Reference "Blocking" for scm_leave_guile/scm_enter_guile.

[bpt/guile.git] / doc / ref / libguile-concepts.texi

@c -*-texinfo-*-
@c This is part of the GNU Guile Reference Manual.
@c Copyright (C)  1996, 1997, 2000, 2001, 2002, 2003, 2004, 2005
@c   Free Software Foundation, Inc.
@c See the file guile.texi for copying conditions.

@page
@node General Libguile Concepts
@section General concepts for using libguile

When you want to embed the Guile Scheme interpreter into your program or
library, you need to link it against the @file{libguile} library
(@pxref{Linking Programs With Guile}).  Once you have done this, your C
code has access to a number of data types and functions that can be used
to invoke the interpreter, or make new functions that you have written
in C available to be called from Scheme code, among other things.

Scheme is different from C in a number of significant ways, and Guile
tries to make the advantages of Scheme available to C as well.  Thus, in
addition to a Scheme interpreter, libguile also offers dynamic types,
garbage collection, continuations, arithmetic on arbitrary sized
numbers, and other things.

The two fundamental concepts are dynamic types and garbage collection.
You need to understand how libguile offers them to C programs in order
to use the rest of libguile.  Also, the more general control flow of
Scheme caused by continuations needs to be dealt with.

Running asynchronous signal handlers and multi-threading is known to C
code already, but there are of course a few additional rules when using
them together with libguile.

@menu
* Dynamic Types::               Dynamic Types.
* Garbage Collection::          Garbage Collection.
* Control Flow::                Control Flow.
* Asynchronous Signals::        Asynchronous Signals
* Multi-Threading::             Multi-Threading
@end menu

@node Dynamic Types
@subsection Dynamic Types

Scheme is a dynamically-typed language; this means that the system
cannot, in general, determine the type of a given expression at compile
time.  Types only become apparent at run time.  Variables do not have
fixed types; a variable may hold a pair at one point, an integer at the
next, and a thousand-element vector later.  Instead, values, not
variables, have fixed types.

In order to implement standard Scheme functions like @code{pair?} and
@code{string?} and provide garbage collection, the representation of
every value must contain enough information to accurately determine its
type at run time.  Often, Scheme systems also use this information to
determine whether a program has attempted to apply an operation to an
inappropriately typed value (such as taking the @code{car} of a string).

Because variables, pairs, and vectors may hold values of any type,
Scheme implementations use a uniform representation for values --- a
single type large enough to hold either a complete value or a pointer
to a complete value, along with the necessary typing information.

In Guile, this uniform representation of all Scheme values is the C type
@code{SCM}.  This is an opaque type and its size is typically equivalent
to that of a pointer to @code{void}.  Thus, @code{SCM} values can be
passed around efficiently and they take up reasonably little storage on
their own.

The most important rule is: You never access a @code{SCM} value
directly; you only pass it to functions or macros defined in libguile.

As an obvious example, although a @code{SCM} variable can contain
integers, you can of course not compute the sum of two @code{SCM} values
by adding them with the C @code{+} operator.  You must use the libguile
function @code{scm_sum}.

Less obvious and therefore more important to keep in mind is that you
also cannot directly test @code{SCM} values for trueness.  In Scheme,
the value @code{#f} is considered false and of course a @code{SCM}
variable can represent that value.  But there is no guarantee that the
@code{SCM} representation of @code{#f} looks false to C code as well.
You need to use @code{scm_is_true} or @code{scm_is_false} to test a
@code{SCM} value for trueness or falseness, respectively.

You also can not directly compare two @code{SCM} values to find out
whether they are identical (that is, whether they are @code{eq?} in
Scheme terms).  You need to use @code{scm_is_eq} for this.

The one exception is that you can directly assign a @code{SCM} value to
a @code{SCM} variable by using the C @code{=} operator.

The following (contrieved) example shows how to do it right.  It
implements a function of two arguments (@var{a} and @var{flag}) that
returns @var{a}+1 if @var{flag} is true, else it returns @var{a}
unchanged.

@example
SCM
my_incrementing_function (SCM a, SCM flag)
@{
  SCM result;

  if (scm_is_true (flag))
    result = scm_sum (a, scm_from_int (1));
  else
    result = a;

  return result;
@}
@end example

Often, you need to convert between @code{SCM} values and approriate C
values.  For example, we needed to convert the integer @code{1} to its
@code{SCM} representation in order to add it to @var{a}.  Libguile
provides many function to do these conversions, both from C to
@code{SCM} and from @code{SCM} to C.

The conversion functions follow a common naming pattern: those that make
a @code{SCM} value from a C value have names of the form
@code{scm_from_@var{type} (@dots{})} and those that convert a @code{SCM}
value to a C value use the form @code{scm_to_@var{type} (@dots{})}.

However, it is best to avoid converting values when you can.  When you
must combine C values and @code{SCM} values in a computation, it is
often better to convert the C values to @code{SCM} values and do the
computation by using libguile functions than to the other way around
(converting @code{SCM} to C and doing the computation some other way).

As a simple example, consider this version of
@code{my_incrementing_function} from above:

@example
SCM
my_other_incrementing_function (SCM a, SCM flag)
@{
  int result;

  if (scm_is_true (flag))
    result = scm_to_int (a) + 1;
  else
    result = scm_to_int (a);

  return scm_from_int (result);
@}
@end example

This version is much less general than the original one: it will only
work for values @var{A} that can fit into a @code{int}.  The original
function will work for all values that Guile can represent and that
@code{scm_sum} can understand, including integers bigger than @code{long
long}, floating point numbers, complex numbers, and new numerical types
that have been added to Guile by third-party libraries.

Also, computing with @code{SCM} is not necessarily inefficient.  Small
integers will be encoded directly in the @code{SCM} value, for example,
and do not need any additional memory on the heap.  See @ref{Data
Representation} to find out the details.

Some special @code{SCM} values are available to C code without needing
to convert them from C values:

@multitable {Scheme value} {C representation}
@item Scheme value @tab C representation
@item @nicode{#f}  @tab @nicode{SCM_BOOL_F}
@item @nicode{#t}  @tab @nicode{SCM_BOOL_T}
@item @nicode{()}  @tab @nicode{SCM_EOL}
@end multitable

In addition to @code{SCM}, Guile also defines the related type
@code{scm_t_bits}.  This is an unsigned integral type of sufficient
size to hold all information that is directly contained in a
@code{SCM} value.  The @code{scm_t_bits} type is used internally by
Guile to do all the bit twiddling explained in @ref{Data
Representation}, but you will encounter it occasionally in low-level
user code as well.


@node Garbage Collection
@subsection Garbage Collection

As explained above, the @code{SCM} type can represent all Scheme values.
Some values fit entirely into a @code{SCM} value (such as small
integers), but other values require additional storage in the heap (such
as strings and vectors).  This additional storage is managed
automatically by Guile.  You don't need to explicitely deallocate it
when a @code{SCM} value is no longer used.

Two things must be guaranteed so that Guile is able to manage the
storage automatically: it must know about all blocks of memory that have
ever been allocated for Scheme values, and it must know about all Scheme
values that are still being used.  Given this knowledge, Guile can
periodically free all blocks that have been allocated but are not used
by any active Scheme values.  This activity is called @dfn{garbage
collection}.

It is easy for Guile to remember all blocks of memory that is has
allocated for use by Scheme values, but you need to help it with finding
all Scheme values that are in use by C code.

You do this when writing a SMOB mark function, for example
(@pxref{Garbage Collecting Smobs}).  By calling this function, the
garbage collector learns about all references that your SMOB has to
other @code{SCM} values.

Other references to @code{SCM} objects, such as global variables of type
@code{SCM} or other random data structures in the heap that contain
fields of type @code{SCM}, can be made visible to the garbage collector
by calling the functions @code{scm_gc_protect} or
@code{scm_permanent_object}.  You normally use these funtions for long
lived objects such as a hash table that is stored in a global variable.
For temporary references in local variables or function arguments, using
these functions would be too expensive.

These references are handled differently: Local variables (and function
arguments) of type @code{SCM} are automatically visible to the garbage
collector.  This works because the collector scans the stack for
potential references to @code{SCM} objects and considers all referenced
objects to be alive.  The scanning considers each and every word of the
stack, regardless of what it is actually used for, and then decides
whether it could possible be a reference to a @code{SCM} object.  Thus,
the scanning is guaranteed to find all actual references, but it might
also find words that only accidentally look like references.  These
`false positives' might keep @code{SCM} objects alive that would
otherwise be considered dead.  While this might waste memory, keeping an
object around longer than it strictly needs to is harmless.  This is why
this technique is called ``conservative garbage collection''.  In
practice, the wasted memory seems to be no problem.

The stack of every thread is scanned in this way and the registers of
the CPU and all other memory locations where local variables or function
parameters might show up are included in this scan as well.

The consequence of the conservative scanning is that you can just
declare local variables and function parameters of type @code{SCM} and
be sure that the garbage collector will not free the corresponding
objects.

However, a local variable or function parameter is only protected as
long as it is really on the stack (or in some register).  As an
optimization, the C compiler might reuse its location for some other
value and the @code{SCM} object would no longer be protected.  Normally,
this leads to exactly the right behabvior: the compiler will only
overwrite a reference when it is no longer needed and thus the object
becomes unprotected precisely when the reference disappears, just as
wanted.

There are situations, however, where a @code{SCM} object needs to be
around longer than its reference from a local variable or function
parameter.  This happens, for example, when you retrieve the array of
characters from a Scheme string and work on that array directly.  The
reference to the @code{SCM} string object might be dead after the
character array has been retrieved, but the array itself is still in use
and thus the string object must be protected.  The compiler does not
know about this connection and might overwrite the @code{SCM} reference
too early.

To get around this problem, you can use @code{scm_remember_upto_here_1}
and its cousins.  It will keep the compiler from overwriting the
reference.  For a typical example of its use, see @ref{Remembering
During Operations}.

@node Control Flow
@subsection Control Flow

Scheme has a more general view of program flow than C, both locally and
non-locally.

Controlling the local flow of control involves things like gotos, loops,
calling functions and returning from them.  Non-local control flow
refers to situations where the program jumps across one or more levels
of function activations without using the normal call or return
operations.

The primitive means of C for local control flow is the @code{goto}
statement, together with @code{if}.  Loops done with @code{for},
@code{while} or @code{do} could in principle be rewritten with just
@code{goto} and @code{if}.  In Scheme, the primitive means for local
control flow is the @emph{function call} (together with @code{if}).
Thus, the repetition of some computation in a loop is ultimately
implemented by a function that calls itself, that is, by recursion.

This approach is theoretically very powerful since it is easier to
reason formally about recursion than about gotos.  In C, using
recursion exclusively would not be practical, tho, since it would eat
up the stack very quickly.  In Scheme, however, it is practical:
function calls that appear in a @dfn{tail position} do not use any
additional stack space (@pxref{Tail Calls}).

A function call is in a tail position when it is the last thing the
calling function does.  The value returned by the called function is
immediately returned from the calling function.  In the following
example, the call to @code{bar-1} is in a tail position, while the
call to @code{bar-2} is not.  (The call to @code{1-} in @code{foo-2}
is in a tail position, tho.)

@lisp
(define (foo-1 x)
  (bar-1 (1- x)))

(define (foo-2 x)
  (1- (bar-2 x)))
@end lisp

Thus, when you take care to recurse only in tail positions, the
recursion will only use constant stack space and will be as good as a
loop constructed from gotos.

Scheme offers a few syntactic abstractions (@code{do} and @dfn{named}
@code{let}) that make writing loops slightly easier.

But only Scheme functions can call other functions in a tail position:
C functions can not.  This matters when you have, say, two functions
that call each other recursively to form a common loop.  The following
(unrealistic) example shows how one might go about determing whether a
non-negative integer @var{n} is even or odd.

@lisp
(define (my-even? n)
  (cond ((zero? n) #t)
        (else (my-odd? (1- n)))))

(define (my-odd? n)
  (cond ((zero? n) #f)
        (else (my-even? (1- n)))))
@end lisp

Because the calls to @code{my-even?} and @code{my-odd?} are in tail
positions, these two procedures can be applied to arbitrary large
integers without overflowing the stack.  (They will still take a lot
of time, of course.)

However, when one or both of the two procedures would be rewritten in
C, it could no longer call its companion in a tail position (since C
does not have this concept).  You might need to take this
consideration into account when deciding which parts of your program
to write in Scheme and which in C.

In addition to calling functions and returning from them, a Scheme
program can also exit non-locally from a function so that the control
flow returns directly to an outer level.  This means that some functions
might not return at all.

Even more, it is not only possible to jump to some outer level of
control, a Scheme program can also jump back into the middle of a
function that has already exited.  This might cause some functions to
return more than once.

In general, these non-local jumps are done by invoking
@dfn{continuations} that have previously been captured using
@code{call-with-current-continuation}.  Guile also offers a slightly
restricted set of functions, @code{catch} and @code{throw}, that can
only be used for non-local exits.  This restriction makes them more
efficient.  Error reporting (with the function @code{error}) is
implemented by invoking @code{throw}, for example.  The functions
@code{catch} and @code{throw} belong to the topic of @dfn{exceptions}.

Since Scheme functions can call C functions and vice versa, C code can
experience the more general control flow of Scheme as well.  It is
possible that a C function will not return at all, or will return more
than once.  While C does offer @code{setjmp} and @code{longjmp} for
non-local exits, it is still an unusual thing for C code.  In
contrast, non-local exits are very common in Scheme, mostly to report
errors.

You need to be prepared for the non-local jumps in the control flow
whenever you use a function from @code{libguile}: it is best to assume
that any @code{libguile} function might signal an error or run a pending
signal handler (which in turn can do arbitrary things).

It is often necessary to take cleanup actions when the control leaves a
function non-locally.  Also, when the control returns non-locally, some
setup actions might be called for.  For example, the Scheme function
@code{with-output-to-port} needs to modify the global state so that
@code{current-output-port} returns the port passed to
@code{with-output-to-port}.  The global output port needs to be reset to
its previous value when @code{with-output-to-port} returns normally or
when it is exited non-locally.  Likewise, the port needs to be set again
when control enters non-locally.

Scheme code can use the @code{dynamic-wind} function to arrange for the
setting and resetting of the global state.  C code could use the
corresponding @code{scm_internal_dynamic_wind} function, but it might
prefer to use the @dfn{frames} concept that is more natural for C code,
(@pxref{Frames}).

@node Asynchronous Signals
@subsection Asynchronous Signals

You can not call libguile functions from handlers for POSIX signals, but
you can register Scheme handlers for POSIX signals such as
@code{SIGINT}.  These handlers do not run during the actual signal
delivery.  Instead, they are run when the program (more precisely, the
thread that the handler has been registered for) reaches the next
@emph{safe point}.

The libguile functions themselves have many such safe points.
Consequently, you must be prepared for arbitrary actions anytime you
call a libguile function.  For example, even @code{scm_cons} can contain
a safe point and when a signal handler is pending for your thread,
calling @code{scm_cons} will run this handler and anything might happen,
including a non-local exit although @code{scm_cons} would not ordinarily
do such a thing on its own.

If you do not want to allow the running of asynchronous signal handlers,
you can block them temporarily with @code{scm_frame_block_asyncs}, for
example.  See @xref{System asyncs}.

Since signal handling in Guile relies on safe points, you need to make
sure that your functions do offer enough of them.  Normally, calling
libguile functions in the normal course of action is all that is needed.
But when a thread might spent a long time in a code section that calls
no libguile function, it is good to include explicit safe points.  This
can allow the user to interrupt your code with @key{C-c}, for example.

You can do this with the macro @code{SCM_TICK}.  This macro is
syntactically a statement.  That is, you could use it like this:

@example
while (1)
  @{
    SCM_TICK;
    do_some_work ();
  @}
@end example

Frequent execution of a safe point is even more important in multi
threaded programs, @xref{Multi-Threading}.

@node Multi-Threading
@subsection Multi-Threading

Guile can be used in multi-threaded programs just as well as in
single-threaded ones.

Each thread that wants to use functions from libguile must put itself
into @emph{guile mode} and must then follow a few rules.  If it doesn't
want to honor these rules in certain situations, a thread can
temporarily leave guile mode (but can no longer use libguile functions
during that time, of course).

Threads enter guile mode by calling @code{scm_with_guile},
@code{scm_boot_guile}, or @code{scm_init_guile}.  As explained in the
reference documentation for these functions, Guile will then learn about
the stack bounds of the thread and can protect the @code{SCM} values
that are stored in local variables.  When a thread puts itself into
guile mode for the first time, it gets a Scheme representation and is
listed by @code{all-threads}, for example.

While in guile mode, a thread promises to reach a safe point reasonably
frequently (@pxref{Asynchronous Signals}).  In addition to running
signal handlers, these points are also potential rendezvous points of
all guile mode threads where Guile can orchestrate global things like
garbage collection.  Consequently, when a thread in guile mode blocks
and does no longer frequent safe points, it might cause all other guile
mode threads to block as well.  To prevent this from happening, a guile
mode thread should either only block in libguile functions (who know how
to do it right), or should temporarily leave guile mode with
@code{scm_without_guile} or
@code{scm_leave_guile}/@code{scm_enter_guile}.

For some common blocking operations, Guile provides convenience
functions.  For example, if you want to lock a pthread mutex while in
guile mode, you might want to use @code{scm_pthread_mutex_lock} which is
just like @code{pthread_mutex_lock} except that it leaves guile mode
while blocking.


All libguile functions are (intended to be) robust in the face of
multiple threads using them concurrently.  This means that there is no
risk of the internal data structures of libguile becoming corrupted in
such a way that the process crashes.

A program might still produce non-sensical results, though.  Taking
hashtables as an example, Guile guarantees that you can use them from
multiple threads concurrently and a hashtable will always remain a valid
hashtable and Guile will not crash when you access it.  It does not
guarantee, however, that inserting into it concurrently from two threads
will give useful results: only one insertion might actually happen, none
might happen, or the table might in general be modified in a totally
arbitrary manner.  (It will still be a valid hashtable, but not the one
that you might have expected.)  Guile might also signal an error when it
detects a harmful race condition.

Thus, you need to put in additional synchronizations when multiple
threads want to use a single hashtable, or any other mutable Scheme
object.

When writing C code for use with libguile, you should try to make it
robust as well.  An example that converts a list into a vector will help
to illustrate.  Here is a correct version:

@example
SCM
my_list_to_vector (SCM list)
@{
  SCM vector = scm_make_vector (scm_length (list), SCM_UNDEFINED);
  size_t len, i;

  len = SCM_SIMPLE_VECTOR_LENGTH (vector);
  i = 0;
  while (i < len && scm_is_pair (list))
    @{
      SCM_SIMPLE_VECTOR_SET (vector, i, SCM_CAR (list));
      list = SCM_CDR (list);
      i++;
    @}

  return vector;
@}
@end example

The first thing to note is that storing into a @code{SCM} location
concurrently from multiple threads is guaranteed to be robust: you don't
know which value wins but it will in any case be a valid @code{SCM}
value.

But there is no guarantee that the list referenced by @var{list} is not
modified in another thread while the loop iterates over it.  Thus, while
copying its elements into the vector, the list might get longer or
shorter.  For this reason, the loop must check both that it doesn't
overrun the vector (@code{SCM_SIMPLE_VECTOR_SET} does no range-checking)
and that it doesn't overrung the list (@code{SCM_CAR} and @code{SCM_CDR}
likewise do no type checking).

It is safe to use @code{SCM_CAR} and @code{SCM_CDR} on the local
variable @var{list} once it is known that the variable contains a pair.
The contents of the pair might change spontaneously, but it will always
stay a valid pair (and a local variable will of course not spontaneously
point to a different Scheme object).

Likewise, a simple vector such as the one returned by
@code{scm_make_vector} is guaranteed to always stay the same length so
that it is safe to only use SCM_SIMPLE_VECTOR_LENGTH once and store the
result.  (In the example, @var{vector} is safe anyway since it is a
fresh object that no other thread can possibly know about until it is
returned from @code{my_list_to_vector}.)

Of course the behavior of @code{my_list_to_vector} is suboptimal when
@var{list} does indeed gets asynchronously lengthened or shortened in
another thread.  But it is robust: it will always return a valid vector.
That vector might be shorter than expected, or its last elements might
be unspecified, but it is a valid vector and if a program wants to rule
out these cases, it must avoid modifying the list asynchronously.

Here is another version that is also correct:

@example
SCM
my_pedantic_list_to_vector (SCM list)
@{
  SCM vector = scm_make_vector (scm_length (list), SCM_UNDEFINED);
  size_t len, i;

  len = SCM_SIMPLE_VECTOR_LENGTH (vector);
  i = 0;
  while (i < len)
    @{
      SCM_SIMPLE_VECTOR_SET (vector, i, scm_car (list));
      list = scm_cdr (list);
      i++;
    @}

  return vector;
@}
@end example

This version uses the type-checking and thread-robust functions
@code{scm_car} and @code{scm_cdr} instead of the faster, but less robust
macros @code{SCM_CAR} and @code{SCM_CDR}.  When the list is shortened
(that is, when @var{list} holds a non-pair), @code{scm_car} will throw
an error.  This might be preferable to just returning a half-initialized
vector.

The API for accessing vectors and arrays of various kinds from C takes a
slightly different approach to thread-robustness.  In order to get at
the raw memory that stores the elements of an array, you need to
@emph{reserve} that array as long as you need the raw memory.  During
the time an array is reserved, its elements can still spontaneously
change their values, but the memory itself and other things like the
size of the array are guaranteed to stay fixed.  Any operation that
would change these parameters of an array that is currently reserved
will signal an error.  In order to avoid these errors, a program should
of course put suitable synchronization mechanisms in place.  As you can
see, Guile itself is again only concerned about robustness, not about
correctness: without proper synchronization, your program will likely
not be correct, but the worst consequence is an error message.