🎰 Support __slots__? · Issue #28 · ericvsmith/dataclasses · GitHub

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__repr__() method to provide a nice string representation and an. How to add default values to data class fields; How data classes allow for ordering of Data classes have no explicit syntax for working with slots, but the normal way of.


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__slots__ is an attribute you can add to a Python class when defining it. into play when we start getting and setting values in rapid succession: being instantiated (it's part of the classes default __dict__), __dict__ isn't.


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__repr__() method to provide a nice string representation and an. How to add default values to data class fields; How data classes allow for ordering of Data classes have no explicit syntax for working with slots, but the normal way of.


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The question is: do we even want to support setting __slots__? Sure, you can add slots manually to dataclasses, but then you lose default values, and This tracker is just for the backport of dataclasses features to Python.


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Was there a reason that __slots__ makes initialized variables read-only? It would be useful to have overridable default values (even if it.


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The question is: do we even want to support setting __slots__? Sure, you can add slots manually to dataclasses, but then you lose default values, and This tracker is just for the backport of dataclasses features to Python.


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__slots__ is an attribute you can add to a Python class when defining it. into play when we start getting and setting values in rapid succession: being instantiated (it's part of the classes default __dict__), __dict__ isn't.


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The default can be overridden by defining __slots__ in a new-style just enough space in each instance to hold a value for each variable.


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python __slots__ default values

And that there's no real difference between the dataclass and attrs libraries in access-speed. I propose to punt this down the road. We'd want to make sure the implications of this are understood by the users. Results: Slots win heavily in the memory usage department, regardless of whether you use dataclass or attrs. To illustrate the need, here's an example for a class with 3 attributes, on bit Python 3. Have a question about this project? It should be easy to programmatically determine if they should be added in the child or not. However, this would be difficult or maybe impossible. What's not to love?! They get accessed pretty fast, and they take much less space than even the new smaller dict like a tuple amount of space. Though fields with a default value must come after any fields without a default. Dataclasses is a subset of attrs. I suggest taking this to python-ideas if you'd like to champion one of these ideas. This tracker is just for the backport of dataclasses features to Python 3. I think we should either go with 2 or 3. Thinking it over, I think my use-case is different to what dataclasses are for, and so compatibility probably doesn't make sense anyway. Or will there be internal dataclass bugs caused by lacking a dict? Copy link Quote reply. I suggest you raise this issue on the python-ideas mailing list. Although they are not mainstream, they are still used. I am however not sure about API that we should use. As for data access benchmarks: The result varied too much between runs to draw any conclusions except to say that slots was slightly faster than dictionary-based storage. It's interesting that you can combine the two approaches when you don't set defaults, but the defaults are part of what make this useful in the first place. When this issue is on python-ideas, I'll post my thoughts there. Without slots, the usability of data classes is really limited. Already have an account?

GitHub is home to over 50 million developers working together to host and review code, manage projects, and build python __slots__ default values together.

This should be a strictly dominant addition. For more info it's worth, there is also typing. When I would want to use something like this, it is almost always in a situation where I will have many instances of the same simple data points.

I'll post on the mailing list. Sign up. Jump to bottom. The decorator then returns the new class. DM Refactor Posix and S3 datastores to reduce code python __slots__ default values But I have decided to use attrs instead.

So with attrs you can do everything and more. Reload to refresh your session. Skip to content. New issue. You signed in with another tab or window.

I removed slots in PR The git tag last-version-with-slots points to the code python __slots__ default values slots was working. NamedTuple which uses slots and you can also give a field a default value.

I totally think slots should be default behavior. Owner Author. Issue 28 : Remove support for setting slots. Something else I haven't thought of. For a company that does not allow external packages due to code safety reasonsuse dataclasses.

Sign in to your account. But dataclass loses with its lack of features, lack of default values if slots are used, and tedious way to write slots manually see class "D". I agree. Eric-Arellano mentioned this issue Apr 4, Sign up for free to join this conversation on GitHub.

Already on GitHub? It's very wasteful to have a struct-like data holder class, which relies on a bloated dynamic dictionary for storage. The slots behavior should be the only behavior and dict should be banished from dataclasses.

This comment from YouTube sums it up well: For a company that does not allow external python __slots__ default values due to code safety reasonsuse dataclasses. Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Attrs allows auto-generating "slots" more info optimize memory usage, and allows adding validators if you want, etc.

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My talk even misses this point facepalm. And dataclass with manually written slots reduce total usage by 8 bytes static number, does not change based on how many fields the class has compared to attrs-with-slots. To break it down: slots add a data descriptor to the class that points to a slot in a struct-like datastructure. Support might be added b… …. It offers more features, less memory, and more speed since slots are faster than dictionaries. For everyone else, always use the attrs package. Sure, you can add slots manually to dataclasses, but then you lose default values, and you have to manually write each variable name in the slots list. In the meantime people can also use NamedTuple if they just want slots. Dismiss Join GitHub today GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. So forget about dataclasses. Use the attrs library with slots. The reason this isn't in dataclasses itself is because all other features just involve adding methods to your class. Sign in to comment. The class instances generated are exactly the same size regardless of the attrs or dataclass libraries are used The class instances only use bytes in memory. And the dataclass instance with manually written slots was only 8 bytes smaller than the equivalent attrs instance, which can be explained by attrs metadata variables or something like that, and isn't much extra RAM to pay for all the huge benefits of attrs. Linked pull requests. Support might be added back at a later date. It is much better.