The Compiler Frontend: Parsing and Type Checking - The Runtime System - Real World OCaml (2013)

Real World OCaml (2013)

Part III. The Runtime System

Chapter 22. The Compiler Frontend: Parsing and Type Checking

Compiling source code into executable programs is a fairly complex libraries, linkers, and assemblers. It’s important to understand how these fit together to help with your day-to-day workflow of developing, debugging, and deploying applications.

OCaml has a strong emphasis on static type safety and rejects source code that doesn’t meet its requirements as early as possible. The compiler does this by running the source code through a series of checks and transformations. Each stage performs its job (e.g., type checking, optimization, or code generation) and discards some information from the previous stage. The final native code output is low-level assembly code that doesn’t know anything about the OCaml modules or objects that the compiler started with.

You don’t have to do all of this manually, of course. The compiler frontends (ocamlc and ocamlopt) are invoked via the command line and chain the stages together for you. Sometimes though, you’ll need to dive into the toolchain to hunt down a bug or investigate a performance problem. This chapter explains the compiler pipeline in more depth so you understand how to harness the command-line tools effectively.

In this chapter, we’ll cover the following topics:

§ The compilation pipeline and what each stage represents

§ Source preprocessing via Camlp4 and the intermediate forms

§ The type-checking process, including module resolution

The details of the compilation process into executable code can be found next, in Chapter 23.

An Overview of the Toolchain

The OCaml tools accept textual source code as input, using the filename extensions .ml and .mli for modules and signatures, respectively. We explained the basics of the build process in Chapter 4, so we’ll assume you’ve built a few OCaml programs already by this point.

Each source file represents a compilation unit that is built separately. The compiler generates intermediate files with different filename extensions to use as it advances through the compilation stages. The linker takes a collection of compiled units and produces a standalone executable or library archive that can be reused by other applications.

The overall compilation pipeline looks like this:

Diagram

image with no caption

Notice that the pipeline branches toward the end. OCaml has multiple compiler backends that reuse the early stages of compilation but produce very different final outputs. The bytecode can be run by a portable interpreter and can even be transformed into JavaScript (via js_of_ocaml) or C source code (via OCamlCC). The native code compiler generates specialized executable binaries suitable for high-performance applications.

OBTAINING THE COMPILER SOURCE CODE

Although it’s not necessary to understand the examples, you may find it useful to have a copy of the OCaml source tree checked out while you read through this chapter. The source code is available from multiple places:

§ Stable releases as zip and tar archives from the OCaml download site

§ A Subversion anonymous mirror of the main development sources available on the development resources page online

§ A Git mirror of the Subversion repository with all the history and development branches included, browsable online at GitHub

The source tree is split up into subdirectories. The core compiler consists of:

config/

Configuration directives to tailor OCaml for your operating system and architecture.

bytecomp/ and byterun/

Bytecode compiler and runtime, including the garbage collector (GC).

asmcomp/ and asmrun/

Native-code compiler and runtime. The native runtime symlinks many modules from the byterun directory to share code, most notably the GC.

parsing/

The OCaml lexer, parser, and libraries for manipulating them.

typing/

The static type checking implementation and type definitions.

camlp4/

The source code macro preprocessor.

driver/

Command-line interfaces for the compiler tools.

A number of tools and scripts are also built alongside the core compiler:

debugger/

The interactive bytecode debugger.

toplevel/

Interactive top-level console.

emacs/

: A caml-mode for the Emacs editor.

stdlib/

The compiler standard library, including the Pervasives module.

ocamlbuild/

Build system that automates common OCaml compilation modes.

otherlibs/

Optional libraries such as the Unix and graphics modules.

tools/

Command-line utilities such as ocamldep that are installed with the compiler.

testsuite/

Regression tests for the core compiler.

We’ll go through each of the compilation stages now and explain how they will be useful to you during day-to-day OCaml development.

Parsing Source Code

When a source file is passed to the OCaml compiler, its first task is to parse the text into a more structured abstract syntax tree (AST). The parsing logic is implemented in OCaml itself using the techniques described earlier in Chapter 16. The lexer and parser rules can be found in the parsingdirectory in the source distribution.

Syntax Errors

The OCaml parser’s goal is to output a well-formed AST data structure to the next phase of compilation, and so it any source code that doesn’t match basic syntactic requirements. The compiler emits a syntax error in this situation, with a pointer to the filename and line and character number that’s as close to the error as possible.

Here’s an example syntax error that we obtain by performing a module assignment as a statement instead of as a let binding:

OCaml

let () =

moduleMyString = String;

()

The code results in a syntax error when compiled:

Terminal

$ ocamlc -c broken_module.ml

File "broken_module.ml", line 2, characters 2-8:

Error: Syntax error

The correct version of this source code creates the MyString module correctly via a local open, and compiles successfully:

OCaml

let () =

letmoduleMyString = Stringin

()

The syntax error points to the line and character number of the first token that couldn’t be parsed. In the broken example, the module keyword isn’t a valid token at that point in parsing, so the error location information is correct.

Automatically Indenting Source Code

Sadly, syntax errors do get more inaccurate sometimes, depending on the nature of your mistake. Try to spot the deliberate error in the following function definitions:

OCaml

let concat_and_print x y =

let v = x ^ y in

print_endline v;

v;

let add_and_print x y =

let v = x + y in

print_endline (string_of_int v);

v

let () =

let _x = add_and_print 1 2 in

let _y = concat_and_print "a" "b" in

()

When you compile this file, you’ll get a syntax error again:

Terminal

$ ocamlc -c follow_on_function.ml

File "follow_on_function.ml", line 11, characters 0-3:

Error: Syntax error

The line number in the error points to the end of the add_and_print function, but the actual error is at the end of the first function definition. There’s an extra semicolon at the end of the first definition that causes the second definition to become part of the first let binding. This eventually results in a parsing error at the very end of the second function.

This class of bug (due to a single errant character) can be hard to spot in a large body of code. Luckily, there’s a great tool available via OPAM called ocp-indent that applies structured indenting rules to your source code on a line-by-line basis. This not only beautifies your code layout, but it also makes this syntax error much easier to locate.

Let’s run our erroneous file through ocp-indent and see how it processes it:

Terminal

$ ocp-indent follow_on_function.ml

let concat_and_print x y =

let v = x ^ y in

print_endline v;

v;

let add_and_print x y =

let v = x + y in

print_endline (string_of_int v);

v

let () =

let _x = add_and_print 1 2 in

let _y = concat_and_print "a" "b" in

()

The add_and_print definition has been indented as if it were part of the first concat_and_print definition, and the errant semicolon is now much easier to spot. We just need to remove that semicolon and rerun ocp-indent to verify that the syntax is correct:

Terminal

$ ocp-indent follow_on_function_fixed.ml

let concat_and_print x y =

let v = x ^ y in

print_endline v;

v

let add_and_print x y =

let v = x + y in

print_endline (string_of_int v);

v

let () =

let _x = add_and_print 1 2 in

let _y = concat_and_print "a" "b" in

()

The ocp-indent home page documents how to integrate it with your favorite editor. All the Core libraries are formatted using it to ensure consistency, and it’s a good idea to do this before publishing your own source code online.

Generating Documentation from Interfaces

Whitespace and source code comments are removed during parsing and aren’t significant in determining the semantics of the program. However, other tools in the OCaml distribution can interpret comments for their own ends.

The ocamldoc tool uses specially formatted comments in the source code to generate documentation bundles. These comments are combined with the function definitions and signatures, and output as structured documentation in a variety of formats. It can generate HTML pages, LaTeX and PDF documents, UNIX manual pages, and even module dependency graphs that can be viewed using Graphviz.

Here’s a sample of some source code that’s been annotated with ocamldoc comments:

OCaml

(** example.ml: The first special comment of the file is the comment

associated with the whole module. *)

(** Comment for exception My_exception. *)

exceptionMy_exceptionof (int -> int) * int

(** Comment for type [weather] *)

type weather =

| Rainofint (** The comment for construtor Rain *)

| Sun (** The comment for constructor Sun *)

(** Find the current weather for a country

@author Anil Madhavapeddy

@param location The country to get the weather for.

*)

let what_is_the_weather_in location =

match location with

| `Cambridge -> Rain 100

| `New_york -> Rain 20

| `California -> Sun

The ocamldoc comments are distinguished by beginning with the double asterisk. There are formatting conventions for the contents of the comment to mark metadata. For instance, the @tag fields mark specific properties such as the author of that section of code.

Try compiling the HTML documentation and UNIX man pages by running ocamldoc over the source file:

Terminal

$ mkdir -p html man/man3

$ ocamldoc -html -d html doc.ml

$ ocamldoc -man -d man/man3 doc.ml

$ man -M man Doc

You should now have HTML files inside the html/ directory and also be able to view the UNIX manual pages held in man/man3. There are quite a few comment formats and options to control the output for the various backends. Refer to the OCaml manual for the complete list.

USING CUSTOM OCAMLDOC GENERATORS

The default HTML output stylesheets from ocamldoc are pretty spartan and distinctly Web 1.0. The tool supports plugging in custom documentation generators, and there are several available that provide prettier or more detailed output:

§ Argot is an enhanced HTML generator that supports code folding and searching by name or type definition.

§ ocamldoc generators add support for Bibtex references within comments and generating literate documentation that embeds the code alongside the comments.

§ JSON output is available via a custom generator in Xen.

Preprocessing Source Code

One powerful feature in OCaml is a facility to extend the standard-language grammar without having to modify the compiler. You can roughly think of it as a type-safe version of the cpp preprocessor used in C/C++ to control conditional compilation directives.

The OCaml distribution includes a system called Camlp4 for writing extensible parsers. This provides some OCaml libraries that are used to define grammars, as well as dynamically loadable syntax extensions of such grammars. Camlp4 modules register new language keywords and later transform these keywords (or indeed, any portion of the input program) into conventional OCaml code that can be understood by the rest of the compiler.

We’ve already seen several Core libraries that use Camlp4:

Fieldslib

Generates first-class values that represent fields of a record

Sexplib

To convert types to textual s-expressions

Bin_prot

For efficient binary conversion and parsing

These libraries all extend the language in quite a minimal way by adding a with keyword to type declarations to signify that extra code should be generated from that declaration. For example, here’s a trivial use of Sexplib and Fieldslib:

OCaml

openSexplib.Std

type t = {

foo: int;

bar: string

} with sexp, fields

Compiling this code will normally give you a syntax error if you do so without Camlp4, since the with keyword isn’t normally allowed after a type definition:

Terminal

$ ocamlfind ocamlc -c type_conv_example.ml

File "type_conv_example.ml", line 6, characters 2-6:

Error: Syntax error

Now add in the syntax extension packages for Fieldslib and Sexplib, and everything will compile again:

Terminal

$ ocamlfind ocamlc -c -syntax camlp4o -package sexplib.syntax \

-package fieldslib.syntax type_conv_example.ml

We’ve specified a couple of additional flags here. The -syntax flag directs ocamlfind to add the -pp flag to the compiler command line. This flag instructs the compiler to run the preprocessor during its parsing phase.

The -package flag imports other OCaml libraries. The .syntax suffix in the package name is a convention that indicates these libraries are preprocessors that should be run during parsing. The syntax extension modules are dynamically loaded into the camlp4o command, which rewrites the input source code into conventional OCaml code that has no trace of the new keywords. The compiler then compiles this transformed code with no knowledge of the preprocessor’s actions.

Both Fieldslib and Sexplib need this new with keyword, but they both can’t register the same extension. Instead, a library called Type_conv provides the common extension framework for them to use. Type_conv registers the with grammar extension to Camlp4, and the OCamlfind packaging ensures that it’s loaded before Fieldslib or Sexplib.

The two extensions generate boilerplate OCaml code based on the type definition at compilation time. This avoids the performance hit of doing the code generation dynamically and also doesn’t require a just-in-time (JIT) runtime that can be a source of unpredictable dynamic behavior. Instead, all the extra code is simply generated at compilation time via Camlp4, and type information can be discarded from the runtime image.

The syntax extensions accept an input AST and output a modified one. If you’re not familiar with the Camlp4 module in question, how do you figure out what changes it’s made to your code? The obvious way is to read the documentation that accompanies the extension. Another approach is to use the toplevel to explore the extension’s behavior or run Camlp4 manually yourself to see the transformation in action. We’ll show you how to do both of these now.

Using Camlp4 Interactively

The utop toplevel can run the phrases that you type through camlp4 automatically. You should have at least these lines in your ~/.ocamlinit file in your home directory (see this Real World OCaml page for more information):

OCaml utop

# #use"topfind" ;;

- : unit = ()

Findlib has been successfully loaded. Additional directives:

#require "package";; to load a package

#list;; to list the available packages

#camlp4o;; to load camlp4 (standard syntax)

#camlp4r;; to load camlp4 (revised syntax)

#predicates "p,q,...";; to set these predicates

Topfind.reset();; to force that packages will be reloaded

#thread;; to enable threads

- : unit = ()

# #camlp4o ;;

The first directive loads the ocamlfind top-level interface that lets you require ocamlfind packages (including all their dependent packages). The second directive instructs the toplevel to filter all phrases via Camlp4. You can now run utop and load the syntax extensions in. We’ll use thecomparelib syntax extension for our experiments.

OCaml provides a built-in polymorphic comparison operator that inspects the runtime representation of two values to see if they’re equal. As we noted in Chapter 13, the polymorphic comparison is less efficient than defining explicit comparison functions between values. However, it quickly becomes tedious to manually define comparison functions for complex type definitions.

Let’s see how comparelib solves this problem by running it in utop:

OCaml utop (part 1)

# #require"comparelib.syntax" ;;

# typet = { foo: string; bar : t } ;;

type t = { foo : string; bar : t; }

# typet = { foo: string; bar: t } withcompare ;;

type t = { foo : string; bar : t; }

val compare : t -> t -> int = <fun>

val compare_t : t -> t -> int = <fun>

The first definition of t is a standard OCaml phrase and results in the expected output. The second one includes the with compare directive. This is intercepted by comparelib and transformed into the original type definition with two new functions also included.

Running Camlp4 from the Command Line

The toplevel is a quick way to examine the signatures generated from the extensions, but how can we see what these new functions actually do? We can’t do this from utop directly, since it embeds the Camlp4 invocation as an automated part of its operation.

Let’s turn to the command line to obtain the result of the comparelib transformation instead. Create a file that contains the type declaration from earlier:

OCaml

type t = {

foo: string;

bar: t

} with compare

We need to run the Camlp4 binary with the library paths to Comparelib and Type_conv. Let’s use a small shell script to wrap this invocation:

Shell script

#!/bin/sh

OCAMLFIND="ocamlfind query -predicates syntax,preprocessor -r"

INCLUDE=`$OCAMLFIND -i-format comparelib.syntax`

ARCHIVES=`$OCAMLFIND -a-format comparelib.syntax`

camlp4o -printer o $INCLUDE $ARCHIVES $1

The script uses the ocamlfind package manager to list the include and library paths needed by comparelib. It then invokes the camlp4o preprocessor with these paths and outputs the resulting AST to the standard output:

Terminal

$ sh camlp4_dump.cmd comparelib_test.ml

type t = { foo : string; bar : t }

let _ = fun (_ : t) -> ()

let rec compare : t -> t -> int =

fun a__001_ b__002_ ->

if Pervasives.( == ) a__001_ b__002_

then 0

else

(let ret =

(Pervasives.compare : string -> string -> int) a__001_.foo

b__002_.foo

in

if Pervasives.( <> ) ret 0

then ret

else compare a__001_.bar b__002_.bar)

let _ = compare

let compare_t = compare

let _ = compare_t

The output contains the original type definition accompanied by some automatically generated code that implements an explicit comparison function for each field in the record. If you’re using the extension in your compiler command line, this generated code is then compiled as if you had typed it in yourself.

Note that although the generated code uses Pervasives.compare, it is also annotated with a string type. This lets the compiler use a specialized string comparison function and not actually call the runtime polymorphic comparison function. This has implications for correctness, too: recall from Chapter 13 that comparelib provides reliable comparison functions that work for values that are logically the same but that have differing internal representations (e.g., Int.Set.t).

A STYLE NOTE: WILDCARDS IN LET BINDINGS

You may have noticed the let _ = fun construct in the autogenerated code above. The underscore in a let binding is just the same as a wildcard underscore in a pattern match, and tells the compiler to accept any return value and discard it immediately.

This is fine for mechanically generated code from Type_conv but should be avoided in code that you write by hand. If it’s a unit-returning expression, then write a unit binding explicitly instead. This will cause a type error if the expression changes type in the future (e.g., due to code refactoring):

Syntax

let () = <expr>

If the expression has a different type, then write it explicitly:

OCaml

let (_:some_type) = <expr>

let () = ignore (<expr> : some_type)

)(* if the expression returns a unit Deferred.t *)

let () = don't_wait_for (<expr>

The last one is used to ignore Async expressions that should run in the background rather than blocking in the current thread.

One other important reason for using wildcard matches is to bind a variable name to something that you want to use in future code but don’t want to use right away. This would normally generate an “unused value” compiler warning. These warnings are suppressed for any variable name that’s prepended with an underscore:

OCaml

let fn x y =

let _z = x + y in

()

Although you don’t use _z in your code, this will never generate an unused variable warning.

Preprocessing Module Signatures

Another useful feature of type_conv is that it can generate module signatures, too. Copy the earlier type definition into a comparelib_test.mli that’s got exactly the same content:

OCaml

type t = {

foo: string;

bar: t

} with compare

If you rerun the Camlp4 dumper script now, you’ll see that different code is produced for signature files:

Terminal

$ sh camlp4_dump.cmd comparelib_test.mli

type t = { foo : string; bar : t }

val compare : t -> t -> int

The external signature generated by comparelib is much simpler than the actual code. Running Camlp4 directly on the original source code lets you see these all these transformations precisely.

DON’T OVERDO THE SYNTAX EXTENSIONS

Syntax extensions are a powerful extension mechanism that can completely alter your source code’s layout and style. Core includes a very conservative set of extensions that take care to minimize the syntax changes. There are a number of third-party libraries that are much more ambitious — some introduce whitespace-sensitive indentation, while others build entirely new embedded languages using OCaml as a host language, and yet others introduce conditional compilation for macros or optional logging.

While it’s tempting to compress all your boilerplate code into Camlp4 extensions, it can make your source code much harder for other people to quickly read and understand. Core mainly focuses on type-driven code generation using the type_conv extension and doesn’t fundamentally change the OCaml syntax.

Another thing to consider before deploying your own syntax extension is compatibility with other extensions. Two separate extensions can create a grammar clash that leads to odd syntax errors and hard-to-reproduce bugs. That’s why most of Core’s syntax extensions go through type_conv, which acts as a single point for extending the grammar via the with keyword.

Further Reading on Camlp4

We’ve deliberately only shown you how to use Camlp4 extensions here, and not how to build your own. The full details of building new extensions are fairly daunting and could be the subject of an entirely new book.

The best resources to get started are:

§ A series of blog posts by Jake Donham describe the internals of Camlp4 and its syntax extension mechanism

§ The online Camlp4 wiki

§ Using OPAM to install existing Camlp4 extensions and inspecting their source code

Static Type Checking

After obtaining a valid abstract syntax tree, the compiler has to verify that the code obeys the rules of the OCaml type system. Code that is syntactically correct but misuses values is rejected with an explanation of the problem.

Although type checking is done in a single pass in OCaml, it actually consists of three distinct steps that happen simultaneously:

automatic type inference

An algorithm that calculates types for a module without requiring manual type annotations

module system

Combines software components with explicit knowledge of their type signatures

explicit subtyping

Checks for objects and polymorphic variants

Automatic type inference lets you write succinct code for a particular task and have the compiler ensure that your use of variables is locally consistent.

Type inference doesn’t scale to very large codebases that depend on separate compilation of files. A small change in one module may ripple through thousands of other files and libraries and require all of them to be recompiled. The module system solves this by providing the facility to combine and manipulate explicit type signatures for modules within a large project, and also to reuse them via functors and first-class modules.

Subtyping in OCaml objects is always an explicit operation (via the :> operator). This means that it doesn’t complicate the core type inference engine and can be tested as a separate concern.

Displaying Inferred Types from the Compiler

We’ve already seen how you can explore type inference directly from the toplevel. It’s also possible to generate type signatures for an entire file by asking the compiler to do the work for you. Create a file with a single type definition and value:

OCaml

type t = Foo | Bar

let v = Foo

Now run the compiler with the -i flag to infer the type signature for that file. This runs the type checker but doesn’t compile the code any further after displaying the interface to the standard output:

Terminal

$ ocamlc -i typedef.ml

type t = Foo | Bar

val v : t

The output is the default signature for the module that represents the input file. It’s often useful to redirect this output to an mli file to give you a starting signature to edit the external interface without having to type it all in by hand.

The compiler stores a compiled version of the interface as a cmi file. This interface is either obtained from compiling an mli signature file for a module, or by the inferred type if there is only an ml implementation present.

The compiler makes sure that your ml and mli files have compatible signatures. The type checker throws an immediate error if this isn’t the case:

Terminal

$ echo type t = Foo > test.ml

$ echo type t = Bar > test.mli

$ ocamlc -c test.mli test.ml

File "test.ml", line 1:

Error: The implementation test.ml does not match the interface test.cmi:

Type declarations do not match:

type t = Foo

is not included in

type t = Bar

File "test.ml", line 1, characters 5-12: Actual declaration

Fields number 1 have different names, Foo and Bar.

WHICH COMES FIRST: THE ML OR THE MLI?

There are two schools of thought on which order OCaml code should be written in. It’s very easy to begin writing code by starting with an ml file and using the type inference to guide you as you build up your functions. The mli file can then be generated as described, and the exported functions documented.

If you’re writing code that spans multiple files, it’s sometimes easier to start by writing all the mli signatures and checking that they type-check against one another. Once the signatures are in place, you can write the implementations with the confidence that they’ll all glue together correctly, with no cyclic dependencies among the modules.

As with any such stylistic debate, you should experiment with which system works best for you. Everyone agrees on one thing though: no matter in what order you write them, production code should always explicitly define an mli file for every ml file in the project. It’s also perfectly fine to have an mli file without a corresponding ml file if you’re only declaring signatures (such as module types).

Signature files provide a place to write succinct documentation and to abstract internal details that shouldn’t be exported. Maintaining separate signature files also speeds up incremental compilation in larger code bases, since recompiling a mli signature is much faster than a full compilation of the implementation to native code.

Type Inference

Type inference is the process of determining the appropriate types for expressions based on their use. It’s a feature that’s partially present in many other languages such as Haskell and Scala, but OCaml embeds it as a fundamental feature throughout the core language.

OCaml type inference is based on the Hindley-Milner algorithm, which is notable for its ability to infer the most general type for an expression without requiring any explicit type annotations. The algorithm can deduce multiple types for an expression and has the notion of a principal typethat is the most general choice from the possible inferences. Manual type annotations can specialize the type explicitly, but the automatic inference selects the most general type unless told otherwise.

OCaml does have some language extensions that strain the limits of principal type inference, but by and large, most programs you write will never require annotations (although they sometimes help the compiler produce better error messages).

Adding type annotations to find errors

It’s often said that the hardest part of writing OCaml code is getting past the type checker — but once the code does compile, it works correctly the first time! This is an exaggeration of course, but it can certainly feel true when moving from a dynamically typed language. The OCaml static type system protects you from certain classes of bugs such as memory errors and abstraction violations by rejecting your program at compilation time rather than by generating an error at runtime. Learning how to navigate the type checker’s compile-time feedback is key to building robust libraries and applications that take full advantage of these static checks.

There are a couple of tricks to make it easier to quickly locate type errors in your code. The first is to introduce manual type annotations to narrow down the source of your error more accurately. These annotations shouldn’t actually change your types and can be removed once your code is correct. However, they act as anchors to locate errors while you’re still writing your code.

Manual type annotations are particularly useful if you use lots of polymorphic variants or objects. Type inference with row polymorphism can generate some very large signatures, and errors tend to propagate more widely than if you are using more explicitly typed variants or classes.

For instance, consider this broken example that expresses some simple algebraic operations over integers:

OCaml

letrec algebra =

function

| `Add (x,y) -> (algebra x) + (algebra y)

| `Sub (x,y) -> (algebra x) - (algebra y)

| `Mul (x,y) -> (algebra x) * (algebra y)

| `Num x -> x

let _ =

algebra (

`Add (

(`Num 0),

(`Sub (

(`Num 1),

(`Mul (

(`Nu 3),(`Num 2)

))

))

))

There’s a single character typo in the code so that it uses Nu instead of Num. The resulting type error is impressive:

Terminal

$ ocamlc -c broken_poly.ml

File "broken_poly.ml", line 9, characters 10-154:

Error: This expression has type

[> `Add of

([< `Add of 'a * 'a

| `Mul of 'a * 'a

| `Num of int

| `Sub of 'a * 'a

> `Num ]

as 'a) *

[> `Sub of 'a * [> `Mul of [> `Nu of int ] * [> `Num of int ] ] ] ]

but an expression was expected of type 'a

The second variant type does not allow tag(s) `Nu

The type error is perfectly accurate, but rather verbose and with a line number that doesn’t point to the exact location of the incorrect variant name. The best the compiler can do is to point you in the general direction of the algebra function application.

This is because the type checker doesn’t have enough information to match the inferred type of the algebra definition to its application a few lines down. It calculates types for both expressions separately, and when they don’t match up, outputs the difference as best it can.

Let’s see what happens with an explicit type annotation to help the compiler out:

OCaml

type t = [

| `Addof t * t

| `Subof t * t

| `Mulof t * t

| `Numofint

]

letrec algebra (x:t) =

match x with

| `Add (x,y) -> (algebra x) + (algebra y)

| `Sub (x,y) -> (algebra x) - (algebra y)

| `Mul (x,y) -> (algebra x) * (algebra y)

| `Num x -> x

let _ =

algebra (

`Add (

(`Num 0),

(`Sub (

(`Num 1),

(`Mul (

(`Nu 3),(`Num 2)

))

))

))

This code contains exactly the same error as before, but we’ve added a closed type definition of the polymorphic variants, and a type annotation to the algebra definition. The compiler error we get is much more useful now:

Terminal

$ ocamlc -i broken_poly_with_annot.ml

File "broken_poly_with_annot.ml", line 22, characters 14-21:

Error: This expression has type [> `Nu of int ]

but an expression was expected of type t

The second variant type does not allow tag(s) `Nu

This error points directly to the correct line number that contains the typo. Once you fix the problem, you can remove the manual annotations if you prefer more succinct code. You can also leave the annotations there, of course, to help with future refactoring and debugging.

Enforcing principal typing

The compiler also has a stricter principal type checking mode that is activated via the -principal flag. This warns about risky uses of type information to ensure that the type inference has one principal result. A type is considered risky if the success or failure of type inference depends on the order in which subexpressions are typed.

The principality check only affects a few language features:

§ Polymorphic methods for objects

§ Permuting the order of labeled arguments in a function from their type definition

§ Discarding optional labeled arguments

§ Generalized algebraic data types (GADTs) present from OCaml 4.0 onward

§ Automatic disambiguation of record field and constructor names (since OCaml 4.1)

Here’s an example of principality warnings when used with record disambiguation.

OCaml

type s = { foo: int; bar: unit }

type t = { foo: int }

let f x =

x.bar;

x.foo

Inferring the signature with -principal will show you a new warning:

Terminal

$ ocamlc -i -principal non_principal.ml

File "non_principal.ml", line 6, characters 4-7:

Warning 18: this type-based field disambiguation is not principal.

type s = { foo : int; bar : unit; }

type t = { foo : int; }

val f : s -> int

This example isn’t principal, since the inferred type for x.foo is guided by the inferred type of x.bar, whereas principal typing requires that each subexpression’s type can be calculated independently. If the x.bar use is removed from the definition of f, its argument would be of type t and nottype s.

You can fix this either by permuting the order of the type declarations, or by adding an explicit type annotation:

OCaml

type s = { foo: int; bar: unit }

type t = { foo: int }

let f (x:s) =

x.bar;

x.foo

There is now no ambiguity about the inferred types, since we’ve explicitly given the argument a type, and the order of inference of the subexpressions no longer matters.

Terminal

$ ocamlc -i -principal principal.ml

type s = { foo : int; bar : unit; }

type t = { foo : int; }

val f : s -> int

The ocamlbuild equivalent is to add the tag principal to your build. The corebuild wrapper script actually adds this by default, but it does no harm to explicitly repeat it:

Terminal

$ corebuild -tag principal principal.cmi non_principal.cmi

File "non_principal.ml", line 6, characters 4-7:

Warning 18: this type-based field disambiguation is not principal.

Ideally, all code should systematically use -principal. It reduces variance in type inference and enforces the notion of a single known type. However, there are drawbacks to this mode: type inference is slower, and the cmi files become larger. This is generally only a problem if you extensively use objects, which usually have larger type signatures to cover all their methods.

If compiling in principal mode works, it is guaranteed that the program will pass type checking in nonprincipal mode, too. For this reason, the corebuild wrapper script activates principal mode by default, preferring stricter type inference over a small loss in compilation speed and extra disk space usage.

Bear in mind that the cmi files generated in principal mode differ from the default mode. Try to ensure that you compile your whole project with it activated. Getting the files mixed up won’t let you violate type safety, but it can result in the type checker failing unexpectedly very occasionally. In this case, just recompile with a clean source tree.

Modules and Separate Compilation

The OCaml module system enables smaller components to be reused effectively in large projects while still retaining all the benefits of static type safety. We covered the basics of using modules earlier in Chapter 4. The module language that operates over these signatures also extends to functors and first-class modules, described in Chapter 9 and Chapter 10, respectively.

This section discusses how the compiler implements them in more detail. Modules are essential for larger projects that consist of many source files (also known as compilation units). It’s impractical to recompile every single source file when changing just one or two files, and the module system minimizes such recompilation while still encouraging code reuse.

The mapping between files and modules

Individual compilation units provide a convenient way to break up a big module hierarchy into a collection of files. The relationship between files and modules can be explained directly in terms of the module system.

Create a file called alice.ml with the following contents:

OCaml

let friends = [ Bob.name ]

and a corresponding signature file:

OCaml

val friends : Bob.t list

These two files are exactly analogous to including the following code directly in another module that references Alice:

OCaml

moduleAlice : sig

val friends : Bob.t list

end = struct

let friends = [ Bob.name ]

end

Defining a module search path

In the preceding example, Alice also has a reference to another module Bob. For the overall type of Alice to be valid, the compiler also needs to check that the Bob module contains at least a Bob.name value and defines a Bob.t type.

The type checker resolves such module references into concrete structures and signatures in order to unify types across module boundaries. It does this by searching a list of directories for a compiled interface file matching that module’s name. For example, it will look for alice.cmi andbob.cmi on the search path and use the first ones it encounters as the interfaces for Alice and Bob.

The module search path is set by adding -I flags to the compiler command line with the directory containing the cmi files as the argument. Manually specifying these flags gets complex when you have lots of libraries, and is the reason why the OCamlfind frontend to the compiler exists. OCamlfind automates the process of turning third-party package names and build descriptions into command-line flags that are passed to the compiler command line.

By default, only the current directory and the OCaml standard library will be searched for cmi files. The Pervasives module from the standard library will also be opened by default in every compilation unit. The standard library location is obtained by running ocamlc -where and can be overridden by setting the CAMLLIB environment variable. Needless to say, don’t override the default path unless you have a good reason to (such as setting up a cross-compilation environment).

INSPECTING COMPILATION UNITS WITH OCAMLOBJINFO

For separate compilation to be sound, we need to ensure that all the cmi files used to type-check a module are the same across compilation runs. If they vary, this raises the possibility of two modules checking different type signatures for a common module with the same name. This in turn lets the program completely violate the static type system and can lead to memory corruption and crashes.

OCaml guards against this by recording a MD5 checksum in every cmi. Let’s examine our earlier typedef.ml more closely:

Terminal

$ ocamlc -c typedef.ml

$ ocamlobjinfo typedef.cmi

File typedef.cmi

Unit name: Typedef

Interfaces imported:

bd274dc132ce5c3d8b6774d19cd373a6 Typedef

36b5bc8227dc9914c6d9fd9bdcfadb45 Pervasives

ocamlobjinfo examines the compiled interface and displays what other compilation units it depends on. In this case, we don’t use any external modules other than Pervasives. Every module depends on Pervasives by default, unless you use the -nopervasives flag (this is an advanced use case, and you shouldn’t normally need it).

The long alphanumeric identifier beside each module name is a hash calculated from all the types and values exported from that compilation unit. It’s used during type-checking and linking to ensure that all of the compilation units have been compiled consistently against one another. A difference in the hashes means that a compilation unit with the same module name may have conflicting type signatures in different modules. The compiler will reject such programs with an error similar to this:

Terminal

$ ocamlc -c foo.ml

File "foo.ml", line 1, characters 0-1:

Error: The files /home/build/bar.cmi

and /usr/lib/ocaml/map.cmi make inconsistent assumptions

over interface Map

This hash check is very conservative, but ensures that separate compilation remains type-safe all the way up to the final link phase. Your build system should ensure that you never see the preceding error messages, but if you do run into it, just clean out your intermediate files and recompile from scratch.

Packing Modules Together

The module-to-file mapping described so far rigidly enforces a 1:1 mapping between a top-level module and a file. It’s often convenient to split larger modules into separate files to make editing easier, but still compile them all into a single OCaml module.

The -pack compiler option accepts a list of compiled object files (.cmo in bytecode and .cmx for native code) and their associated .cmi compiled interfaces, and combines them into a single module that contains them as submodules of the output. Packing thus generates an entirely new .cmo (or.cmx file) and .cmi that includes the input modules.

Packing for native code introduces an additional requirement: the modules that are intended to be packed must be compiled with the -for-pack argument that specifies the eventual name of the pack. The easiest way to handle packing is to let ocamlbuild figure out the command-line arguments for you, so let’s try that out next with a simple example.

First, create a couple of toy modules called A.ml and B.ml that contain a single value. You will also need a _tags file that adds the -for-pack option for the cmx files (but careful to exclude the pack target itself). Finally, the X.mlpack file contains the list of modules that are intended to be packed under module X. There are special rules in ocamlbuild that tell it how to map %.mlpack files to the packed %.cmx or %.cmo equivalent:

Terminal

$ cat A.ml

let v = "hello"

$ cat B.ml

let w = 42

$ cat _tags

<*.cmx> and not "X.cmx": for-pack(X)

$ cat X.mlpack

A

B

You can now run corebuild to build the X.cmx file directly, but let’s create a new module to link against X to complete the example:

OCaml

let v = X.A.v

let w = X.B.w

You can now compile this test module and see that its inferred interface is the result of using the packed contents of X. We further verify this by examining the imported interfaces in Test and confirming that neither A nor B are mentioned in there and that only the packed X module is used:

Terminal

$ corebuild test.inferred.mli test.cmi

$ cat _build/test.inferred.mli

val v : string

val w : int

$ ocamlobjinfo _build/test.cmi

File _build/test.cmi

Unit name: Test

Interfaces imported:

906fc1b74451f0c24ceaa085e0f26e5f Test

36b5bc8227dc9914c6d9fd9bdcfadb45 Pervasives

25f4b4e10ec64c56b2987f5900045fec X

PACKING AND SEARCH PATHS

One very common build error that happens with packing is confusion resulting from building the packed cmi in the same directory as the submodules. When you add this directory to your module search path, the submodules are also visible. If you forget to include the top-level prefix (e.g., X.A) and instead use a submodule directly (A), then this will compile and link fine.

However, the types of A and X.A are not automatically equivalent so the type checker will complain if you attempt to mix and match the packed and unpacked versions of the library.

This mostly only happens with unit tests, since they are built at the same time as the library. You can avoid it by being aware of the need to open the packed module from the test, or only using the library after it has been installed (and hence not exposing the intermediate compiled modules).

Shorter Module Paths in Type Errors

Core uses the OCaml module system quite extensively to provide a complete replacement standard library. It collects these modules into a single Std module, which provides a single module that needs to be opened to import the replacement modules and functions.

There’s one downside to this approach: type errors suddenly get much more verbose. We can see this if you run the vanilla OCaml toplevel (not utop).

Terminal

$ ocaml

# List.map print_endline "" ;;

Error: This expression has type string but an expression was expected of type

string list

This type error without Core.Std has a straightforward type error. When we switch to Core, though, it gets more verbose:

Terminal

$ ocaml

# open Core.Std ;;

# List.map ~f:print_endline "" ;;

Error: This expression has type string but an expression was expected of type

'a Core.Std.List.t = 'a list

The default List module in OCaml is overridden by Core.Std.List. The compiler does its best to show the type equivalence, but at the cost of a more verbose error message.

The compiler can remedy this via a so-called short paths heuristic. This causes the compiler to search all the type aliases for the shortest module path and use that as the preferred output type. The option is activated by passing -short-paths to the compiler, and works on the toplevel, too.

Terminal

$ ocaml -short-paths

# open Core.Std;;

# List.map ~f:print_endline "foo";;

Error: This expression has type string but an expression was expected of type

'a list

The utop enhanced toplevel activates short paths by default, which is why we have not had to do this before in our interactive examples. However, the compiler doesn’t default to the short path heuristic, since there are some situations where the type aliasing information is useful to know, and it would be lost in the error if the shortest module path is always picked.

You’ll need to choose for yourself if you prefer short paths or the default behavior in your own projects, and pass the -short-paths flag to the compiler if you need it.

The Typed Syntax Tree

When the type checking process has successfully completed, it is combined with the AST to form a typed abstract syntax tree. This contains precise location information for every token in the input file, and decorates each token with concrete type information.

The compiler can output this as compiled cmt and cmti files that contain the typed AST for the implementation and signatures of a compilation unit. This is activated by passing the -bin-annot flag to the compiler.

The cmt files are particularly useful for IDE tools to match up OCaml source code at a specific location to the inferred or external types.

Using ocp-index for Autocompletion

One such command-line tool to display autocompletion information in your editor is ocp-index. Install it via OPAM as follows:

Terminal

$ opam install ocp-index

$ ocp-index

Let’s refer back to our Ncurses binding example from the beginning of Chapter 19. This module defined bindings for the Ncurses library. First, compile the interfaces with -bin-annot so that we can obtain the cmt and cmti files, and then run ocp-index in completion mode:

Terminal

$ corebuild -pkg ctypes.foreign -tag bin_annot ncurses.cmi

$ ocp-index complete -I . Ncur

Ncurses module

$ ocp-index complete -I . Ncurses.a

Ncurses.addstr val string -> unit

$ ocp-index complete -I . Ncurses.

Ncurses.window val Ncurses.window Ctypes.typ

Ncurses.wrefresh val Ncurses.window -> unit

Ncurses.initscr val unit -> Ncurses.window

Ncurses.endwin val unit -> unit

Ncurses.refresh val unit -> unit

Ncurses.newwin val int -> int -> int -> int -> Ncurses.window

Ncurses.mvwaddch val Ncurses.window -> int -> int -> char -> unit

Ncurses.mvwaddstr val Ncurses.window -> int -> int -> string -> unit

Ncurses.addstr val string -> unit

Ncurses.box val Ncurses.window -> char -> char -> unit

Ncurses.cbreak val unit -> int

You need to pass ocp-index a set of directories to search for cmt files in, and a fragment of text to autocomplete. As you can imagine, autocompletion is invaluable on larger codebases. See the ocp-index home page for more information on how to integrate it with your favorite editor.

Examining the Typed Syntax Tree Directly

The compiler has a couple of advanced flags that can dump the raw output of the internal AST representation. You can’t depend on these flags to give the same output across compiler revisions, but they are a useful learning tool.

We’ll use our toy typedef.ml again:

OCaml

type t = Foo | Bar

let v = Foo

Let’s first look at the untyped syntax tree that’s generated from the parsing phase:

Terminal

$ ocamlc -dparsetree typedef.ml 2>&1

[

structure_item (typedef.ml[1,0+0]..[1,0+18])

Pstr_type

[

"t" (typedef.ml[1,0+5]..[1,0+6])

type_declaration (typedef.ml[1,0+5]..[1,0+18])

ptype_params =

[]

ptype_cstrs =

[]

ptype_kind =

Ptype_variant

[

(typedef.ml[1,0+9]..[1,0+12])

"Foo" (typedef.ml[1,0+9]..[1,0+12])

[]

None

(typedef.ml[1,0+15]..[1,0+18])

"Bar" (typedef.ml[1,0+15]..[1,0+18])

[]

None

]

ptype_private = Public

ptype_manifest =

None

]

structure_item (typedef.ml[2,19+0]..[2,19+11])

Pstr_value Nonrec

[

<def>

pattern (typedef.ml[2,19+4]..[2,19+5])

Ppat_var "v" (typedef.ml[2,19+4]..[2,19+5])

expression (typedef.ml[2,19+8]..[2,19+11])

Pexp_construct "Foo" (typedef.ml[2,19+8]..[2,19+11])

None

false

]

]

This is rather a lot of output for a simple two-line program, but it shows just how much structure the OCaml parser generates even from a small source file.

Each portion of the AST is decorated with the precise location information (including the filename and character location of the token). This code hasn’t been type checked yet, so the raw tokens are all included.

The typed AST that is normally output as a compiled cmt file can be displayed in a more developer-readable form via the -dtypedtree option:

Terminal

$ ocamlc -dtypedtree typedef.ml 2>&1

[

structure_item (typedef.ml[1,0+0]..typedef.ml[1,0+18])

Pstr_type

[

t/1008

type_declaration (typedef.ml[1,0+5]..typedef.ml[1,0+18])

ptype_params =

[]

ptype_cstrs =

[]

ptype_kind =

Ptype_variant

[

"Foo/1009"

[]

"Bar/1010"

[]

]

ptype_private = Public

ptype_manifest =

None

]

structure_item (typedef.ml[2,19+0]..typedef.ml[2,19+11])

Pstr_value Nonrec

[

<def>

pattern (typedef.ml[2,19+4]..typedef.ml[2,19+5])

Ppat_var "v/1011"

expression (typedef.ml[2,19+8]..typedef.ml[2,19+11])

Pexp_construct "Foo"

[]

false

]

]

The typed AST is more explicit than the untyped syntax tree. For instance, the type declaration has been given a unique name (t/1008), as has the v value (v/1011).

You’ll rarely need to look at this raw output from the compiler unless you’re building IDE tools such as ocp-index, or are hacking on extensions to the core compiler itself. However, it’s useful to know that this intermediate form exists before we delve further into the code generation process next, in Chapter 23.

There are several new integrated tools emerging that combine these typed AST files with common editors such as Emacs or Vim. The best of these is Merlin, which adds value and module autocompletion, displays inferred types and can build and display errors directly from within your editor. There are instructions available on its homepage for configuring Merlin with your favorite editor.