similar cases in practice which need just a little bit of hint about data types to clarify their tasks. "Type hinting" fills in this sweet spot and at the same time flags logical bugs like passing float where int is expected.

## 2 Type Hinting

Type hinting is the idea of adding annotations about data type for variables, function arguments etc. These are usually parsed and checked before runtime and usually are similar in spirit to something like automatic spell-checkers. Doing this helps in marking inconsistencies in variables which flow around here and there. I came to know about type hinting from JavaScript. There is flow which lets you add hints in plain JS without much intrusion and strip them off using something like babel in the compilation step.

Here is a sample taken from flow's homepage.

// @flow
function bar(x): string {
return x.length;
}
bar('Hello, world!');


You drop hints when needed and running flow gives you the error it detects

3:   return x.length;
^^^^^^^^ number. This type is incompatible with the expected return type of
2: function bar(x): string {
^^^^^^ string


Then there is TypeScript which behaves more like a superset of JS but with the same idea. Your development process gets assisted by static types and then the code gets converted to plain JS and runs like a duck.

## 3 mypy

Although not that popular, Python has in-language support for adding type hints which can be checked by something like mypy. What this means for our example is that you could do something like the following:

def noot_noot(pingu: Pingu, n_noots: int):
pass

noot_noot(Pingu(), 1.3)


This time, running mypy gives the following:

Argument 2 to "noot_noot" has incompatible type "float"; expected "int"


Running this code itself will not give any error if there is nothing in noot_noot which relies on n_noots not being a float (for example range(n_noots)). This is just handy for something as trivial as this. But gets really useful when you have a lot of structured data going in and out of things. The typing module provides many primitives to build tailored types. For example, if my program works with geographical coordinates (a pair of numbers) of cities (string), I could do something like the following:

from typing import Dict, Tuple

Coordinate = Tuple[float, float]

def minimum_trip_distance(cities: Dict[str, Coordinate]) -> float:
pass


Notice the nice name of the type which helps in identifying the associated object. We know whenever there is Coordinate that its going to be pair of floats and not more. mypy's support for types can be seen in its doc.

Here are a few reasons other than the already helpful type checking to use these hints:

• Its not really much to write and actually saves keystrokes as compared to writing unnecessary and passive documentation strings.
• It avoids runtime overheads as compared to defining a logical type using a dummy class.

There are concerns about the readability of code as such when using hints as it goes against python's philosophy. I feel like readability should not be judged by how it looks to a non-programmer but to a python programmer. Its easier for me to read that a function takes coordinates (which is known to be a pair of numbers since I decided to read the code dealing with geography) rather than an argument described solely by its name and / or docstring.

## 4 Keeping it Optional

Typing is something that feels like it comes attached with performance benefits. But using mypy for around a month now has convinced me that just the documentation part is reason enough to use it here and there. It helps keep track of tiny things like whether I am passing str or a stream when a function works on a file. This itself has reduced the load on variable naming for me a lot. Also, if you are not writing a hackish script, it does help to put barriers at places to frame the program.

Most importantly, it really is non-intrusive and purely optional. You could use hints wherever needed and skip where is it unnecessary and verbose (though I am not sure if this is a recommended practice).

## 5 Final thoughts

Static type checking in python is not that popular as compared to JS. But JS community is particularly well known to quickly get hands on new technologies. The python community is somewhat different. The users have different expectations from the language and the language has molded itself to be easy for the users. To elaborate on this: you won't see f-strings getting hugely popular right away because:

• the users don't care about it if the older ways are working (format() or similar in this case)
• packages / libraries supporting babel-ish ideas are not that common to find in python. Even if you are living on the edge kind of person, you can't just go on your way that easily. (Though I would blame the v2-v3 divide for this)

Other than that, support for 3rd party modules is not that extensive as of now. There is typeshed but doesn't compare to something like DefinitelyTyped. But this really is a reflection of how popular type hinting is. If not many are going to use it, there will always be lesser stubs in there.

Of course your IDE / editor needs to support on-the-fly type checking to actually be helpful. Emacs has flycheck which has an extension for adding mypy as a checker. PyCharm also supports it.