In this example, the fields y and z will be marked as keyword-only fields: @dataclass class Point: x: float _: KW_ONLY y: float z: float p = Point(0, y=1.5, z=2.0) In a single dataclass, it is an error to specify more than one field whose type ...

Instead of using a set, I think it makes more sense to use a dict type in this case. This should be O(1) for lookup, and also this way we can avoid next to find an element by its Speaker hashed value. Example below. from pprint import pprint from typing import List from dataclasses import dataclass, field @dataclass class Speaker: id: int name: str statements: List[str] = field(default_factory=list) def __eq__(self, other): return self.id == other.id and self.name == other.name def __hash__(self): return hash((self.id, self.name)) test = [(1, 'john', 'foo'), (1, 'john', 'bar'), (2, 'jane', 'near'), (2, 'george', 'far')] speakers = {} for id, name, statement in test: key = Speaker(id, name) speaker = speakers.setdefault(key, key) speaker.statements.append(statement) print(speakers) print() pprint(list(speakers.values()))

May 12, 2025 - As we saw above, when using the dataclass decorator, the __init__, __repr__, and __eq__ methods are implemented for us. The creation of all these methods is set by the init, repr, and eq parameters of dataclass. These three parameters are True by default.

March 8, 2024 - For example, the following is an immutable version of the Position class you saw earlier: ... from dataclasses import dataclass @dataclass(frozen=True) class Position: name: str lon: float = 0.0 lat: float = 0.0

July 11, 2025 - A way to set default value should be provided when init is set to False. repr : If true (the default), this field is included in the string returned by the generated __repr__() method. compare : If true (the default), this field is included in the generated equality and comparison methods (__eq__(), __gt__(), et al.). ... from dataclasses import dataclass, field @dataclass class GfgArticle: title: str = field(compare = False) author: str = field(repr = False) language: str = field(default ='Python3') upvotes: int = field(init = False, default = 0) # DataClass objects # Note the difference in their title value article1 = GfgArticle("DataClass", "vibhu4agarwal") article2 = GfgArticle("Python Packaging", "vibhu4agarwal") print(article1) print(article1.author) print(article1 == article2) Output:

The easiest way I've found to solve this is to utilize the kw_only flag which makes it so that every field<>value must be explicitly set on the dataclass. Ofc you can still set a field<>value incorrectly but at least you're forced to read the field you're setting before doing so. ... """ Example 3: Explicit dataclasses * Show dataclasses at scale """ print("Example 3: Explicit dataclasses") @dataclass(frozen=True) class NoKeywordDC: aThousand: int # always one aTwelveHundred: int # always two aElevenHundred: int # always three many_dcs = [ NoKeywordDC( 1000, 1200, 1100 ), NoKeywordDC( 1000, 1200, 1100 ), NoKeywordDC( 1000, 1200, 1100 ), NoKeywordDC( 1000, 1100, 1200 ), NoKeywordDC( 1000, 1200, 1100 ) ] # Q: Which one is set wrong?

March 15, 2024 - Despite all their features, data ... functionality. Here is the Exercise class again: from dataclasses import dataclass @dataclass class Exercise: name: str reps: int sets: int weight: float ex1 = Exercise("Bench press", 10, 3, 52.5) # Verifying Exercise is a regular class ex1.name ...

It takes advantage of Python's type annotations (if you still don't use them, you really should) to automatically generate boilerplate code you'd have to mechanically type yourself otherwise. As a point of comparison, here's how you would create a Vehicle class with a wheels attribute using a regular class declaration: class Vehicle: def __init__(self, wheels: int): self.wheels = wheels · Nothing fancy, really. Now, the @dataclass version:

July 15, 2025 - # default field example from dataclasses import dataclass, field # A class for holding an employees content @dataclass class employee: # Attributes Declaration # using Type Hints name: str emp_id: str age: int # default field set # city : str = "patna" city: str = field(default="patna") emp = employee("Satyam", "ksatyam858", 21) print(emp)

October 22, 2025 - In this example, we’ve created a __post_init__ method to set shelf_id to None if the book’s condition is initialized as "Discarded". Note how we use field to initialize shelf_id, and pass init as False to field. This means shelf_id won’t be initialized in __init__, but it is registered as a field with the dataclass overall, with type information. Another way to customize Python dataclass setup is to use the InitVar type.

October 18, 2024 - All classes inherit from the built-in object class, and the __setattr__ method on object does the actual attribute-setting behind the scenes. So we can make new instances of this dataclass without an exception being raised: ... And we still can't directly assign to any of the attributes on this new dataclass because it's frozen, which is exactly what we want: >>> r.width = 5 Traceback (most recent call last): File "<python-input-3>", line 1, in <module> r.width = 5 ^^^^^^^ File "<string>", line 17, in __setattr__ dataclasses.FrozenInstanceError: cannot assign to field 'width'

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If the frozen parameter is set to True, we cannot assign values to fields. frozen.py · #!/usr/bin/python from dataclasses import dataclass @dataclass(frozen=True) class Person: name: str age: int p = Person('John Doe', 34) p.occupation = 'gardener' print(p) print(p.occupation) In the example, the frozen parameter is set to True.

>>> from dataclasses import dataclass >>> @dataclass ... class Point: ... x: int ... y: int ...

There were undesirable side effects of this decision, so the final decision is to disallow the 3 known built-in mutable types: list, dict, and set. For a complete discussion of this and other options, see [14]. Sometimes the generated __init__ method does not suffice. For example, suppose you wanted to have an object to store *args and **kwargs: @dataclass(init=False) class ArgHolder: args: List[Any] kwargs: Mapping[Any, Any] def __init__(self, *args, **kwargs): self.args = args self.kwargs = kwargs a = ArgHolder(1, 2, three=3)

A dataclass field may be annotated with Final[...]. For example, x: Final[int] in a dataclass body specifies a dataclass field x, which will be initialized in the generated __init__ and cannot be assigned to thereafter. A Final dataclass field initialized in the class body is not a class attribute ...

October 23, 2024 - >>> from dataclasses import dataclass >>> >>> @dataclass ... class Email: ... subject: str ... body: str ... sender: str ... recipients: list = [] ... cc: list = [] ... Traceback (most recent call last): File "<python-input-9>", line 1, in <module> @dataclass ^^^^^^^^^ File "/usr/lib/python3.13/dataclasses.py", line 1305, in dataclass return wrap(cls) File "/usr/lib/python3.13/dataclasses.py", line 1295, in wrap return _process_class(cls, init, repr, eq, order, unsafe_hash, frozen, match_args, kw_only, slots, weakref_slot) File "/usr/lib/python3.13/dataclasses.py", line 1008, in _process_class

Having an immutable class with a __hash__ method means that we can use our class in sets and dictionaries. We illustrate this in the following example: from dataclasses import dataclass @dataclass(frozen=True) class ImmutableRobot: name: str brandname: str robot1 = ImmutableRobot("Marvin", "NanoGuardian XR-2000") robot2 = ImmutableRobot("R2D2", "QuantumTech Sentinel-7") robot3 = ImmutableRobot("Marva", "MachinaMaster MM-42") # we create a set of Robots: robots = {robot1, robot2, robot3} print("The robots in the set robots:") for robo in robots: print(robo) # now a dictionary with robots as keys: activity = {robot1: 'activated', robot2: 'activated', robot3: 'deactivated'} print("\nAll the activated robots:") for robo, mode in activity.items(): if mode == 'activated': print(f"{robo} is activated")

September 7, 2023 - The class syntax can be used with typing.NamedTuple starting from Python 3.6. This allows you to add your own methods or override existing ones, for example, define your own __str__ method. Book is still a subclass of tuple. import datetime from dataclasses import dataclass @dataclass(frozen=True) class Book: title: str author: str isbn: int pub_date: datetime.datetime rating: float = 4.98 # Book is not a subclass of tuple print(issubclass(Book, tuple)) # output: False book = Book( title='Learning Python', author='Mark Lutz', isbn=1449355730, pub_date=datetime.date(2013, 7, 30), ) print(book.title) # Learning Python print(book.rating) # 4.98, by default print(type(book)) # <class '__main__.Book'> print(book) # Book(title='Learning Python', author='Mark...)

July 5, 2022 - It’s a common Python gotchas (see here for mutable default arguments in functions). You must not use the direct default value, you have to use the utility dataclasses.field which allows you to give a factory to initialize your property. Here is the example for List: