Improving my C++ time queue

Another code snippet that can be found in a few of my projects is the “time queue”, which is a simple ‘priority queue’ style data structure that I use to defer actions to a later time.

With this specific data structure, I have multiple implementations that clearly came from the same source. One indicator for that is a snarky comment in both about how std::list is clearly not the best choice for the underlying data structure. They have diverged a bit since then though.

Requirements

In my use case not use time points, but only durations in standard-library nomenclature. This is a pretty restrictive requirement, because otherwise any priority queue (e.g. from boost or even from the standard library) can be used quite well. On the other hand, it allows me to use floating-point durations with predictable accuracy. The queue has two important functions:

  1. insert to insert a timeout duration and a payload.
  2. tick is called with a specific duration and then reports the payloads that have timed out since their insertions.

Typically tick is called a lot more frequently than insert, and it should be fast. The payload is typically something like a std::function or an id for a state-machine that needs to be pulsed.

The basic idea is to only keep the duration difference to the previous item in the list. Only the first item keeps its total timeout. This way, when tick is called, usually only the first item needs to be updated. tick only has to touch more items when they time out.

Simple Implementation

One of the implementations for void insert(TimeType timeout, PayloadType payload) looks like this:

if (tick_active_)
{
  deferred_.push_back({ .remaining = after, .payload = std::move(payload) });
  return;
}

auto i = queue_.begin();
for (; i != queue_.end() && timeout > i->remaining; ++i)
  timeout -= i->remaining;

if (i != queue_.end())
  i->remaining -= timeout;

queue_.insert(i, { .remaining = after, .payload = std::move(payload) });

There is a special case there that guards against inserting into queue_ (which is still a very bad std::list) by instead inserting into deferred_ (which is a std::vector, phew). We will see why this is useful in the implementation for template void tick(TimeType delta, Executor execute):

tick_active_ = true;
auto i = queue_.begin();
for (; i != queue_.end() && delta >= i->remaining; ++i)
{
  delta -= i->remaining;
  execute(i->payload);
}

if (i != queue_.end())
  i->remaining -= delta;

queue_.erase(queue_.begin(), i);
tick_active_ = false;

while (!deferred_.empty())
{
  auto& entry = deferred_.back();
  insert(entry.remaining, std::move(entry.payload));
  deferred_.pop_back();
}

The timed out items are reported via a callback that is supplied as Executor execute. Of course, these can do anything, including inserting new items, which can invalidate the iterator. This is a common use case, in fact, as many deferred actions will naturally want follow ups (let’s ignore for the moment that the implementation is nowhere near exception safe…). The items that were deferred to deferred_ in insert get added to queue_ after the iteration is complete.

This worked well enough to ship, but the other implementation had another good idea. Instead of reporting the timed-out items to a callback, it just returned them in a vector. The whole tick_active_ guard becomes unnecessary, as any processing on the returned items is naturally deferred until after the iteration:

std::vector<PayloadType> tick(TimeType delta)
{
  std::vector<PayloadType> result;
  auto i = queue_.begin();
  for (; i != queue_.end() && delta >= i->remaining; ++i)
  {
    delta -= i->remaining;
    result.push_back(i->payload);
  }

  if (i != queue_.end())
    i->remaining -= delta;

  queue_.erase(queue_.begin(), i);
  return result;
}

This solves the insert-while-tick problem, and lets us use the result neatly in a range-based for-loop like this: for (auto const& payload : queue.tick(delta)) {}. Which I personally always find a little bit nicer than inversion-of-control. However, the cost is at least one extra allocation for timed-out items. This might be acceptable, but maybe we can do better for very little extra complexity.

Return of the second list

Edit: The previous version of this article tried to keep the timed-out items at the beginning of the vector before returning them as a std::span. As commenter Steffen pointed out, this again prevents us from inserting while iterating on the result, as any insert might invalidate the backing-vector.

We can get rid of the allocation for most of the tick calls, even if they return a non-empty list. Remember that a std::vector does not deallocate its capacity even when it’s cleared unless that is explicitly requested, e.g. via shrink_to_fit. So instead of returning a new vector each time, we’re keeping one around for the timed out items and return a const-ref to it from tick:

std::vector<PayloadType> const& tick(TimeType delta)
{
  timed_out_.clear();
  auto i = queue_.begin();
  for (; i != queue_.end() && delta >= i->remaining; ++i)
  {
    delta -= i->remaining;
    timed_out_.push_back(std::move(i->payload));
  }

  if (i != queue_.end())
    i->remaining -= delta;

  queue_.erase(queue_.begin(), i);
  return timed_out_;
}

This solution is pretty similar to the deferred list from the first version, but instead of ‘locking’ the main list while iterating, we’re now separating the items we’re iterating on.

Copying and moving rows between tables in PostgreSQL

In this article, I’ll show some helpful tips for copying and moving data between database tables in PostgreSQL.

Copying

The simplest operation is copying rows from one table to another table. The associated SQL query is known to most. You can simply combine an INSERT with a SELECT:

INSERT INTO short_books
  SELECT *
    FROM books
    WHERE pages < 50;

Of course, if you want to copy a complete table, you must first create the target table with the same columns. Instead of just repeating the original CREATE TABLE with all the column definitions with a different name, there is a shortcut in the form of CREATE TABLE … LIKE.

CREATE TABLE books_copy (LIKE books);

If you want the copy to inherit all constraints, indices and defaults of the source table you can add INCLUDING ALL:

CREATE TABLE books_copy (LIKE books INCLUDING ALL);

Instead of executing a CREATE TABLE first and then an INSERT, you can also directly combine CREATE TABLE with a SELECT:

CREATE TABLE books_copy AS
  SELECT * FROM books;

Moving

The direct method of moving specific rows from one table to another table is a bit less known. You can of course first copy the rows into the target table and then delete the rows from the source table. However, this is also possible with just one statement, in one go. To do this, you need to know the RETURNING clause. It can be appended to a DELETE or UPDATE statement and causes the affected rows to be returned as the result set after the respective action:

DELETE FROM books
  WHERE pages < 50
  RETURNING
    title, author, pages;

This can be used in combination with the WITH … AS clause to move rows between tables with just one SQL statement:

WITH selection AS (
  DELETE FROM books
  WHERE pages < 50
  RETURNING *
)
INSERT INTO short_books
  SELECT * FROM selection;

The function of WITH can be thought of as defining a named temporary view that can only be used in the current statement.

Web Security for Frontend and Backend

The web is everywhere and we use it for tons of important tasks like online banking, shopping and communication. So it becomes increasingly important to implement proper security. As attacks like cross-site scripting (XSS) or cross-site request forgery (CSRF) are wide-spread browsers, web standards designers and web application developers implement more and more mechanisms to make such attacks harder or even impossible. This puts a certain burden on both frontend and backend developers.

Since security is hard and should not be an afterthought I would like to give you some advice when implementing a web app using a Javascript-frontend and a backend service written in some of the common languages/frameworks like .NET, Micronaut, Javalin, Flask or the like.

Frontend advice

I prefer traditional cookie-based sessions to JWT-based approaches for interactive web frontends because of simplicity, browser support and the possibility to use it without Javascript. For service-to-service communication bearer tokens of some kind may be more appropriate. Your Javascript client has to include the credentials in the fetch() calls to cause the browser to send the cookie.

Unfortunately, incorrect use of cookies may be insecure, so be sure to check up-to-date advice on cookies; see some hints below in the backend part because cookies are configured and issued there.

Backend advice

Modern web security requires additional measures on the server side to ensure secure authentication and communication with web clients. You should use https whereever possible to gain at least transport security and avoid many cases of sniffing credentials or changing content between client and backend.

Improving security of cookies

First of all, cookies should be HttpOnly so that scripts cannot access the contents of a cookie. Furthermore you should ideally set the SameSite and Secure attributes appropriately and use https whenever possible. That way you have mitigated the most common attacks on your session handling and authentication.

Another bonus for cookies is that browsers can inform you about problems with your cookie setup:

Configuring Cross-Origin Resource Sharing (CORS)

Nowadays it is common for web app to be served from a different host than the backend API. This is a potential problem because attackers may sneak scripts into the browser of a user and use the existing session to access the resources in an illegal way. Therefore another means of improving security of web apps running in browsers was introduced with the access control using CORS.

For browsers to be able to prevent or allow requests to certain resources the backend has to provide appropriate Access-Control-headers, most notably Access-Control-Allow-Origin and Access-Control-Allow-Credentials. Make sure to set these values correctly or your frontend will have trouble to access your backend or you introduce a potential security whole.

Fortunately many web frameworks make it easy to configure CORS, see Micronaut documentation for example.

Conclusion

Security is always important and browser vendors keep implementing additional measures to mitigate problems in the current web environment. Make sure you keep up with the latest advice and measures and implement them in your applications.

Applying the Golden Circle to software development

When I was a young and impressionable software developer (1998), the slogan of the year was “the code is the documentation”. This essentially meant that comments, and (inline) code comments in particular, were a sign of bad code. The reasoning was (and still is) that if you can’t articulate your ideas clear enough in source code, adding additional text won’t rescue your communication. “Communication” is the conveying of what you want to accomplish with your code towards two listeners: the computer and the next human that works with your code. The computer is often the easier part, because it just does as it is told without interpretation.

Some years later (2004), Jeff Atwood, the author of the influential codinghorror blog, still condemns most of the comments we could find in contemporary source code. But there is more nuance than just “comments are bad” and it is cleared up later (2006) that there is a difference in what should be expressed in source code and what should be expressed in comments. Yes, you should write comments, but the “right kind”.

According to Jeff Atwood, the source code contains the “how”. It tells the story in all its details for the next human and the computer. The comments, on the other hand, are not intended for the computer and shouldn’t contain details. They should contain the “why”, the high-level picture and the motivation behind the specific “how” that we find.

The code tells you how, the comments tell you why” (2006) is a great way to describe the expected content of both “layers”.

But my feeling was (and still is) that something is missing in that description. My programs aren’t just code and comments, there are more things that I try to tell my story with. And just a few weeks ago, I had a sudden idea that I might be able to describe what that missing piece could be. It is just an idea and the puzzle probably is still missing pieces, but it feels “right” enough that I want to write this blog post to discuss the idea. But I need to talk about something else first.

In 2009, Simon Sinek presents the Golden Circle to the world. The TED talk is probably the most energetic piece of explanation in human history. The Golden Circle is “the world’s simplest idea”, defining three layers of “clarity” to actions:

  • What: The “lowest” level, meaning that every person knows “what they are doing”.
  • How: The “intermediate” level. Some people know “how they do it”. They explicitly choose their method of doing and can reason about it.
  • Why: The “highest” level. According to Simon Sinek, only a few people know “why they do it”. He talks about “purpose, cause and belief”.

If you don’t know about the Golden Circle yet, please watch the 20 minutes TED talk while I wait here for you. If you want to think about it first – I’m patient. The Golden Circle has inspired and guided me ever since. Not that I’m very good at applying it in my business or personal life, but it stayed with me and gave me a coordinate system to categorize things.

And with that categorization practice, I feel as if the layers in Jeff Atwood’s blog post from 2006 are misnamed and one crucial layer is missing:

  • What: The code tells you what (not how!). It is the detailed step-by-step recipe to replicate a behaviour. It is so simple that even a computer can do it, without being aware of it.
  • How: This is the missing layer. I want to talk about it in a minute.
  • Why: That’s the part that is correctly placed and named: The why of a story requires the spoken word. Only comments are viable for this kind of information. The computer (as of today) has no understanding what any of it means.

The missing layer is the “How”. In my idea, I envisioned that everything that is deliberately put in the code, but not readily understood by a computer, like structures, patterns, idioms or even names (I call them “activated comments”) are there for the “How”. We structure our code not because the computer requires it, the compiling stages of our programming languages even interfold and compact it until it is a binary blob. We don’t name our variables and types because the computer would learn something from them. The first thing a compiler does is to shorten our names to unreadable “symbols”. Most of our patterns get replaced by other, more minute patterns that the compiler puts into place. We put these things in our code because it helps us understand “how the story goes”. It provides us with guidance how to make sense of the mess. The structure tells you how to approach the program.

The computer only knows about “What”. There are maybe some indications about a simple “How”-awareness in some technologies, but most of the time, the computer is deaf to human communication.

Which brings me to my description of code and comment, as an updated version of Jeff Atwood’s motto:

“The code tells you what, the structure tell you how and the comments tell you why”

By “structure”, I mean everything that gets lost during translation for the computer, but is visible for the human reader. It entails high-level things like “architecture” or “code design” and lower-end decisions like names and formatting. If you have a better word for it, let me know!

I hope that this blog post inspired you to have a thought yourself. Don’t hesitate and tell us your thought in the comment below.

Lineendings in repository

Git normally leaves files and their lineendings untouched. However, it is often desired to have uniform line endings in a project. Git provides support for this.

Config Variable

What some may already know is the configuration variable core.autocrlf. With this, a developer can locally specify that his newly created files are checked in to Git with LF. By setting the variable to “true” the files will be converted to CRLF locally by Git on Windows and converted back when saved to the repository. If the variable is set to “input” the files are used locally with the same lineending as in Git without conversion.
The problem is, this normalization only affects new files and each developer must set it locally. If you set core.autocrlf to false, files can still be checked in with not normalized line endings.

Gitattributes File

Another possibility is the .gitattributes file. The big advantage is that the file is checked in similarly to the .gitignore file and the settings therefore apply to all developers. To do this, the .gitattributes file is created in the repository and a path pattern and the text attribute are defined in it. The setting affects how the files are stored locally for the git switch, git checkout and git merge commands and how the files are stored in the repository for git add and git commit.

*.jpg          -text

The text attribute can be unset, then neither check-in nor check-out will do any conversions

*              text=auto

The attribute can also be set to auto. In this case, the line endings will be converted to LF at check-in if Git recognizes the file contents as text. However, if the file is already CRLF in the repository, no conversion takes place and the files remain CRLF. In the example above, the settings are set for all file types.

*.txt         text
*.vcproj      text eol=crlf
*.sh          text eol=lf

If the attribute is set, the lineending are stored in the default repository with LF. But eol can also be used to force fixed line endings for specific file types.

*.ps1	      text working-tree-encoding=UTF-16

Furthermore, settings such as the encoding can be set via the gitattributes file by using working-tree-encoding attribute. Everything else can be read in the documentation of the gitattributes file.

We use this possibility more and more often in our projects. Partly only to set single file types like .sh files to LF or to normalize the whole project.

SQLite in ASP.NET 6.0: Access your database file via HTTP Endpoint

It is one of our fundamental principles to always choose the most-easy-while-capable tool for a job. For this, we try not to shower our customers with the newest, most hip technology available, but to use a technology stack we are

  • comfortable with
  • quick to provide the required minimum of customer value
  • keeping enough options open in order anything changes

One of the heavily affected aspects in that regard is the choice of data storage. There are a lot of different design paradigms one can choose from, but with the “most easy” aspect at hand, the question mostly resolves around the needs of the customer, not the wants (or “might be useful one day”) of the developer.

If your customer already has their PostgreSQL databases distributed in their Kubernetes as an example, it might be advisable to aim for that. If the customer does not have any integrated structure yet, I start with the question:

Is anything more necessary than a single-file database?

For one of our ASP.NET 6.0 applications, this was answered with the choice of Sqlite, due to it being native to the Microsoft universe including Entity Framework, which has many common use cases already answered, i.e. gives you way of caring about your application logic more than their database abstractions.

(It might be said that for .NET, an interesting project seems to have been LiteDB, which also operates on a single database file, but at the time of this writing, seems to have gone stale in development / support, and therefore fell out of my favour soon. Sad.).

Now we have a project in which we are closely in touch with the customer and their live system, very often had it been useful to access their platform and take a snapshot of the database for backup or assurance of our logic, and with the technical overhead in that specific case (which required several steps of sequentially granting remote access), I thought myself:

Why can’t I have a (sufficiently secured) HTTP endpoint that gives me this SQLite file as a File download?

The solution was a bit tricky because either the file was not read-accessible during that HTTP request (having been open already), the filestream was not possible because it was being closed too early, or the encoding of the resulting file would not fit. What finally worked was:

        private readonly static System.Text.Encoding enc1252 =
            CodePagesEncodingProvider.Instance.GetEncoding(1252);

        [HttpGet("database")]
        public ActionResult GetDatabase()
        {
            var dataSource = "sqlite.db";
            if (!System.IO.File.Exists(dataSource))
            {
                return NotFound(dataSource);
            }
            db.SaveChanges();
            // Note: CloseConnection() was not required!

            using var fs = new FileStream(dataSource, FileMode.Open, FileAccess.Read, FileShare.ReadWrite);
            var reader = new StreamReader(fs, enc1252);
            var data = reader.ReadToEnd();
            var ms = new MemoryStream(enc1252.GetBytes(data));
            return new FileStreamResult(ms, "application/octet-stream");
        }

Feel free to comment on that way because I found it more than none-trivial to arrive there, but maybe I missed something obvious. Some definite stumbling stones definitively were in

  • The Mime Type “application/octet-stream”, which for some reason would not work with the more adequately sounding choice “application/x-sqlite3” – I have no idea why.
  • The Encoding, which on our system was the Windows CodePages-1252 default, which needed to be specified not only in the interpretation of our bytes stream (second location), but also in the definition of the StreamReader itself (first location).
  • Please note that if your database is encoded via CP-1252, you also need the System.Text.Encoding.CodePages package (available via NuGet)
  • What looks like a missing “using”, is really intentional: If the StreamReader was opened with “using var reader = …”, it had the effect of being disposed before the request was handled correctly – I ran into an error of FileStreamResult: “Cannot access a closed Stream.” – keeping the StreamReader open solved that and the internet told me that this is still not a memory leak; the StreamReader reader gets disposed when the FileStream fs is disposed (see the using in front of that), but it still feels weird.

If you have any comments on that, I’d be very glad to learn from them, but if you don’t and you just have another use case for that problem – I’m happy to help!

Simple abstractions are good abstractions

I think that a lot of accidental complexity in software is produced by not picking the simplest abstraction for the job. Let me lead with an example: Consider this code from a code generator that generates C++ code:

std::ostringstream extra_properties;
if (!attribute.unit.empty())
{
  extra_properties << fmt::format("\n      properties.set_unit(\"{0}\");", attribute.unit);
}
if (!attribute.min_value.empty())
{
  extra_properties << fmt::format("\n      properties.set_min_value(\"{0}\");", attribute.min_value);
}
if (!attribute.max_value.empty())
{
  extra_properties << fmt::format("\n      properties.set_max_value(\"{0}\");", attribute.max_value);
}

It has a lot of ugly duplication: basically everything but the method names and values. So, how do we get rid of the duplication? Just a couple of years ago, I would probably have used a function for that:

void property_snippet(std::ostringstream& str, std::string const& method_name, std::string const& value)
{
  if (value.empty())
    return;
  str << fmt::format("\n      properties.{0}(\"{1}\");", method_name, value);
}

And then turn the call site code into:

property_snippet(extra_properties, "set_unit", attribute.unit);
property_snippet(extra_properties, "set_min_value", attribute.min_value);
property_snippet(extra_properties, "set_max_value", attribute.max_value);

Back then, I would have said that this is a definite improvement, but nowadays I am not so sure anymore. The call-site is a lot more concise, but we still have about half its code duplicated: the first half of each line. The additional function adds lots of complexity that is not necesarily offset by the gain at the call-site: the declaration with all the parameters. And the code gets separated, which is only really good if the function does a little bit more than this one.

This variant can, however, be made simpler with lambdas that capture extra_properties instead of passing it each time. While that is a better solution, I would argue that function objects and capturing are not necessarily simple either, so this only makes second place.

Nowdays, my first go-to abstraction is an in-place list and a loop:

std::tuple<char const*, std::string> methods_and_values[] = {
  {"set_unit", attribute.unit},
  {"set_min_value", attribute.min_value},
  {"set_max_value", attribute.max_value},
};

for (auto [method_name, value] : methods_and_values)
{
  if (value.empty())
    continue;
  extra_properties << fmt::format("\n      properties.{0}(\"{1}\");", method_name, value);
}

For me, this has the added benefit that is clearly separates the ‘inert’ data part of the code and the ‘active’ transformation. While this example is C++, this works in almost languages that I know of, even such arcane beasts as Xbase++.

PostgreSQL’s new MERGE command

PostgreSQL version 15 introduces a new SQL command: the MERGE command. This allows merging a table into another table. The MERGE command has existed for some time in other databases such as Oracle or SQL Server.

The principle of this command is that you have a target table in which you want to insert or remove data based on a source table under certain conditions, or you want to update existing entries with data from the source table. The source table doesn’t have to be a real table, it can just as easily be a SELECT query.

How to use it, step-by-step

The command begins with MERGE INTO, followed by the name of the target table. We call it dest here:

MERGE
  INTO dest ...

Then you specify the source table with USING, here we call it src:

MERGE
  INTO dest
  USING src
  ...

If you want to use a SELECT query as the source instead of a real table, you can do it like this:

MERGE
  INTO dest
  USING (SELECT ... FROM ...) AS src
  ...

Now you need a condition that is used to match entries from one table to entries from the other table. This is specified after ON. In this example we simply use the IDs of the two tables:

MERGE
  INTO dest
  USING src
  ON dest.id=src.id
  ...

This is followed by a case distinction that describes what should happen if the condition either applies or not. The possible actions can be: UPDATE, DELETE, INSERT, or DO NOTHING.

The two cases are specified with WHEN MATCHED THEN and WHEN NOT MATCHED THEN:

MERGE
  INTO dest
  USING src
  ON dest.id=src.id
  WHEN MATCHED THEN
    UPDATE SET ...
  WHEN NOT MATCHED THEN
    INSERT (...) VALUES (...);

If a match exists, then reasonable actions are UPDATE, DELETE, or DO NOTHING. If no match exists, then reasonable actions are INSERT or DO NOTHING.

In the WHEN cases, additional conditions can be specified with AND:

MERGE
  INTO dest
  USING src
  ON dest.id=src.id
  WHEN MATCHED AND dest.value > src.value THEN
    DELETE
  WHEN MATCHED THEN
    UPDATE SET ...
  WHEN NOT MATCHED THEN
    DO NOTHING;

A realistic example

Here’s an example demonstrating a use case that might occur in the real world:

MERGE
  INTO account a
  USING transaction t
  ON a.id=t.account_id
WHEN MATCHED THEN
  UPDATE SET balance = a.balance + t.amount
WHEN NOT MATCHED THEN
  INSERT (id, balance) VALUES (t.account_id, t.amount);

This statement processes a table of monetary transactions and applies them to their matching customer accounts by adding the amount of each transaction to the balance of the matching account. If no matching account exists it will be created and the initial balance is the amount of the first transaction.

Speeding up your HQL

Using an object-relational-mapper (ORM) to persist your entities, manage their state and query subsets for lists or reports is a wide-spread practice and may speed up your development.

If not used correctly, it may introduce unexpected performance problems because of unefficient default queries and the overhead this mapping introduces as most of the time table rows are converted to domain objects. Often this results in many queries and the n+1 query problem.

Nevertheless, the benefits of using an ORM may outweigh the problems and most problems can be mitigated by features and a correct usage of the tool.

Today I want to present a performance problem we had using GORM/Hibernate and how we easily fixed it without major code restructuring or workarounds.

The Problem

We used a HQL-query to load quite a lot of entities which took about 3 seconds. This was acceptable for our customer. If the user however tried to narrow down the results using a filter loading a smaller amount of the same entities took over 1 minute. Obviously, this was totally unacceptable and counter-intuitive.

The Analysis

Further analysis revealed, that a particular part of the WHERE-clause was responsible for the observed slowdown:

FROM Report r
WHERE r.project.proposal.id = p.id

So we did filter the root entity Report on an entity called Proposal but needed to load an associated Project entity for all reports to consider. So even if we are just using entity-ids to filter the innocently looking path r.project.proposal.id leads to loading and mapping of hundreds of Project entities.

The Solution

In our example we can fortunately do a lot better without big changes to our domain model, the application code or the query.

The relevant part of the schema looks like below:

In the above schema we can see, that both, a Report and a Proposal are associated with a certain project. Remember, that in Hibernate your entities contain only the id of their one-to-one mapped sub-entities by default. This means that if we change the filter clause to

WHERE r.project.id = p.project.id

we skip loading and mapping of all the Project entities and only load the needed reports and proposals. Since they both contain the project id we can use that in our filter. This resulted in more than a 10x speedup with such a simple and non-invasive change.

General Takeaway

ORMs can be a great tool but it is very easy to shoot yourself into the foot. With enough care you can achieve both simple code and good performance but you may run into non-obvious problems every now and then.

Help me with the Spiderman Operator

From time to time, I encounter a silly syntax in Java that I silently dubbed the “spiderman operator” because of all the syntactically pointing that’s going on. My problem is that it’s not very readable, I don’t know an alternative syntax for it and my programming style leads me more often to it than I am willing to ignore.

The spiderman operator looks like this:

x -> () -> x

In its raw form, it means that you have a function that takes x and returns a Supplier of x:

Function<X, Supplier<X>> rawForm = x -> () -> x;

That in itself is not very useful or mysterious, but if you take into account that the Supplier<X> is just one possible type you can return, because in Java, as long as the signature fits, the thing sits, it gets funnier.

A possible use case

Let’s define a type that is an interface with just one method:

public interface DomainValue {
    BigDecimal value();
}

In Java, the @FunctionalInterface annotation is not required to let the interface be, in fact, a functional interface. It only needs to have one method without implementation. How can we provide methods with implementation in Java interfaces. Default methods are the way:

@FunctionalInterface
public interface DomainValue {
    BigDecimal value();

    default String denotation() {
        return getClass().getSimpleName();
    }
}

Let’s say that we want to load domain values from a key-value-store with the following access method:

Optional<Double> loadEntry(String key)

If there is no entry with the given key or the syntax is not suitable to be interpreted as a double, the method returns Optional.emtpy(). Else it returns the double value wrapped in an Optional shell. We can convert it to our domain value like this:

Optional<DomainValue> myValue = 
    loadEntry("current")
        .map(BigDecimal::new)
        .map(x -> () -> x);

And there it is, the spiderman operator. We convert from Double to BigDecimal and then to DomainValue by saying that we want to convert our BigDecimal to “something that can supply a BigDecimal”, which is exactly what our DomainValue can do.

A bigger use case

Right now, the DomainValue type is nothing more than a mantle around a numerical value. But we can expand our domain to have more specific types:

public interface Voltage extends DomainValue {
}
public interface Power extends DomainValue {
    @Override
    default String denotation() {
        return "Electric power";
    }
}

Boring!

public interface Current extends DomainValue {
    default Power with(Voltage voltage) {
	return () -> value().multiply(voltage.value());
    }
}

Ok, this is maybe no longer boring. We can implement a lot of domain functionality just in interfaces and then instantiate ad-hoc types:

Voltage europeanVoltage = () -> BigDecimal.valueOf(220);
Current powerSupply = () -> BigDecimal.valueOf(2);
Power usage = powerSupply.with(europeanVoltage);

Or we load the values from our key-value-store:

Optional<Voltage> maybeVoltage = 
    loadEntry("voltage")
        .map(BigDecimal::new)
        .map(x -> () -> x);

Optional<Current> maybeCurrent = 
    loadEntry("current")
        .map(BigDecimal::new)
        .map(x -> () -> x);

You probably see it already: We have some duplicated code! The strange thing is, it won’t go away so easily.

The first call for help

But first I want to sanitize the code syntactically. The duplication is bad, but the spiderman operator is just unreadable.

If you have an idea how the syntax of the second map() call can be improved, please comment below! Just one request: Make sure your idea compiles beforehands.

Failing to eliminate the duplication

There is nothing easier than eliminating the duplication above: The code is syntactically identical and only the string parameter is different – well, and the return type. We will see how this affects us.

What we cannot do:

<DV extends DomainValue> Optional<DV> loadFor(String entry) {
    Optional<BigDecimal> maybeValue = load(entry);
    return maybeValue.map(x -> () -> x);
}

Suddenly, the spiderman operator does not compile with the error message:

The target type of this expression must be a functional interface

I can see the problem: Subtypes of DomainValue are not required to stay compatible to the functional interface requirement (just one method without implementation).

Interestingly, if we work with a wildcard for the generic, it compiles:

Optional<? extends DomainValue> loadFor(String entry) {
    Optional<BigDecimal> maybeValue = load(entry);
    return maybeValue.map(x -> () -> x);
}

The problem is that we still need to downcast to our specific subtype afterwards. But we can use this insight and move the downcast into the method:

<DV extends DomainValue> Optional<DV> loadFor(
	String entry,
	Class<DV> type
) {
	Optional<BigDecimal> maybeValue = load(entry);
	return maybeValue.map(x -> type.cast(x));
}

Which makes our code readable enough, but at the price of using reflection:

Optional<Voltage> european = loadFor("voltage", Voltage.class);
Optional<Current> powerSupply = loadFor("current", Current.class);

I’m not a fan of this solution, because downcasts are dangerous and reflection is dangerous, too. Mixing two dangerous things doesn’t neutralize the danger most of the time. This code will fail during runtime sooner or later, without any compiler warning us about it. If you don’t believe me, add a second method without implementation to the Current interface and see if the compiler warns you. Hint: This is what you will see at runtime:

java.lang.ClassCastException: Cannot cast java.math.BigDecimal to Current

But, to our surprise, it doesn’t even need a second method. The code above doesn’t work. Even if we reintroduce our spiderman operator (with an additional assignment to help the type inference), the cast won’t work:

<DV extends DomainValue> Optional<DV> loadFor(
    String entry,
    Class<DV> type
) {
    Optional<BigDecimal> maybeValue = load(entry);
    Optional<DomainValue> maybeDomainValue = maybeValue.map(x -> () -> x);
    return maybeDomainValue.map(x -> type.cast(x));
}

The ClassCastException just got a lot more mysterious:

java.lang.ClassCastException: Cannot cast Loader$$Lambda$8/0x00000008000028c0 to Current

My problem is that I am stuck. There is working code that uses the spiderman operator and produces code duplication, but there is no way around the duplication that I can think of. I can get objects for the supertype (DomainValue), but not for a specific subtype of it. If I want that, I have to accept duplication. Or am I missing something?

The second call for help

If you can think about a way to eliminate the duplication, please tell me (or us) in the comments. This problem doesn’t need to be solved for my peace of mind or the sanity of my code – the duplication is confined to a particular place.

Being used to roam nearly without boundaries in the Java syntax (25 years of thinking in Java will do that to you), this particular limitation hit hard. If you can give me some ideas, I would be grateful.