Lifetimes are a fascinating feature of Rust and the human experience. This is a technical blog, so let’s focus on the former. I was admittedly a slow adopter for leveraging lifetimes to safely borrow data in Rust. In the treewalk implementation of Memphis, my Python interpreter written in Rust, I hardly leverage lifetimes (by cloning incessantly) and I repeatedly elude the borrow checker (by using interior mutability, also incessantly) whenever possible.
My fellow Rustaceans, I am here to today to tell you this ends now. Read my lips……no more shortcuts.
Okay okay, let’s be real. What is a shortcut versus what’s the right way is a matter of priorities and perspective. We’ve all made mistakes, and I’m here to take accountability for mine.
I began writing an interpreter six weeks after I first installed rustc because I have no chill. With that haranguing and posturing out of the way, let’s begin today’s lecture on how we can use lifetimes as our lifeline to improve my bloated interpreter codebase.
Identifying and avoiding cloned data
A Rust lifetime is a mechanism which provides a compile-time guarantee that any references do not outlive the objects to which they refer. They allow us to avoid the “dangling pointer” problem from C and C++.
This is assuming you leverage them at all! Cloning is a convenient workaround when you want to avoid the complexities associated with managing lifetimes, though the downside is increased memory usage and a slight delay related to each time data is copied.
Using lifetimes also forces you to think more idiomatically about owners and borrowing in Rust, which I was eager to do.
I chose my first candidate as the tokens from a Python input file. My original implementation, which relied heavily on ChatGPT guidance while I was sitting on Amtrak, used this flow:
- we pass our Python text to a Builder
- the Builder creates a Lexer, which tokenizes the input stream
- the Builder then creates a Parser, which clones the token stream to hold its own copy
- the Builder is used to create an Interpreter, which repeatedly asks the Parser for its next parsed statement and evaluates it until we reach the end of the token stream
The convenient aspect of cloning the token stream is that the Lexer was free to be dropped after step 3. By updating my architecture to have the Lexer own the tokens and the Parser just borrow them, the Lexer would now be required to stay alive much longer. Rust lifetimes would guarantee this for us: as long as the Parser existed holding a reference to a borrowed token, the compiler would guarantee that the Lexer which own those tokens still existed, ensuring a valid reference.
Like all code always, this ended up being a bigger change than I expected. Let’s see why!
The new parser
Before updating the Parser to borrow the tokens from the Lexer, it looked like this. The two fields of interest for today’s discussion are tokens and current_token. We have no idea how large the Vec<Token> is, but it is distinctly ours (i.e. we are not borrowing it).
After borrowing the tokens from the Lexer, it looks fairly similar, but now we see a LIFETIME! By connecting tokens to the lifetime 'a, the Rust compiler will not allow the owner of the tokens (which is our Lexer) and the tokens themselves to be dropped while our Parser still references them. This feels safe and fancy!
Another small difference you may notice is this line:
This is a small optimization that I began considering once my Parser was moving in the direction of “memory-efficient.” Rather than instantiating a new Token::Eof each time the Parser needs to check if it is at the end of the text stream, the new model allowed me to instantiate only a single token and reference &EOF repeatedly.
Again, this is a small optimization, but it speaks to the larger mindset of each piece of data existing only once in memory and every consumer just referencing it when needed, which Rust both encourages you to do and snugly holds your hand along the way.
Speaking of optimization, I really should have benchmarked the memory usage before and after. Since I did not, I have nothing more to say on the matter.
As I alluded to earlier, tying the lifetime of my Lexer and Parser together a large impact on my Builder pattern. Let’s see what that looks like!
The new Builder: MemphisContext
In the flow I described above, remember how I mentioned that the Lexer could be dropped as soon as the Parser created its own copy of the tokens? This had unintentionally influenced the design of my Builder, which was intended to be the component which supports orchestrating Lexer, Parser, and Interpreter interactions, whether you begin with a Python text stream or a path to a Python file.
As you can see below, there are a few other non-ideal aspects to this design:
- needing to call a dangerous
downcast method to get the Interpreter.
- why did I think it was okay to return a
Parser to every unit test just to then pass it right back into interpreter.run(&mut parser)?!
Below is the new MemphisContext interface. This mechanism manages the Lexer lifetime internally (to keep our references alive long enough to keep our Parser happy!) and only exposes what is needed to run this test.
context.run_and_return_interpreter() is still a bit clunky and speaks to another design problem I may tackle down the road: when you run the interpreter, do you want to return only the final return value or something which lets you access arbitrary values from the symbol table? This method opts for the latter approach. I actually think there’s a case to do both, and will keep tweaking my API to allow for this as we go.
Incidentally, this change improved my ability to evaluate an arbitrary piece of Python code. If you’ll recall from my WebAssembly saga, I had to rely on my crosscheck TreewalkAdapter to do that at the time. Now, our Wasm interface is much cleaner.
The interface context.evaluate_oneshot() returns the expression result rather than a full symbol table. I wonder if there’s a better way to ensure any of the “oneshot” methods can only operate on a context once, ensuring that no consumers use them in a stateful context. I’ll keep simmering on that!
Want to build your own HTTP server from scratch in Rust?
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Was this worth it?
Memphis is first-and-foremost a learning exercise, so this was absolutely worth it!
In addition to sharing the tokens between the Lexer and the Parser, I created an interface to evaluate Python code with significantly less boilerplate. While sharing data introduced additional complexity, these changes bring clear benefits: reduced memory usage, improved safety guarantees through stricter lifetime management, and a streamlined API that’s easier to maintain and extend.
I’m choosing to believe this was the right approach, mostly to maintain my self-esteem. Ultimately, I aim to write code that clearly reflects the principles of software and computer engineering. We can now open the Memphis source, point to the single owner of the tokens, and sleep soundly at night!
