PEP 346 – User Defined (”with
”) Statements
- Author:
- Nick Coghlan <ncoghlan at gmail.com>
- Status:
- Withdrawn
- Type:
- Standards Track
- Created:
- 06-May-2005
- Python-Version:
- 2.5
- Post-History:
Table of Contents
- Abstract
- Author’s Note
- Introduction
- Relationship with other PEPs
- User defined statements
- Generators
- Default value for
yield
- Template generator decorator:
statement_template
- Template generator wrapper:
__enter__()
method - Template generator wrapper:
__exit__()
method - Injecting exceptions into generators
- Generator finalisation
- Generator finalisation:
TerminateIteration
exception - Generator finalisation:
__del__()
method - Deterministic generator finalisation
- Generators as user defined statement templates
- Default value for
- Examples
- Open Issues
- Rejected Options
- Having the basic construct be a looping construct
- Allowing statement templates to suppress exceptions
- Differentiating between non-exceptional exits
- Not injecting raised exceptions into generators
- Making all generators statement templates
- Using
do
as the keyword - Not having a keyword
- Enhancing
try
statements - Having the template protocol directly reflect
try
statements
- Iterator finalisation (WITHDRAWN)
- Acknowledgements
- References
- Copyright
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.
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, PEP 340 and PEP 343, as those PEPs all describe alternative mechanisms for handling deterministic resource management.
It does not compete with PEP 342 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. 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 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
- 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).
- 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()
- 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
- 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()
- 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"
- 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")
- Find the first file with a specific header:
for name in filenames: with open(name) as f: if f.read(2) == 0xFEB0: break
- 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
- 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
- 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)
- 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!"
- 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.
- 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 [1].
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 [2].
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
Copyright
This document has been placed in the public domain.
Source: https://github.com/python/peps/blob/main/pep-0346.txt
Last modified: 2022-01-21 11:03:51 GMT