Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Discovering Descriptors
Search
Mariano Anaya
June 09, 2017
Programming
0
200
Discovering Descriptors
Presented at PyCon CZ 2017 on June 9th
Mariano Anaya
June 09, 2017
Tweet
Share
More Decks by Mariano Anaya
See All by Mariano Anaya
Demystifying Coroutines and Asynchronous Programming in Python
rmariano
1
180
Demystifying coroutines and asynchronous programming in Pyhon
rmariano
1
380
Exploring Generators & Coroutines
rmariano
1
820
Discovering-Descriptors_ep.pdf
rmariano
1
390
Beyond Coverage
rmariano
0
190
Clean Code in Python
rmariano
2
2.3k
Other Decks in Programming
See All in Programming
米国のサイバーセキュリティタイムラインと見る Goの暗号パッケージの進化
tomtwinkle
1
370
AHC061解説
shun_pi
0
280
手戻りゼロ? Spec Driven Developmentとは@KAG AI week
tmhirai
1
100
CopilotKit + AG-UIを学ぶ
nearme_tech
PRO
1
120
社内規程RAGの精度を73.3% → 100%に改善した話
oharu121
12
7.1k
RAGでハマりがちな"Excelの罠"を、データの構造化で突破する
harumiweb
8
2.2k
Oxlint JS plugins
kazupon
1
1.2k
AI主導でFastAPIのWebサービスを作るときに 人間が構造化すべき境界線
okajun35
0
460
atmaCup #23でAIコーディングを活用した話
ml_bear
4
720
要求定義・仕様記述・設計・検証の手引き - 理論から学ぶ明確で統一された成果物定義
orgachem
PRO
1
520
PostgreSQL を使った快適な go test 環境を求めて
otakakot
0
380
Geminiの機能を調べ尽くしてみた
naruyoshimi
0
190
Featured
See All Featured
Done Done
chrislema
186
16k
Why You Should Never Use an ORM
jnunemaker
PRO
61
9.8k
Mobile First: as difficult as doing things right
swwweet
225
10k
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
10
1.1k
Practical Orchestrator
shlominoach
191
11k
How to Ace a Technical Interview
jacobian
281
24k
What does AI have to do with Human Rights?
axbom
PRO
1
2k
Applied NLP in the Age of Generative AI
inesmontani
PRO
4
2.1k
The AI Search Optimization Roadmap by Aleyda Solis
aleyda
1
5.3k
Claude Code のすすめ
schroneko
67
220k
SEOcharity - Dark patterns in SEO and UX: How to avoid them and build a more ethical web
sarafernandez
0
130
Building a Modern Day E-commerce SEO Strategy
aleyda
45
8.7k
Transcript
Discovering Descriptors Mariano Anaya Prague - PyCon CZ - June
2017 rmariano rmarianoa
def “Learning about descriptors not only provides access to a
larger toolset, it creates a deeper understanding of how Python works and an appreciation for the elegance of its design”. - Raymond Hettinger
Introduction In general: >>> obj = DomainModel() >>> obj.x =
'value' >>> obj.x 'value'
Control Access to Data But what if… When doing “obj.x”
we could run arbitrary code?
Control Access to Data But what if… When doing “obj.x”
we could run arbitrary code? By another object.
Control Access to Data But what if… When doing “obj.x”
we could run arbitrary code? By another object (of a different class).
A First Look at Descriptors
Introduction Descriptors enable control over core operations (get, set, delete),
of an attribute in an object.
Descriptor Methods __get__(self, instance, owner) __set__(self, instance, value) __delete__(self, instance)
__set_name__(self, owner, name) * * Python 3.6
None
Types of Descriptors • Non-data descriptors (a.k.a “non-overriding”) ◦ Don’t
implement __set__ ◦ Instance attributes take precedence • Data descriptors (a.k.a. “overriding”) ◦ Implement __get__, __set__ ◦ Override instance’s __dict__
__get__ Problem: automatically format date values of other attributes. Two
classes: Descriptor + Managed class
Descriptor
__get__: Default Value class DateFormatter: FORMAT = "%Y-%m-%d %H:%M" def
__init__(self, name=None): self.name = name def __get__(self, instance, owner): if instance is None: return self date_value = getattr(instance, self.name) if date_value is None: return '' return date_value.strftime(self.FORMAT)
Managed Class
__get__: Managed Class class FileStat: """Stats of a file in
a virtual file system""" str_created_at = DateFormatter('created_at') str_updated_at = DateFormatter('updated_at') str_removed_at = DateFormatter() def __init__(self, fname, created, updated=None, removed=None): self.filename = fname self.created_at = created self.updated_at = updated self.removed_at = removed
>>> created = updated = datetime(2017, 6, 9, 11, 15,
19) >>> f1 = FileStat('/home/mariano/file1', created, updated) >>> f1.str_created_at '2017-06-09 11:15' >>> f1.str_updated_at '2017-06-09 11:15' >>> f1.str_removed_at ''
Resolution Order
>>> f1 = FileStat(...) >>> f1.str_created_at Statement f1.__dict__ { 'created_at':
... 'filename': '/home/...', 'removed_at': ..., 'updated_at': ... }
>>> f1 = FileStat(...) >>> f1.str_created_at Statement FileStat.__dict__ mappingproxy({'__dict__': ...,
'__doc__': "...", '__init__': ..., 'str_created_at': <DateFormatter at 0x..>, 'str_removed_at': <DateFormatter at 0x..>, 'str_updated_at': <DateFormatter at 0x..>})
>>> f1 = FileStat(...) >>> f1.str_created_at Statement >>> hasattr(FileStat.__dict__['str_created_at'], '__get__')
True
__get__: Syntax Sugar >>> f1 = FileStat(...) >>> f1.str_created_at Translates
into: FileStat.str_created_at.__get__(f1, FileStat)
__get__(self, instance, owner) When called like <class>.<descriptor> instance is None
>>> FileStat.str_created_at <__main__.DateFormatter object at 0x...> Access Through the Class
Name of the Descriptor
class FileStat: """Stats of a file in a virtual file
system""" str_created_at = DateFormatter('created_at') str_updated_at = DateFormatter('updated_at') str_removed_at = DateFormatter()
Before __set_name__ Some techniques to have an “automatic configuration”: Class
decorator or metaclass
__set_name__(self, owner, name) Called automatically with the name of the
attribute, on the LHS. class owner: name = Descriptor()
__set_name__ class DateFormatter: def __init__(self, name=None): self.name = name ...
def __set_name__(self, owner, name): if self.name is None: _, _, self.name = name.partition('_')
__set__ Problem: Given an attribute of an object, keep count
of how many times its value was changed.
Data Descriptor: __set__ Some strategies: 1. Properties (with setter) 2.
Override __setattr__() 3. Descriptors!
class TracedProperty: """Count how many times an attribute changed its
value""" def __set_name__(self, owner, name): self.name = name self.count_name = f'count_{name}' def __set__(self, instance, value): ...
class TracedProperty: ... def __set__(self, instance, value): try: current_value =
instance.__dict__[self.name] except KeyError: instance.__dict__[self.count_name] = 0 else: if current_value != value: instance.__dict__[self.count_name] += 1 instance.__dict__[self.name] = value
class Traveller: city = TracedProperty() country = TracedProperty() def __init__(self,
name): self.name = name
>>> tourist = Traveller('John Smith') >>> tourist.city = 'Barcelona' >>>
tourist.country = 'Spain' >>> tourist.count_city 0 >>> tourist.count_country 0 >>> tourist.city = 'Stockholm' >>> tourist.country = 'Sweden' >>> tourist.count_city 1 >>> tourist.count_country 1 >>> tourist.city = 'Gothenburg' >>> tourist.count_city 2 >>> tourist.count_country 1 >>> tourist.country = 'Sweden' >>> tourist.count_country 1
tourist = Traveller() tourist.city = 'Stockholm' Traveller.city.__set__(tourist, 'Stockholm') __set__: Syntax
sugar Translates to:
__delete__ Called when deleting an attribute by using the descriptor,
like: del <instance>.<descriptor>
__delete__ class ProtectedAttribute: """Attribute that is protected against deletion""" def
__set_name__(self, owner, name): self.name = name def __delete__(self, instance): raise AttributeError(f"Can't delete {self.name} for {instance!s}") def __set__(self, instance, value): ...
class ProtectedUser: username = ProtectedAttribute() def __init__(self, username, location): self.username
= username self.location = location def __str__(self): return f"{self.__class__.__name__}[{self.username}]"
>>> usr = ProtectedUser('jsmith', '127.0.0.1') >>> usr.username 'jsmith' >>> del
usr.username Traceback (most recent call last): ... AttributeError: Can't delete username for ProtectedUser[jsmith] >>> usr.location '127.0.0.1' >>> del usr.location >>> usr.location Traceback (most recent call last): ... AttributeError: 'ProtectedUser' object has no attribute 'location'
What makes a good descriptor?
What makes a good descriptor? The same thing that makes
any good Python object: consistency with Python itself (to be Pythonic).
Descriptors are deployed in the language infrastructure. • @property, @classmethod,
@staticmethod • Methods (functions) Descriptors in CPython
Functions are Descriptors They have a __get__ method. That’s why
they can work as instance methods! <function>.__get__ returns the function bound to an object.
class Class: def method(self, *args): return f'{self!s} got {args}' >>>
Class.__dict__ mappingproxy({'__dict__': ... 'method': <function Class.method>}) >>> isinstance(Class.__dict__['method'], types.FunctionType) True
>>> instance = Class() >>> instance.method('arg1', 'arg2') "instance got ('arg1',
'arg2')" Method Call >>> Class.method.__get__(instance, Class)('arg1', 'arg2') "instance got ('arg1', 'arg2')" It’s actually...
Extended Uses
Improve decorators that change the signature.
Apply to Functions & Methods as well Problem: A decorator
that changes the signature, has to work both for functions and methods. E.g. abstract away repeated code.
def resolver_function(root, args, context, info): helper = DomainObject(root, args, context,
info) ... helper.process() helper.task1() helper.task2() return helper.task1()
class DomainArgs: def __init__(self, func): self.func = func wraps(func)(self) def
__call__(self, root, args, context, info): helper = DomainObject(root, args, context, info) return self.func(helper) @DomainArgs def resolver_function(helper): helper.task1() ...
class ViewResolver: @DomainArgs def resolve_method(self, helper): response = helper.process() return
f"Method: {response}" Try to Decorate a Method
>>> vr1.resolve_method('root', 'args', 'context', 'info') ------------------------------------ TypeError Traceback (most recent
call last) 39 def __call__(self, root, args, context, info): 40 helper = DomainObject(root, args, context, info) ---> 41 return self.func(helper) 42 TypeError: resolve_method() missing 1 required positional argument: 'helper' Doesn’t handle self!
class DomainArgs: ... def __get__(self, instance, owner): mapped = self.func.__get__(instance,
owner) return self.__class__(mapped) >>> vr = ViewResolver() >>> vr.method_resolver('root', 'args', 'context', 'info') 'Method resolver: root, args, context, info' Fix: __get__
It’s possible to have object-oriented design with descriptors.
Work as generalized properties.
Can help on debugging.
Closing Remarks
Implement the minimum required interface.
Use for general-purpose solutions.
Thanks! @rmarianoa