The type system is a programmer's best friend

This page summarizes the projects mentioned and recommended in the original post on

Our great sponsors
  • WorkOS - The modern API for authentication & user identity.
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • - Learn 300+ open source libraries for free using AI.
  • Squants

    The Scala API for Quantities, Units of Measure and Dimensional Analysis

  • Vogen

    A semi-opinionated library which is a source generator and a code analyser. It Source generates Value Objects

    I usually run into issues at the boundaries in the system.

    Usually moving from primitives into complex types does not account for serialization and deserialization between db and the client. This can be very annoying to work with in something like C#.

    Usually it ends up resulting in alot more types and a lot more mapping between types.

    However this has its own benefits, but is very boilerplate-y and is sluggish to work with when your domain changes.

    Luckily, for C#, now exists thanks to source code generators which soothes some of the issues.

  • WorkOS

    The modern API for authentication & user identity. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  • swift-tagged

    🏷 A wrapper type for safer, expressive code.

    I’ve done something similar (not including rockets, don’t worry!) in Swift with its typealias feature. Thankfully there is a way to actually force compiler errors in such situations with something like

  • TypeScript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

    Little mini example in terms of LSP behaviour is fixing this bug:

    I edit the results of gotoDefinition on the way through so I always jump to the one I want.

  • Django

    The Web framework for perfectionists with deadlines.

    > I don't understand why you're talking about statistical sampling. Aside from random functions, functions are deterministic, unit testing isn't about random sampling. That's not the problem here.

    Completely and utterly incorrect. You are not understanding. Your preconceived notion that unit testing has nothing to do with random sampling is WRONG. Unit Testing IS Random sampling.

    If you want 100% coverage on your unit tests you need to test EVERY POSSIBILITY. You don't. Because every possibility is too much. Instead you test a few possibilities. How you select those few possibilities is "random." You sample a few random possibilities OUT OF a domain. Unit Testing IS random sampling. They are one in the same. That random sample says something about the entire population of possible inputs.

    >Next month some code elsewhere changes and that function ends up getting called with a string containing json instead, so now it blows up in production, you have an outage until someone fixed it. Not great. You might think maybe you were so careful that you actually earlier had unit tests passing a string instead, so maybe it could've been caught before causing an outage. But unlikely.

    Rare. In theory what you write is true. In practice people are careful not to do this; and unit tests mostly prevent this. I can prove it to you. Entire web stacks are written in python without types. That means most of those unit tests were successful. Random Sampling statistically covers most of what you need.

    If it blows up production the fix for python happens in minutes. A seg fault in C++, well that won't happen in minutes. Even locating the offending line, let alone the fix could take days.

    >Following month some code elsewhere ends up pulling a different json library which produces subtly incompatible json objects and one of those gets passed in, again blowing up in production. You definitely didn't have unit tests for this one because two months ago when the code was written you had never heard of this incompatible json library. Another outage, CEO is getting angry.

    Yeah except first off in practice most people tend to not be so stupid as to do this, additionally unit tests will catch this. How do I know? Because companies like yelp have had typeless python as webstacks for years and years and years and this mostly works. C++ isn't used because it's mostly a bigger nightmare.

    There are plenty of companies for years and years have functioned very successfully using python without types. To say that those companies are all wrong is a mistake. Your company is likely doing something wrong... python functions just fine with or without types.

    >And this is one of the 5 arguments, same applies for all of them so there is exponential complexity in attempting to cover every scenario with unit tests. So you can't.

    I think you should think very carefully about what I said. You're not understanding it. Unit testing Works. You know this. It's used in industry, there's a reason why WE use it. But your logic here is implying something false.

    You're implying that because of exponential complexity it's useless to write unit tests. Because you are only covering a fraction of possible inputs (aka domain). But then this doesn't make sense because we both know unit testing works to an extent.

    What you're not getting is WHY it works. It works because it's a statistical sample of all possible inputs. It's like taking a statistical sample of the population of people. A small sample of people says something about the ENTIRE population of people. Just like how a small amount of unit tests Says something about the correctness of the entire population of Possible inputs.

    >This isn't a theoretical example, it's happening in our service very regularly. It was a huge mistake to use python for production code but it's too expensive to change now, at least for now.

    The problem here is there are practical examples of python in production that do work. Entire frameworks have been written in python. Django. You look at your company but blindly ignore the rest of the industry. Explain why this is so popular if it doesn't work: It literally makes no sense.

    Also if you're so in love with types you can actually use python with type annotations and an external type checker like mypy. These types can be added to your code base without changing your code. Python types with an external checker are actually more powerful then C++ types. It will give you equivalent type safety (with greater flexibility then C++) to a static language if you choose to go this route. I believe both yelp and Instagram decided to do add type annotations and type checking to their code and CI pipeline to grab the additional 10% of safety you get from types.

    But do note, both of those companies handled production python JUST FINE before python type annotations. You'd do well do analyze why your company has so many problems and why yelp and instagram supported a typeless python stack just fine.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

Suggest a related project

Related posts