TIL

The handful of times I’ve reached for typing.TypeGuard in Python, I’ve always been confused by its behavior and ended up ditching it with a # type: ignore comment. For the uninitiated, TypeGuard allows you to apply custom type narrowing1. For example, let’s say you have a function named pretty_print that accepts a few different types and prints them differently onto the console: from typing import assert_never def pretty_print(val: int | float | str) -> None: if isinstance(val, int): # assert_type(val, int) print(f"Integer: {val}") elif isinstance(val, float): # assert_type(val, float) print(f"Float: {val}") elif isinstance(val, str): # assert_type(val, str) print(f"String: {val}") else: assert_never(val) If you run it through mypy, in each branch, the type checker automatically narrows the type and knows exactly what the type of val is....

These days, I don’t build hierarchical types through inheritance even when writing languages that support it. Type composition has replaced almost all of my use cases where I would’ve reached for inheritance before. I’ve written1 about how to escape the template pattern2 hellscape and replace that with strategy pattern3 in Python before. While by default, Go saves you from shooting yourself in the foot by disallowing inheritance, it wasn’t obvious to me how I could apply the strategy pattern to make things more composable and testable....

I used reach for reflection whenever I needed a Retry function in Go. It’s fun to write, but gets messy quite quickly. Here’s a rudimentary Retry function that does the following: It takes in another function that accepts arbitrary arguments. Then tries to execute the wrapped function. If the wrapped function returns an error after execution, Retry attempts to run the underlying function n times with some backoff. The following implementation leverages the reflect module to achieve the above goals....

Despite moonlighting as a gopher for a while, the syntax for type assertion and type switches still trips me up every time I need to go for one of them. So, to avoid digging through the docs or crafting stodgy LLM prompts multiple times, I decided to jot this down in a gobyexample1 style for the next run. Type assertion Type assertion in Go allows you to access an interface variable’s underlying concrete type....

I’ve been a happy user of pydantic1 settings to manage all my app configurations since the 1.0 era. When pydantic 2.0 was released, the settings portion became a separate package called pydantic_settings2. It does two things that I love: it automatically reads the environment variables from the .env file and allows you to declaratively convert the string values to their desired types like integers, booleans, etc. Plus, it lets you override the variables defined in ....

As of now, unlike Python or NodeJS, Go doesn’t allow you to specify your development dependencies separately from those of the application. However, I like to specify the dev dependencies explicitly for better reproducibility. While working on a new CLI tool1 for checking dead URLs in markdown files, I came across this neat convention: you can specify dev dependencies in a tools.go file and then exclude them while building the binary using a build tag....

While I tend to avoid *args and **kwargs in my function signatures, it’s not always possible to do so without hurting API ergonomics. Especially when you need to write functions that call other helper functions with the same signature. Typing *args and **kwargs has always been a pain since you couldn’t annotate them precisely before. For example, if all the positional and keyword arguments of a function had the same type, you could do this:...

You can use @dataclass(frozen=True) to make instances of a data class immutable during runtime. However, there’s a small caveat—instantiating a frozen data class is slightly slower than a non-frozen one. This is because, when you enable frozen=True, Python has to generate __setattr__ and __delattr__ methods during class definition time and invoke them for each instantiation. Below is a quick benchmark comparing the instantiation times of a mutable dataclass and a frozen one (in Python 3....

Despite using VSCode as my primary editor, I never really bothered to set up the native debugger to step through application code running inside Docker containers. Configuring the debugger to work with individual files, libraries, or natively running servers is trivial1. So, I use it in those cases and just resort back to my terminal for debugging containerized apps running locally. However, after seeing a colleague’s workflow in a pair-programming session, I wanted to configure the debugger to cover this scenario too....

I’m one of those people who will sit in front of a computer for hours, fiddling with algorithms or debugging performance issues, yet won’t spend 10 minutes to improve their workflows. While I usually get away with this, every now and then, my inertia slithers back to bite me. The latest episode was me realizing how tedious it is to move config files across multiple devices when I was configuring a new MacBook Air and Mac Mini at the same time....

This site1 is built with Hugo2 and served via GitHub pages3. Recently, I decided to change the font here to make things more consistent across different devices. However, I didn’t want to go with Google Fonts for a few reasons: CDN is another dependency. Hosting static assets on GitHub Pages has served me well. Google Fonts tracks users and violates4 GDPR in Germany. Google Analytics does that too. But since I’m using the latter anyway, this might come off a bit apocryphal....

I was curious to see if I could prototype a simple load balancer in a single Go script. Go’s standard library and goroutines make this trivial. Here’s what the script needs to do: Spin up two backend servers that’ll handle the incoming requests. Run a reverse proxy load balancer in the foreground. The load balancer will accept client connections and round-robin them to one of the backend servers; balancing the inbound load....

I was cobbling together a long-running Go script to send webhook messages to a system when some events occur. The initial script would continuously poll a Kafka topic for events and spawn new goroutines to make HTTP requests to the destination. This had two problems: It could create unlimited goroutines if many events arrived quickly It might overload the destination system by making many concurrent requests In Python, I’d use just asyncio....

A TOTP1 based 2FA system has two parts. One is a client that generates the TOTP code. The other part is a server. The server verifies the code. If the client and the server-generated codes match, the server allows the inbound user to access the target system. The code usually expires after 30 seconds and then, you’ll have to regenerate it to be able to authenticate. As per RFC-62382, the server shares a base-32 encoded secret key with the client....

I love Go’s implicit interfaces. While convenient, they can also introduce subtle bugs unless you’re careful. Types expected to conform to certain interfaces can fluidly add or remove methods. The compiler will only complain if an identifier anticipates an interface, but is passed a type that doesn’t implement that interface. This can be problematic if you need to export types that are required to implement specific interfaces as part of their API contract....

Before the release of version 1.21, you couldn’t set levels for your log messages in Go without either using third-party libraries or writing your own boilerplates. Coming from Python, I’ve always found this odd, considering that this capability has been in the Python standard library forever. However, it seems like the new log/slog subpackage in Go allows you to do that and a whole lot more. Apart from being able to add levels to log messages, slog also allows you to emit JSON-structured log messages and group them by certain attributes....

The 100k context window of Claude 21 has been a huge boon for me since now I can paste a moderately complex problem to the chat window and ask questions about it. In that spirit, it recently refactored some pretty gnarly conditional logic for me in such an elegant manner that it absolutely blew me away. Now, I know how bitmasks2 work and am aware of the existence of enum.Flag3 in Python....

This morning, while browsing Hacker News, I came across a neat trick1 that allows you to share textual data by leveraging DNS TXT records. It can be useful for sharing a small amount of data in environments that restrict IP but allow DNS queries, or to bypass censorship. To test this out, I opened my domain registrar’s panel and created a new TXT type DNS entry with a base64 encoded message containing the poem A Poison Tree by William Blake....

Unless I’m hand rolling my own ORM-like feature or validation logic, I rarely need to write custom descriptors in Python. The built-in descriptor magics like @classmethod, @property, @staticmethod, and vanilla instance methods usually get the job done. However, every time I need to dig my teeth into descriptors, I reach for this fantastic how to1 guide by Raymond Hettinger. You should definitely set aside the time to read it if you haven’t already....

Python offers a ton of ways like os.system or os.spawn* to create new processes and run arbitrary commands in your system. However, the documentation usually encourages you to use the subprocess1 module for creating and managing child processes. The subprocess module exposes a high-level run() function that provides a simple interface for running a subprocess and waiting for it to complete. It accepts the command to run as a list of strings, starts the subprocess, waits for it to finish, and then returns a CompletedProcess object with information about the result....