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PEP 346 -- User Defined ("with") Statements

PEP:346
Title:User Defined ("with") Statements
Author:Nick Coghlan <ncoghlan at gmail.com>
Status:Withdrawn
Type:Standards Track
Created:6-May-2005
Python-Version:2.5
Post-History:

Abstract

This PEP is a combination of PEP 310's "Reliable Acquisition/Release Pairs" with the "Anonymous Block Statements" of Guido's PEP 340. This PEP aims to take the good parts of PEP 340, blend them with parts of PEP 310 and rearrange the lot into an elegant whole. It borrows from various other PEPs in order to paint a complete picture, and is intended to stand on its own.

Author's Note

During the discussion of PEP 340, I maintained drafts of this PEP as PEP 3XX on my own website (since I didn't have CVS access to update a submitted PEP fast enough to track the activity on python-dev).

Since the first draft of this PEP, Guido wrote PEP 343 as a simplified version of PEP 340. PEP 343 (at the time of writing) uses the exact same semantics for the new statements as this PEP, but uses a slightly different mechanism to allow generators to be used to write statement templates. However, Guido has indicated that he intends to accept a new PEP being written by Raymond Hettinger that will integrate PEP 288 and PEP 325, and will permit a generator decorator like the one described in this PEP to be used to write statement templates for PEP 343. The other difference was the choice of keyword ('with' versus 'do') and Guido has stated he will organise a vote on that in the context of PEP 343.

Accordingly, the version of this PEP submitted for archiving on python.org is to be WITHDRAWN immediately after submission. PEP 343 and the combined generator enhancement PEP will cover the important ideas.

Introduction

This PEP proposes that Python's ability to reliably manage resources be enhanced by the introduction of a new with statement that allows factoring out of arbitrary try/finally and some try/except/else boilerplate. The new construct is called a 'user defined statement', and the associated class definitions are called 'statement templates'.

The above is the main point of the PEP. However, if that was all it said, then PEP 310 would be sufficient and this PEP would be essentially redundant. Instead, this PEP recommends additional enhancements that make it natural to write these statement templates using appropriately decorated generators. A side effect of those enhancements is that it becomes important to appropriately deal with the management of resources inside generators.

This is quite similar to PEP 343, but the exceptions that occur are re-raised inside the generators frame, and the issue of generator finalisation needs to be addressed as a result. The template generator decorator suggested by this PEP also creates reusable templates, rather than the single use templates of PEP 340.

In comparison to PEP 340, this PEP eliminates the ability to suppress exceptions, and makes the user defined statement a non-looping construct. The other main difference is the use of a decorator to turn generators into statement templates, and the incorporation of ideas for addressing iterator finalisation.

If all that seems like an ambitious operation. . . well, Guido was the one to set the bar that high when he wrote PEP 340 :)

Relationship with other PEPs

This PEP competes directly with PEP 310 [1], PEP 340 [2] and PEP 343 [3], as those PEPs all describe alternative mechanisms for handling deterministic resource management.

It does not compete with PEP 342 [4] which splits off PEP 340's enhancements related to passing data into iterators. The associated changes to the for loop semantics would be combined with the iterator finalisation changes suggested in this PEP. User defined statements would not be affected.

Neither does this PEP compete with the generator enhancements described in PEP 288 [5]. While this PEP proposes the ability to inject exceptions into generator frames, it is an internal implementation detail, and does not require making that ability publicly available to Python code. PEP 288 is, in part, about making that implementation detail easily accessible.

This PEP would, however, make the generator resource release support described in PEP 325 [6] redundant - iterators which require finalisation should provide an appropriate implementation of the statement template protocol.

User defined statements

To steal the motivating example from PEP 310, correct handling of a synchronisation lock currently looks like this:

the_lock.acquire()
try:
    # Code here executes with the lock held
finally:
    the_lock.release()

Like PEP 310, this PEP proposes that such code be able to be written as:

with the_lock:
    # Code here executes with the lock held

These user defined statements are primarily designed to allow easy factoring of try blocks that are not easily converted to functions. This is most commonly the case when the exception handling pattern is consistent, but the body of the try block changes. With a user-defined statement, it is straightforward to factor out the exception handling into a statement template, with the body of the try clause provided inline in the user code.

The term 'user defined statement' reflects the fact that the meaning of a with statement is governed primarily by the statement template used, and programmers are free to create their own statement templates, just as they are free to create their own iterators for use in for loops.

Usage syntax for user defined statements

The proposed syntax is simple:

with EXPR1 [as VAR1]:
    BLOCK1

Semantics for user defined statements

the_stmt = EXPR1
stmt_enter = getattr(the_stmt, "__enter__", None)
stmt_exit = getattr(the_stmt, "__exit__", None)
if stmt_enter is None or stmt_exit is None:
    raise TypeError("Statement template required")

VAR1 = stmt_enter() # Omit 'VAR1 =' if no 'as' clause
exc = (None, None, None)
try:
    try:
        BLOCK1
    except:
        exc = sys.exc_info()
        raise
finally:
    stmt_exit(*exc)

Other than VAR1, none of the local variables shown above will be visible to user code. Like the iteration variable in a for loop, VAR1 is visible in both BLOCK1 and code following the user defined statement.

Note that the statement template can only react to exceptions, it cannot suppress them. See Rejected Options for an explanation as to why.

Statement template protocol: __enter__

The __enter__() method takes no arguments, and if it raises an exception, BLOCK1 is never executed. If this happens, the __exit__() method is not called. The value returned by this method is assigned to VAR1 if the as clause is used. Object's with no other value to return should generally return self rather than None to permit in-place creation in the with statement.

Statement templates should use this method to set up the conditions that are to exist during execution of the statement (e.g. acquisition of a synchronisation lock).

Statement templates which are not always usable (e.g. closed file objects) should raise a RuntimeError if an attempt is made to call __enter__() when the template is not in a valid state.

Statement template protocol: __exit__

The __exit__() method accepts three arguments which correspond to the three "arguments" to the raise statement: type, value, and traceback. All arguments are always supplied, and will be set to None if no exception occurred. This method will be called exactly once by the with statement machinery if the __enter__() method completes successfully.

Statement templates perform their exception handling in this method. If the first argument is None, it indicates non-exceptional completion of BLOCK1 - execution either reached the end of block, or early completion was forced using a return, break or continue statement. Otherwise, the three arguments reflect the exception that terminated BLOCK1.

Any exceptions raised by the __exit__() method are propagated to the scope containing the with statement. If the user code in BLOCK1 also raised an exception, that exception would be lost, and replaced by the one raised by the __exit__() method.

Factoring out arbitrary exception handling

Consider the following exception handling arrangement:

SETUP_BLOCK
try:
    try:
        TRY_BLOCK
    except exc_type1, exc:
        EXCEPT_BLOCK1
    except exc_type2, exc:
        EXCEPT_BLOCK2
    except:
        EXCEPT_BLOCK3
    else:
        ELSE_BLOCK
finally:
    FINALLY_BLOCK

It can be roughly translated to a statement template as follows:

class my_template(object):

    def __init__(self, *args):
        # Any required arguments (e.g. a file name)
        # get stored in member variables
        # The various BLOCK's will need updating to reflect
        # that.

    def __enter__(self):
        SETUP_BLOCK

    def __exit__(self, exc_type, value, traceback):
        try:
            try:
                if exc_type is not None:
                    raise exc_type, value, traceback
            except exc_type1, exc:
                EXCEPT_BLOCK1
            except exc_type2, exc:
                EXCEPT_BLOCK2
            except:
                EXCEPT_BLOCK3
            else:
                ELSE_BLOCK
        finally:
            FINALLY_BLOCK

Which can then be used as:

with my_template(*args):
    TRY_BLOCK

However, there are two important semantic differences between this code and the original try statement.

Firstly, in the original try statement, if a break, return or continue statement is encountered in TRY_BLOCK, only FINALLY_BLOCK will be executed as the statement completes. With the statement template, ELSE_BLOCK will also execute, as these statements are treated like any other non-exceptional block termination. For use cases where it matters, this is likely to be a good thing (see transaction in the Examples), as this hole where neither the except nor the else clause gets executed is easy to forget when writing exception handlers.

Secondly, the statement template will not suppress any exceptions. If, for example, the original code suppressed the exc_type1 and exc_type2 exceptions, then this would still need to be done inline in the user code:

try:
    with my_template(*args):
        TRY_BLOCK
except (exc_type1, exc_type2):
    pass

However, even in these cases where the suppression of exceptions needs to be made explicit, the amount of boilerplate repeated at the calling site is significantly reduced (See Rejected Options for further discussion of this behaviour).

In general, not all of the clauses will be needed. For resource handling (like files or synchronisation locks), it is possible to simply execute the code that would have been part of FINALLY_BLOCK in the __exit__() method. This can be seen in the following implementation that makes synchronisation locks into statement templates as mentioned at the beginning of this section:

# New methods of synchronisation lock objects

def __enter__(self):
    self.acquire()
    return self

def __exit__(self, *exc_info):
    self.release()

Generators

With their ability to suspend execution, and return control to the calling frame, generators are natural candidates for writing statement templates. Adding user defined statements to the language does not require the generator changes described in this section, thus making this PEP an obvious candidate for a phased implementation (with statements in phase 1, generator integration in phase 2). The suggested generator updates allow arbitrary exception handling to be factored out like this:

@statement_template
def my_template(*arguments):
    SETUP_BLOCK
    try:
        try:
            yield
        except exc_type1, exc:
            EXCEPT_BLOCK1
        except exc_type2, exc:
            EXCEPT_BLOCK2
        except:
            EXCEPT_BLOCK3
        else:
            ELSE_BLOCK
    finally:
        FINALLY_BLOCK

Notice that, unlike the class based version, none of the blocks need to be modified, as shared values are local variables of the generator's internal frame, including the arguments passed in by the invoking code. The semantic differences noted earlier (all non-exceptional block termination triggers the else clause, and the template is unable to suppress exceptions) still apply.

Default value for yield

When creating a statement template with a generator, the yield statement will often be used solely to return control to the body of the user defined statement, rather than to return a useful value.

Accordingly, if this PEP is accepted, yield, like return, will supply a default value of None (i.e. yield and yield None will become equivalent statements).

This same change is being suggested in PEP 342. Obviously, it would only need to be implemented once if both PEPs were accepted :)

Template generator decorator: statement_template

As with PEP 343, a new decorator is suggested that wraps a generator in an object with the appropriate statement template semantics. Unlike PEP 343, the templates suggested here are reusable, as the generator is instantiated anew in each call to __enter__(). Additionally, any exceptions that occur in BLOCK1 are re-raised in the generator's internal frame:

class template_generator_wrapper(object):

    def __init__(self, func, func_args, func_kwds):
         self.func = func
         self.args = func_args
         self.kwds = func_kwds
         self.gen = None

    def __enter__(self):
        if self.gen is not None:
            raise RuntimeError("Enter called without exit!")
        self.gen = self.func(*self.args, **self.kwds)
        try:
            return self.gen.next()
        except StopIteration:
            raise RuntimeError("Generator didn't yield")

    def __exit__(self, *exc_info):
        if self.gen is None:
            raise RuntimeError("Exit called without enter!")
        try:
            try:
                if exc_info[0] is not None:
                    self.gen._inject_exception(*exc_info)
                else:
                    self.gen.next()
            except StopIteration:
                pass
            else:
                raise RuntimeError("Generator didn't stop")
        finally:
            self.gen = None

def statement_template(func):
    def factory(*args, **kwds):
        return template_generator_wrapper(func, args, kwds)
    return factory

Template generator wrapper: __enter__() method

The template generator wrapper has an __enter__() method that creates a new instance of the contained generator, and then invokes next() once. It will raise a RuntimeError if the last generator instance has not been cleaned up, or if the generator terminates instead of yielding a value.

Template generator wrapper: __exit__() method

The template generator wrapper has an __exit__() method that simply invokes next() on the generator if no exception is passed in. If an exception is passed in, it is re-raised in the contained generator at the point of the last yield statement.

In either case, the generator wrapper will raise a RuntimeError if the internal frame does not terminate as a result of the operation. The __exit__() method will always clean up the reference to the used generator instance, permitting __enter__() to be called again.

A StopIteration raised by the body of the user defined statement may be inadvertently suppressed inside the __exit__() method, but this is unimportant, as the originally raised exception still propagates correctly.

Injecting exceptions into generators

To implement the __exit__() method of the template generator wrapper, it is necessary to inject exceptions into the internal frame of the generator. This is new implementation level behaviour that has no current Python equivalent.

The injection mechanism (referred to as _inject_exception in this PEP) raises an exception in the generator's frame with the specified type, value and traceback information. This means that the exception looks like the original if it is allowed to propagate.

For the purposes of this PEP, there is no need to make this capability available outside the Python implementation code.

Generator finalisation

To support resource management in template generators, this PEP will eliminate the restriction on yield statements inside the try block of a try/finally statement. Accordingly, generators which require the use of a file or some such object can ensure the object is managed correctly through the use of try/finally or with statements.

This restriction will likely need to be lifted globally - it would be difficult to restrict it so that it was only permitted inside generators used to define statement templates. Accordingly, this PEP includes suggestions designed to ensure generators which are not used as statement templates are still finalised appropriately.

Generator finalisation: TerminateIteration exception

A new exception is proposed:

class TerminateIteration(Exception): pass

The new exception is injected into a generator in order to request finalisation. It should not be suppressed by well-behaved code.

Generator finalisation: __del__() method

To ensure a generator is finalised eventually (within the limits of Python's garbage collection), generators will acquire a __del__() method with the following semantics:

def __del__(self):
    try:
        self._inject_exception(TerminateIteration, None, None)
    except TerminateIteration:
        pass

Deterministic generator finalisation

There is a simple way to provide deterministic finalisation of generators - give them appropriate __enter__() and __exit__() methods:

def __enter__(self):
    return self

def __exit__(self, *exc_info):
    try:
        self._inject_exception(TerminateIteration, None, None)
    except TerminateIteration:
        pass

Then any generator can be finalised promptly by wrapping the relevant for loop inside a with statement:

with all_lines(filenames) as lines:
    for line in lines:
        print lines

(See the Examples for the definition of all_lines, and the reason it requires prompt finalisation)

Compare the above example to the usage of file objects:

with open(filename) as f:
    for line in f:
        print f

Generators as user defined statement templates

When used to implement a user defined statement, a generator should yield only once on a given control path. The result of that yield will then be provided as the result of the generator's __enter__() method. Having a single yield on each control path ensures that the internal frame will terminate when the generator's __exit__() method is called. Multiple yield statements on a single control path will result in a RuntimeError being raised by the __exit__() method when the internal frame fails to terminate correctly. Such an error indicates a bug in the statement template.

To respond to exceptions, or to clean up resources, it is sufficient to wrap the yield statement in an appropriately constructed try statement. If execution resumes after the yield without an exception, the generator knows that the body of the do statement completed without incident.

Examples

  1. A template for ensuring that a lock, acquired at the start of a block, is released when the block is left:

    # New methods on synchronisation locks
        def __enter__(self):
            self.acquire()
            return self
    
        def __exit__(self, *exc_info):
            lock.release()
    

    Used as follows:

    with myLock:
        # Code here executes with myLock held.  The lock is
        # guaranteed to be released when the block is left (even
        # if via return or by an uncaught exception).
    
  2. A template for opening a file that ensures the file is closed when the block is left:

    # New methods on file objects
        def __enter__(self):
            if self.closed:
                raise RuntimeError, "Cannot reopen closed file handle"
            return self
    
        def __exit__(self, *args):
            self.close()
    

    Used as follows:

    with open("/etc/passwd") as f:
        for line in f:
            print line.rstrip()
    
  3. A template for committing or rolling back a database transaction:

    def transaction(db):
        try:
            yield
        except:
            db.rollback()
        else:
            db.commit()
    

    Used as follows:

    with transaction(the_db):
        make_table(the_db)
        add_data(the_db)
        # Getting to here automatically triggers a commit
        # Any exception automatically triggers a rollback
    
  4. It is possible to nest blocks and combine templates:

    @statement_template
    def lock_opening(lock, filename, mode="r"):
        with lock:
            with open(filename, mode) as f:
                yield f
    

    Used as follows:

    with lock_opening(myLock, "/etc/passwd") as f:
        for line in f:
            print line.rstrip()
    
  5. Redirect stdout temporarily:

    @statement_template
    def redirected_stdout(new_stdout):
        save_stdout = sys.stdout
        try:
            sys.stdout = new_stdout
            yield
        finally:
            sys.stdout = save_stdout
    

    Used as follows:

    with open(filename, "w") as f:
        with redirected_stdout(f):
            print "Hello world"
    
  6. A variant on open() that also returns an error condition:

    @statement_template
    def open_w_error(filename, mode="r"):
        try:
            f = open(filename, mode)
        except IOError, err:
            yield None, err
        else:
            try:
                yield f, None
            finally:
                f.close()
    

    Used as follows:

    do open_w_error("/etc/passwd", "a") as f, err:
        if err:
            print "IOError:", err
        else:
            f.write("guido::0:0::/:/bin/sh\n")
    
  7. Find the first file with a specific header:

    for name in filenames:
        with open(name) as f:
            if f.read(2) == 0xFEB0:
                break
    
  8. Find the first item you can handle, holding a lock for the entire loop, or just for each iteration:

    with lock:
        for item in items:
            if handle(item):
                break
    
    for item in items:
        with lock:
            if handle(item):
                break
    
  9. Hold a lock while inside a generator, but release it when returning control to the outer scope:

    @statement_template
    def released(lock):
        lock.release()
        try:
            yield
        finally:
            lock.acquire()
    

    Used as follows:

    with lock:
        for item in items:
            with released(lock):
                yield item
    
  10. Read the lines from a collection of files (e.g. processing multiple configuration sources):

    def all_lines(filenames):
        for name in filenames:
            with open(name) as f:
                for line in f:
                    yield line
    

    Used as follows:

    with all_lines(filenames) as lines:
        for line in lines:
            update_config(line)
    
  11. Not all uses need to involve resource management:

    @statement_template
    def tag(*args, **kwds):
        name = cgi.escape(args[0])
        if kwds:
            kwd_pairs = ["%s=%s" % cgi.escape(key), cgi.escape(value)
                         for key, value in kwds]
            print '<%s %s>' % name, " ".join(kwd_pairs)
        else:
            print '<%s>' % name
        yield
        print '</%s>' % name
    

    Used as follows:

    with tag('html'):
        with tag('head'):
           with tag('title'):
              print 'A web page'
        with tag('body'):
           for par in pars:
              with tag('p'):
                 print par
           with tag('a', href="http://www.python.org"):
               print "Not a dead parrot!"
    
  12. From PEP 343, another useful example would be an operation that blocks signals. The use could be like this:

    from signal import blocked_signals
    
    with blocked_signals():
        # code executed without worrying about signals
    

    An optional argument might be a list of signals to be blocked; by default all signals are blocked. The implementation is left as an exercise to the reader.

  13. Another use for this feature is for Decimal contexts:

    # New methods on decimal Context objects
    
    def __enter__(self):
        if self._old_context is not None:
            raise RuntimeError("Already suspending other Context")
        self._old_context = getcontext()
        setcontext(self)
    
    def __exit__(self, *args):
        setcontext(self._old_context)
        self._old_context = None
    

    Used as follows:

    with decimal.Context(precision=28):
       # Code here executes with the given context
       # The context always reverts after this statement
    

Open Issues

None, as this PEP has been withdrawn.

Rejected Options

Having the basic construct be a looping construct

The major issue with this idea, as illustrated by PEP 340's block statements, is that it causes problems with factoring try statements that are inside loops, and contain break and continue statements (as these statements would then apply to the block construct, instead of the original loop). As a key goal is to be able to factor out arbitrary exception handling (other than suppression) into statement templates, this is a definite problem.

There is also an understandability problem, as can be seen in the Examples. In the example showing acquisition of a lock either for an entire loop, or for each iteration of the loop, if the user defined statement was itself a loop, moving it from outside the for loop to inside the for loop would have major semantic implications, beyond those one would expect.

Finally, with a looping construct, there are significant problems with TOOWTDI, as it is frequently unclear whether a particular situation should be handled with a conventional for loop or the new looping construct. With the current PEP, there is no such problem - for loops continue to be used for iteration, and the new do statements are used to factor out exception handling.

Another issue, specifically with PEP 340's anonymous block statements, is that they make it quite difficult to write statement templates directly (i.e. not using a generator). This problem is addressed by the current proposal, as can be seen by the relative simplicity of the various class based implementations of statement templates in the Examples.

Allowing statement templates to suppress exceptions

Earlier versions of this PEP gave statement templates the ability to suppress exceptions. The BDFL expressed concern over the associated complexity, and I agreed after reading an article by Raymond Chen about the evils of hiding flow control inside macros in C code [7].

Removing the suppression ability eliminated a whole lot of complexity from both the explanation and implementation of user defined statements, further supporting it as the correct choice. Older versions of the PEP had to jump through some horrible hoops to avoid inadvertently suppressing exceptions in __exit__() methods - that issue does not exist with the current suggested semantics.

There was one example (auto_retry) that actually used the ability to suppress exceptions. This use case, while not quite as elegant, has significantly more obvious control flow when written out in full in the user code:

def attempts(num_tries):
    return reversed(xrange(num_tries))

for retry in attempts(3):
    try:
        make_attempt()
    except IOError:
        if not retry:
            raise

For what it's worth, the perverse could still write this as:

for attempt in auto_retry(3, IOError):
    try:
        with attempt:
            make_attempt()
    except FailedAttempt:
        pass

To protect the innocent, the code to actually support that is not included here.

Differentiating between non-exceptional exits

Earlier versions of this PEP allowed statement templates to distinguish between exiting the block normally, and exiting via a return, break or continue statement. The BDFL flirted with a similar idea in PEP 343 and its associated discussion. This added significant complexity to the description of the semantics, and it required each and every statement template to decide whether or not those statements should be treated like exceptions, or like a normal mechanism for exiting the block.

This template-by-template decision process raised great potential for confusion - consider if one database connector provided a transaction template that treated early exits like an exception, whereas a second connector treated them as normal block termination.

Accordingly, this PEP now uses the simplest solution - early exits appear identical to normal block termination as far as the statement template is concerned.

Not injecting raised exceptions into generators

PEP 343 suggests simply invoking next() unconditionally on generators used to define statement templates. This means the template generators end up looking rather unintuitive, and the retention of the ban against yielding inside try/finally means that Python's exception handling capabilities cannot be used to deal with management of multiple resources.

The alternative which this PEP advocates (injecting raised exceptions into the generator frame), means that multiple resources can be managed elegantly as shown by lock_opening in the Examples

Making all generators statement templates

Separating the template object from the generator itself makes it possible to have reusable generator templates. That is, the following code will work correctly if this PEP is accepted:

open_it = lock_opening(parrot_lock, "dead_parrot.txt")

with open_it as f:
    # use the file for a while

with open_it as f:
    # use the file again

The second benefit is that iterator generators and template generators are very different things - the decorator keeps that distinction clear, and prevents one being used where the other is required.

Finally, requiring the decorator allows the native methods of generator objects to be used to implement generator finalisation.

Using do as the keyword

do was an alternative keyword proposed during the PEP 340 discussion. It reads well with appropriately named functions, but it reads poorly when used with methods, or with objects that provide native statement template support.

When do was first suggested, the BDFL had rejected PEP 310's with keyword, based on a desire to use it for a Pascal/Delphi style with statement. Since then, the BDFL has retracted this objection, as he no longer intends to provide such a statement. This change of heart was apparently based on the C# developers reasons for not providing the feature [8].

Not having a keyword

This is an interesting option, and can be made to read quite well. However, it's awkward to look up in the documentation for new users, and strikes some as being too magical. Accordingly, this PEP goes with a keyword based suggestion.

Enhancing try statements

This suggestion involves give bare try statements a signature similar to that proposed for with statements.

I think that trying to write a with statement as an enhanced try statement makes as much sense as trying to write a for loop as an enhanced while loop. That is, while the semantics of the former can be explained as a particular way of using the latter, the former is not an instance of the latter. The additional semantics added around the more fundamental statement result in a new construct, and the two different statements shouldn't be confused.

This can be seen by the fact that the 'enhanced' try statement still needs to be explained in terms of a 'non-enhanced' try statement. If it's something different, it makes more sense to give it a different name.

Having the template protocol directly reflect try statements

One suggestion was to have separate methods in the protocol to cover different parts of the structure of a generalised try statement. Using the terms try, except, else and finally, we would have something like:

class my_template(object):

    def __init__(self, *args):
        # Any required arguments (e.g. a file name)
        # get stored in member variables
        # The various BLOCK's will need to updated to reflect
        # that.

    def __try__(self):
        SETUP_BLOCK

    def __except__(self, exc, value, traceback):
        if isinstance(exc, exc_type1):
            EXCEPT_BLOCK1
        if isinstance(exc, exc_type2):
            EXCEPT_BLOCK2
        else:
            EXCEPT_BLOCK3

    def __else__(self):
        ELSE_BLOCK

    def __finally__(self):
        FINALLY_BLOCK

Aside from preferring the addition of two method slots rather than four, I consider it significantly easier to be able to simply reproduce a slightly modified version of the original try statement code in the __exit__() method (as shown in Factoring out arbitrary exception handling), rather than have to split the functionality amongst several different methods (or figure out which method to use if not all clauses are used by the template).

To make this discussion less theoretical, here is the transaction example implemented using both the two method and the four method protocols instead of a generator. Both implementations guarantee a commit if a break, return or continue statement is encountered (as does the generator-based implementation in the Examples section):

class transaction_2method(object):

    def __init__(self, db):
        self.db = db

    def __enter__(self):
        pass

    def __exit__(self, exc_type, *exc_details):
        if exc_type is None:
            self.db.commit()
        else:
            self.db.rollback()

class transaction_4method(object):

    def __init__(self, db):
        self.db = db
        self.commit = False

    def __try__(self):
        self.commit = True

    def __except__(self, exc_type, exc_value, traceback):
        self.db.rollback()
        self.commit = False

    def __else__(self):
        pass

    def __finally__(self):
        if self.commit:
            self.db.commit()
            self.commit = False

There are two more minor points, relating to the specific method names in the suggestion. The name of the __try__() method is misleading, as SETUP_BLOCK executes before the try statement is entered, and the name of the __else__() method is unclear in isolation, as numerous other Python statements include an else clause.

Iterator finalisation (WITHDRAWN)

The ability to use user defined statements inside generators is likely to increase the need for deterministic finalisation of iterators, as resource management is pushed inside the generators, rather than being handled externally as is currently the case.

The PEP currently suggests handling this by making all generators statement templates, and using with statements to handle finalisation. However, earlier versions of this PEP suggested the following, more complex, solution, that allowed the author of a generator to flag the need for finalisation, and have for loops deal with it automatically. It is included here as a long, detailed rejected option.

Iterator protocol addition: __finish__

An optional new method for iterators is proposed, called __finish__(). It takes no arguments, and should not return anything.

The __finish__ method is expected to clean up all resources the iterator has open. Iterators with a __finish__() method are called 'finishable iterators' for the remainder of the PEP.

Best effort finalisation

A finishable iterator should ensure that it provides a __del__ method that also performs finalisation (e.g. by invoking the __finish__() method). This allows Python to still make a best effort at finalisation in the event that deterministic finalisation is not applied to the iterator.

Deterministic finalisation

If the iterator used in a for loop has a __finish__() method, the enhanced for loop semantics will guarantee that that method will be executed, regardless of the means of exiting the loop. This is important for iterator generators that utilise user defined statements or the now permitted try/finally statements, or for new iterators that rely on timely finalisation to release allocated resources (e.g. releasing a thread or database connection back into a pool).

for loop syntax

No changes are suggested to for loop syntax. This is just to define the statement parts needed for the description of the semantics:

for VAR1 in EXPR1:
    BLOCK1
else:
    BLOCK2

Updated for loop semantics

When the target iterator does not have a __finish__() method, a for loop will execute as follows (i.e. no change from the status quo):

itr = iter(EXPR1)
exhausted = False
while True:
    try:
        VAR1 = itr.next()
    except StopIteration:
        exhausted = True
        break
    BLOCK1
if exhausted:
    BLOCK2

When the target iterator has a __finish__() method, a for loop will execute as follows:

itr = iter(EXPR1)
exhausted = False
try:
    while True:
        try:
            VAR1 = itr.next()
        except StopIteration:
            exhausted = True
            break
        BLOCK1
    if exhausted:
        BLOCK2
finally:
    itr.__finish__()

The implementation will need to take some care to avoid incurring the try/finally overhead when the iterator does not have a __finish__() method.

Generator iterator finalisation: __finish__() method

When enabled with the appropriate decorator, generators will have a __finish__() method that raises TerminateIteration in the internal frame:

def __finish__(self):
    try:
        self._inject_exception(TerminateIteration)
    except TerminateIteration:
        pass

A decorator (e.g. needs_finish()) is required to enable this feature, so that existing generators (which are not expecting finalisation) continue to work as expected.

Partial iteration of finishable iterators

Partial iteration of a finishable iterator is possible, although it requires some care to ensure the iterator is still finalised promptly (it was made finishable for a reason!). First, we need a class to enable partial iteration of a finishable iterator by hiding the iterator's __finish__() method from the for loop:

class partial_iter(object):

    def __init__(self, iterable):
        self.iter = iter(iterable)

    def __iter__(self):
        return self

    def next(self):
        return self.itr.next()

Secondly, an appropriate statement template is needed to ensure the iterator is finished eventually:

@statement_template
def finishing(iterable):
      itr = iter(iterable)
      itr_finish = getattr(itr, "__finish__", None)
      if itr_finish is None:
          yield itr
      else:
          try:
              yield partial_iter(itr)
          finally:
              itr_finish()

This can then be used as follows:

do finishing(finishable_itr) as itr:
    for header_item in itr:
        if end_of_header(header_item):
            break
        # process header item
    for body_item in itr:
        # process body item

Note that none of the above is needed for an iterator that is not finishable - without a __finish__() method, it will not be promptly finalised by the for loop, and hence inherently allows partial iteration. Allowing partial iteration of non-finishable iterators as the default behaviour is a key element in keeping this addition to the iterator protocol backwards compatible.

Acknowledgements

The acknowledgements section for PEP 340 applies, since this text grew out of the discussion of that PEP, but additional thanks go to Michael Hudson, Paul Moore and Guido van Rossum for writing PEP 310 and PEP 340 in the first place, and to (in no meaningful order) Fredrik Lundh, Phillip J. Eby, Steven Bethard, Josiah Carlson, Greg Ewing, Tim Delaney and Arnold deVos for prompting particular ideas that made their way into this text.

References

[1]Reliable Acquisition/Release Pairs (http://www.python.org/dev/peps/pep-0310/)
[2]Anonymous block statements (http://www.python.org/dev/peps/pep-0340/)
[3]Anonymous blocks, redux (http://www.python.org/dev/peps/pep-0343/)
[4]Enhanced Iterators (http://www.python.org/dev/peps/pep-0342/)
[5]Generator Attributes and Exceptions (http://www.python.org/dev/peps/pep-0288/)
[6]Resource-Release Support for Generators (http://www.python.org/dev/peps/pep-0325/)
[7]A rant against flow control macros (http://blogs.msdn.com/oldnewthing/archive/2005/01/06/347666.aspx)
[8]Why doesn't C# have a 'with' statement? (http://msdn.microsoft.com/vcsharp/programming/language/ask/withstatement/)
Source: https://github.com/python/peps/blob/master/pep-0346.txt