APIs only a mother could love

Lately we’ve been integrating more 3rd party APIs than usual, and the experience was less than great in almost every case. Let’s take a look at how ugly some APIs will get. In the descriptions below, company names have been redacted to protect the (not so) innocent.

XML is not hip, we must offer JSON

One of our 3rd party vendors has a geocoding API that is based on XML. Of course, this data exchange format is seen as somewhat crusty and not very hip. So, they also offer the API in JSON.

Great, you would say. Unfortunately, the JSON responses are just mechanically transformed versions of the original “native” XML. That means you can get some truly hilarious output. Here’s one small detail in a response:

  "AdditionalData": [
      "value": "Nederland",
      "key": "CountryName"
      "value": "Noord-Brabant",
      "key": "StateName"
      "value": "Eindhoven",
      "key": "CountyName"

We kind of got suckered into using the JSON API (it looked easier!), so now our code has to normalise this so we can more easily access the dictionary using keys:

  "AdditionalData": {
      "CountryName": "Nederland",
      "StateName": "Noord-Brabant",
      "CountyName": "Eindhoven"

In cases like this, you really wish they either created a custom JSON format, or just stuck with the XML:

<AdditionalData key="CountryName">Nederland</AdditionalData>
<AdditionalData key="StateName">Noord-Brabant</AdditionalData>
<AdditionalData key="CountyName">Eindhoven</AdditionalData>

Even though this is still somewhat awkward (lots of repeated stuff), at least you can query this easily using XPath, which is a proper XML standard (I guess the XML committee had some good ideas after all!):

country = address.findtext('AdditionalData[@key="CountryName"]')

SOAP only really works in Java-like languages, so let’s offer REST

In the same vein as the above, one vendor has an API that’s based on RPC via SOAP. Despite “Simple” being in the original meaning of the acronym, this standard is anything but simple. Especially in dynamic languages, SOAP is a pain to implement. They probably got so many complaints from users of dynamic languages that they decided to offer a “REST” interface as well.

Unfortunately, doing REST properly is hard even for people well-versed in the HTTP spec, which means when you try to do it as a semi-automated shim around an RPC API, things will inevitably get ugly.

For starters, almost all endpoints in this API must be invoked via the GET method, even those which modify state! The HTTP specification makes a fundamental distinction between methods which are safe, methods which are idempotent and methods which are neither.

The spec is very clear that GET and HEAD are should not change things on the server (they’re supposed to be “safe”):

In particular, the convention has been established that the GET and HEAD methods SHOULD NOT have the significance of taking an action other than retrieval.

And they certainly should not do a different thing every time you call them (they’re supposed to be “idempotent”):

Methods can also have the property of “idempotence” in that (aside from error or expiration issues) the side-effects of N > 0 identical requests is the same as for a single request. The methods GET, HEAD, PUT and DELETE share this property.

It looks like people have complained about this to the vendor, because newer endpoints that mutate things use the POST method (or perhaps they ran into URI length limits in the GET query params…). Unfortunately, they kept the old API and still allow only GET for those. This means it’s pretty random and you have to really check the docs because your intuition is not going to be of any use here.

Also, error reporting is overrated

Not implementing REST correctly is somewhat excusable (even the “experts” can get it wrong), but what really made that same API a pain to work with is the fact that they don’t consistently implement error handling.

For example, it supports storing a route between several waypoints. When you save such a route, you will get a response containing XML like <result>123</result>. The 123 is an identifier you can use when doing other operations on the route.

Usually, when something goes wrong you get a 400 error status with an exception code and message in it (sometimes even revealing internal server details!). But in this particular route API, it will return <result>0</result>. This can mean anything from “required fields are missing” to “uniqueness constraint failed”. Unfortunately, we have a big issue with this API where it sometimes returns a zero result for exactly the same request we successfully managed to send before. If we re-send it, sometimes it will work. This makes it impossible to debug, of course.

When we asked support about this, they simply said “zero means an error”, as if that were the most normal thing in the world…. Getting proper error messages is going to take months according to the vendor, so we’re completely stuck with debugging this, as it will fail seemingly(!) randomly.

Don’t worry, we’ll keep track of everything for you

One API we work with uses OAuth 2. This is its own tire fire of an incomplete spec and inconsistent implementations. To get a good idea of how many issues there are, just check the issue queue requests-oauthlib, a popular OAuth implementation for Python. Other language implementations seem to have similar issues with tokens expiring seemingly without rhyme or reason.

That’s bad enough as it is, and we still need to figure out a good way of dealing with token expiry. But one thing that really grinds my gears is the API for downloading “new events”. It’s a financial/workflow package in which orders are entered. When a new order comes in, we have to process it and create a matching shop order to produce the items.

The API is defined as follows: You pass in an identifier of your own choosing, and you will receive from the server all the new orders since the last request that was made with that particular identifier. This allows for easy support of multiple servers; we have development, staging and production identifiers, which means we can test as much as we want without interfering with the production server.

The problem with this is: what happens when an import crashes or the connection is lost? Then you will lose those updates, and there’s no way of retrieving them again (apart from downloading them manually)! A better design would be to specifically request for the items you’ve seen to be marked as “seen”, or to tag each event with an incrementing sequence or timestamp so that you can easily record the most recent event you saw, and request more recent events.

More braindeadness

One fun little detail: We had quite some trouble with getting the OAuth implementation to work. When we asked support about this, they stated (multiple times) that our application/x-www-form-urlencoded POST request should not contain url-encoded values. Words fail me to explain how broken this would be. After a quick look at their reference libraries for this API, most of them seem use URL encoding, so it’s not even true.

This is another important lesson: Bad support can really push a bad API over the edge and make it a terrible one.

So, how does one design a good API?

Designing good APIs is a bit of an art, and we realise that it’s quite difficult to do a good job. One of the better books about building good RESTful APIs is Build APIs You Won’t Hate by Phil Sturgeon.

And don’t be afraid to stick with what you know: don’t implement a new API using a fancy new mechanism just because it’s the hip thing to do, or if you do, redesign the API from scratch. You can always keep the old endpoints for compatiblity, and phase it out later.

And, finally, write comprehensive documentation with good examples! It doesn’t matter how bad an API is, if the documentation is clear and complete, a developer will know up front what to expect, and it will hurt a lot less.

Let’s wrap up with some examples of good APIs which you can study. Of course, this is no wall of shame, so we can finally name some names :)


The Mollie payment API is both well-designed and extremely well-documented. It’s been years since I used it, but it left a lasting impression of how easy and well-documented it was.

Key points of the documentation are that there’s both a reference and a tutorial, the docs are split up in sections that make sense and have flow charts illustrating the basic design. A nice touch in the reference are the interactive examples for making requests in several languages. This includes cURL, which is very important if you’re interested in building your own client library or just debugging stuff at a low level.

With regards to the API itself: the most important part is that it is versioned, which can be important for compatibility. And, very importantly, there’s a changelog! The API is based on proper REST principles and supports two authentication methods: OAuth (which can be important for fine-grained access control) and API keys (which are hard to mess up when just getting started).

Finally, there’s a test mode to test how payments work without actually making money transfers. This uses the same account, so everything else is the same, which really helps when debugging things.

Amazon S3

The Amazon S3 API for storing “objects” is quite well-known and pretty popular. So popular in fact, that there are several third party “object store” providers which implement this API on top of their own backend. I’ve recently dealt with such a third-party implementation to implement an S3 backend for Ugarit, which is a fascinating backup system. In doing so, I had to update the CHICKEN S3 library a bit to make it work with the third-party provider I was using at the time, so I got to know the API a bit.

The first thing I noticed about the S3 API is that it is truly vast; it offers tons of bells and whistles. Most people won’t need to use those. Luckily you can ignore a lot of that complexity when you don’t need it. It won’t get in your way when you’re not using it; that’s good design!

I only don’t like much how authentication is handled. You have to sign your request, which requires you to craft a sort of “canonicalized” request. There are a lot of ways this can go wrong, especially because you to know the headers that will be sent. This may require some hackery to make sure this lines up with the headers that your HTTP client will (automatically) send.

The documentation is extensive, but it doesn’t seem very friendly and it feels very scattered, probably due to the sheer size of the API. One aspect of good API design is knowing the goals you’re trying to accomplish and setting limits on what you’re willing to support in the API. Not every API needs to support every conceivable thing; consistency, correctness and ease of use are more important.

The documentation is also a bit vague about the pitfalls of this API; later I learned that (in the Amazon implementation at least) the store is eventually consistent. This may mean in practice that after you store an object, you might not see it in a listing and retrieval might fail. You might also get an earlier version of the object. This has a massive impact on the design of any system that uses the API, so the docs could be a bit clearer about this. The introduction to S3 explains this, but the API reference does not mention it even once.

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