Re: [Python-ideas] "old" values in postconditions
I am fine with your proposed syntax. It’s certainly lucid. Perhaps it would be a good idea to get people accustomed to “non-magic” syntax.
I still have a feeling that most developers would like to store the state in many different custom ways. Please explain. (Expressions like thunk(all)(a == b for a, b in P.arg.meth()) would be valid.) I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them).
Except for a > b > c being one flat expression with 5 members, it seems fairly easy to recreate an AST, which can then be compiled down to a code object. The code object can be fun with a custom “locals()” Below is my concept code for such a P object. from ast import * # not done: enforce Singleton property on EmptySymbolType class EmptySymbolType(object): ... EmptySymbol = EmptySymbolType() # empty symbols are placeholders class MockP(object): # "^" is xor @icontract.pre(lambda symbol, astnode: (symbol is None) ^ (astnode is None)) def __init__(self, symbol=None, value=EmptySymbol, astnode=None, initsymtable=(,)): self.symtable = dict(initsymtable) if symbol: self.expr = Expr(value=Name(id=symbol, ctx=Load())) self.symtable = {symbol: value} else: self.expr = astnode self.frozen = False def __add__(self, other): wrapped = MockP.wrap_value(other) return MockP(astnode=Expr(value=BinOp(self.expr, Add(), wrapped.expr), initsymtable={**self.symtable, **wrapped.symtable}) def compile(self): ... def freeze(self): # frozen objects wouldn’t have an overrided getattr, allowing for icontract to manipulate the MockP object using its public interface self.frozen = True @classmethod def wrap_value(cls, obj): # create a MockP object from a value. Generate a random identifier and set that as the key in symtable, the AST node is the name of that identifier, retrieving its value through simple expression evaluation. ... thunk = MockP.wrap_value P = MockP('P') # elsewhere: ensure P is only accessed via valid “dot attribute access” inside @snapshot so contracts fail early, or don’t and allow Magic like __dict__ to occur on P.
On Sep 27, 2018, at 9:49 PM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi James,
I still have a feeling that most developers would like to store the state in many different custom ways. I see also thunk and snapshot with wrapper objects to be much more complicated to implement and maintain; I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them). Then the linters need also to work around such wrappers... It might also scare users off since it looks like too much magic. Another concern I also have is that it's probably very hard to integrate these wrappers with mypy later -- but I don't really have a clue about that, only my gut feeling?
What about we accepted to repeat "lambda P, " prefix, and have something like this:
@snapshot( lambda P, some_name: len(P.some_property), lambda P, another_name: hash(P.another_property) )
It's not too verbose for me and you can still explain in three-four sentences what happens below the hub in the library's docs. A pycharm/pydev/vim/emacs plugins could hide the verbose parts.
I performed a small experiment to test how this solution plays with pylint and it seems OK that arguments are not used in lambdas.
Cheers, Marko
On Thu, 27 Sep 2018 at 12:27, James Lu <jamtlu@gmail.com> wrote: Why couldn’t we record the operations done to a special object and replay them?
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals etc.). Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (e.g., so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
from icontract import snapshot, P, thunk @snapshot(some_identifier=P.self.some_method(P.some_argument.some_attr))
P is an object of our own type, let’s call the type MockP. MockP returns new MockP objects when any operation is done to it. MockP * MockP = MockP. MockP.attr = MockP. MockP objects remember all the operations done to them, and allow the owner of a MockP object to re-apply the same operations
“thunk” converts a function or object or class to a MockP object, storing the function or object for when the operation is done.
thunk(function)(<MockP expression>)
Of course, you could also thunk objects like so: thunk(3) * P.number. (Though it might be better to keep the 3 after P.number in this case so P.number’s __mult__ would be invoked before 3’s __mult__ is invokes.
In most cases, you’d save any operations that can be done on a copy of the data as generated by @snapshot in @postcondiion. thunk is for rare scenarios where 1) it’s hard to capture the state, for example an object that manages network state (or database connectivity etc) and whose stage can only be read by an external classmethod 2) you want to avoid using copy.deepcopy.
I’m sure there’s some way to override isinstance through a meta class or dunder subclasshook.
I suppose this mocking method could be a shorthand for when you don’t need the full power of a lambda. It’s arguably more succinct and readable, though YMMV.
I look forward to reading your opinion on this and any ideas you might have.
On Sep 26, 2018, at 3:56 PM, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Yes, though if we’re talking syntax using kwargs would probably be better. Using “P” instead of “_”: (I agree that _ smells of ignored arguments)
@snapshot(some_identifier=lambda P: ..., some_identifier2=lambda P: ...)
Kwargs has the advantage that you can extend multiple lines without repeating @snapshot, though many lines of @capture would probably be more intuitive since each decorator captures one variable.
Why uppercase "P" and not lowercase (uppercase implies a constant for me)?
To me, the capital letters are more prominent and explicit- easier to see when reading code. It also implies its a constant for you- you shouldn’t be modifying it, because then you’d be interfering with the function itself.
Side node: maybe it would be good to have an @icontract.nomutate (probably use a different name, maybe @icontract.readonly) that makes sure a method doesn’t mutate its own __dict__ (and maybe the __dict__ of the members of its __dict__). It wouldn’t be necessary to put the decorator on every read only function, just the ones your worried might mutate.
Maybe a @icontract.nomutate(param=“paramname”) that ensures the __dict__ of all members of the param name have the same equality or identity before and after. The semantics would need to be worked out.
On Sep 26, 2018, at 8:58 AM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi James,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Am I correct?
"_" looks a bit hard to read for me (implying ignored arguments).
Why uppercase "P" and not lowercase (uppercase implies a constant for me)? Then "O" for "old" and "P" for parameters in a condition: @post(lambda O, P: ...) ?
It also has the nice property that it follows both the temporal and the alphabet order :)
On Wed, 26 Sep 2018 at 14:30, James Lu <jamtlu@gmail.com> wrote: I still prefer snapshot, though capture is a good name too. We could use generator syntax and inspect the argument names.
Instead of “a”, perhaps use “_”. Or maybe use “A.”, for arguments. Some people might prefer “P” for parameters, since parameters sometimes means the value received while the argument means the value passed.
(#A1)
from icontract import snapshot, __ @snapshot(some_func(_.some_argument.some_attr) for some_identifier, _ in __)
Or (#A2)
@snapshot(some_func(some_argument.some_attr) for some_identifier, _, some_argument in __)
— Or (#A3)
@snapshot(lambda some_argument,_,some_identifier: some_func(some_argument.some_attr))
Or (#A4)
@snapshot(lambda _,some_identifier: some_func(_.some_argument.some_attr)) @snapshot(lambda _,some_identifier, other_identifier: some_func(_.some_argument.some_attr), other_func(_.self))
I like #A4 the most because it’s fairly DRY and avoids the extra punctuation of
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)})
On Sep 26, 2018, at 12:23 AM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi,
Franklin wrote: > The name "before" is a confusing name. It's not just something that > happens before. It's really a pre-`let`, adding names to the scope of > things after it, but with values taken before the function call. Based > on that description, other possible names are `prelet`, `letbefore`, > `predef`, `defpre`, `beforescope`. Better a name that is clearly > confusing than one that is obvious but misleading.
James wrote: > I suggest that instead of “@before” it’s “@snapshot” and instead of “old” it’s “snapshot”.
I like "snapshot", it's a bit clearer than prefixing/postfixing verbs with "pre" which might be misread (e.g., "prelet" has a meaning in Slavic languages and could be subconsciously misread, "predef" implies to me a pre-definition rather than prior-to-definition , "beforescope" is very clear for me, but it might be confusing for others as to what it actually refers to ). What about "@capture" (7 letters for captures versus 8 for snapshot)? I suppose "@let" would be playing with fire if Python with conflicting new keywords since I assume "let" to be one of the candidates.
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals etc.). Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (e.g., so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
I'd still go with the dictionary to allow for this extra freedom. We could have a convention: "a" denotes to the current arguments, and "b" denotes the captured values. It might make an interesting hint that we put "b" before "a" in the condition. You could also interpret "b" as "before" and "a" as "after", but also "a" as "arguments".
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)}) @post(lambda b, a, result: b.some_identifier > result + a.another_argument.another_attr) def some_func(some_argument: SomeClass, another_argument: AnotherClass) -> SomeResult: ... "b" can be omitted if it is not used. Under the hub, all the arguments to the condition would be passed by keywords.
In case of inheritance, captures would be inherited as well. Hence the library would check at run-time that the returned dictionary with captured values has no identifier that has been already captured, and the linter checks that statically, before running the code. Reading values captured in the parent at the code of the child class might be a bit hard -- but that is case with any inherited methods/properties. In documentation, I'd list all the captures of both ancestor and the current class.
I'm looking forward to reading your opinion on this and alternative suggestions :) Marko
> On Tue, 25 Sep 2018 at 18:12, Franklin? Lee <leewangzhong+python@gmail.com> wrote: > On Sun, Sep 23, 2018 at 2:05 AM Marko Ristin-Kaufmann > <marko.ristin@gmail.com> wrote: > > > > Hi, > > > > (I'd like to fork from a previous thread, "Pre-conditions and post-conditions", since it got long and we started discussing a couple of different things. Let's discuss in this thread the implementation of a library for design-by-contract and how to push it forward to hopefully add it to the standard library one day.) > > > > For those unfamiliar with contracts and current state of the discussion in the previous thread, here's a short summary. The discussion started by me inquiring about the possibility to add design-by-contract concepts into the core language. The idea was rejected by the participants mainly because they thought that the merit of the feature does not merit its costs. This is quite debatable and seems to reflect many a discussion about design-by-contract in general. Please see the other thread, "Why is design-by-contract not widely adopted?" if you are interested in that debate. > > > > We (a colleague of mine and I) decided to implement a library to bring design-by-contract to Python since we don't believe that the concept will make it into the core language anytime soon and we needed badly a tool to facilitate our work with a growing code base. > > > > The library is available at http://github.com/Parquery/icontract. The hope is to polish it so that the wider community could use it and once the quality is high enough, make a proposal to add it to the standard Python libraries. We do need a standard library for contracts, otherwise projects with conflicting contract libraries can not integrate (e.g., the contracts can not be inherited between two different contract libraries). > > > > So far, the most important bits have been implemented in icontract: > > > > Preconditions, postconditions, class invariants > > Inheritance of the contracts (including strengthening and weakening of the inherited contracts) > > Informative violation messages (including information about the values involved in the contract condition) > > Sphinx extension to include contracts in the automatically generated documentation (sphinx-icontract) > > Linter to statically check that the arguments of the conditions are correct (pyicontract-lint) > > > > We are successfully using it in our code base and have been quite happy about the implementation so far. > > > > There is one bit still missing: accessing "old" values in the postcondition (i.e., shallow copies of the values prior to the execution of the function). This feature is necessary in order to allow us to verify state transitions. > > > > For example, consider a new dictionary class that has "get" and "put" methods: > > > > from typing import Optional > > > > from icontract import post > > > > class NovelDict: > > def length(self)->int: > > ... > > > > def get(self, key: str) -> Optional[str]: > > ... > > > > @post(lambda self, key, value: self.get(key) == value) > > @post(lambda self, key: old(self.get(key)) is None and old(self.length()) + 1 == self.length(), > > "length increased with a new key") > > @post(lambda self, key: old(self.get(key)) is not None and old(self.length()) == self.length(), > > "length stable with an existing key") > > def put(self, key: str, value: str) -> None: > > ... > > > > How could we possible implement this "old" function? > > > > Here is my suggestion. I'd introduce a decorator "before" that would allow you to store whatever values in a dictionary object "old" (i.e. an object whose properties correspond to the key/value pairs). The "old" is then passed to the condition. Here is it in code: > > > > # omitted contracts for brevity > > class NovelDict: > > def length(self)->int: > > ... > > > > # omitted contracts for brevity > > def get(self, key: str) -> Optional[str]: > > ... > > > > @before(lambda self, key: {"length": self.length(), "get": self.get(key)}) > > @post(lambda self, key, value: self.get(key) == value) > > @post(lambda self, key, old: old.get is None and old.length + 1 == self.length(), > > "length increased with a new key") > > @post(lambda self, key, old: old.get is not None and old.length == self.length(), > > "length stable with an existing key") > > def put(self, key: str, value: str) -> None: > > ... > > > > The linter would statically check that all attributes accessed in "old" have to be defined in the decorator "before" so that attribute errors would be caught early. The current implementation of the linter is fast enough to be run at save time so such errors should usually not happen with a properly set IDE. > > > > "before" decorator would also have "enabled" property, so that you can turn it off (e.g., if you only want to run a postcondition in testing). The "before" decorators can be stacked so that you can also have a more fine-grained control when each one of them is running (some during test, some during test and in production). The linter would enforce that before's "enabled" is a disjunction of all the "enabled"'s of the corresponding postconditions where the old value appears. > > > > Is this a sane approach to "old" values? Any alternative approach you would prefer? What about better naming? Is "before" a confusing name? > > The dict can be splatted into the postconditions, so that no special > name is required. This would require either that the lambdas handle > **kws, or that their caller inspect them to see what names they take. > Perhaps add a function to functools which only passes kwargs that fit. > Then the precondition mechanism can pass `self`, `key`, and `value` as > kwargs instead of args. > > For functions that have *args and **kwargs, it may be necessary to > pass them to the conditions as args and kwargs instead. > > The name "before" is a confusing name. It's not just something that > happens before. It's really a pre-`let`, adding names to the scope of > things after it, but with values taken before the function call. Based > on that description, other possible names are `prelet`, `letbefore`, > `predef`, `defpre`, `beforescope`. Better a name that is clearly > confusing than one that is obvious but misleading. > > By the way, should the first postcondition be `self.get(key) is > value`, checking for identity rather than equality? _______________________________________________ Python-ideas mailing list Python-ideas@python.org https://mail.python.org/mailman/listinfo/python-ideas Code of Conduct: http://python.org/psf/codeofconduct/
Hi James, I'm a bit short on time today, and would need some more time and attention to understand the proposal you wrote. I'll try to come back to you tomorrow. In any case, I need to refactor icontract's decorators to use conditions like lambda P: and lambda P, result: first before adding snapshot functionality. What about having @snapshot_with and @snapshot? @Snapshot_with does what you propose and @snapshot expects a lambda P, identifier: ? After the refactoring, maybe the same could be done for defining contracts as well? (Requires and requires_that?) If the documentation is clear, I'd expect the user to be able to distinguish the two. The first approach is shorter, and uses magic, but fails in some rare situations. The other method is more verbose, but always works. Cheers, Marko Le sam. 29 sept. 2018 à 00:35, James Lu <jamtlu@gmail.com> a écrit :
I am fine with your proposed syntax. It’s certainly lucid. Perhaps it would be a good idea to get people accustomed to “non-magic” syntax.
I still have a feeling that most developers would like to store the state in many different custom ways.
Please explain. (Expressions like thunk(all)(a == b for a, b in P.arg.meth()) would be valid.)
I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them).
Except for a > b > c being one flat expression with 5 members, it seems fairly easy to recreate an AST, which can then be compiled down to a code object. The code object can be fun with a custom “locals()”
Below is my concept code for such a P object.
from ast import *
# not done: enforce Singleton property on EmptySymbolType
class EmptySymbolType(object): ...
EmptySymbol = EmptySymbolType() # empty symbols are placeholders
class MockP(object):
# "^" is xor
@icontract.pre(lambda symbol, astnode: (symbol is None) ^ (astnode is None))
def __init__(self, symbol=None, value=EmptySymbol, astnode=None, initsymtable=(,)):
self.symtable = dict(initsymtable)
if symbol:
self.expr = Expr(value=Name(id=symbol, ctx=Load()))
self.symtable = {symbol: value}
else:
self.expr = astnode
self.frozen = False
def __add__(self, other):
wrapped = MockP.wrap_value(other)
return MockP(astnode=Expr(value=BinOp(self.expr, Add(), wrapped.expr), initsymtable={**self.symtable, **wrapped.symtable})
def compile(self): ...
def freeze(self):
# frozen objects wouldn’t have an overrided getattr, allowing for icontract to manipulate the MockP object using its public interface
self.frozen = True
@classmethod
def wrap_value(cls, obj):
# create a MockP object from a value. Generate a random identifier and set that as the key in symtable, the AST node is the name of that identifier, retrieving its value through simple expression evaluation.
...
thunk = MockP.wrap_value
P = MockP('P')
# elsewhere: ensure P is only accessed via valid “dot attribute access” inside @snapshot so contracts fail early, or don’t and allow Magic like __dict__ to occur on P.
On Sep 27, 2018, at 9:49 PM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi James,
I still have a feeling that most developers would like to store the state in many different custom ways. I see also thunk and snapshot with wrapper objects to be much more complicated to implement and maintain; I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them). Then the linters need also to work around such wrappers... It might also scare users off since it looks like too much magic. Another concern I also have is that it's probably very hard to integrate these wrappers with mypy later -- but I don't really have a clue about that, only my gut feeling?
What about we accepted to repeat "lambda P, " prefix, and have something like this:
@snapshot( lambda P, some_name: len(P.some_property), lambda P, another_name: hash(P.another_property) )
It's not too verbose for me and you can still explain in three-four sentences what happens below the hub in the library's docs. A pycharm/pydev/vim/emacs plugins could hide the verbose parts.
I performed a small experiment to test how this solution plays with pylint and it seems OK that arguments are not used in lambdas.
Cheers, Marko
On Thu, 27 Sep 2018 at 12:27, James Lu <jamtlu@gmail.com> wrote:
Why couldn’t we record the operations done to a special object and replay them?
Actually, I think there is probably no way around a decorator that
captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
from icontract import snapshot, P, thunk @snapshot(some_identifier=P.self.some_method(P.some_argument.some_attr))
P is an object of our own type, let’s call the type MockP. MockP returns new MockP objects when any operation is done to it. MockP * MockP = MockP. MockP.attr = MockP. MockP objects remember all the operations done to them, and allow the owner of a MockP object to re-apply the same operations
“thunk” converts a function or object or class to a MockP object, storing the function or object for when the operation is done.
thunk(function)(<MockP expression>)
Of course, you could also thunk objects like so: thunk(3) * P.number. (Though it might be better to keep the 3 after P.number in this case so P.number’s __mult__ would be invoked before 3’s __mult__ is invokes.
In most cases, you’d save any operations that can be done on a copy of the data as generated by @snapshot in @postcondiion. thunk is for rare scenarios where 1) it’s hard to capture the state, for example an object that manages network state (or database connectivity etc) and whose stage can only be read by an external classmethod 2) you want to avoid using copy.deepcopy.
I’m sure there’s some way to override isinstance through a meta class or dunder subclasshook.
I suppose this mocking method could be a shorthand for when you don’t need the full power of a lambda. It’s arguably more succinct and readable, though YMMV.
I look forward to reading your opinion on this and any ideas you might have.
On Sep 26, 2018, at 3:56 PM, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Yes, though if we’re talking syntax using kwargs would probably be better. Using “P” instead of “_”: (I agree that _ smells of ignored arguments)
@snapshot(some_identifier=lambda P: ..., some_identifier2=lambda P: ...)
Kwargs has the advantage that you can extend multiple lines without repeating @snapshot, though many lines of @capture would probably be more intuitive since each decorator captures one variable.
Why uppercase "P" and not lowercase (uppercase implies a constant for me)?
To me, the capital letters are more prominent and explicit- easier to see when reading code. It also implies its a constant for you- you shouldn’t be modifying it, because then you’d be interfering with the function itself.
Side node: maybe it would be good to have an @icontract.nomutate (probably use a different name, maybe @icontract.readonly) that makes sure a method doesn’t mutate its own __dict__ (and maybe the __dict__ of the members of its __dict__). It wouldn’t be necessary to put the decorator on every read only function, just the ones your worried might mutate.
Maybe a @icontract.nomutate(param=“paramname”) that ensures the __dict__ of all members of the param name have the same equality or identity before and after. The semantics would need to be worked out.
On Sep 26, 2018, at 8:58 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Am I correct?
"_" looks a bit hard to read for me (implying ignored arguments).
Why uppercase "P" and not lowercase (uppercase implies a constant for me)? Then "O" for "old" and "P" for parameters in a condition: @post(lambda O, P: ...) ?
It also has the nice property that it follows both the temporal and the alphabet order :)
On Wed, 26 Sep 2018 at 14:30, James Lu <jamtlu@gmail.com> wrote:
I still prefer snapshot, though capture is a good name too. We could use generator syntax and inspect the argument names.
Instead of “a”, perhaps use “_”. Or maybe use “A.”, for arguments. Some people might prefer “P” for parameters, since parameters sometimes means the value received while the argument means the value passed.
(#A1)
from icontract import snapshot, __ @snapshot(some_func(_.some_argument.some_attr) for some_identifier, _ in __)
Or (#A2)
@snapshot(some_func(some_argument.some_attr) for some_identifier, _, some_argument in __)
— Or (#A3)
@snapshot(lambda some_argument,_,some_identifier: some_func(some_argument.some_attr))
Or (#A4)
@snapshot(lambda _,some_identifier: some_func(_.some_argument.some_attr)) @snapshot(lambda _,some_identifier, other_identifier: some_func(_.some_argument.some_attr), other_func(_.self))
I like #A4 the most because it’s fairly DRY and avoids the extra punctuation of
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)})
On Sep 26, 2018, at 12:23 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi,
Franklin wrote:
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
James wrote:
I suggest that instead of “@before” it’s “@snapshot” and instead of “ old” it’s “snapshot”.
I like "snapshot", it's a bit clearer than prefixing/postfixing verbs with "pre" which might be misread (*e.g., *"prelet" has a meaning in Slavic languages and could be subconsciously misread, "predef" implies to me a pre-*definition* rather than prior-to-definition , "beforescope" is very clear for me, but it might be confusing for others as to what it actually refers to ). What about "@capture" (7 letters for captures *versus *8 for snapshot)? I suppose "@let" would be playing with fire if Python with conflicting new keywords since I assume "let" to be one of the candidates.
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
I'd still go with the dictionary to allow for this extra freedom. We could have a convention: "a" denotes to the current arguments, and "b" denotes the captured values. It might make an interesting hint that we put "b" before "a" in the condition. You could also interpret "b" as "before" and "a" as "after", but also "a" as "arguments".
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)}) @post(lambda b, a, result: b.some_identifier > result + a.another_argument.another_attr) def some_func(some_argument: SomeClass, another_argument: AnotherClass) -> SomeResult: ...
"b" can be omitted if it is not used. Under the hub, all the arguments to the condition would be passed by keywords.
In case of inheritance, captures would be inherited as well. Hence the library would check at run-time that the returned dictionary with captured values has no identifier that has been already captured, and the linter checks that statically, before running the code. Reading values captured in the parent at the code of the child class might be a bit hard -- but that is case with any inherited methods/properties. In documentation, I'd list all the captures of both ancestor and the current class.
I'm looking forward to reading your opinion on this and alternative suggestions :) Marko
On Tue, 25 Sep 2018 at 18:12, Franklin? Lee < leewangzhong+python@gmail.com> wrote:
On Sun, Sep 23, 2018 at 2:05 AM Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi,
(I'd like to fork from a previous thread, "Pre-conditions and
post-conditions", since it got long and we started discussing a couple of different things. Let's discuss in this thread the implementation of a library for design-by-contract and how to push it forward to hopefully add it to the standard library one day.)
For those unfamiliar with contracts and current state of the
discussion in the previous thread, here's a short summary. The discussion started by me inquiring about the possibility to add design-by-contract concepts into the core language. The idea was rejected by the participants mainly because they thought that the merit of the feature does not merit its costs. This is quite debatable and seems to reflect many a discussion about design-by-contract in general. Please see the other thread, "Why is design-by-contract not widely adopted?" if you are interested in that debate.
We (a colleague of mine and I) decided to implement a library to
bring design-by-contract to Python since we don't believe that the concept will make it into the core language anytime soon and we needed badly a tool to facilitate our work with a growing code base.
The library is available at http://github.com/Parquery/icontract.
The hope is to polish it so that the wider community could use it and once the quality is high enough, make a proposal to add it to the standard Python libraries. We do need a standard library for contracts, otherwise projects with conflicting contract libraries can not integrate (e.g., the contracts can not be inherited between two different contract libraries).
So far, the most important bits have been implemented in icontract:
Preconditions, postconditions, class invariants Inheritance of the contracts (including strengthening and weakening
Informative violation messages (including information about the values involved in the contract condition) Sphinx extension to include contracts in the automatically generated documentation (sphinx-icontract) Linter to statically check that the arguments of the conditions are correct (pyicontract-lint)
We are successfully using it in our code base and have been quite happy about the implementation so far.
There is one bit still missing: accessing "old" values in the
of the inherited contracts) postcondition (i.e., shallow copies of the values prior to the execution of the function). This feature is necessary in order to allow us to verify state transitions.
For example, consider a new dictionary class that has "get" and "put"
methods:
from typing import Optional
from icontract import post
class NovelDict: def length(self)->int: ...
def get(self, key: str) -> Optional[str]: ...
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key: old(self.get(key)) is None and
old(self.length()) + 1 == self.length(),
"length increased with a new key") @post(lambda self, key: old(self.get(key)) is not None and
old(self.length()) == self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
How could we possible implement this "old" function?
Here is my suggestion. I'd introduce a decorator "before" that would
allow you to store whatever values in a dictionary object "old" (i.e. an object whose properties correspond to the key/value pairs). The "old" is then passed to the condition. Here is it in code:
# omitted contracts for brevity class NovelDict: def length(self)->int: ...
# omitted contracts for brevity def get(self, key: str) -> Optional[str]: ...
@before(lambda self, key: {"length": self.length(), "get":
self.get(key)})
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key, old: old.get is None and old.length + 1
== self.length(),
"length increased with a new key") @post(lambda self, key, old: old.get is not None and old.length
== self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
The linter would statically check that all attributes accessed in
"old" have to be defined in the decorator "before" so that attribute errors would be caught early. The current implementation of the linter is fast enough to be run at save time so such errors should usually not happen with a properly set IDE.
"before" decorator would also have "enabled" property, so that you
can turn it off (e.g., if you only want to run a postcondition in testing). The "before" decorators can be stacked so that you can also have a more fine-grained control when each one of them is running (some during test, some during test and in production). The linter would enforce that before's "enabled" is a disjunction of all the "enabled"'s of the corresponding postconditions where the old value appears.
Is this a sane approach to "old" values? Any alternative approach you
would prefer? What about better naming? Is "before" a confusing name?
The dict can be splatted into the postconditions, so that no special name is required. This would require either that the lambdas handle **kws, or that their caller inspect them to see what names they take. Perhaps add a function to functools which only passes kwargs that fit. Then the precondition mechanism can pass `self`, `key`, and `value` as kwargs instead of args.
For functions that have *args and **kwargs, it may be necessary to pass them to the conditions as args and kwargs instead.
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
By the way, should the first postcondition be `self.get(key) is value`, checking for identity rather than equality?
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Hi James, What about a tool that we discussed, to convert contracts back and forth to readable form on IDe save/load with the following syntax: def some_func(arg1:int, arg2:int)-> int: # typing on the phone so no indent With requiring: Assert arg1 < arg2, "some message" With snapshotting: Var1= some_func(arg1) With ensuring: If some_enabling_condition: Assert arg1 + arg2 < var1 If no snapshot, with ensuring is dedented. Only simple assignments allowed in snapshots, only asserts and ifs allowed in require/ensure blocks. Result is reserved for the result of the function. No statements allowed in require/ensure. The same with class invariants. Works with ast and autocomplete in pycharm. Sorry for the hasty message :) Marko Le sam. 29 sept. 2018 à 07:36, Marko Ristin-Kaufmann <marko.ristin@gmail.com> a écrit :
Hi James, I'm a bit short on time today, and would need some more time and attention to understand the proposal you wrote. I'll try to come back to you tomorrow.
In any case, I need to refactor icontract's decorators to use conditions like lambda P: and lambda P, result: first before adding snapshot functionality.
What about having @snapshot_with and @snapshot? @Snapshot_with does what you propose and @snapshot expects a lambda P, identifier: ?
After the refactoring, maybe the same could be done for defining contracts as well? (Requires and requires_that?)
If the documentation is clear, I'd expect the user to be able to distinguish the two. The first approach is shorter, and uses magic, but fails in some rare situations. The other method is more verbose, but always works.
Cheers, Marko
Le sam. 29 sept. 2018 à 00:35, James Lu <jamtlu@gmail.com> a écrit :
I am fine with your proposed syntax. It’s certainly lucid. Perhaps it would be a good idea to get people accustomed to “non-magic” syntax.
I still have a feeling that most developers would like to store the state in many different custom ways.
Please explain. (Expressions like thunk(all)(a == b for a, b in P.arg.meth()) would be valid.)
I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them).
Except for a > b > c being one flat expression with 5 members, it seems fairly easy to recreate an AST, which can then be compiled down to a code object. The code object can be fun with a custom “locals()”
Below is my concept code for such a P object.
from ast import *
# not done: enforce Singleton property on EmptySymbolType
class EmptySymbolType(object): ...
EmptySymbol = EmptySymbolType() # empty symbols are placeholders
class MockP(object):
# "^" is xor
@icontract.pre(lambda symbol, astnode: (symbol is None) ^ (astnode is None))
def __init__(self, symbol=None, value=EmptySymbol, astnode=None, initsymtable=(,)):
self.symtable = dict(initsymtable)
if symbol:
self.expr = Expr(value=Name(id=symbol, ctx=Load()))
self.symtable = {symbol: value}
else:
self.expr = astnode
self.frozen = False
def __add__(self, other):
wrapped = MockP.wrap_value(other)
return MockP(astnode=Expr(value=BinOp(self.expr, Add(), wrapped.expr), initsymtable={**self.symtable, **wrapped.symtable})
def compile(self): ...
def freeze(self):
# frozen objects wouldn’t have an overrided getattr, allowing for icontract to manipulate the MockP object using its public interface
self.frozen = True
@classmethod
def wrap_value(cls, obj):
# create a MockP object from a value. Generate a random identifier and set that as the key in symtable, the AST node is the name of that identifier, retrieving its value through simple expression evaluation.
...
thunk = MockP.wrap_value
P = MockP('P')
# elsewhere: ensure P is only accessed via valid “dot attribute access” inside @snapshot so contracts fail early, or don’t and allow Magic like __dict__ to occur on P.
On Sep 27, 2018, at 9:49 PM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
I still have a feeling that most developers would like to store the state in many different custom ways. I see also thunk and snapshot with wrapper objects to be much more complicated to implement and maintain; I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them). Then the linters need also to work around such wrappers... It might also scare users off since it looks like too much magic. Another concern I also have is that it's probably very hard to integrate these wrappers with mypy later -- but I don't really have a clue about that, only my gut feeling?
What about we accepted to repeat "lambda P, " prefix, and have something like this:
@snapshot( lambda P, some_name: len(P.some_property), lambda P, another_name: hash(P.another_property) )
It's not too verbose for me and you can still explain in three-four sentences what happens below the hub in the library's docs. A pycharm/pydev/vim/emacs plugins could hide the verbose parts.
I performed a small experiment to test how this solution plays with pylint and it seems OK that arguments are not used in lambdas.
Cheers, Marko
On Thu, 27 Sep 2018 at 12:27, James Lu <jamtlu@gmail.com> wrote:
Why couldn’t we record the operations done to a special object and replay them?
Actually, I think there is probably no way around a decorator that
captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
from icontract import snapshot, P, thunk @snapshot(some_identifier=P.self.some_method(P.some_argument.some_attr))
P is an object of our own type, let’s call the type MockP. MockP returns new MockP objects when any operation is done to it. MockP * MockP = MockP. MockP.attr = MockP. MockP objects remember all the operations done to them, and allow the owner of a MockP object to re-apply the same operations
“thunk” converts a function or object or class to a MockP object, storing the function or object for when the operation is done.
thunk(function)(<MockP expression>)
Of course, you could also thunk objects like so: thunk(3) * P.number. (Though it might be better to keep the 3 after P.number in this case so P.number’s __mult__ would be invoked before 3’s __mult__ is invokes.
In most cases, you’d save any operations that can be done on a copy of the data as generated by @snapshot in @postcondiion. thunk is for rare scenarios where 1) it’s hard to capture the state, for example an object that manages network state (or database connectivity etc) and whose stage can only be read by an external classmethod 2) you want to avoid using copy.deepcopy.
I’m sure there’s some way to override isinstance through a meta class or dunder subclasshook.
I suppose this mocking method could be a shorthand for when you don’t need the full power of a lambda. It’s arguably more succinct and readable, though YMMV.
I look forward to reading your opinion on this and any ideas you might have.
On Sep 26, 2018, at 3:56 PM, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Yes, though if we’re talking syntax using kwargs would probably be better. Using “P” instead of “_”: (I agree that _ smells of ignored arguments)
@snapshot(some_identifier=lambda P: ..., some_identifier2=lambda P: ...)
Kwargs has the advantage that you can extend multiple lines without repeating @snapshot, though many lines of @capture would probably be more intuitive since each decorator captures one variable.
Why uppercase "P" and not lowercase (uppercase implies a constant for me)?
To me, the capital letters are more prominent and explicit- easier to see when reading code. It also implies its a constant for you- you shouldn’t be modifying it, because then you’d be interfering with the function itself.
Side node: maybe it would be good to have an @icontract.nomutate (probably use a different name, maybe @icontract.readonly) that makes sure a method doesn’t mutate its own __dict__ (and maybe the __dict__ of the members of its __dict__). It wouldn’t be necessary to put the decorator on every read only function, just the ones your worried might mutate.
Maybe a @icontract.nomutate(param=“paramname”) that ensures the __dict__ of all members of the param name have the same equality or identity before and after. The semantics would need to be worked out.
On Sep 26, 2018, at 8:58 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Am I correct?
"_" looks a bit hard to read for me (implying ignored arguments).
Why uppercase "P" and not lowercase (uppercase implies a constant for me)? Then "O" for "old" and "P" for parameters in a condition: @post(lambda O, P: ...) ?
It also has the nice property that it follows both the temporal and the alphabet order :)
On Wed, 26 Sep 2018 at 14:30, James Lu <jamtlu@gmail.com> wrote:
I still prefer snapshot, though capture is a good name too. We could use generator syntax and inspect the argument names.
Instead of “a”, perhaps use “_”. Or maybe use “A.”, for arguments. Some people might prefer “P” for parameters, since parameters sometimes means the value received while the argument means the value passed.
(#A1)
from icontract import snapshot, __ @snapshot(some_func(_.some_argument.some_attr) for some_identifier, _ in __)
Or (#A2)
@snapshot(some_func(some_argument.some_attr) for some_identifier, _, some_argument in __)
— Or (#A3)
@snapshot(lambda some_argument,_,some_identifier: some_func(some_argument.some_attr))
Or (#A4)
@snapshot(lambda _,some_identifier: some_func(_.some_argument.some_attr)) @snapshot(lambda _,some_identifier, other_identifier: some_func(_.some_argument.some_attr), other_func(_.self))
I like #A4 the most because it’s fairly DRY and avoids the extra punctuation of
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)})
On Sep 26, 2018, at 12:23 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi,
Franklin wrote:
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
James wrote:
I suggest that instead of “@before” it’s “@snapshot” and instead of “ old” it’s “snapshot”.
I like "snapshot", it's a bit clearer than prefixing/postfixing verbs with "pre" which might be misread (*e.g., *"prelet" has a meaning in Slavic languages and could be subconsciously misread, "predef" implies to me a pre-*definition* rather than prior-to-definition , "beforescope" is very clear for me, but it might be confusing for others as to what it actually refers to ). What about "@capture" (7 letters for captures *versus *8 for snapshot)? I suppose "@let" would be playing with fire if Python with conflicting new keywords since I assume "let" to be one of the candidates.
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
I'd still go with the dictionary to allow for this extra freedom. We could have a convention: "a" denotes to the current arguments, and "b" denotes the captured values. It might make an interesting hint that we put "b" before "a" in the condition. You could also interpret "b" as "before" and "a" as "after", but also "a" as "arguments".
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)}) @post(lambda b, a, result: b.some_identifier > result + a.another_argument.another_attr) def some_func(some_argument: SomeClass, another_argument: AnotherClass) -> SomeResult: ...
"b" can be omitted if it is not used. Under the hub, all the arguments to the condition would be passed by keywords.
In case of inheritance, captures would be inherited as well. Hence the library would check at run-time that the returned dictionary with captured values has no identifier that has been already captured, and the linter checks that statically, before running the code. Reading values captured in the parent at the code of the child class might be a bit hard -- but that is case with any inherited methods/properties. In documentation, I'd list all the captures of both ancestor and the current class.
I'm looking forward to reading your opinion on this and alternative suggestions :) Marko
On Tue, 25 Sep 2018 at 18:12, Franklin? Lee < leewangzhong+python@gmail.com> wrote:
On Sun, Sep 23, 2018 at 2:05 AM Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi,
(I'd like to fork from a previous thread, "Pre-conditions and
post-conditions", since it got long and we started discussing a couple of different things. Let's discuss in this thread the implementation of a library for design-by-contract and how to push it forward to hopefully add it to the standard library one day.)
For those unfamiliar with contracts and current state of the
discussion in the previous thread, here's a short summary. The discussion started by me inquiring about the possibility to add design-by-contract concepts into the core language. The idea was rejected by the participants mainly because they thought that the merit of the feature does not merit its costs. This is quite debatable and seems to reflect many a discussion about design-by-contract in general. Please see the other thread, "Why is design-by-contract not widely adopted?" if you are interested in that debate.
We (a colleague of mine and I) decided to implement a library to
bring design-by-contract to Python since we don't believe that the concept will make it into the core language anytime soon and we needed badly a tool to facilitate our work with a growing code base.
The library is available at http://github.com/Parquery/icontract.
The hope is to polish it so that the wider community could use it and once the quality is high enough, make a proposal to add it to the standard Python libraries. We do need a standard library for contracts, otherwise projects with conflicting contract libraries can not integrate (e.g., the contracts can not be inherited between two different contract libraries).
So far, the most important bits have been implemented in icontract:
Preconditions, postconditions, class invariants Inheritance of the contracts (including strengthening and weakening
Informative violation messages (including information about the values involved in the contract condition) Sphinx extension to include contracts in the automatically generated documentation (sphinx-icontract) Linter to statically check that the arguments of the conditions are correct (pyicontract-lint)
We are successfully using it in our code base and have been quite happy about the implementation so far.
There is one bit still missing: accessing "old" values in the
of the inherited contracts) postcondition (i.e., shallow copies of the values prior to the execution of the function). This feature is necessary in order to allow us to verify state transitions.
For example, consider a new dictionary class that has "get" and
"put" methods:
from typing import Optional
from icontract import post
class NovelDict: def length(self)->int: ...
def get(self, key: str) -> Optional[str]: ...
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key: old(self.get(key)) is None and
old(self.length()) + 1 == self.length(),
"length increased with a new key") @post(lambda self, key: old(self.get(key)) is not None and
old(self.length()) == self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
How could we possible implement this "old" function?
Here is my suggestion. I'd introduce a decorator "before" that would
allow you to store whatever values in a dictionary object "old" (i.e. an object whose properties correspond to the key/value pairs). The "old" is then passed to the condition. Here is it in code:
# omitted contracts for brevity class NovelDict: def length(self)->int: ...
# omitted contracts for brevity def get(self, key: str) -> Optional[str]: ...
@before(lambda self, key: {"length": self.length(), "get":
self.get(key)})
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key, old: old.get is None and old.length + 1
== self.length(),
"length increased with a new key") @post(lambda self, key, old: old.get is not None and old.length
== self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
The linter would statically check that all attributes accessed in
"old" have to be defined in the decorator "before" so that attribute errors would be caught early. The current implementation of the linter is fast enough to be run at save time so such errors should usually not happen with a properly set IDE.
"before" decorator would also have "enabled" property, so that you
can turn it off (e.g., if you only want to run a postcondition in testing). The "before" decorators can be stacked so that you can also have a more fine-grained control when each one of them is running (some during test, some during test and in production). The linter would enforce that before's "enabled" is a disjunction of all the "enabled"'s of the corresponding postconditions where the old value appears.
Is this a sane approach to "old" values? Any alternative approach
you would prefer? What about better naming? Is "before" a confusing name?
The dict can be splatted into the postconditions, so that no special name is required. This would require either that the lambdas handle **kws, or that their caller inspect them to see what names they take. Perhaps add a function to functools which only passes kwargs that fit. Then the precondition mechanism can pass `self`, `key`, and `value` as kwargs instead of args.
For functions that have *args and **kwargs, it may be necessary to pass them to the conditions as args and kwargs instead.
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
By the way, should the first postcondition be `self.get(key) is value`, checking for identity rather than equality?
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Hi James, Just a PS to the previous syntax: with contracts: with preconditions: assert arg1 < arg2 with snapshot as S: S.var1 = some_func(arg1) with postconditions, \ result: # result would be annotated with "# type:" if return type is annotated. assert arg1 < S.var1 < arg2 For classes: class SomeClass: with invariants, selfie as self: # type: SomeClass assert 0 < self.x < sqrt(self.x) The advantage: no variable shadowing, valid python code, autocomplete works in Pycharm, even mypy could be made to work. "With contracts" makes it easier and less error prone to group preconditions and postconditions. The converter would check that there is no "with contracts" in the body of the function except in the first statement and the same for class invariants. icontract.dummies would provide these dummy context managers (all of them would raise exceptions on enter so that the code can not run by accident). The converter would add/remove these imports automatically. Cheers, Marko Le sam. 29 sept. 2018 à 17:55, Marko Ristin-Kaufmann <marko.ristin@gmail.com> a écrit :
Hi James, What about a tool that we discussed, to convert contracts back and forth to readable form on IDe save/load with the following syntax:
def some_func(arg1:int, arg2:int)-> int: # typing on the phone so no indent With requiring: Assert arg1 < arg2, "some message" With snapshotting: Var1= some_func(arg1)
With ensuring: If some_enabling_condition: Assert arg1 + arg2 < var1
If no snapshot, with ensuring is dedented. Only simple assignments allowed in snapshots, only asserts and ifs allowed in require/ensure blocks. Result is reserved for the result of the function.
No statements allowed in require/ensure.
The same with class invariants.
Works with ast and autocomplete in pycharm.
Sorry for the hasty message :) Marko
Le sam. 29 sept. 2018 à 07:36, Marko Ristin-Kaufmann < marko.ristin@gmail.com> a écrit :
Hi James, I'm a bit short on time today, and would need some more time and attention to understand the proposal you wrote. I'll try to come back to you tomorrow.
In any case, I need to refactor icontract's decorators to use conditions like lambda P: and lambda P, result: first before adding snapshot functionality.
What about having @snapshot_with and @snapshot? @Snapshot_with does what you propose and @snapshot expects a lambda P, identifier: ?
After the refactoring, maybe the same could be done for defining contracts as well? (Requires and requires_that?)
If the documentation is clear, I'd expect the user to be able to distinguish the two. The first approach is shorter, and uses magic, but fails in some rare situations. The other method is more verbose, but always works.
Cheers, Marko
Le sam. 29 sept. 2018 à 00:35, James Lu <jamtlu@gmail.com> a écrit :
I am fine with your proposed syntax. It’s certainly lucid. Perhaps it would be a good idea to get people accustomed to “non-magic” syntax.
I still have a feeling that most developers would like to store the state in many different custom ways.
Please explain. (Expressions like thunk(all)(a == b for a, b in P.arg.meth()) would be valid.)
I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them).
Except for a > b > c being one flat expression with 5 members, it seems fairly easy to recreate an AST, which can then be compiled down to a code object. The code object can be fun with a custom “locals()”
Below is my concept code for such a P object.
from ast import *
# not done: enforce Singleton property on EmptySymbolType
class EmptySymbolType(object): ...
EmptySymbol = EmptySymbolType() # empty symbols are placeholders
class MockP(object):
# "^" is xor
@icontract.pre(lambda symbol, astnode: (symbol is None) ^ (astnode is None))
def __init__(self, symbol=None, value=EmptySymbol, astnode=None, initsymtable=(,)):
self.symtable = dict(initsymtable)
if symbol:
self.expr = Expr(value=Name(id=symbol, ctx=Load()))
self.symtable = {symbol: value}
else:
self.expr = astnode
self.frozen = False
def __add__(self, other):
wrapped = MockP.wrap_value(other)
return MockP(astnode=Expr(value=BinOp(self.expr, Add(), wrapped.expr), initsymtable={**self.symtable, **wrapped.symtable})
def compile(self): ...
def freeze(self):
# frozen objects wouldn’t have an overrided getattr, allowing for icontract to manipulate the MockP object using its public interface
self.frozen = True
@classmethod
def wrap_value(cls, obj):
# create a MockP object from a value. Generate a random identifier and set that as the key in symtable, the AST node is the name of that identifier, retrieving its value through simple expression evaluation.
...
thunk = MockP.wrap_value
P = MockP('P')
# elsewhere: ensure P is only accessed via valid “dot attribute access” inside @snapshot so contracts fail early, or don’t and allow Magic like __dict__ to occur on P.
On Sep 27, 2018, at 9:49 PM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
I still have a feeling that most developers would like to store the state in many different custom ways. I see also thunk and snapshot with wrapper objects to be much more complicated to implement and maintain; I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them). Then the linters need also to work around such wrappers... It might also scare users off since it looks like too much magic. Another concern I also have is that it's probably very hard to integrate these wrappers with mypy later -- but I don't really have a clue about that, only my gut feeling?
What about we accepted to repeat "lambda P, " prefix, and have something like this:
@snapshot( lambda P, some_name: len(P.some_property), lambda P, another_name: hash(P.another_property) )
It's not too verbose for me and you can still explain in three-four sentences what happens below the hub in the library's docs. A pycharm/pydev/vim/emacs plugins could hide the verbose parts.
I performed a small experiment to test how this solution plays with pylint and it seems OK that arguments are not used in lambdas.
Cheers, Marko
On Thu, 27 Sep 2018 at 12:27, James Lu <jamtlu@gmail.com> wrote:
Why couldn’t we record the operations done to a special object and replay them?
Actually, I think there is probably no way around a decorator that
captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
from icontract import snapshot, P, thunk @snapshot(some_identifier=P.self.some_method(P.some_argument.some_attr))
P is an object of our own type, let’s call the type MockP. MockP returns new MockP objects when any operation is done to it. MockP * MockP = MockP. MockP.attr = MockP. MockP objects remember all the operations done to them, and allow the owner of a MockP object to re-apply the same operations
“thunk” converts a function or object or class to a MockP object, storing the function or object for when the operation is done.
thunk(function)(<MockP expression>)
Of course, you could also thunk objects like so: thunk(3) * P.number. (Though it might be better to keep the 3 after P.number in this case so P.number’s __mult__ would be invoked before 3’s __mult__ is invokes.
In most cases, you’d save any operations that can be done on a copy of the data as generated by @snapshot in @postcondiion. thunk is for rare scenarios where 1) it’s hard to capture the state, for example an object that manages network state (or database connectivity etc) and whose stage can only be read by an external classmethod 2) you want to avoid using copy.deepcopy.
I’m sure there’s some way to override isinstance through a meta class or dunder subclasshook.
I suppose this mocking method could be a shorthand for when you don’t need the full power of a lambda. It’s arguably more succinct and readable, though YMMV.
I look forward to reading your opinion on this and any ideas you might have.
On Sep 26, 2018, at 3:56 PM, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Yes, though if we’re talking syntax using kwargs would probably be better. Using “P” instead of “_”: (I agree that _ smells of ignored arguments)
@snapshot(some_identifier=lambda P: ..., some_identifier2=lambda P: ...)
Kwargs has the advantage that you can extend multiple lines without repeating @snapshot, though many lines of @capture would probably be more intuitive since each decorator captures one variable.
Why uppercase "P" and not lowercase (uppercase implies a constant for me)?
To me, the capital letters are more prominent and explicit- easier to see when reading code. It also implies its a constant for you- you shouldn’t be modifying it, because then you’d be interfering with the function itself.
Side node: maybe it would be good to have an @icontract.nomutate (probably use a different name, maybe @icontract.readonly) that makes sure a method doesn’t mutate its own __dict__ (and maybe the __dict__ of the members of its __dict__). It wouldn’t be necessary to put the decorator on every read only function, just the ones your worried might mutate.
Maybe a @icontract.nomutate(param=“paramname”) that ensures the __dict__ of all members of the param name have the same equality or identity before and after. The semantics would need to be worked out.
On Sep 26, 2018, at 8:58 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Am I correct?
"_" looks a bit hard to read for me (implying ignored arguments).
Why uppercase "P" and not lowercase (uppercase implies a constant for me)? Then "O" for "old" and "P" for parameters in a condition: @post(lambda O, P: ...) ?
It also has the nice property that it follows both the temporal and the alphabet order :)
On Wed, 26 Sep 2018 at 14:30, James Lu <jamtlu@gmail.com> wrote:
I still prefer snapshot, though capture is a good name too. We could use generator syntax and inspect the argument names.
Instead of “a”, perhaps use “_”. Or maybe use “A.”, for arguments. Some people might prefer “P” for parameters, since parameters sometimes means the value received while the argument means the value passed.
(#A1)
from icontract import snapshot, __ @snapshot(some_func(_.some_argument.some_attr) for some_identifier, _ in __)
Or (#A2)
@snapshot(some_func(some_argument.some_attr) for some_identifier, _, some_argument in __)
— Or (#A3)
@snapshot(lambda some_argument,_,some_identifier: some_func(some_argument.some_attr))
Or (#A4)
@snapshot(lambda _,some_identifier: some_func(_.some_argument.some_attr)) @snapshot(lambda _,some_identifier, other_identifier: some_func(_.some_argument.some_attr), other_func(_.self))
I like #A4 the most because it’s fairly DRY and avoids the extra punctuation of
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)})
On Sep 26, 2018, at 12:23 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi,
Franklin wrote:
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
James wrote:
I suggest that instead of “@before” it’s “@snapshot” and instead of “ old” it’s “snapshot”.
I like "snapshot", it's a bit clearer than prefixing/postfixing verbs with "pre" which might be misread (*e.g., *"prelet" has a meaning in Slavic languages and could be subconsciously misread, "predef" implies to me a pre-*definition* rather than prior-to-definition , "beforescope" is very clear for me, but it might be confusing for others as to what it actually refers to ). What about "@capture" (7 letters for captures *versus *8 for snapshot)? I suppose "@let" would be playing with fire if Python with conflicting new keywords since I assume "let" to be one of the candidates.
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
I'd still go with the dictionary to allow for this extra freedom. We could have a convention: "a" denotes to the current arguments, and "b" denotes the captured values. It might make an interesting hint that we put "b" before "a" in the condition. You could also interpret "b" as "before" and "a" as "after", but also "a" as "arguments".
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)}) @post(lambda b, a, result: b.some_identifier > result + a.another_argument.another_attr) def some_func(some_argument: SomeClass, another_argument: AnotherClass) -> SomeResult: ...
"b" can be omitted if it is not used. Under the hub, all the arguments to the condition would be passed by keywords.
In case of inheritance, captures would be inherited as well. Hence the library would check at run-time that the returned dictionary with captured values has no identifier that has been already captured, and the linter checks that statically, before running the code. Reading values captured in the parent at the code of the child class might be a bit hard -- but that is case with any inherited methods/properties. In documentation, I'd list all the captures of both ancestor and the current class.
I'm looking forward to reading your opinion on this and alternative suggestions :) Marko
On Tue, 25 Sep 2018 at 18:12, Franklin? Lee < leewangzhong+python@gmail.com> wrote:
On Sun, Sep 23, 2018 at 2:05 AM Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote: > > Hi, > > (I'd like to fork from a previous thread, "Pre-conditions and post-conditions", since it got long and we started discussing a couple of different things. Let's discuss in this thread the implementation of a library for design-by-contract and how to push it forward to hopefully add it to the standard library one day.) > > For those unfamiliar with contracts and current state of the discussion in the previous thread, here's a short summary. The discussion started by me inquiring about the possibility to add design-by-contract concepts into the core language. The idea was rejected by the participants mainly because they thought that the merit of the feature does not merit its costs. This is quite debatable and seems to reflect many a discussion about design-by-contract in general. Please see the other thread, "Why is design-by-contract not widely adopted?" if you are interested in that debate. > > We (a colleague of mine and I) decided to implement a library to bring design-by-contract to Python since we don't believe that the concept will make it into the core language anytime soon and we needed badly a tool to facilitate our work with a growing code base. > > The library is available at http://github.com/Parquery/icontract. The hope is to polish it so that the wider community could use it and once the quality is high enough, make a proposal to add it to the standard Python libraries. We do need a standard library for contracts, otherwise projects with conflicting contract libraries can not integrate (e.g., the contracts can not be inherited between two different contract libraries). > > So far, the most important bits have been implemented in icontract: > > Preconditions, postconditions, class invariants > Inheritance of the contracts (including strengthening and weakening of the inherited contracts) > Informative violation messages (including information about the values involved in the contract condition) > Sphinx extension to include contracts in the automatically generated documentation (sphinx-icontract) > Linter to statically check that the arguments of the conditions are correct (pyicontract-lint) > > We are successfully using it in our code base and have been quite happy about the implementation so far. > > There is one bit still missing: accessing "old" values in the postcondition (i.e., shallow copies of the values prior to the execution of the function). This feature is necessary in order to allow us to verify state transitions. > > For example, consider a new dictionary class that has "get" and "put" methods: > > from typing import Optional > > from icontract import post > > class NovelDict: > def length(self)->int: > ... > > def get(self, key: str) -> Optional[str]: > ... > > @post(lambda self, key, value: self.get(key) == value) > @post(lambda self, key: old(self.get(key)) is None and old(self.length()) + 1 == self.length(), > "length increased with a new key") > @post(lambda self, key: old(self.get(key)) is not None and old(self.length()) == self.length(), > "length stable with an existing key") > def put(self, key: str, value: str) -> None: > ... > > How could we possible implement this "old" function? > > Here is my suggestion. I'd introduce a decorator "before" that would allow you to store whatever values in a dictionary object "old" (i.e. an object whose properties correspond to the key/value pairs). The "old" is then passed to the condition. Here is it in code: > > # omitted contracts for brevity > class NovelDict: > def length(self)->int: > ... > > # omitted contracts for brevity > def get(self, key: str) -> Optional[str]: > ... > > @before(lambda self, key: {"length": self.length(), "get": self.get(key)}) > @post(lambda self, key, value: self.get(key) == value) > @post(lambda self, key, old: old.get is None and old.length + 1 == self.length(), > "length increased with a new key") > @post(lambda self, key, old: old.get is not None and old.length == self.length(), > "length stable with an existing key") > def put(self, key: str, value: str) -> None: > ... > > The linter would statically check that all attributes accessed in "old" have to be defined in the decorator "before" so that attribute errors would be caught early. The current implementation of the linter is fast enough to be run at save time so such errors should usually not happen with a properly set IDE. > > "before" decorator would also have "enabled" property, so that you can turn it off (e.g., if you only want to run a postcondition in testing). The "before" decorators can be stacked so that you can also have a more fine-grained control when each one of them is running (some during test, some during test and in production). The linter would enforce that before's "enabled" is a disjunction of all the "enabled"'s of the corresponding postconditions where the old value appears. > > Is this a sane approach to "old" values? Any alternative approach you would prefer? What about better naming? Is "before" a confusing name?
The dict can be splatted into the postconditions, so that no special name is required. This would require either that the lambdas handle **kws, or that their caller inspect them to see what names they take. Perhaps add a function to functools which only passes kwargs that fit. Then the precondition mechanism can pass `self`, `key`, and `value` as kwargs instead of args.
For functions that have *args and **kwargs, it may be necessary to pass them to the conditions as args and kwargs instead.
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
By the way, should the first postcondition be `self.get(key) is value`, checking for identity rather than equality?
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P.p.s. to raise a custom exception: if not (arg1 < S.var1 < arg2): "Some description" raise SomeException(arg1, S.var1, arg2) The converter enforces that only "if not" statement is allowed, only a string description (optional) followed by a raise in the body of if-statement. This is later at back-conversion to python easy to transform into a lambda. Cheers, Marko Le sam. 29 sept. 2018 à 20:56, Marko Ristin-Kaufmann <marko.ristin@gmail.com> a écrit :
Hi James, Just a PS to the previous syntax:
with contracts: with preconditions: assert arg1 < arg2
with snapshot as S: S.var1 = some_func(arg1) with postconditions, \ result: # result would be annotated with "# type:" if return type is annotated. assert arg1 < S.var1 < arg2
For classes: class SomeClass: with invariants, selfie as self: # type: SomeClass assert 0 < self.x < sqrt(self.x)
The advantage: no variable shadowing, valid python code, autocomplete works in Pycharm, even mypy could be made to work. "With contracts" makes it easier and less error prone to group preconditions and postconditions. The converter would check that there is no "with contracts" in the body of the function except in the first statement and the same for class invariants.
icontract.dummies would provide these dummy context managers (all of them would raise exceptions on enter so that the code can not run by accident). The converter would add/remove these imports automatically.
Cheers, Marko
Le sam. 29 sept. 2018 à 17:55, Marko Ristin-Kaufmann < marko.ristin@gmail.com> a écrit :
Hi James, What about a tool that we discussed, to convert contracts back and forth to readable form on IDe save/load with the following syntax:
def some_func(arg1:int, arg2:int)-> int: # typing on the phone so no indent With requiring: Assert arg1 < arg2, "some message" With snapshotting: Var1= some_func(arg1)
With ensuring: If some_enabling_condition: Assert arg1 + arg2 < var1
If no snapshot, with ensuring is dedented. Only simple assignments allowed in snapshots, only asserts and ifs allowed in require/ensure blocks. Result is reserved for the result of the function.
No statements allowed in require/ensure.
The same with class invariants.
Works with ast and autocomplete in pycharm.
Sorry for the hasty message :) Marko
Le sam. 29 sept. 2018 à 07:36, Marko Ristin-Kaufmann < marko.ristin@gmail.com> a écrit :
Hi James, I'm a bit short on time today, and would need some more time and attention to understand the proposal you wrote. I'll try to come back to you tomorrow.
In any case, I need to refactor icontract's decorators to use conditions like lambda P: and lambda P, result: first before adding snapshot functionality.
What about having @snapshot_with and @snapshot? @Snapshot_with does what you propose and @snapshot expects a lambda P, identifier: ?
After the refactoring, maybe the same could be done for defining contracts as well? (Requires and requires_that?)
If the documentation is clear, I'd expect the user to be able to distinguish the two. The first approach is shorter, and uses magic, but fails in some rare situations. The other method is more verbose, but always works.
Cheers, Marko
Le sam. 29 sept. 2018 à 00:35, James Lu <jamtlu@gmail.com> a écrit :
I am fine with your proposed syntax. It’s certainly lucid. Perhaps it would be a good idea to get people accustomed to “non-magic” syntax.
I still have a feeling that most developers would like to store the state in many different custom ways.
Please explain. (Expressions like thunk(all)(a == b for a, b in P.arg.meth()) would be valid.)
I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them).
Except for a > b > c being one flat expression with 5 members, it seems fairly easy to recreate an AST, which can then be compiled down to a code object. The code object can be fun with a custom “locals()”
Below is my concept code for such a P object.
from ast import *
# not done: enforce Singleton property on EmptySymbolType
class EmptySymbolType(object): ...
EmptySymbol = EmptySymbolType() # empty symbols are placeholders
class MockP(object):
# "^" is xor
@icontract.pre(lambda symbol, astnode: (symbol is None) ^ (astnode is None))
def __init__(self, symbol=None, value=EmptySymbol, astnode=None, initsymtable=(,)):
self.symtable = dict(initsymtable)
if symbol:
self.expr = Expr(value=Name(id=symbol, ctx=Load()))
self.symtable = {symbol: value}
else:
self.expr = astnode
self.frozen = False
def __add__(self, other):
wrapped = MockP.wrap_value(other)
return MockP(astnode=Expr(value=BinOp(self.expr, Add(), wrapped.expr), initsymtable={**self.symtable, **wrapped.symtable})
def compile(self): ...
def freeze(self):
# frozen objects wouldn’t have an overrided getattr, allowing for icontract to manipulate the MockP object using its public interface
self.frozen = True
@classmethod
def wrap_value(cls, obj):
# create a MockP object from a value. Generate a random identifier and set that as the key in symtable, the AST node is the name of that identifier, retrieving its value through simple expression evaluation.
...
thunk = MockP.wrap_value
P = MockP('P')
# elsewhere: ensure P is only accessed via valid “dot attribute access” inside @snapshot so contracts fail early, or don’t and allow Magic like __dict__ to occur on P.
On Sep 27, 2018, at 9:49 PM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
I still have a feeling that most developers would like to store the state in many different custom ways. I see also thunk and snapshot with wrapper objects to be much more complicated to implement and maintain; I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them). Then the linters need also to work around such wrappers... It might also scare users off since it looks like too much magic. Another concern I also have is that it's probably very hard to integrate these wrappers with mypy later -- but I don't really have a clue about that, only my gut feeling?
What about we accepted to repeat "lambda P, " prefix, and have something like this:
@snapshot( lambda P, some_name: len(P.some_property), lambda P, another_name: hash(P.another_property) )
It's not too verbose for me and you can still explain in three-four sentences what happens below the hub in the library's docs. A pycharm/pydev/vim/emacs plugins could hide the verbose parts.
I performed a small experiment to test how this solution plays with pylint and it seems OK that arguments are not used in lambdas.
Cheers, Marko
On Thu, 27 Sep 2018 at 12:27, James Lu <jamtlu@gmail.com> wrote:
Why couldn’t we record the operations done to a special object and replay them?
Actually, I think there is probably no way around a decorator that
captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
from icontract import snapshot, P, thunk
@snapshot(some_identifier=P.self.some_method(P.some_argument.some_attr))
P is an object of our own type, let’s call the type MockP. MockP returns new MockP objects when any operation is done to it. MockP * MockP = MockP. MockP.attr = MockP. MockP objects remember all the operations done to them, and allow the owner of a MockP object to re-apply the same operations
“thunk” converts a function or object or class to a MockP object, storing the function or object for when the operation is done.
thunk(function)(<MockP expression>)
Of course, you could also thunk objects like so: thunk(3) * P.number. (Though it might be better to keep the 3 after P.number in this case so P.number’s __mult__ would be invoked before 3’s __mult__ is invokes.
In most cases, you’d save any operations that can be done on a copy of the data as generated by @snapshot in @postcondiion. thunk is for rare scenarios where 1) it’s hard to capture the state, for example an object that manages network state (or database connectivity etc) and whose stage can only be read by an external classmethod 2) you want to avoid using copy.deepcopy.
I’m sure there’s some way to override isinstance through a meta class or dunder subclasshook.
I suppose this mocking method could be a shorthand for when you don’t need the full power of a lambda. It’s arguably more succinct and readable, though YMMV.
I look forward to reading your opinion on this and any ideas you might have.
On Sep 26, 2018, at 3:56 PM, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Yes, though if we’re talking syntax using kwargs would probably be better. Using “P” instead of “_”: (I agree that _ smells of ignored arguments)
@snapshot(some_identifier=lambda P: ..., some_identifier2=lambda P: ...)
Kwargs has the advantage that you can extend multiple lines without repeating @snapshot, though many lines of @capture would probably be more intuitive since each decorator captures one variable.
Why uppercase "P" and not lowercase (uppercase implies a constant for me)?
To me, the capital letters are more prominent and explicit- easier to see when reading code. It also implies its a constant for you- you shouldn’t be modifying it, because then you’d be interfering with the function itself.
Side node: maybe it would be good to have an @icontract.nomutate (probably use a different name, maybe @icontract.readonly) that makes sure a method doesn’t mutate its own __dict__ (and maybe the __dict__ of the members of its __dict__). It wouldn’t be necessary to put the decorator on every read only function, just the ones your worried might mutate.
Maybe a @icontract.nomutate(param=“paramname”) that ensures the __dict__ of all members of the param name have the same equality or identity before and after. The semantics would need to be worked out.
On Sep 26, 2018, at 8:58 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Am I correct?
"_" looks a bit hard to read for me (implying ignored arguments).
Why uppercase "P" and not lowercase (uppercase implies a constant for me)? Then "O" for "old" and "P" for parameters in a condition: @post(lambda O, P: ...) ?
It also has the nice property that it follows both the temporal and the alphabet order :)
On Wed, 26 Sep 2018 at 14:30, James Lu <jamtlu@gmail.com> wrote:
I still prefer snapshot, though capture is a good name too. We could use generator syntax and inspect the argument names.
Instead of “a”, perhaps use “_”. Or maybe use “A.”, for arguments. Some people might prefer “P” for parameters, since parameters sometimes means the value received while the argument means the value passed.
(#A1)
from icontract import snapshot, __ @snapshot(some_func(_.some_argument.some_attr) for some_identifier, _ in __)
Or (#A2)
@snapshot(some_func(some_argument.some_attr) for some_identifier, _, some_argument in __)
— Or (#A3)
@snapshot(lambda some_argument,_,some_identifier: some_func(some_argument.some_attr))
Or (#A4)
@snapshot(lambda _,some_identifier: some_func(_.some_argument.some_attr)) @snapshot(lambda _,some_identifier, other_identifier: some_func(_.some_argument.some_attr), other_func(_.self))
I like #A4 the most because it’s fairly DRY and avoids the extra punctuation of
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)})
On Sep 26, 2018, at 12:23 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi,
Franklin wrote:
> The name "before" is a confusing name. It's not just something that > happens before. It's really a pre-`let`, adding names to the scope of > things after it, but with values taken before the function call. > Based > on that description, other possible names are `prelet`, `letbefore`, > `predef`, `defpre`, `beforescope`. Better a name that is clearly > confusing than one that is obvious but misleading.
James wrote:
> I suggest that instead of “@before” it’s “@snapshot” and instead of > “old” it’s “snapshot”.
I like "snapshot", it's a bit clearer than prefixing/postfixing verbs with "pre" which might be misread (*e.g., *"prelet" has a meaning in Slavic languages and could be subconsciously misread, "predef" implies to me a pre-*definition* rather than prior-to-definition , "beforescope" is very clear for me, but it might be confusing for others as to what it actually refers to ). What about "@capture" (7 letters for captures *versus *8 for snapshot)? I suppose "@let" would be playing with fire if Python with conflicting new keywords since I assume "let" to be one of the candidates.
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
I'd still go with the dictionary to allow for this extra freedom. We could have a convention: "a" denotes to the current arguments, and "b" denotes the captured values. It might make an interesting hint that we put "b" before "a" in the condition. You could also interpret "b" as "before" and "a" as "after", but also "a" as "arguments".
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)}) @post(lambda b, a, result: b.some_identifier > result + a.another_argument.another_attr) def some_func(some_argument: SomeClass, another_argument: AnotherClass) -> SomeResult: ...
"b" can be omitted if it is not used. Under the hub, all the arguments to the condition would be passed by keywords.
In case of inheritance, captures would be inherited as well. Hence the library would check at run-time that the returned dictionary with captured values has no identifier that has been already captured, and the linter checks that statically, before running the code. Reading values captured in the parent at the code of the child class might be a bit hard -- but that is case with any inherited methods/properties. In documentation, I'd list all the captures of both ancestor and the current class.
I'm looking forward to reading your opinion on this and alternative suggestions :) Marko
On Tue, 25 Sep 2018 at 18:12, Franklin? Lee < leewangzhong+python@gmail.com> wrote:
> On Sun, Sep 23, 2018 at 2:05 AM Marko Ristin-Kaufmann > <marko.ristin@gmail.com> wrote: > > > > Hi, > > > > (I'd like to fork from a previous thread, "Pre-conditions and > post-conditions", since it got long and we started discussing a couple of > different things. Let's discuss in this thread the implementation of a > library for design-by-contract and how to push it forward to hopefully add > it to the standard library one day.) > > > > For those unfamiliar with contracts and current state of the > discussion in the previous thread, here's a short summary. The discussion > started by me inquiring about the possibility to add design-by-contract > concepts into the core language. The idea was rejected by the participants > mainly because they thought that the merit of the feature does not merit > its costs. This is quite debatable and seems to reflect many a discussion > about design-by-contract in general. Please see the other thread, "Why is > design-by-contract not widely adopted?" if you are interested in that > debate. > > > > We (a colleague of mine and I) decided to implement a library to > bring design-by-contract to Python since we don't believe that the concept > will make it into the core language anytime soon and we needed badly a tool > to facilitate our work with a growing code base. > > > > The library is available at http://github.com/Parquery/icontract. > The hope is to polish it so that the wider community could use it and once > the quality is high enough, make a proposal to add it to the standard > Python libraries. We do need a standard library for contracts, otherwise > projects with conflicting contract libraries can not integrate (e.g., the > contracts can not be inherited between two different contract libraries). > > > > So far, the most important bits have been implemented in icontract: > > > > Preconditions, postconditions, class invariants > > Inheritance of the contracts (including strengthening and > weakening of the inherited contracts) > > Informative violation messages (including information about the > values involved in the contract condition) > > Sphinx extension to include contracts in the automatically > generated documentation (sphinx-icontract) > > Linter to statically check that the arguments of the conditions > are correct (pyicontract-lint) > > > > We are successfully using it in our code base and have been quite > happy about the implementation so far. > > > > There is one bit still missing: accessing "old" values in the > postcondition (i.e., shallow copies of the values prior to the execution of > the function). This feature is necessary in order to allow us to verify > state transitions. > > > > For example, consider a new dictionary class that has "get" and > "put" methods: > > > > from typing import Optional > > > > from icontract import post > > > > class NovelDict: > > def length(self)->int: > > ... > > > > def get(self, key: str) -> Optional[str]: > > ... > > > > @post(lambda self, key, value: self.get(key) == value) > > @post(lambda self, key: old(self.get(key)) is None and > old(self.length()) + 1 == self.length(), > > "length increased with a new key") > > @post(lambda self, key: old(self.get(key)) is not None and > old(self.length()) == self.length(), > > "length stable with an existing key") > > def put(self, key: str, value: str) -> None: > > ... > > > > How could we possible implement this "old" function? > > > > Here is my suggestion. I'd introduce a decorator "before" that > would allow you to store whatever values in a dictionary object "old" (i.e. > an object whose properties correspond to the key/value pairs). The "old" is > then passed to the condition. Here is it in code: > > > > # omitted contracts for brevity > > class NovelDict: > > def length(self)->int: > > ... > > > > # omitted contracts for brevity > > def get(self, key: str) -> Optional[str]: > > ... > > > > @before(lambda self, key: {"length": self.length(), "get": > self.get(key)}) > > @post(lambda self, key, value: self.get(key) == value) > > @post(lambda self, key, old: old.get is None and old.length + > 1 == self.length(), > > "length increased with a new key") > > @post(lambda self, key, old: old.get is not None and > old.length == self.length(), > > "length stable with an existing key") > > def put(self, key: str, value: str) -> None: > > ... > > > > The linter would statically check that all attributes accessed in > "old" have to be defined in the decorator "before" so that attribute errors > would be caught early. The current implementation of the linter is fast > enough to be run at save time so such errors should usually not happen with > a properly set IDE. > > > > "before" decorator would also have "enabled" property, so that you > can turn it off (e.g., if you only want to run a postcondition in testing). > The "before" decorators can be stacked so that you can also have a more > fine-grained control when each one of them is running (some during test, > some during test and in production). The linter would enforce that before's > "enabled" is a disjunction of all the "enabled"'s of the corresponding > postconditions where the old value appears. > > > > Is this a sane approach to "old" values? Any alternative approach > you would prefer? What about better naming? Is "before" a confusing name? > > The dict can be splatted into the postconditions, so that no special > name is required. This would require either that the lambdas handle > **kws, or that their caller inspect them to see what names they take. > Perhaps add a function to functools which only passes kwargs that > fit. > Then the precondition mechanism can pass `self`, `key`, and `value` > as > kwargs instead of args. > > For functions that have *args and **kwargs, it may be necessary to > pass them to the conditions as args and kwargs instead. > > The name "before" is a confusing name. It's not just something that > happens before. It's really a pre-`let`, adding names to the scope of > things after it, but with values taken before the function call. > Based > on that description, other possible names are `prelet`, `letbefore`, > `predef`, `defpre`, `beforescope`. Better a name that is clearly > confusing than one that is obvious but misleading. > > By the way, should the first postcondition be `self.get(key) is > value`, checking for identity rather than equality? > _______________________________________________ Python-ideas mailing list Python-ideas@python.org https://mail.python.org/mailman/listinfo/python-ideas Code of Conduct: http://python.org/psf/codeofconduct/
Hi James, I reread the proposal with MockP. I still don't get the details, but if I think I understand the basic idea. You put a placeholder and whenever one of its methods is called (including dunders), you record it and finally assemble an AST and compile a lambda function to be executed at actual call later. But that would still fail if you want to have: @snapshot(var1=some_func(MockP.arg1, MockP.arg2)) , right? Or there is a way to record that? Cheers, Marko Le sam. 29 sept. 2018 à 00:35, James Lu <jamtlu@gmail.com> a écrit :
I am fine with your proposed syntax. It’s certainly lucid. Perhaps it would be a good idea to get people accustomed to “non-magic” syntax.
I still have a feeling that most developers would like to store the state in many different custom ways.
Please explain. (Expressions like thunk(all)(a == b for a, b in P.arg.meth()) would be valid.)
I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them).
Except for a > b > c being one flat expression with 5 members, it seems fairly easy to recreate an AST, which can then be compiled down to a code object. The code object can be fun with a custom “locals()”
Below is my concept code for such a P object.
from ast import *
# not done: enforce Singleton property on EmptySymbolType
class EmptySymbolType(object): ...
EmptySymbol = EmptySymbolType() # empty symbols are placeholders
class MockP(object):
# "^" is xor
@icontract.pre(lambda symbol, astnode: (symbol is None) ^ (astnode is None))
def __init__(self, symbol=None, value=EmptySymbol, astnode=None, initsymtable=(,)):
self.symtable = dict(initsymtable)
if symbol:
self.expr = Expr(value=Name(id=symbol, ctx=Load()))
self.symtable = {symbol: value}
else:
self.expr = astnode
self.frozen = False
def __add__(self, other):
wrapped = MockP.wrap_value(other)
return MockP(astnode=Expr(value=BinOp(self.expr, Add(), wrapped.expr), initsymtable={**self.symtable, **wrapped.symtable})
def compile(self): ...
def freeze(self):
# frozen objects wouldn’t have an overrided getattr, allowing for icontract to manipulate the MockP object using its public interface
self.frozen = True
@classmethod
def wrap_value(cls, obj):
# create a MockP object from a value. Generate a random identifier and set that as the key in symtable, the AST node is the name of that identifier, retrieving its value through simple expression evaluation.
...
thunk = MockP.wrap_value
P = MockP('P')
# elsewhere: ensure P is only accessed via valid “dot attribute access” inside @snapshot so contracts fail early, or don’t and allow Magic like __dict__ to occur on P.
On Sep 27, 2018, at 9:49 PM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi James,
I still have a feeling that most developers would like to store the state in many different custom ways. I see also thunk and snapshot with wrapper objects to be much more complicated to implement and maintain; I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them). Then the linters need also to work around such wrappers... It might also scare users off since it looks like too much magic. Another concern I also have is that it's probably very hard to integrate these wrappers with mypy later -- but I don't really have a clue about that, only my gut feeling?
What about we accepted to repeat "lambda P, " prefix, and have something like this:
@snapshot( lambda P, some_name: len(P.some_property), lambda P, another_name: hash(P.another_property) )
It's not too verbose for me and you can still explain in three-four sentences what happens below the hub in the library's docs. A pycharm/pydev/vim/emacs plugins could hide the verbose parts.
I performed a small experiment to test how this solution plays with pylint and it seems OK that arguments are not used in lambdas.
Cheers, Marko
On Thu, 27 Sep 2018 at 12:27, James Lu <jamtlu@gmail.com> wrote:
Why couldn’t we record the operations done to a special object and replay them?
Actually, I think there is probably no way around a decorator that
captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
from icontract import snapshot, P, thunk @snapshot(some_identifier=P.self.some_method(P.some_argument.some_attr))
P is an object of our own type, let’s call the type MockP. MockP returns new MockP objects when any operation is done to it. MockP * MockP = MockP. MockP.attr = MockP. MockP objects remember all the operations done to them, and allow the owner of a MockP object to re-apply the same operations
“thunk” converts a function or object or class to a MockP object, storing the function or object for when the operation is done.
thunk(function)(<MockP expression>)
Of course, you could also thunk objects like so: thunk(3) * P.number. (Though it might be better to keep the 3 after P.number in this case so P.number’s __mult__ would be invoked before 3’s __mult__ is invokes.
In most cases, you’d save any operations that can be done on a copy of the data as generated by @snapshot in @postcondiion. thunk is for rare scenarios where 1) it’s hard to capture the state, for example an object that manages network state (or database connectivity etc) and whose stage can only be read by an external classmethod 2) you want to avoid using copy.deepcopy.
I’m sure there’s some way to override isinstance through a meta class or dunder subclasshook.
I suppose this mocking method could be a shorthand for when you don’t need the full power of a lambda. It’s arguably more succinct and readable, though YMMV.
I look forward to reading your opinion on this and any ideas you might have.
On Sep 26, 2018, at 3:56 PM, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Yes, though if we’re talking syntax using kwargs would probably be better. Using “P” instead of “_”: (I agree that _ smells of ignored arguments)
@snapshot(some_identifier=lambda P: ..., some_identifier2=lambda P: ...)
Kwargs has the advantage that you can extend multiple lines without repeating @snapshot, though many lines of @capture would probably be more intuitive since each decorator captures one variable.
Why uppercase "P" and not lowercase (uppercase implies a constant for me)?
To me, the capital letters are more prominent and explicit- easier to see when reading code. It also implies its a constant for you- you shouldn’t be modifying it, because then you’d be interfering with the function itself.
Side node: maybe it would be good to have an @icontract.nomutate (probably use a different name, maybe @icontract.readonly) that makes sure a method doesn’t mutate its own __dict__ (and maybe the __dict__ of the members of its __dict__). It wouldn’t be necessary to put the decorator on every read only function, just the ones your worried might mutate.
Maybe a @icontract.nomutate(param=“paramname”) that ensures the __dict__ of all members of the param name have the same equality or identity before and after. The semantics would need to be worked out.
On Sep 26, 2018, at 8:58 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Am I correct?
"_" looks a bit hard to read for me (implying ignored arguments).
Why uppercase "P" and not lowercase (uppercase implies a constant for me)? Then "O" for "old" and "P" for parameters in a condition: @post(lambda O, P: ...) ?
It also has the nice property that it follows both the temporal and the alphabet order :)
On Wed, 26 Sep 2018 at 14:30, James Lu <jamtlu@gmail.com> wrote:
I still prefer snapshot, though capture is a good name too. We could use generator syntax and inspect the argument names.
Instead of “a”, perhaps use “_”. Or maybe use “A.”, for arguments. Some people might prefer “P” for parameters, since parameters sometimes means the value received while the argument means the value passed.
(#A1)
from icontract import snapshot, __ @snapshot(some_func(_.some_argument.some_attr) for some_identifier, _ in __)
Or (#A2)
@snapshot(some_func(some_argument.some_attr) for some_identifier, _, some_argument in __)
— Or (#A3)
@snapshot(lambda some_argument,_,some_identifier: some_func(some_argument.some_attr))
Or (#A4)
@snapshot(lambda _,some_identifier: some_func(_.some_argument.some_attr)) @snapshot(lambda _,some_identifier, other_identifier: some_func(_.some_argument.some_attr), other_func(_.self))
I like #A4 the most because it’s fairly DRY and avoids the extra punctuation of
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)})
On Sep 26, 2018, at 12:23 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi,
Franklin wrote:
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
James wrote:
I suggest that instead of “@before” it’s “@snapshot” and instead of “ old” it’s “snapshot”.
I like "snapshot", it's a bit clearer than prefixing/postfixing verbs with "pre" which might be misread (*e.g., *"prelet" has a meaning in Slavic languages and could be subconsciously misread, "predef" implies to me a pre-*definition* rather than prior-to-definition , "beforescope" is very clear for me, but it might be confusing for others as to what it actually refers to ). What about "@capture" (7 letters for captures *versus *8 for snapshot)? I suppose "@let" would be playing with fire if Python with conflicting new keywords since I assume "let" to be one of the candidates.
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
I'd still go with the dictionary to allow for this extra freedom. We could have a convention: "a" denotes to the current arguments, and "b" denotes the captured values. It might make an interesting hint that we put "b" before "a" in the condition. You could also interpret "b" as "before" and "a" as "after", but also "a" as "arguments".
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)}) @post(lambda b, a, result: b.some_identifier > result + a.another_argument.another_attr) def some_func(some_argument: SomeClass, another_argument: AnotherClass) -> SomeResult: ...
"b" can be omitted if it is not used. Under the hub, all the arguments to the condition would be passed by keywords.
In case of inheritance, captures would be inherited as well. Hence the library would check at run-time that the returned dictionary with captured values has no identifier that has been already captured, and the linter checks that statically, before running the code. Reading values captured in the parent at the code of the child class might be a bit hard -- but that is case with any inherited methods/properties. In documentation, I'd list all the captures of both ancestor and the current class.
I'm looking forward to reading your opinion on this and alternative suggestions :) Marko
On Tue, 25 Sep 2018 at 18:12, Franklin? Lee < leewangzhong+python@gmail.com> wrote:
On Sun, Sep 23, 2018 at 2:05 AM Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi,
(I'd like to fork from a previous thread, "Pre-conditions and
post-conditions", since it got long and we started discussing a couple of different things. Let's discuss in this thread the implementation of a library for design-by-contract and how to push it forward to hopefully add it to the standard library one day.)
For those unfamiliar with contracts and current state of the
discussion in the previous thread, here's a short summary. The discussion started by me inquiring about the possibility to add design-by-contract concepts into the core language. The idea was rejected by the participants mainly because they thought that the merit of the feature does not merit its costs. This is quite debatable and seems to reflect many a discussion about design-by-contract in general. Please see the other thread, "Why is design-by-contract not widely adopted?" if you are interested in that debate.
We (a colleague of mine and I) decided to implement a library to
bring design-by-contract to Python since we don't believe that the concept will make it into the core language anytime soon and we needed badly a tool to facilitate our work with a growing code base.
The library is available at http://github.com/Parquery/icontract.
The hope is to polish it so that the wider community could use it and once the quality is high enough, make a proposal to add it to the standard Python libraries. We do need a standard library for contracts, otherwise projects with conflicting contract libraries can not integrate (e.g., the contracts can not be inherited between two different contract libraries).
So far, the most important bits have been implemented in icontract:
Preconditions, postconditions, class invariants Inheritance of the contracts (including strengthening and weakening
Informative violation messages (including information about the values involved in the contract condition) Sphinx extension to include contracts in the automatically generated documentation (sphinx-icontract) Linter to statically check that the arguments of the conditions are correct (pyicontract-lint)
We are successfully using it in our code base and have been quite happy about the implementation so far.
There is one bit still missing: accessing "old" values in the
of the inherited contracts) postcondition (i.e., shallow copies of the values prior to the execution of the function). This feature is necessary in order to allow us to verify state transitions.
For example, consider a new dictionary class that has "get" and "put"
methods:
from typing import Optional
from icontract import post
class NovelDict: def length(self)->int: ...
def get(self, key: str) -> Optional[str]: ...
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key: old(self.get(key)) is None and
old(self.length()) + 1 == self.length(),
"length increased with a new key") @post(lambda self, key: old(self.get(key)) is not None and
old(self.length()) == self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
How could we possible implement this "old" function?
Here is my suggestion. I'd introduce a decorator "before" that would
allow you to store whatever values in a dictionary object "old" (i.e. an object whose properties correspond to the key/value pairs). The "old" is then passed to the condition. Here is it in code:
# omitted contracts for brevity class NovelDict: def length(self)->int: ...
# omitted contracts for brevity def get(self, key: str) -> Optional[str]: ...
@before(lambda self, key: {"length": self.length(), "get":
self.get(key)})
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key, old: old.get is None and old.length + 1
== self.length(),
"length increased with a new key") @post(lambda self, key, old: old.get is not None and old.length
== self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
The linter would statically check that all attributes accessed in
"old" have to be defined in the decorator "before" so that attribute errors would be caught early. The current implementation of the linter is fast enough to be run at save time so such errors should usually not happen with a properly set IDE.
"before" decorator would also have "enabled" property, so that you
can turn it off (e.g., if you only want to run a postcondition in testing). The "before" decorators can be stacked so that you can also have a more fine-grained control when each one of them is running (some during test, some during test and in production). The linter would enforce that before's "enabled" is a disjunction of all the "enabled"'s of the corresponding postconditions where the old value appears.
Is this a sane approach to "old" values? Any alternative approach you
would prefer? What about better naming? Is "before" a confusing name?
The dict can be splatted into the postconditions, so that no special name is required. This would require either that the lambdas handle **kws, or that their caller inspect them to see what names they take. Perhaps add a function to functools which only passes kwargs that fit. Then the precondition mechanism can pass `self`, `key`, and `value` as kwargs instead of args.
For functions that have *args and **kwargs, it may be necessary to pass them to the conditions as args and kwargs instead.
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
By the way, should the first postcondition be `self.get(key) is value`, checking for identity rather than equality?
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Hi James, I copy/pasted the discussion re the readability tool to an issue on github: https://github.com/Parquery/icontract/issues/48 Would you mind opening a separate issue and copy/pasting what you find relevant re MockP approach in a separate issue? I think it's time to fork the issues and have separate threads with code highlighting etc. Is that OK with you? Cheers, Marko On Sat, 29 Sep 2018 at 21:22, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi James, I reread the proposal with MockP. I still don't get the details, but if I think I understand the basic idea. You put a placeholder and whenever one of its methods is called (including dunders), you record it and finally assemble an AST and compile a lambda function to be executed at actual call later.
But that would still fail if you want to have: @snapshot(var1=some_func(MockP.arg1, MockP.arg2)) , right? Or there is a way to record that?
Cheers, Marko
Le sam. 29 sept. 2018 à 00:35, James Lu <jamtlu@gmail.com> a écrit :
I am fine with your proposed syntax. It’s certainly lucid. Perhaps it would be a good idea to get people accustomed to “non-magic” syntax.
I still have a feeling that most developers would like to store the state in many different custom ways.
Please explain. (Expressions like thunk(all)(a == b for a, b in P.arg.meth()) would be valid.)
I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them).
Except for a > b > c being one flat expression with 5 members, it seems fairly easy to recreate an AST, which can then be compiled down to a code object. The code object can be fun with a custom “locals()”
Below is my concept code for such a P object.
from ast import *
# not done: enforce Singleton property on EmptySymbolType
class EmptySymbolType(object): ...
EmptySymbol = EmptySymbolType() # empty symbols are placeholders
class MockP(object):
# "^" is xor
@icontract.pre(lambda symbol, astnode: (symbol is None) ^ (astnode is None))
def __init__(self, symbol=None, value=EmptySymbol, astnode=None, initsymtable=(,)):
self.symtable = dict(initsymtable)
if symbol:
self.expr = Expr(value=Name(id=symbol, ctx=Load()))
self.symtable = {symbol: value}
else:
self.expr = astnode
self.frozen = False
def __add__(self, other):
wrapped = MockP.wrap_value(other)
return MockP(astnode=Expr(value=BinOp(self.expr, Add(), wrapped.expr), initsymtable={**self.symtable, **wrapped.symtable})
def compile(self): ...
def freeze(self):
# frozen objects wouldn’t have an overrided getattr, allowing for icontract to manipulate the MockP object using its public interface
self.frozen = True
@classmethod
def wrap_value(cls, obj):
# create a MockP object from a value. Generate a random identifier and set that as the key in symtable, the AST node is the name of that identifier, retrieving its value through simple expression evaluation.
...
thunk = MockP.wrap_value
P = MockP('P')
# elsewhere: ensure P is only accessed via valid “dot attribute access” inside @snapshot so contracts fail early, or don’t and allow Magic like __dict__ to occur on P.
On Sep 27, 2018, at 9:49 PM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
I still have a feeling that most developers would like to store the state in many different custom ways. I see also thunk and snapshot with wrapper objects to be much more complicated to implement and maintain; I'm thinking mostly about all the edge cases which we would not be able to cover (and how complex that would be to cover them). Then the linters need also to work around such wrappers... It might also scare users off since it looks like too much magic. Another concern I also have is that it's probably very hard to integrate these wrappers with mypy later -- but I don't really have a clue about that, only my gut feeling?
What about we accepted to repeat "lambda P, " prefix, and have something like this:
@snapshot( lambda P, some_name: len(P.some_property), lambda P, another_name: hash(P.another_property) )
It's not too verbose for me and you can still explain in three-four sentences what happens below the hub in the library's docs. A pycharm/pydev/vim/emacs plugins could hide the verbose parts.
I performed a small experiment to test how this solution plays with pylint and it seems OK that arguments are not used in lambdas.
Cheers, Marko
On Thu, 27 Sep 2018 at 12:27, James Lu <jamtlu@gmail.com> wrote:
Why couldn’t we record the operations done to a special object and replay them?
Actually, I think there is probably no way around a decorator that
captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
from icontract import snapshot, P, thunk @snapshot(some_identifier=P.self.some_method(P.some_argument.some_attr))
P is an object of our own type, let’s call the type MockP. MockP returns new MockP objects when any operation is done to it. MockP * MockP = MockP. MockP.attr = MockP. MockP objects remember all the operations done to them, and allow the owner of a MockP object to re-apply the same operations
“thunk” converts a function or object or class to a MockP object, storing the function or object for when the operation is done.
thunk(function)(<MockP expression>)
Of course, you could also thunk objects like so: thunk(3) * P.number. (Though it might be better to keep the 3 after P.number in this case so P.number’s __mult__ would be invoked before 3’s __mult__ is invokes.
In most cases, you’d save any operations that can be done on a copy of the data as generated by @snapshot in @postcondiion. thunk is for rare scenarios where 1) it’s hard to capture the state, for example an object that manages network state (or database connectivity etc) and whose stage can only be read by an external classmethod 2) you want to avoid using copy.deepcopy.
I’m sure there’s some way to override isinstance through a meta class or dunder subclasshook.
I suppose this mocking method could be a shorthand for when you don’t need the full power of a lambda. It’s arguably more succinct and readable, though YMMV.
I look forward to reading your opinion on this and any ideas you might have.
On Sep 26, 2018, at 3:56 PM, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Yes, though if we’re talking syntax using kwargs would probably be better. Using “P” instead of “_”: (I agree that _ smells of ignored arguments)
@snapshot(some_identifier=lambda P: ..., some_identifier2=lambda P: ...)
Kwargs has the advantage that you can extend multiple lines without repeating @snapshot, though many lines of @capture would probably be more intuitive since each decorator captures one variable.
Why uppercase "P" and not lowercase (uppercase implies a constant for me)?
To me, the capital letters are more prominent and explicit- easier to see when reading code. It also implies its a constant for you- you shouldn’t be modifying it, because then you’d be interfering with the function itself.
Side node: maybe it would be good to have an @icontract.nomutate (probably use a different name, maybe @icontract.readonly) that makes sure a method doesn’t mutate its own __dict__ (and maybe the __dict__ of the members of its __dict__). It wouldn’t be necessary to put the decorator on every read only function, just the ones your worried might mutate.
Maybe a @icontract.nomutate(param=“paramname”) that ensures the __dict__ of all members of the param name have the same equality or identity before and after. The semantics would need to be worked out.
On Sep 26, 2018, at 8:58 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James,
Actually, following on #A4, you could also write those as multiple decorators: @snpashot(lambda _, some_identifier: some_func(_, some_argument.some_attr) @snpashot(lambda _, other_identifier: other_func(_.self))
Am I correct?
"_" looks a bit hard to read for me (implying ignored arguments).
Why uppercase "P" and not lowercase (uppercase implies a constant for me)? Then "O" for "old" and "P" for parameters in a condition: @post(lambda O, P: ...) ?
It also has the nice property that it follows both the temporal and the alphabet order :)
On Wed, 26 Sep 2018 at 14:30, James Lu <jamtlu@gmail.com> wrote:
I still prefer snapshot, though capture is a good name too. We could use generator syntax and inspect the argument names.
Instead of “a”, perhaps use “_”. Or maybe use “A.”, for arguments. Some people might prefer “P” for parameters, since parameters sometimes means the value received while the argument means the value passed.
(#A1)
from icontract import snapshot, __ @snapshot(some_func(_.some_argument.some_attr) for some_identifier, _ in __)
Or (#A2)
@snapshot(some_func(some_argument.some_attr) for some_identifier, _, some_argument in __)
— Or (#A3)
@snapshot(lambda some_argument,_,some_identifier: some_func(some_argument.some_attr))
Or (#A4)
@snapshot(lambda _,some_identifier: some_func(_.some_argument.some_attr)) @snapshot(lambda _,some_identifier, other_identifier: some_func(_.some_argument.some_attr), other_func(_.self))
I like #A4 the most because it’s fairly DRY and avoids the extra punctuation of
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)})
On Sep 26, 2018, at 12:23 AM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi,
Franklin wrote:
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
James wrote:
I suggest that instead of “@before” it’s “@snapshot” and instead of “ old” it’s “snapshot”.
I like "snapshot", it's a bit clearer than prefixing/postfixing verbs with "pre" which might be misread (*e.g., *"prelet" has a meaning in Slavic languages and could be subconsciously misread, "predef" implies to me a pre-*definition* rather than prior-to-definition , "beforescope" is very clear for me, but it might be confusing for others as to what it actually refers to ). What about "@capture" (7 letters for captures *versus *8 for snapshot)? I suppose "@let" would be playing with fire if Python with conflicting new keywords since I assume "let" to be one of the candidates.
Actually, I think there is probably no way around a decorator that captures/snapshots the data before the function call with a lambda (or even a separate function). "Old" construct, if we are to parse it somehow from the condition function, would limit us only to shallow copies (and be complex to implement as soon as we are capturing out-of-argument values such as globals *etc.)*. Moreove, what if we don't need shallow copies? I could imagine a dozen of cases where shallow copy is not what the programmer wants: for example, s/he might need to make deep copies, hash or otherwise transform the input data to hold only part of it instead of copying (*e.g., *so as to allow equality check without a double copy of the data, or capture only the value of certain property transformed in some way).
I'd still go with the dictionary to allow for this extra freedom. We could have a convention: "a" denotes to the current arguments, and "b" denotes the captured values. It might make an interesting hint that we put "b" before "a" in the condition. You could also interpret "b" as "before" and "a" as "after", but also "a" as "arguments".
@capture(lambda a: {"some_identifier": some_func(a.some_argument.some_attr)}) @post(lambda b, a, result: b.some_identifier > result + a.another_argument.another_attr) def some_func(some_argument: SomeClass, another_argument: AnotherClass) -> SomeResult: ...
"b" can be omitted if it is not used. Under the hub, all the arguments to the condition would be passed by keywords.
In case of inheritance, captures would be inherited as well. Hence the library would check at run-time that the returned dictionary with captured values has no identifier that has been already captured, and the linter checks that statically, before running the code. Reading values captured in the parent at the code of the child class might be a bit hard -- but that is case with any inherited methods/properties. In documentation, I'd list all the captures of both ancestor and the current class.
I'm looking forward to reading your opinion on this and alternative suggestions :) Marko
On Tue, 25 Sep 2018 at 18:12, Franklin? Lee < leewangzhong+python@gmail.com> wrote:
On Sun, Sep 23, 2018 at 2:05 AM Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Hi,
(I'd like to fork from a previous thread, "Pre-conditions and
post-conditions", since it got long and we started discussing a couple of different things. Let's discuss in this thread the implementation of a library for design-by-contract and how to push it forward to hopefully add it to the standard library one day.)
For those unfamiliar with contracts and current state of the
discussion in the previous thread, here's a short summary. The discussion started by me inquiring about the possibility to add design-by-contract concepts into the core language. The idea was rejected by the participants mainly because they thought that the merit of the feature does not merit its costs. This is quite debatable and seems to reflect many a discussion about design-by-contract in general. Please see the other thread, "Why is design-by-contract not widely adopted?" if you are interested in that debate.
We (a colleague of mine and I) decided to implement a library to
bring design-by-contract to Python since we don't believe that the concept will make it into the core language anytime soon and we needed badly a tool to facilitate our work with a growing code base.
The library is available at http://github.com/Parquery/icontract.
The hope is to polish it so that the wider community could use it and once the quality is high enough, make a proposal to add it to the standard Python libraries. We do need a standard library for contracts, otherwise projects with conflicting contract libraries can not integrate (e.g., the contracts can not be inherited between two different contract libraries).
So far, the most important bits have been implemented in icontract:
Preconditions, postconditions, class invariants Inheritance of the contracts (including strengthening and weakening
Informative violation messages (including information about the values involved in the contract condition) Sphinx extension to include contracts in the automatically generated documentation (sphinx-icontract) Linter to statically check that the arguments of the conditions are correct (pyicontract-lint)
We are successfully using it in our code base and have been quite happy about the implementation so far.
There is one bit still missing: accessing "old" values in the
of the inherited contracts) postcondition (i.e., shallow copies of the values prior to the execution of the function). This feature is necessary in order to allow us to verify state transitions.
For example, consider a new dictionary class that has "get" and
"put" methods:
from typing import Optional
from icontract import post
class NovelDict: def length(self)->int: ...
def get(self, key: str) -> Optional[str]: ...
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key: old(self.get(key)) is None and
old(self.length()) + 1 == self.length(),
"length increased with a new key") @post(lambda self, key: old(self.get(key)) is not None and
old(self.length()) == self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
How could we possible implement this "old" function?
Here is my suggestion. I'd introduce a decorator "before" that would
allow you to store whatever values in a dictionary object "old" (i.e. an object whose properties correspond to the key/value pairs). The "old" is then passed to the condition. Here is it in code:
# omitted contracts for brevity class NovelDict: def length(self)->int: ...
# omitted contracts for brevity def get(self, key: str) -> Optional[str]: ...
@before(lambda self, key: {"length": self.length(), "get":
self.get(key)})
@post(lambda self, key, value: self.get(key) == value) @post(lambda self, key, old: old.get is None and old.length + 1
== self.length(),
"length increased with a new key") @post(lambda self, key, old: old.get is not None and old.length
== self.length(),
"length stable with an existing key") def put(self, key: str, value: str) -> None: ...
The linter would statically check that all attributes accessed in
"old" have to be defined in the decorator "before" so that attribute errors would be caught early. The current implementation of the linter is fast enough to be run at save time so such errors should usually not happen with a properly set IDE.
"before" decorator would also have "enabled" property, so that you
can turn it off (e.g., if you only want to run a postcondition in testing). The "before" decorators can be stacked so that you can also have a more fine-grained control when each one of them is running (some during test, some during test and in production). The linter would enforce that before's "enabled" is a disjunction of all the "enabled"'s of the corresponding postconditions where the old value appears.
Is this a sane approach to "old" values? Any alternative approach
you would prefer? What about better naming? Is "before" a confusing name?
The dict can be splatted into the postconditions, so that no special name is required. This would require either that the lambdas handle **kws, or that their caller inspect them to see what names they take. Perhaps add a function to functools which only passes kwargs that fit. Then the precondition mechanism can pass `self`, `key`, and `value` as kwargs instead of args.
For functions that have *args and **kwargs, it may be necessary to pass them to the conditions as args and kwargs instead.
The name "before" is a confusing name. It's not just something that happens before. It's really a pre-`let`, adding names to the scope of things after it, but with values taken before the function call. Based on that description, other possible names are `prelet`, `letbefore`, `predef`, `defpre`, `beforescope`. Better a name that is clearly confusing than one that is obvious but misleading.
By the way, should the first postcondition be `self.get(key) is value`, checking for identity rather than equality?
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Hi Marko, I just found the time to reply to these.
I reread the proposal with MockP. I still don't get the details, but if I think I understand the basic idea. You put a placeholder and whenever one of its methods is called (including dunders), you record it and finally assemble an AST and compile a lambda function to be executed at actual call later. Precisely.
But that would still fail if you want to have: @snapshot(var1=some_func(MockP.arg1, MockP.arg2)) , right? Or there is a way to record that?
This would still fail. You would record it like this: @snapshot(var1=thunk(some_func)(MockP.arg1, MockP.arg2)) thunk stores the function for later and produces another MockP object that listens for __call__. By the way, MockP is the class while P is a virgin instance of MockP. MockP instances are immutable, so any operation on a MockP instance creates a new object or MockP instance. I’m also beginning to lean towards @snapshot(var1=...) @snapshot(var2=...) I suspect this would deal better with VCS. This syntax does have a a nice visual alignment. I’m not entirely sure what kind of indentation PEP 8 recommends and editors give, so the point may be moot if the natural indentation also gives the same visual alignment. Though both should be supported so the best syntax may win. James Lu
On Sep 29, 2018, at 3:22 PM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
I reread the proposal with MockP. I still don't get the details, but if I think I understand the basic idea. You put a placeholder and whenever one of its methods is called (including dunders), you record it and finally assemble an AST and compile a lambda function to be executed at actual call later.
But that would still fail if you want to have: @snapshot(var1=some_func(MockP.arg1, MockP.arg2)) , right? Or there is a way to record that?
Hi Marko, Going back to your proposal on repeating lambda P as a convention. I do find @snapshot(some_identifier=P -> P.self(P.arg1), some_identifier2=P -> P.arg1 + P.arg2) acceptable. Should we keep some kind of document to keep track of all the different proposals? I’m thinking an editable document like HackMD where we can label all the different ideas to keep them straight in our head. James Lu
Hi Marko,
If the documentation is clear, I'd expect the user to be able to distinguish the two. The first approach is shorter, and uses magic, but fails in some rare situations. The other method is more verbose, but always works. I like this idea.
James Lu
On Sep 29, 2018, at 1:36 AM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
If the documentation is clear, I'd expect the user to be able to distinguish the two. The first approach is shorter, and uses magic, but fails in some rare situations. The other method is more verbose, but always works.
Hi Marko, Regarding the “transpile into Python” syntax with with statements: Can I see an example of this syntax when used in pathlib? I’m a bit worried this syntax is too long and “in the way”, unlike decorators which are before the function body. Or do you mean that both MockP and your syntax should be supported? Would with requiring: assert arg1 < arg2, “message” Be the code you type or the code that’s actually run? James Lu
On Sep 29, 2018, at 2:56 PM, Marko Ristin-Kaufmann <marko.ristin@gmail.com> wrote:
Just
Hi James, (I'm just about to go to sleep, so I'll answer the other messages tomorrow.) Should we keep some kind of document to keep track of all the different
proposals? I’m thinking an editable document like HackMD where we can label all the different ideas to keep them straight in our head.
I thought github issues would be a suitable place for that: https://github.com/Parquery/icontract/issues It reads a bit easier as a discussion rather than a single document -- if anybody else needs to follow. What do you think? On Sun, 30 Sep 2018 at 22:07, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Going back to your proposal on repeating lambda P as a convention.
I do find
@snapshot(some_identifier=P -> P.self(P.arg1), some_identifier2=P -> P.arg1 + P.arg2)
acceptable.
Should we keep some kind of document to keep track of all the different proposals? I’m thinking an editable document like HackMD where we can label all the different ideas to keep them straight in our head.
James Lu
Hi Marko, Regarding switching over to GitHub issues: * I copy-pasted the MockP original code to GitHub issues. * There's a clunky way to view the discussion at https://mail.python.org/pipermail/python-ideas/2018-September/subject.html#s... . * The less clunky way to view the discussion is to subscribe to the mailing list and use Gmail to move all the messages from python-ideas to python ideas list and all the messages from the discussions we have to a "contracts" label and view the discussion with your email client. * A week earlier I didn't think I'd be saying this, but I like email for discussion better. It works on mobile and I can send messages offline, and I send 90% of my messages on my phone and when I'm offline. Unless you know an alternative (WhatsApp, maybe?) that fits my use cases off the top of your head, I think we should stick to email. * My proposal: We split the discussion into a new email thread, we keep the latest agreed upon proposal on GitHub issues. On Sun, Sep 30, 2018 at 4:32 PM Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James, (I'm just about to go to sleep, so I'll answer the other messages tomorrow.)
Should we keep some kind of document to keep track of all the different
proposals? I’m thinking an editable document like HackMD where we can label all the different ideas to keep them straight in our head.
I thought github issues would be a suitable place for that: https://github.com/Parquery/icontract/issues
It reads a bit easier as a discussion rather than a single document -- if anybody else needs to follow. What do you think?
On Sun, 30 Sep 2018 at 22:07, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Going back to your proposal on repeating lambda P as a convention.
I do find
@snapshot(some_identifier=P -> P.self(P.arg1), some_identifier2=P -> P.arg1 + P.arg2)
acceptable.
Should we keep some kind of document to keep track of all the different proposals? I’m thinking an editable document like HackMD where we can label all the different ideas to keep them straight in our head.
James Lu
Hi James, Sure, let's do that! I'm fine with emails, too. I needed only a bit of structure since we lumped so many issues together, but maybe it's just my OCD :) Le lun. 1 oct. 2018 à 04:05, James Lu <jamtlu@gmail.com> a écrit :
Hi Marko,
Regarding switching over to GitHub issues: * I copy-pasted the MockP original code to GitHub issues. * There's a clunky way to view the discussion at https://mail.python.org/pipermail/python-ideas/2018-September/subject.html#s... . * The less clunky way to view the discussion is to subscribe to the mailing list and use Gmail to move all the messages from python-ideas to python ideas list and all the messages from the discussions we have to a "contracts" label and view the discussion with your email client. * A week earlier I didn't think I'd be saying this, but I like email for discussion better. It works on mobile and I can send messages offline, and I send 90% of my messages on my phone and when I'm offline. Unless you know an alternative (WhatsApp, maybe?) that fits my use cases off the top of your head, I think we should stick to email. * My proposal: We split the discussion into a new email thread, we keep the latest agreed upon proposal on GitHub issues.
On Sun, Sep 30, 2018 at 4:32 PM Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
Hi James, (I'm just about to go to sleep, so I'll answer the other messages tomorrow.)
Should we keep some kind of document to keep track of all the different
proposals? I’m thinking an editable document like HackMD where we can label all the different ideas to keep them straight in our head.
I thought github issues would be a suitable place for that: https://github.com/Parquery/icontract/issues
It reads a bit easier as a discussion rather than a single document -- if anybody else needs to follow. What do you think?
On Sun, 30 Sep 2018 at 22:07, James Lu <jamtlu@gmail.com> wrote:
Hi Marko,
Going back to your proposal on repeating lambda P as a convention.
I do find
@snapshot(some_identifier=P -> P.self(P.arg1), some_identifier2=P -> P.arg1 + P.arg2)
acceptable.
Should we keep some kind of document to keep track of all the different proposals? I’m thinking an editable document like HackMD where we can label all the different ideas to keep them straight in our head.
James Lu
Hi James, I agree. Having a snapshot decorator per variable also has the advantage that we can add parameters to the decorator (e.g., snapshots also need "enabled" and "description" argument). How should we distinguish the two approaches? (I suppose you would also apply them to requests, ensures and invariant decorator, right?) Is there a terminology? Lambda-based conditions might be the name for the conventional approach with @requests(lambda P: ...). What should we term the approach you proposed? Re naming: @requests(lambda P: P.arg1 < P.arg2) and @requests_that(P.arg1 < P.arg2)? Le dim. 30 sept. 2018 à 22:07, James Lu <jamtlu@gmail.com> a écrit :
Hi Marko,
I just found the time to reply to these.
I reread the proposal with MockP. I still don't get the details, but if I think I understand the basic idea. You put a placeholder and whenever one of its methods is called (including dunders), you record it and finally assemble an AST and compile a lambda function to be executed at actual call later. Precisely.
But that would still fail if you want to have: @snapshot(var1=some_func(MockP.arg1, MockP.arg2)) , right? Or there is a way to record that?
This would still fail. You would record it like this: @snapshot(var1=thunk(some_func)(MockP.arg1, MockP.arg2))
thunk stores the function for later and produces another MockP object that listens for __call__.
By the way, MockP is the class while P is a virgin instance of MockP. MockP instances are immutable, so any operation on a MockP instance creates a new object or MockP instance.
I’m also beginning to lean towards @snapshot(var1=...) @snapshot(var2=...)
I suspect this would deal better with VCS.
This syntax does have a a nice visual alignment. I’m not entirely sure what kind of indentation PEP 8 recommends and editors give, so the point may be moot if the natural indentation also gives the same visual alignment.
Though both should be supported so the best syntax may win.
James Lu
On Sep 29, 2018, at 3:22 PM, Marko Ristin-Kaufmann < marko.ristin@gmail.com> wrote:
I reread the proposal with MockP. I still don't get the details, but if I think I understand the basic idea. You put a placeholder and whenever one of its methods is called (including dunders), you record it and finally assemble an AST and compile a lambda function to be executed at actual call later.
But that would still fail if you want to have: @snapshot(var1=some_func(MockP.arg1, MockP.arg2)) , right? Or there is a way to record that?
participants (2)
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James Lu -
Marko Ristin-Kaufmann