DataClasses provides a decorator and functions for automatically adding generated special methods such as __init__ () , __repr__ () and __eq__ () to user-defined classes. Python 3. 6, it raises an interesting question: does that guarantee apply to 3. Web Developer. dumps () method of the JSON module has a cls. Python 3. Let's take the below JSON string as example and work with it during the steps: We can see that we need to create two classes : "Test" and "User" since "users" property is an array of object with "id" and "name". There are cases where subclassing pydantic. class WithId (typing. Class instances can also have methods. If it is True, then that particular class attribute for which field function is used with repr parameter as True, is included in the string which is returned by the default __repr__ method of the dataclass. The main reason being that if __slots__ is defined manually or (3. I need c to be displayed along with a and b when printing the object,. ClassVar. Improve this answer. New in version 2. Currently, I ahve to manually pass all the json fields to dataclass. The member variables [. 1 Answer. 目次[ 非表示] 1. Summary: in this tutorial, you’ll learn about the Python exceptions and how to handle them gracefully in programs. I can add input validation via the __post_init__() function like this:Suppose I have a dataclass like. Create a new instance of the target class. By the end of this article, you should be able to: Construct object in dataclasses. If provided, it represents a single-argument callable used to convert all values when assigning to the associated attribute. Note. When the dataclass is being created by the dataclass() decorator, it looks through all of the class’s base classes in reverse MRO (that is, starting at object) and, for each dataclass that it finds, adds the fields from that base class to an ordered mapping of fields. passing dictionary keys. These have a name, a salary, as well as an attribute. I have a python3 dataclass or NamedTuple, with only enum and bool fields. Output: Transaction (sender=’Aryaman’, receiver=’Ankur’, date=’2020-06-18′, amount=1. 94 µs). Using such a thing for dict keys is a hugely bad idea. A dataclass decorator can be used to implement classes that define objects with only data and very minimal functionalities. to_dict. fields() Using dataclasses. The main purpose is to provide a decorator @dataclass to ease the declaration and the usage of classes based. dataclass with the addition of Pydantic validation. py, so no help from the Git log. 12. dataclassで書いたほうがきれいに書けますね！ dataclassでは型チェックしてくれない? 今回の本題です。 user_name: strやuser_id: intで型指定していて、型チェックしているように見えますが、実際は普通のアノテーションです。. 1. A basic example using different types: from pydantic import BaseModel class ClassicBar(BaseModel): count_drinks: int is_open: bool data = {'count_drinks': '226', 'is_open': 'False'} cb = ClassicBar(**data). 以上のようにdataclassでは、slots = True とすると、__slots__ を自動的に生成してくれる。 まとめ. I wonder if there's some corner case where the factory could be invoked in __post_init__ without knowing that it was already invoked in __init__. passing. Hashes for argparse_dataclass-2. dumps() method handles the conversion of a dictionary to a JSON string without any issues. If you're on board with using third-party libraries, a solid option is to leverage the dataclass-wizard library for this task, as shown below; one advantage that it offers - which really helps in this particular. 10. ) Every object has an identity. name = divespot. The dataclass () decorator will add various “dunder” methods. When you want to use a dict to store an object which has always the same attributes, then you should not put it in a dict but use a Dataclass. This module provides a decorator and functions for automatically adding generated special methods. This solution uses an undocumented feature, the __dataclass_fields__ attribute, but it works at least in Python 3. This module provides a decorator and functions for automatically adding generated special methods such as __init__ () and __repr__ () to user-defined classes. I do not know Kotlin, but in Python, a dataclass can be seen as a structured dict. There are several advantages over regular Python classes which we’ll explore in this article. tar. 0) FOO2 = Foo (2, 0. db") to the top of the definition, and the dataclass will now be bound to the file db. I've been reading up on Python 3. I would like to define a class like this: @dataclass class MyClass: accountID: str accountClass: str id: str openTime: str priceDifference: floatThe best approach in Python 3. However, if working on legacy software with Python 2. In the following example, we are going to define a dataclass named Person with 2 attributes: name and age. 1. The comparison includes: size of the object; time to create the object; time to retrieve the attribute; I have created 5 different classes. I’ve been reading up on Python 3. 7 as a utility tool for storing data. The resulting dataclass-function can now be used in the following way: # regular dataclass @dataclass class Position: name: str lon: float lat: float # this one will introspect its fields and try to add magic properties @dataclass(introspect=True) class Section: positions: List[Position] And that's it. ;. @dataclass(init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False) class C. 6 or higher. The Author dataclass includes a list of Item dataclasses. 0. It was introduced in python 3. The next step would be to add a from_dog classmethod, something like this maybe: from dataclasses import dataclass, asdict @dataclass (frozen=True) class AngryDog (Dog): bite: bool = True @classmethod def from_dog (cls, dog: Dog, **kwargs): return cls (**asdict (dog), **kwargs) But following this pattern, you'll face a specific edge. 如果所添加的方法已存在于类中，则行为将取决于下面所列出的形参。. 7 was released a while ago, and I wanted to test some of the fancy new dataclass+typing features. Unlike in Pyret, there’s no distinction between the name of the dataclass and the name of its constructor; we can build a TodoItem like so:🔖 TL; DR: If you want an immutable container data type with a small subset of fields taking default values, consider named tuples. SQLAlchemy as of version 2. Decode as part of a larger JSON object containing my Data Class (e. You want to be able to dynamically add new fields after the class already exists, and. The module is new in Python 3. It serializes dataclass, datetime, numpy, and UUID instances natively. Data classes. 7. First, we encode the dataclass into a python dictionary rather than a JSON string, using . Here. eq, order, frozen, init and unsafe_hash are parameters supported in the stdlib dataclass, with meanings defined in PEP 557. They are most useful when you have a variable that can take one of a limited selection of values. 以下是dataclass装饰器带来的变化：. To generically type hint a dataclass - since dataclasses are essentially Python classes under the hood, with auto-generated methods and some "extra" class attributes added in to the mix, you could just type hint it with typing. __init__() method (Rectangle. Consider: import json from attr import dataclass from dataclasses_json import dataclass_json @dataclass @dataclass_json class Prod: id:. However, Python is a multi-paradigm language and sometimes function-based code passing (ideally immutable) data around is a lot simple and easier to read/maintain. The benefits we have realized using Python @dataclass. From what I understand, descriptors are essentially an easier approach as compared to declaring a ton of properties, especially if the purpose or usage of said. org. I use them all the time, just love using them. Because you specified default value for them and they're now a class attribute. """ name: str = validate_somehow() unit_price: float = validate_somehow() quantity_on_hand: int = 0. from dataclasses import dataclass from dataclasses_json import dataclass_json @dataclass_json @dataclass class Person: name: str person = Person (name = 'lidatong'). So to make it work you need to call the methods of parent classes manually:Keeps the code lean and it looks like an attribute from the outside: def get_price (symbol): return 123 @dataclass class Stock: symbol: str @property def price (self): return get_price (symbol) stock = Stock ("NVDA") print (stock. One main design goal of Data Classes is to support static type checkers. ) Since creating this library, I've discovered. One way to do that us to use a base class to add the methods. The Data Classes are implemented by. Whilst NamedTuples are designed to be immutable, dataclasses can offer that functionality by setting frozen=True in the decorator, but provide much more flexibility overall. dataclass class Test: value: int def __post_init__ (self): self. 67 ns. full_name = f" {self. 10, here is the PR that solved the issue 43532. You will see this error: E dataclasses. I want to parse json and save it in dataclasses to emulate DTO. 6. Defining a dataclass in Python is simple. Enter dataclasses, introduced in Python 3. 2 Answers. The standard Python libraries for encoding Python into JSON, such as the stdlib’s json, simplejson, and demjson, can only handle Python primitives that have a direct JSON equivalent (e. You have to set the frozen parameter from the dataclass decorator to True to make the data class immutable. I was wondering if dataclass is compatible with the property decorator to define getter and setter functions for the data elements of the dataclass. Also, remember to convert the grades to int. from dataclasses import dataclass @dataclass(frozen=True) class Base: x: int y: int @dataclass(frozen=True) class BaseExtended(Base): z: str. dataclasses. Now I want to assign those common key value from class A to to class B instance. 🔖 TL; DR: If you want an immutable container data type with a small subset of fields taking default values, consider named tuples. Using a property in a dataclass that shares the name of an argument of the __init__ method has an interesting side effect. It benchmarks as the fastest Python library for JSON and is more correct than the standard json library or other third-party libraries. TypeVar ("Klass", bound=WithId) By simply removing the __dataclass_fields__ from the typing. FrozenInstanceError: cannot assign to field 'blocked'. """ cls = obj if isinstance (obj, type) else type (obj) return hasattr (cls, _FIELDS)Enum HOWTO ¶. Main features. @dataclass() class C:. 7 that provides a convenient way to define classes primarily used for storing data. Python Tutorials → In-depth articles and video courses Learning Paths → Guided study plans for accelerated learning Quizzes → Check your learning progress Browse Topics → Focus on a specific area or skill level Community Chat → Learn with other Pythonistas Office Hours → Live Q&A calls with Python experts Podcast → Hear what’s new in the. Secondly, if you still want to freeze Person instances, then you should initialize fields with method __setattr__. Go ahead and execute the following command to run the game with all the available life. I have a dataclass with this structure: from dataclasses import dataclass from typing import List @dataclass class PartData: id: int = 0 name: str = None value: int = 0 @dataclass class. Module-level decorators, classes, and functions¶ @dataclasses. dataclass (*, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False) ¶ This function is a decorator that is used to add generated special method s to classes, as described below. Store the order of arguments given to dataclass initializer. >>> import yaml >>> yaml. Here are the supported features that dataclass-wizard currently provides:. When creating my dataclass, the types don't match as it is considering str != MyEnum. The Dataclass tries to generalise the common requirements of data classes and provide the out-of-the-box, but it also provides class-level and. Let your dataclass inherit from Persistent . class Person: def __init__ (self, first_name, last_name): self. from dataclasses import dataclass, asdict @dataclass class MyDataClass: ''' description of the dataclass ''' a: int b: int # create instance c = MyDataClass (100, 200) print (c) # turn into a dict d = asdict (c) print (d) But i am trying to do the reverse process: dict -> dataclass. The internal code that generates the dataclass's __init__ function can only examine the MRO of the dataclass as it is declared on its own, not when mixed in to another class. Python dataclass from a nested dict. some_property ** 2 cls. With two exceptions described below, nothing in dataclass () examines the type specified in the variable annotation. List: from dataclasses import dataclass from typing import List @dataclass class Test: my_array: List [ChildType] And from Python 3. length and . last_name = self. @dataclass (frozen=True) class Foo (Enum): a: int b: float FOO1 = Foo (1, 1. What are data objects. Dataclass CSV. Here we’re defining a dataclass called TodoItem with three components: a deadline, a list of tags, and a description. In Python, the class name provides what other languages, such as C++ and Java, call the class constructor. fields() to find all the fields in the dataclass. output (given the dataclass-like __repr__ implementation on FieldDateTime to make it look a bit better): NormalDataClass (id=10, dt=FieldDateTime (2021-09-04 20:11:00)) Init-only fields are added as parameters to the generated __init__ method, and are passed to the optional __post_init__ method. Creating a new class creates a new type of object, allowing new instances of that type to be made. A few workarounds exist for this: You can either roll your own JSON parsing helper method, for example a from_json which converts a JSON string to an List instance with a nested. ] are defined using PEP 526 type annotations. 156s test_dataclass 0. Let’s see how it’s done. A field is defined as class variable that has a type. Thanks to @dataclass decorator you can easily create a new custom type with a list of given fields in a declarative manner. Each dataclass is converted to a dict of its. width attributes even though you just had to supply a. 0. from dataclasses import dataclass from enum import Enum class UserType(Enum): CUSTOMER = 0 MODERATOR = 1 ADMIN. For frozen dataclasses, the converter is only used inside a dataclass -synthesized __init__ when setting the attribute. Python dataclass is a feature introduced in Python 3. ), compatible with Jax, TensorFlow, and numpy (with torch support planned). Keep in mind that pydantic. 7's dataclass as an alternative to namedtuples (what I typically use when having to group data in a structure). 155s test_slots 0. 7, this module makes it easier to create data classes. 생성된 모든 메서드의 필드 순서는 클래스 정의에 나타나는 순서입니다. This is useful for reducing ambiguity, especially if any of the field values have commas in them. The main principle behind a dataclass is to minimize the amount of boilerplate code required to create classes. dataclass stores its fields a __dataclass_fields__ attribute which is an instance of Field. (where, of course, my decorator argument doesn't work) that would do all the routine stuff that @dataclass does, and essentially outputs the code of the first snippet. A dataclass definese a record type, a dictionary is a mapping type. This decorator is natively included in Python 3. @dataclass class Foo: x: int _x: int = field. 9 onwards, you can conveniently just use list: from dataclasses import dataclass @dataclass class Test: my. There’s a paragraph in the docs that mentions this: If eq and frozen are both true, by default dataclass () will generate a __hash__ () method for you. 따라서 이 데이터 클래스는 다음과 같이 이전. Write custom JSONEncoder to make class JSON serializable. 4 Answers. – chepner. I would need to take the question about json serialization of @dataclass from Make the Python json encoder support Python's new dataclasses a bit further: consider when they are in a nested structure. i. Properties which. You have 3 options: Set frozen=True (in combination with the default eq=True ), which will make your class immutable and hashable. You can generate the value for id in a __post_init__ method; make sure you mark it as exempt from the __init__ arguments with a dataclass. The goal is to achieve the selected columns in SQL based on the some manual classification of the fields, e. An “Interesting” Data-Class. Full copy of an instance of a dataclass with complex structure. Python3. The Python decorator automatically generates several methods for the class, including an __init__() method. BaseModel. Objects, values and types ¶. All you have to do is wrap the class in the decorator: from dataclasses import dataclass @dataclass. Sorted by: 38. はじめに. This slows down startup time. I am just going to say it, dataclasses are great. 3) Here it won't allow me to create the object & it will throworjson. 7Typing dataclass that can only take enum values. Enum HOWTO. dataclassy is a reimplementation of data classes in Python - an alternative to the built-in dataclasses module that avoids many of its common pitfalls. python-dataclasses. You can use dataclasses. The first piece is defining the user class: We’ve created our properties, assigned a default value to one of them, and slapped a @dataclass decorator up top. 0. A dataclass in python is a specially structured class that is optimized for the storage and representation of data. To generically type hint a dataclass - since dataclasses are essentially Python classes under the hood, with auto-generated methods and some "extra" class attributes added in to the mix, you could just type hint it with typing. Pythonで辞書を使うとき地味に面倒なので、[KEYNAME]での参照です。辞書をdataclass や namedtuple のようにドット表記でアトリビュート参照するように値にアクセスできるようにしたライブラリが datajuggler です。. DataClasses has been added in a recent addition in python 3. And because the tuple structure is written in C, standard methods are faster in NamedTuple (hash, comparing and etc). Motivation: The @dataclass decorator is run every time a dataclass (the class, not an instance) is created. The dataclass decorator is located in the dataclasses module. pop. The dataclass decorator is actually a code generator that automatically adds other methods under the hood. Type checkers like mypy have no problems interpreting it correctly, Person ('John') gets a pass, and Person ('Marc. When a python dataclass has a simple attribute that only needs a default value, it can be defined either of these ways. From the documentation of repr():. It provides a few generic and useful implementations, such as a Container type, which is just a convenience wrapper around a list type in Python. The Author dataclass includes a list of Item dataclasses. The best approach in Python 3. There are also patterns available that allow existing. This has a few advantages, such as being able to use dataclasses. Use argument models_type=’dataclass’ or if you use the cli flag –models_type dataclass or -m dataclassPython. Frozen instances and Immutability. 10. One new and exciting feature that came out in Python 3. 2. Dec 23, 2020 at 13:25. It was started as a "proof of concept" for the problem of fast "mutable" alternative of namedtuple (see question on stackoverflow ). config import YamlDataClassConfig @dataclass class Config. dataclasses — Data Classes. 10. s (auto_attribs=True) class Person: #: each Person has a unique id _counter: count [int] = field (init=False, default=count ()) _unique_id: int. value as a dataclass member, and that's what asdict() will return. ¶. Last but not least, I want to compare the performance of regular Python class, collections. dataclass() デコレータは、 フィールド を探すためにクラスを検査します。 フィールド は 型アノテーション を持つクラス変数として定義されます。 後述する2つの例外を除き、 dataclass() は変数アノテーションで指定した型を検査しません。 44. value) >>> test = Test ("42") >>> type (test. If you run the script from your command line, then you’ll get an output similar to the following: Shell. 7 and higher. Get rid of boilerplate writing classes using dataclasses!In this video we learn about dataclasses and how to use them, as well as the related attrs library t. 82 ns (3. Different behaviour of dataclass default_factory to generate list. It takes advantage of Python's type annotations (if you still don't use them, you really should) to automatically generate boilerplate code. This code only exists in the commit that introduced dataclasses. @dataclass(init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False) class C. In this example, we define a Person class with three attributes: name, age, and email. fields is an iterable whose elements are each either name, (name, type) , or (name, type, Field). 5, 2. In this case, it's a list of Item dataclasses. It was decided to remove direct support for __slots__ from dataclasses for Python 3. items ()} If you're sure that your class only has string values, you can skip the dictionary comprehension entirely: class MessageHeader (BaseModel): message_id: uuid. Learn how to use the dataclass decorator and functions to add special methods such as __init__() and __repr__() to user-defined classes. They are similar to global variables, but they offer a more useful repr () , grouping, type-safety, and a few other features. Python also has built-in list operations; for example, the above loop could be re-written as a filter expression: まず dataclasses から dataclass をインポートし、クラス宣言の前に dataclass デコレーターをつけます。id などの変数は型も用意します。通常、これらの変数は def __init__(self): に入れますが、データクラスではそうした書き方はしません。 The dataclass decorator adds init and repr special methods to a class that does not do any computation with its initialization parameters. Use dataclasses instead of dictionaries to represent the rows in. If the attribute has its default set to an instance of MISSING, it means it didn't has a default. Is there anyway to set this default value? I highly doubt that the code you presented here is the same code generating the exception. In Python, a data class is a class that is designed to only hold data values. 2. ClassVar. dataclassy is designed to be more flexible, less verbose, and more powerful than dataclasses, while retaining a familiar interface. Learn how to use the dataclass decorator and functions to add special methods such as __init__() and __repr__() to user-defined classes. 4 Answers. The approach of using the dataclass default_factory isn't going to work either. 7, they came to solve many of the issues discussed in the previous section. Python (more logically) simply calls them class attributes, as they are attributes associated with the class itself, rather than an instance of the class. クラス変数で型をdataclasses. One last option I would be remiss to not mention, and one I would likely recommend as being a little bit easier to set up than properties, would be the use of descriptors in Python. orjson is a fast, correct JSON library for Python. class MyEnum (Enum): A = "valueA" B = "valueB" @dataclass class MyDataclass: value: MyEnum. But you can add a leading underscore to the field, then the property will work. For Python versions below 3. The decorator gives you a nice __repr__, but yeah. name = name. In the Mutable Default Values section, it's mentioned:. Dataclasses and property decorator. @dataclass_json @dataclass class Source: type: str =None label: str =None path: str =. To use Data Classes, you first need to import the dataclass decorator from the dataclasses module. args = args self. NamedTuple is the faster one while creating data objects (2. Actually, there is no need to cache your singleton isntance in an _instance attribute. import dataclasses # Hocus pocus X = dataclasses. If it is supplied with a False value, then a method to print the values for that attribute has to be defined. It was decided to remove direct support for __slots__ from dataclasses for Python 3. Option5: Use __post_init__ in @dataclass. age = age Code language: Python (python) This Person class has the __init__ method that. 0. With Python 3. This allows you to run code after the initialization method to do any additional setup/checks you might want to perform. The first step would be to create a helper Mixin class, named as SerializableMixin or anything else. (In a sense, and in conformance to Von Neumann’s model of a “stored program computer”, code is also represented by objects. The problem (most probably) isn't related to dataclasses. But let’s also look around and see some third-party libraries. Nested dict to object with default value. Jan 12, 2022 at 18:16. Data classes are just regular classes that are geared towards storing state, rather than containing a lot of logic. kwargs = kwargs a = ArgHolder (1, 2, three=3) My thoughts exactly. Or you can use the attrs package, which allows you to easily set. : from enum import Enum, auto from typing import NamedTuple class MyEnum(Enum): v1 = auto() v2 = auto() v3 = auto() class MyStateDefinition(NamedTuple): a: MyEnum b: [email protected] Python dataclasses Kingsley Ubah 21. 2. Thanks to @dataclass decorator you can easily create a new custom type with a list of given fields in a declarative manner. first_name = first_name self. dataclass with a base class. Without pydantic. Protocol as shown below:__init__のみで使用する変数を指定する. TypedDict is something fundamentally different from a dataclass - to start, at runtime, it does absolutely nothing, and behaves just as a plain dictionary (but provide the metainformation used to create it). While digging into it, found that python 3. Protocol as shown below: __init__のみで使用する変数を指定する. XML dataclasses on PyPI. To emulate immutability, you can pass frozen=True to the dataclass() decorator. Python classes provide all the standard features of Object Oriented Programming: the class inheritance mechanism allows multiple base classes, a derived. For the faster performance on newer projects, DataClass is 8. I would say that comparing these two great modules is like comparing pears with apples, albeit similar in some regards, different overall. Before reading this article you must first understand inheritance, composition and some basic python. Recordclass library. ただし、上記のように型の宣言を必要としています。. This is triggered on specific decorators without understanding their implementation. African in Tech. 7 and above. Ex: from dataclasses import dataclass from pathlib import Path from yamldataclassconfig import create_file_path_field from yamldataclassconfig. To dive deeper into the intent behind adding these constructs to the language you should read the PEPs that led to them being added to the language (other than the bare class). Keep in mind that pydantic. 本記事では、dataclassesの導入ポイントや使い方を紹介します. If so, is this described somewhere?The Dataclass Wizard library provides inherent support for standard Python collections such as list, dict and set, as well as most Generics from the typing module, such as Union and Any. The above defines two immutable classes with x and y attributes, with the BaseExtended class. 7 that provides a convenient way to define classes primarily used for storing data. It is a tough choice if indeed we are confronted with choosing one or the other. repr: If true (the default), a __repr__ () method will be generated. This library converts between python dataclasses and dicts (and json). 7, to create readable and flexible data structures. Understand field dataclass. 3. 1. Python 3 dataclass initialization. See how to add default values, methods, and more to your data classes. Calling a class, like you did with Person, triggers Python’s class instantiation process, which internally runs in two steps:. The json. 214s test_namedtuple_attr 0. namedtuple, typing. Blog post on how to incorporate dataclasses in reading JSON API responses here. ), are the fields in the returned tuple guaranteed to be given in the same order as defined?pydantic is an increasingly popular library for python 3. 7 and Python 3. Our goal is to implement validation logic to ensure that the age cannot be outside the range of 0 to 150. jsonpickle. 0. Dataclass Dict Convert. A frozen dataclass in Python is just a fundamentally confused concept. The json. But how do we change it then, for sure we want it to. Given a dataclass instance, I would like print () or str () to only list the non-default field values. It mainly does data validation and settings management using type hints. Because in Python (initially, more about that later), default-valued arguments must always come after all positional arguments, the dataclass field declaration must also follow this logic and. Here we are returning a dictionary that contains items which is a list of dataclasses. 8 introduced a new type called Literal that can be used here: from dataclasses import dataclass from typing import Literal @dataclass class Person: name: Literal ['Eric', 'John', 'Graham', 'Terry'] = 'Eric'. 3. Python 3. To my understanding, dataclasses. 7 introduced a new module called dataclasses that makes it easier to create simple, immutables data classes. The primary benefit of the dataclass is that it can automatically add several Python methods to the class, such as __init__, __repr__and __eq__. If you want all the features and extensibility of Python classes, use data classes instead. If you run the script from your command line, then you’ll get an output similar to the following: Shell. The last one is an optimised dataclass with a field __slot__. I'm trying to create a custom constructor for my python dataclass that will ideally take in a dict (from request json data) and fill in the attributes of the dataclass. @dataclass class A: key1: str = "" key2: dict = {} key3: Any = "". A Python dataclass, in essence, is a class specifically designed for storing data. 8. Create a DataClass for each Json Root Node. 0) Ankur. That is, these three uses of dataclass () are equivalent: @dataclass class C:. 今回は、Python3. 7 ns). So we can use InitVar for our date_str and pass. BaseModel. dataclass () 装饰器将向类中添加如下的各种 dunder 方法。. 3. Dataclass argument choices with a default option. dump () and json. Just decorate your class definition with the @dataclass decorator to define a dataclass. It consists of two parameters: a data class and a dictionary. Enum types are data types that comprise a static, ordered set of values. 该装饰器会返回调用它的类；不会创建新的类。. I'd like to create a copy of an existing instance of a dataclass and modify it. What you are asking for is realized by the factory method pattern, and can be implemented in python classes straight forwardly using the @classmethod keyword.