Table of Contents
The problem of “I know I have this file, but I don't know where it is” has been around for as long as computers have had hierarchical filesystems. The fifth edition of Unix introduced the find command in 1974; it remains indispensable today. The state of the art has come a long way: modern operating systems ship with advanced document indexing and search capabilities.
There's still a valuable place for find-like capability in the programmer's toolbox. In this chapter, we'll develop a library that gives us many of find's capabilities, without leaving Haskell. We'll explore several different approaches to writing this library, each with different strengths.
If you don't use a Unix-like operating system, or you're not a heavy shell user, it's quite possible you won't have heard of find. Given a list of directories, it searches each one recursively and prints the name of every entry that matches an expression.
Individual expressions can take such forms as “name matches this glob pattern”, “entry is a plain file”, “last modified before this date”, and many more. They can be stitched together into more complex expressions using “and” and “or” operators.
Before we plunge into designing our library, let's solve a few smaller problems. Our first problem is to get a list of the contents of a directory at all, and to do so recursively.
module RecursiveContents (getRecursiveContents) where
import Control.Monad (forM)
import System.Directory (doesDirectoryExist, getDirectoryContents)
import System.FilePath ((</>))
getRecursiveContents :: FilePath -> IO [FilePath]
getRecursiveContents topdir = do
names <- getDirectoryContents topdir
let properNames = filter (not . (`elem` [".", ".."])) names
paths <- forM properNames $ \name -> do
let path = topdir </> name
isDirectory <- doesDirectoryExist path
if isDirectory
then getRecursiveContents path
else return [path]
return (concat paths)The filter expression ensures that a
listing for a single directory won't contain the special
directory names . or ..,
which refer to the current and parent directory, respectively.
If we were to forget to filter these out, we'd recurse
endlessly.
The forM function is a
flipped version of
mapM, which we first saw in the section called “The IO Monad”.
ghci>:m +Control.Monadghci>:type mapMmapM :: (Monad m) => (a -> m b) -> [a] -> m [b]ghci>:type forMforM :: (Monad m) => [a] -> (a -> m b) -> m [b]
The body of the loop checks to see whether the current entry
is a directory. If it is, it recursively calls
getRecursiveContents to list that
directory. Otherwise, it returns a single-element list that is
the name of the current entry. Note that in the body of the
loop, the return is returning a value
from the anonymous function that is the
loop body to its caller,
forM. It is not
returning from getRecursiveContents.
Tie this into our earlier discussion of
return.
Another thing worth pointing out is the use of the variable
isDirectory. In an imperative language such
as Python, we'd normally write if
os.path.isdir(path). However, the
doesDirectoryExist function is an
action; its return type is IO
Bool, not Bool. Since an if expression
requires an expression of type Bool, we have to use
<- to get the Bool result of the
action out of its IO wrapper, so we can use the
plain, unwrapped Bool in the if.
Finally, each call to the loop body yields a list of names,
so the result of forM is a list of lists.
We use concat to flatten it into a single
list.
In the section called “Anonymous (lambda) functions”, we listed some reasons not to use anonymous functions, and yet here we are, using one as the body of a loop. This is one of the most common uses of anonymous functions in Haskell.
We've already seen from their types that
forM and mapM take
functions as arguments. Most loop bodies are blocks of code
that only appear once in a program. Since we're most likely to
use a loop body in only one place, why give it a name?
Of course, it does happen that we need to deploy exactly the same code in several different loops. Rather than cutting and pasting the same anonymous function, it makes sense here to take an existing anonymous function and give it a name.
It might seem a bit odd that there exist two functions
that are identical but for the order in which they accept
their arguments. However, mapM and
forM are convenient in different
circumstances.
Consider our example above, using an anonymous function as
a loop body. If we were to use mapM
instead of forM, we'd have to place the
variable properNames after the body of the
function. In order to get the code to parse correctly, we'd
have to wrap the entire anonymous function in parentheses, or
replace it with a named function that would otherwise be
unnecessary. Try it yourself: copy the code above, replacing
forM with mapM, and
see what this does to the readability of the code.
By contrast, if the body of the loop was already a named
function, and the list over which we were looping was computed
by a complicated expression, we'd have a good case for using
mapM instead.
The stylistic rule of thumb to follow here is to use
whichever of mapM or
forM lets you write the tidiest code. If
the loop body and the expression computing the data over which
you're looping are both short, it doesn't matter which you
use. If the loop is short, but the data is long, use
mapM. If the loop is long, but the data
short, use forM. And if both are long,
use a let or where clause to make one of them short. With
just a little practice, it will become obvious which of these
approaches is best in every instance.
We can use our getRecursiveContents
function as the basis for a simple-minded file finder.
import RecursiveContents (getRecursiveContents) simpleFind :: (FilePath -> Bool) -> FilePath -> IO [FilePath] simpleFind p path = do names <- getRecursiveContents path return (filter p names)
This function takes a predicate that we use to filter the
names returned by getRecursiveContents.
Each name passed to the predicate is a complete path, so how can
we perform a common operation like “find all files ending
in the extension .c”?
The System.FilePath module contains numerous
invaluable functions that help us to manipulate file names. In
this case, we want takeExtension.
ghci>:m +System.FilePathghci>:type takeExtensiontakeExtension :: FilePath -> Stringghci>takeExtension "foo/bar.c"Loading package filepath-1.1.0.0 ... linking ... done. ".c"ghci>takeExtension "quux"""
This gives us a simple matter of writing a function that
takes a path, extracts its extension, and compares it with
.c.
ghci>:load SimpleFinder[1 of 2] Compiling RecursiveContents ( RecursiveContents.hs, interpreted ) [2 of 2] Compiling Main ( SimpleFinder.hs, interpreted ) Ok, modules loaded: RecursiveContents, Main.ghci>:type simpleFind (\p -> takeExtension p == ".c")simpleFind (\p -> takeExtension p == ".c") :: FilePath -> IO [FilePath]
While simpleFind works, it has a few
glaring problems. The first is that the predicate is not very
expressive. It can only look at the name of a directory entry,
and not for example find out whether it's a file or a directory.
This means that our attempt to use
simpleFind will list directories ending in
.c as well as files with the same extension.
The second problem is that simpleFind
gives us no control over how it traverses the filesystem. To
see why this is significant, consider the problem of searching
for a source file in a tree managed by the Subversion revision
control system. Subversion maintains a private
.svn directory in every directory that it
manages; each one contains many subdirectories and files that
are of no interest to us. While we can easily enough filter out
any path containing .svn, it's more
efficient to simply avoid traversing these directories in the
first place. For example, one of us has a Subversion source
tree containing 45,000 files, 30,000 of which are stored in
1,200 different .svn directories. It's
cheaper to avoid traversing those 1,200 directories than to
filter out the 30,000 files they contain.
Finally, simpleFind is strict. If we
have a million files to traverse, we get one huge result
containing a million names, instead of a piecemeal lazy stream
of results. This is bad for both resource usage and
responsiveness.
In the sections that follow, we'll overcome each one of these problems.
Our predicates can only look at file names. This excludes a wide variety of interesting behaviours: for instance, what if we'd like to list files of greater than a given size?
An easy reaction to this is to reach for IO: instead of our predicate being of type FilePath -> Bool, why don't we change it to FilePath -> IO Bool? This would let us perform arbitrary I/O as part of our predicate. As appealing as this might seem, it's also potentially a problem: such a predicate could have arbitrary side effects, since a function with return type IO a can have whatever side effects it pleases.
Let's enlist the type system in our quest to write more predictable, less buggy code: we'll keep predicates pure by avoiding the taint of “IO”. This will ensure that they can't have any nasty side effects. We'll feed them more information, too, so that they can gain the expressiveness we want without also becoming potentially dangerous.
Haskell's portable System.Directory module
provides a useful, albeit limited, set of file metadata.
ghci>:m +System.Directory
We can use doesFileExist and
doesDirectoryExist to determine whether
a directory entry is a file or a directory. There are not
yet portable ways to query for other file types that have
become widely available in recent years, such as named
pipes, hard links and symbolic links.
ghci>:type doesFileExistdoesFileExist :: FilePath -> IO Boolghci>doesFileExist "."Loading package old-locale-1.0.0.0 ... linking ... done. Loading package old-time-1.0.0.0 ... linking ... done. Loading package directory-1.0.0.0 ... linking ... done. Falseghci>:type doesDirectoryExistdoesDirectoryExist :: FilePath -> IO Boolghci>doesDirectoryExist "."True
The getPermissions function lets us
find out whether certain operations on a file or directory
are allowed.
ghci>:type getPermissionsgetPermissions :: FilePath -> IO Permissionsghci>:info Permissionsdata Permissions = Permissions {readable :: Bool, writable :: Bool, executable :: Bool, searchable :: Bool} -- Defined in System.Directory instance Eq Permissions -- Defined in System.Directory instance Ord Permissions -- Defined in System.Directory instance Read Permissions -- Defined in System.Directory instance Show Permissions -- Defined in System.Directoryghci>getPermissions "."Permissions {readable = True, writable = True, executable = False, searchable = True}ghci>:type searchablesearchable :: Permissions -> Boolghci>searchable itTrue
Finally, getModificationTime tells
us when an entry was last modified.
ghci>:type getModificationTimegetModificationTime :: FilePath -> IO System.Time.ClockTimeghci>getModificationTime "."Tue Apr 22 23:12:10 PDT 2008
If we stick with portable, standard Haskell code, these
functions are all we have at our disposal. (We can also find a
file's size using a small hack; see below.) They're also quite
enough to let us illustrate the principles we're interested in,
without letting us get carried away with an example that's too
expansive. If you need to write more demanding code, the
System.Posix and System.Win32 module
families provide much more detailed file metadata for the two
major modern computing platforms.
How many pieces of data does our new, richer predicate need
to see? Since we can find out whether an entry is a file or a
directory by looking at its Permissions, we don't
need to pass in the results of
doesFileExist or
doesDirectoryExist. We thus have four
pieces of data that a richer predicate needs to look at.
type Predicate = FilePath -- path to directory entry
-> Permissions -- permissions
-> Maybe Integer -- file size (Nothing if not file)
-> ClockTime -- last modified
-> BoolNotice that the return value of this predicate is Bool, not IO Bool: the predicate is pure, and cannot perform I/O. With this type in hand, our more expressive finder function is still quite trim.
getFileSize :: FilePath -> IO (Maybe Integer)
betterFind :: Predicate -> FilePath -> IO [FilePath]
betterFind p path = getRecursiveContents path >>= filterM check
where check name = do
perms <- getPermissions name
size <- getFileSize name
modified <- getModificationTime name
return (p name perms size modified)Let's walk through the code. We'll talk about
getFileSize in some detail soon, so let's
skip over it for now.
We can't use filter to call our
predicate p, as p's purity
means it cannot do the I/O needed to gather the metadata it
requires.
This leads us to the unfamiliar function
filterM. It behaves like the normal
filter function, but in this case it
evaluates its predicate in the IO monad, allowing
the predicate to perform I/O.
ghci>:m +Control.Monadghci>:type filterMfilterM :: (Monad m) => (a -> m Bool) -> [a] -> m [a]
Our check predicate is an I/O-capable
wrapper for our pure predicate p. It does all
the “dirty” work of I/O on p's
behalf, so that we can keep p incapable of
unwanted side effects. After gathering the metadata,
check calls p, then uses
return to wrap p's
result with IO.
Although System.Directory doesn't let us find
out what size a file is, we can use the similarly portable
System.IO module to do this. It contains a
function named hFileSize, which returns the
size in bytes of an open file. Here's a simple function that
wraps it.
import Control.Exception (bracket, handle) import System.IO (IOMode(..), hClose, hFileSize, openFile) simpleFileSize :: FilePath -> IO Integer simpleFileSize path = do h <- openFile path ReadMode size <- hFileSize h hClose h return size
While this function works, it's not yet suitable for us to
use. In betterFind, we call
getFileSize unconditionally on all kinds of
directory entry, and expect it to return Nothing if
an entry is not a plain file, or the size wrapped by
Just otherwise. This function instead throws an
exception if an entry is not a plain file or could not be opened
(perhaps due to insufficient permissions), and returns the size
unwrapped.
Here's a safer version of this function.
saferFileSize path = handle (\_ -> return Nothing) $ do h <- openFile path ReadMode size <- hFileSize h hClose h return (Just size)
The body of the function is almost identical, save for the
handle clause. This is our first use of an
exception handler. Exception-related code lives in the
Control.Exception module.
ghci>:m +Control.Exceptionghci>:type handlehandle :: (Exception -> IO a) -> IO a -> IO a
The handle function works by calling
its second argument. If that action returns normally,
handle returns its result. If the action
throws an exception, handle catches the
exception and passes it to the first action. That action is
free to do whatever it wants. It can rethrow the exception or
throws a new exception (topics we'll return to in chapter XXX),
or it can return some value, which will in turn be returned by
handle.
Our exception handler above ignores the exception it's
passed, and returns Nothing. The only change to
the body that follows is that it wraps the file size with
Just.
The saferFileSize function now has the
correct type signature, and it won't throw any exceptions. But
it's still not completely well behaved. There are directory
entries on which openFile will succeed, but
hFileSize will throw an exception. This
can happen with, for example, named pipes. Such an exception
will be caught by handle, but our call to
hClose will never occur.
A Haskell implementation will automatically close the file handle when it notices that the handle is no longer being used, but that will not happen until the garbage collector runs, which can take a while. Until then, the file handle remains open.
File handles are scarce resources. Their scarcity is enforced by the underlying operating system. On Linux, for example, a process is by default only allowed to have 1024 files open simultaneously.
It's not hard to imagine a scenario in which a program that
called a version of betterFind that used
saferFileSize could crash because
betterFind exhausted the supply of open
files before enough garbage file handles could be closed.
This is a particularly pernicious kind of bug, as it has
several aspects that combine make it incredibly difficult to
track down. It will only be triggered if
betterFind visits a sufficiently large
number of non-files to hit the process's open file limit, and
then returns to a caller that tries to open another file before
any of the accumulated garbage file handles is closed. This is
an unlikely enough combination of circumstances. Worse, any
subsequent error will be caused by data that is no longer
reachable from within the program, and has yet to be garbage
collected. Such a bug is thus dependent on the structure of the
program, the contents of the filesystem, and how close the
current run of the program is to triggering the garbage
collector.
Fortunately, we can avoid this kind of error very easily, in fact here we can do so by making our function shorter.
We need hClose to always be called if
openFile succeeds. The
Control.Exception module provides the
bracket function for exactly this
purpose.
ghci>:type bracketbracket :: IO a -> (a -> IO b) -> (a -> IO c) -> IO c
The bracket function takes three
actions as arguments. The first action acquires a resource.
The second releases the resource. The third runs in between,
while the resource is acquired; let's call this the
“use” action. If the “acquire”
action succeeds, the “release” action is
always called. This guarantees that the
resource will always be released. The “use” and
“release” actions are each passed the resource
acquired by the “acquire” action.
If an exception occurs while the “use” action
is executing, bracket calls the
“release” action and rethrows the exception. If
the “use” action succeeds,
bracket calls the “release”
action, and returns the value returned by the
“use” action.
We can now write a function that is completely safe: it will not throw exceptions; neither will it accumulate garbage file handles that could cause spurious failures elsewhere in our program.
getFileSize path = handle (const (return Nothing)) $
bracket (openFile path ReadMode) hClose $ \h -> do
size <- hFileSize h
return (Just size)Look closely at the arguments of
bracket above. The first opens the file,
and returns the open file handle. The second closes the
handle. The third simply calls hFileSize
on the handle and wraps the result in
Just.
We need to use both bracket and
handle for this function to operate
correctly. The former ensures that we don't accumulate garbage
file handles, while the latter gets rid of exceptions.
Let's take a stab at writing a predicate, recalling the type signature for predicates.
type Predicate = FilePath -- path to directory entry
-> Permissions -- permissions
-> Maybe Integer -- file size (Nothing if not file)
-> ClockTime -- last modified
-> BoolOur predicate will check for a C source file that is over 100KB in size.
myTest path _ (Just size) _ =
takeExtension path == ".cpp" && size > 131072
myTest _ _ _ _ = FalseThis isn't especially pleasing. The predicate takes four arguments, always ignores two of them, and requires two equations to define. Surely we can do better.
One approach we can take is to write a function that returns one of its arguments. This one extracts the path from the arguments passed to a Predicate.
pathP path _ _ _ = path
If we don't provide a type signature, a Haskell
implementation will infer a very general type for this function.
This can later lead to error messages that are difficult to
interpret, so let's give pathP a
type.
type InfoP a = FilePath -- path to directory entry
-> Permissions -- permissions
-> Maybe Integer -- file size (Nothing if not file)
-> ClockTime -- last modified
-> a
pathP :: InfoP FilePathWe've gone a step further and created a type synonym that we can use as shorthand for writing other, similarly structured functions.
sizeP :: InfoP Integer sizeP _ _ (Just size) _ = size sizeP _ _ Nothing _ = -1
(We're being a little sneaky here, and returning a size of -1 for entries that are not files, or that we couldn't open.)
In fact, a quick glance shows that the Predicate type that we defined near the beginning of this chapter is the same type as InfoP Bool.
What use are pathP and
sizeP? With a little more glue, we can use
them in a predicate. This is where things start to get
interesting.
equalP :: (Eq a) => InfoP a -> a -> InfoP Bool equalP f k = \w x y z -> f w x y z == k
The type signature of equalP deserves a
little attention. It takes an InfoP a, which is
compatible with both equalP and
sizeP. It takes an a. And it
returns an InfoP Bool, which we already observed is
a synonym for Predicate. In other words,
equalP constructs a predicate.
The equalP function works by returning
an anonymous function. That one takes the arguments accepted by
a predicate, passes them to f, and compares
the result to k.
This equation for equalP emphasises
the fact that we think of it as taking two arguments. Since
Haskell curries all functions, writing
equalP in this way is not actually
necessary. We can omit the anonymous function and rely on
currying to work on our behalf, letting us write a function that
behaves identically.
equalP' :: (Eq a) => InfoP a -> a -> InfoP Bool equalP' f k w x y z = f w x y z == k
Before we continue with our explorations, let's load our module into ghci.
ghci>:load BetterPredicate[1 of 2] Compiling RecursiveContents ( RecursiveContents.hs, interpreted ) [2 of 2] Compiling Main ( BetterPredicate.hs, interpreted ) Ok, modules loaded: Main, RecursiveContents.
Let's see if a simple predicate constructed from these functions will work.
ghci>:type betterFind (sizeP `equalP` 1024)betterFind (sizeP `equalP` 1024) :: FilePath -> IO [FilePath]
Notice that we're not actually calling
betterFind, we're merely making sure that
our expression typechecks. We now have a more expressive way to
list all files that are exactly one kilobyte in size. Our
success gives us enough confidence to continue.
Besides equalP, we'd like to be able
to write other binary functions. We'd prefer not to write
each one out in “longhand”, because that seems
unnecessarily verbose.
To address this, let's put Haskell's powers of abstraction
to use. We'll take the definition of
equalP, and instead of calling
(==) directly, we'll pass in as another
argument the binary function that we want to call.
liftPK :: (a -> b -> c) -> InfoP a -> b -> InfoP c liftPK q f k w x y z = f w x y z `q` k greaterP, lesserP :: (Ord a) => InfoP a -> a -> InfoP Bool greaterP = liftPK (>) lesserP = liftPK (<)
This act of taking a function, such as
(>), and transforming it into another
function that operates in a different context, here
greaterP, is referred to as
lifting it into that context. This
explains the presence of lift in the function's
name. Lifting lets us reuse code and reduce boilerplate.
We'll be using it a lot, in different guises, throughout the
rest of this book.
When we lift a function, we'll often refer to its original and new versions as unlifted and lifted, respectively.
By the way, our placement of f, the
function to lift, as the first argument to
liftPK, was no accident. This made it
possible for us to write such concise definitions of
greaterP and
lesserP. Partial application makes
finding the “best” order for arguments a more
important part of API design in Haskell than in other
languages. In languages without partial application, argument
ordering is a matter of taste and convention. Put an argument
in the wrong place in Haskell, however, and you lose the
concision that partial application gives.
If we want to combine predicates, we can of course follow the obvious path of doing so by hand.
simpleAndP :: InfoP Bool -> InfoP Bool -> InfoP Bool simpleAndP f g w x y z = f w x y z && g w x y z
Now that we know about lifting, however, it becomes tempting to lift our existing Boolean operators.
liftP2 :: (a -> b -> c) -> InfoP a -> InfoP b -> InfoP c liftP2 q f g w x y z = f w x y z `q` g w x y z andP = liftP2 (&&) orP = liftP2 (||)
Notice that liftP2 is very similar to
our earlier liftPK. In fact, it's more
general, because we can write liftPK in
terms of liftP2.
constP :: a -> InfoP a constP k _ _ _ _ = k liftPK' q f k w x y z = f w x y z `q` constP k w x y z
![]() | Combinators |
|---|---|
In Haskell, we refer to functions that take other functions as arguments, returning new functions, as combinators. |
Now that we have some helper functions in place, we can
return to the myTest function we defined
earlier.
myTest path _ (Just size) _ =
takeExtension path == ".cpp" && size > 131072
myTest _ _ _ _ = FalseHow will this function look if we write it using our new combinators?
liftPath :: (FilePath -> a) -> InfoP a
liftPath f w _ _ _ = f w
myTest2 = (liftPath takeExtension `equalP` ".cpp") `andP`
(sizeP `greaterP` 1024)We've added one final combinator,
liftPath, since manipulating file names
is such a common activity.
Our rewrite doesn't really look any shorter than the original function, though it's perhaps a little easier to read.
We can address the length problem by defining new infix operators, taking advantage of a Haskell feature that we first mentioned briefly in the section called “An arithmetic quirk: writing negative numbers”.
(==?) = equalP (&&?) = andP (>?) = greaterP myTest3 = (liftPath takeExtension ==? ".cpp") &&? (sizeP >? 1024) --
We chose names like (==?) for the
lifted functions specifically for their visual similarity to
their unlifted counterparts.
The parentheses in our definition above are necessary,
because we haven't told Haskell about the precedence or
associativity of our new operators. The language specifies
that operators without fixity declarations should be treated
as infixl 9, i.e. they are parsed from left to
right at the lowest allowable precedence level. If we were to
omit the parentheses, the expression would thus be parsed as
(((liftPath takeExtension) ==? ".cpp") &&?
sizeP) >? 1024, which is horribly wrong.
We can respond by writing fixity declarations for our new operators. Our first step is to find out what the fixities of the unlifted operators are, so that we can mimic them.
ghci>:info ==class Eq a where (==) :: a -> a -> Bool ... -- Defined in GHC.Base infix 4 ==ghci>:info &&(&&) :: Bool -> Bool -> Bool -- Defined in GHC.Base infixr 3 &&ghci>:info >class (Eq a) => Ord a where ... (>) :: a -> a -> Bool ... -- Defined in GHC.Base infix 4 >
With these in hand, we can now write a parenthesis-free
expression that will be parsed identically to
myTest3.
infix 4 ==? infixr 3 &&? infix 4 >? myTest4 = liftPath takeExtension ==? ".cpp" &&? sizeP >? 1024
When traversing the filesystem, we'd like to give ourselves
more control over which directories we enter, and when. An easy
way in which we can allow this is to pass in a function that
takes a list of subdirectories of a given directory, and returns
another list. This list can have elements removed, or it can be
ordered differently than the original list, or both. The
simplest such control function is id, which
will return its input list unmodified.
For variety, we're going to change a few aspects of our representation here. Instead of an elaborate function type InfoP a, we'll use a normal algebraic data type to represent substantially the same information.
data Info = Info {
infoPath :: FilePath
, infoPerms :: Maybe Permissions
, infoSize :: Maybe Integer
, infoModTime :: Maybe ClockTime
} deriving (Eq, Ord, Show)
getInfo :: FilePath -> IO InfoWe're using record syntax to give ourselves
“free” accessor functions, such as
infoPath. The type of our
traverse function is simple, as we proposed
above. To obtain Info about a file or directory,
we call the getInfo action.
traverse :: ([Info] -> [Info]) -> FilePath -> IO [Info]
The definition of traverse is short,
but dense.
traverse order path = do
names <- getUsefulContents path
contents <- mapM (getInfo . (path </>)) ("" : names)
liftM concat $ forM (order contents) $ \info -> do
if isDirectory info && infoPath info /= path
then traverse order (infoPath info)
else return [info]
getUsefulContents :: FilePath -> IO [String]
getUsefulContents path = do
names <- getDirectoryContents path
return (filter (not . (`elem` [".", ".."])) names)
isDirectory :: Info -> Bool
isDirectory = maybe False searchable . infoPermsWhile we're not introducing any new techniques here, this is one of the densest function definitions we've yet encountered. Let's walk through it almost line by line, explaining what is going on. The first few lines hold no mystery, as they're almost verbatim copies of code we've already seen.
Things begin to get interesting when we assign to the
variable contents. Let's read this line from
right to left. We already know that
usefulNames is a list of directory entries;
we put the empty string on the front of the list, to represent
the current directory, path. The code
getInfo . (path </>) joins
path and one of these entries together, then
calls getInfo on the result. (Using
(</>) to combine
path with the empty string gives us
path again, which is why we put the empty
string onto the front of our list.) Finally, we use
mapM to apply this function to
path and every one of its directory
entries.
The line that follows is even more dense. Again reading
from right to left, we see that the last element of the line is
an anonymous function. Given one Info value, it
either visits a directory recursively (there's an extra check to
make sure we don't visit path again), or
returns that value as a single-element list (to match the return
type of traverse).
We use forM to apply this function to
each element of the list of Info values returned by
order, the user-supplied traversal control
function.
Finally, at the beginning of the line, we have another use
of lifting. The liftM function takes a
regular function, concat and lifts it into
the IO monad. In other words, it takes the result
of forM (of type [[Info]]) out
of the IO monad, applies
concat to it (yielding a result of type
[Info], which is what we need), and puts the result
back into the IO monad.
Finally, we mustn't forget to define our
getInfo function.
maybeIO :: IO a -> IO (Maybe a) maybeIO act = handle (const (return Nothing)) (Just `liftM` act) getInfo path = do perms <- maybeIO (getPermissions path) size <- maybeIO (bracket (openFile path ReadMode) hClose hFileSize) modified <- maybeIO (getModificationTime path) return (Info path perms size modified)
The only noteworthy thing here is a useful combinator,
maybeIO, which turns an IO
action that might throw an exception into one that wraps its
result in Maybe.
1. | What should you pass to |
2. | Using |
3. | Take the predicates and combinators from the section called “Gluing predicates together” and make them work with our new Info type. |
4. | Write a wrapper for |
Code as dense as traverse isn't all
that unusual in Haskell. The gain in expressiveness is
significant, and it requires a relatively small amount of
practice to be able to fluently read and write code in this
style.
For comparison, here's a less dense presentation of the same code. This might be more typical of a less experienced Haskell programmer.
traverseVerbose order path = do
names <- getDirectoryContents path
let usefulNames = filter (not . (`elem` [".", ".."])) names
contents <- mapM getEntryName ("" : usefulNames)
recursiveContents <- mapM recurse (order contents)
return (concat recursiveContents)
where getEntryName name = getInfo (path </> name)
isDirectory info = case infoPerms info of
Nothing -> False
Just perms -> searchable perms
recurse info = do
if isDirectory info && infoPath info /= path
then traverseVerbose order (infoPath info)
else return [info]All we've done here is make a few substitutions. Instead of
using partial application and function composition liverally,
we've defined some local functions in a where block. In place
of the maybe combinator, we're using a
case expression. And instead of using
liftM, we're manually lifting
concat ourselves.
This is not to say that density is a uniformly good
property. Each line of the original
traverse function is short. We introduce a
local variable (usefulNames) and a local
function (isDirectory) specifically to keep
the lines short and the code clearer. Our names names are
descriptive. While we use function composition and pipelining,
the longest pipeline contains only three elements.
The key to writing maintainable Haskell code is to find a balance between density and readability. Where your code falls on this continuum is likely to be influenced by your level of experience.
As a beginning Haskell programmer, Andrew doesn't know his way around the standard libraries very well. As a result, he duplicates a lot of standard library code.
Zack has been programming for a few months, and has
mastered the use of (.) to compose long
pipelines of code. Every time the needs of his program
change slightly, he has to construct a new pipeline from
scratch, because he can't understand the existing one any
longer and it's too fragile to change in any case.
Monica has been hacking for a while. She's familiar enough with Haskell libraries and idioms to write tight code, but she avoids a hyperdense style in order to keep her code maintainable and easy to refactor in the face of changing needs.
While many good Haskell programming habits come with experience, we have a few general guidelines to offer so that you can write readable code more quickly.
As we already mentioned in the section called “A note about tabs versus spaces”, never use tab characters in Haskell source files. Use spaces.
If you find yourself proudly thinking that a particular piece of code is fiendishly clever, stop and consider whether you'll be able to understand it again after you've stepped away from it for a month.
The conventional way of naming types and variables with
compound names is to use “camel case”, i.e.
myVariableName. This style is almost
universal in Haskell code. Regardless of your opinion of other
naming practices, if you follow a non-standard convention, your
Haskell code will be somewhat jarring to the eyes of other
readers.
Until you've been working with Haskell for a substantial amount of time, spend a few minutes searching for library functions before you write small functions. This applies particularly to ubiquitous types like lists, Maybe, and Either. If the standard libraries don't already provide exactly what you need, you might be able to combine a few functions to obtain the result you desire.
Long pipelines of composed functions are hard to read, where
“long” means a pipeline of more than three or four
elements. If you have such a pipeline, use a let or where
block to break it into smaller pipelines. Give each one of
these pipeline elements a meaningful name, then glue them back
together. If you can't think of a meaningful name for an
element, you probably can't describe what it's supposed to be
doing.
Even though it's easy to resize a text editor window far beyond 80 columns, this is still a very common window width. Wider lines thus get wrapped in 80-column windows, which severely hurts readability. Treating lines as no more than 80 characters long limits the amount of code you can cram onto a single line to a reasonably digestible amount.
A Haskell implementation won't make a fuss about indentation as long as your code follows the layout rules and can hence be parsed unambiguously. That said, some layout patterns are widely used.
The in keyword is usually aligned directly under the let
keyword, with the expression immediately following it.
tidyLet = let foo = undefined
bar = foo * 2
in undefinedWhile it's legal to indent the in
differently, or to let it “dangle” at the end of a
series of equations, the following would generally be considered
odd.
weirdLet = let foo = undefined
bar = foo * 2
in undefined
strangeLet = let foo = undefined
bar = foo * 2 in
undefinedIn contrast, it's usual to let a do dangle at the end of a
line, rather than sit at the beginning of a line.
commonDo = do
something <- undefined
return ()
-- not seen very often
rareDo =
do something <- undefined
return ()Curly braces and semicolons, though legal, are almost never used. There's nothing wrong with them; they just make code look strange due to their rarity. They're really intended to let programs generate Haskell code without having to implement the layout rules, not for human use.
unusualPunctuation =
[ (x,y) | x <- [1..a], y <- [1..b] ] where {
b = 7;
a = 6 }
preferredLayout = [ (x,y) | x <- [1..a], y <- [1..b] ]
where b = 7
a = 6If the right hand side of an equation starts on a new line, it's usually indented a small number of spaces relative to the name of the variable or function that it's defining.
normalIndent =
undefined
strangeIndent =
undefinedThe actual number of spaces used to indent varies, sometimes within a single file. Depths of two, three, and four spaces are about equally common. A single space is legal, but not very visually distinctive, so it's easy to misread.
When indenting a where clause, it's best to make it
visually distinctive.
goodWhere = take 5 lambdas
where lambdas = []
alsoGood =
take 5 lambdas
where
lambdas = []
badWhere = -- legal, but ugly and hard to read
take 5 lambdas
where
lambdas = []While the traverse function gives us
more control than our original betterFind
function, it still has a significant failing: we can avoid
recursing into directories, but we can't filter other names
until after we've generated the entire list of names in a tree.
If we are traversing a directory containing 100,000 files of
which we care about three, we'll allocate a 100,000-element list
before we have a chance to trim it down to the three we really
want.
One approach would be to provide a filter function as a new
argument to traverse, which we would apply
to the list of names as we generate it. This would allow us to
allocate a list of only as many elements as we need.
However, this approach also has a weakness: say we know that we want at most three entries from our list, and that those three entries happen to be the first three of the 100,000 that we traverse. In this case, we'll needlessly visit 99,997 other entries. This is not by any means a contrived example: for example, the Maildir mailbox format stores a folder of email messages as a directory of individual files. It's common for a single directory representing a mailbox to contain tens of thousands of files.
We can address the weaknesses of our two prior traversal functions by taking a different perspective: what if we think of filesystem traversal as a fold over the directory hierarchy?
The familiar folds, foldr and
foldl', neatly generalise the idea of
traversing a list while accumulating a result. It's hardly a
stretch to extend the idea of folding from lists to directory
trees, but we'd like to add an element of
control to our fold. We'll represent this
control as an algebraic data type.
data Iterate seed = Done { unwrap :: seed }
| Skip { unwrap :: seed }
| Recurse { unwrap :: seed }
deriving (Show)
type Iterator seed = seed -> Info -> Iterate seedThe Iterator type gives us a convenient alias for the function that we fold with. It takes a seed and an Info value representing a directory entry, and returns both a new seed and an instruction for our fold function, where the instructions are represented as the constructors of the Iterate type.
If the instruction is Done, traversal
should cease immediately. The value wrapped by
Done should be returned as the result.
If the instruction is Skip and the current
Info represents a directory, traversal will not
recurse into that directory.
Otherwise, the traversal should continue, using the wrapped value as the input to the next call to the fold function.
Our fold is logically a kind of left fold, because we start folding from the first entry we encounter, and the seed for each step is the result of the prior step.
foldTree :: Iterator a -> a -> FilePath -> IO a
foldTree iter seed path = unwrap `liftM` fold seed path
where
fold seed path = getUsefulContents path >>= walk seed
where
walk seed (name:names) = do
let path' = path </> name
info <- getInfo path'
case iter seed info of
done@(Done _) -> return done
Skip seed' -> walk seed' names
Recurse seed' ->
if isDirectory info
then do next <- fold seed' path'
case next of
done@(Done _) -> return done
seed'' -> walk (unwrap seed'') names
else walk seed' names
walk seed _ = return (Recurse seed)There are a few interesting things about the way this code
is written. The first is the use of scoping to avoid having to
pass extra parameters around. The top-level
foldTree function is just a wrapper for
fold that peels off the constructor of the
fold's final result.
Because fold is a local function, we
don't have to pass foldTree's
iter variable into it; it can already access
it in the outer scope. Similarly, walk can
see path in its outer scope. Even though
both fold and foldTree
have variables named path, Haskell's scope
rules ensure that path in the closest
enclosing scope (fold) is the one that
walk can see.
Another point to note is that walk is a
tali recursive loop, instead of an anonymous function called by
forM as in our earlier functions. By
taking the reins ourselves, we can stop early if we need to.
This lets us drop out when our iterator returns
Done.
Although fold calls
walk, walk calls
fold recursively to traverse
subdirectories. Each function returns a seed wrapped in an
Iterate: when fold is called
by walk and returns,
walk examines its result to see whether it
should continue or drop out because it returned
Done. In this way, a return of
Done from the called-supplied iterator
immediately terminates all mutually recursive calls between the
two functions.
What does an iterator look like in practice? Here's a somewhat complicated example that looks for at most three bitmap images, and won't recurse into Subversion metadata directories.
atMostThreePictures :: Iterator [FilePath]
atMostThreePictures paths info =
if isDirectory info && takeBaseName path == ".svn"
then Skip paths
else if extension `elem` ["jpg", "png"] && length paths' == 3
then Done paths'
else Recurse paths'
where extension = map toLower (takeExtension path)
path = infoPath info
paths' = path : pathsTo use this, we'd call foldTree atMostThreePictures
[], giving us a return value of type IO
[FilePath].
Of course, iterators don't have to be this complicated. Here's one that counts the number of directories it encounters.
countDirectories count info =
Recurse (if isDirectory info
then count + 1
else count)Here, the initial seed that we pass to
foldTree should be the number zero.
One of the things that makes our
atMostThreePictures function a little
unwieldy is the nesting of if expressions. Although Haskell
doesn't have multi-way if expressions (often seen in other
languages as else if or elif
blocks), we can emulate them as follows.
Write a case expression, using
undefined as the expression to evaluate,
and a single wild card as the only pattern. Write each branch
of the multi-way if as a guard expression on that
pattern.
secondTake paths info =
case undefined of
_ | isDirectory info && takeBaseName path == ".svn"
-> Skip paths
| extension `elem` ["jpg", "png"] && length paths' == 3
-> Done paths'
| otherwise
-> Recurse paths'
where extension = map toLower (takeExtension path)
path = infoPath info
paths' = path : pathsThis trick relies on Haskell's non-strict evaluation.
Because we use a wild card as a pattern, it doesn't matter
what the expression we're matching on is: it won't be
evaluated. We match on undefined (which
would throw an exception if it were actually evaluated) as a
form of documentation, to make it explicit that we're not
using the case expression in the usual way.
This is a useful form to remember when you have a
complicated series of if expressions that would otherwise be
deeply nested. Often, such expressions tend to march off the
right hand side of the screen as each successive level of
nesting requires more indentation. Using this trick, we get a
clean sequence of as many expressions as we need, each
starting in the same column.