FlatDict

chanfig.FlatDict

Bases: dict

FlatDict with attribute-style access.

FlatDict inherits from built-in dict.

It comes with many easy to use helper methods, such as merge, sort, difference, intersect.

It also has full support for IO operations, such as json and yaml.

Even better, FlatDict has pytorch support built-in. You can directly call FlatDict.cpu() or FlatDict.to("cpu") to move all torch.Tensor objects across devices.

FlatDict works best with Variable objects. Simply call flat_dict.a = Variable(1); flat_dict.b = flat_dict.a, and their values will be synced.

Even better, FlatDict support variable interpolation. Just set the value of one key to another key (surrounded by braces with $ at the begin, like ${xxx}), and calls flat_dict.interpolate(), FlatDict will interpolate their values and create Variable automatically.

FlatDict has many other easy to use helper methods, such as difference, intersect. And has full support for IO operations, such as json and yaml.

FlatDict also has pytorch support built-in. You can directly call flat_dict.cpu() or flat_dict.to("cpu") to move all torch.Tensor objects across devices.

Attributes:

Name	Type	Description
indent		Indentation level in printing and dumping to json or yaml.

Notes

FlatDict rewrite __getattribute__ and __getattr__ to supports attribute-style access to its members. Therefore, all internal attributes should be set and get through flat_dict.setattr and flat_dict.getattr.

Although it is possible to override other internal methods, it is not recommended to do so.

__class__, __dict__, and getattr are reserved and cannot be overrode in any manner.

Examples:

Python Console Session

>>> d = FlatDict()
>>> d.d = 1016
>>> d['d']
1016
>>> d['i'] = 1016
>>> d.i
1016
>>> d.a = Variable(1)
>>> d.b = d.a
>>> d.a, d.b
(1, 1)
>>> d.a += 1
>>> d.a, d.b
(2, 2)
>>> d.a = 3
>>> d.a, d.b
(3, 3)
>>> d.a = Variable('hello')
>>> f"{d.a}, world!"
'hello, world!'
>>> d.a = d.a + ', world!'
>>> d.b
'hello, world!'

Source code in chanfig/flat_dict.py

class FlatDict(dict, metaclass=Dict):
    r"""
    `FlatDict` with attribute-style access.

    `FlatDict` inherits from built-in `dict`.

    It comes with many easy to use helper methods, such as `merge`, `sort`, `difference`, `intersect`.

    It also has full support for IO operations, such as `json` and `yaml`.

    Even better, `FlatDict` has pytorch support built-in.
    You can directly call `FlatDict.cpu()` or `FlatDict.to("cpu")` to move all `torch.Tensor` objects across devices.

    `FlatDict` works best with `Variable` objects.
    Simply call `flat_dict.a = Variable(1); flat_dict.b = flat_dict.a`, and their values will be synced.

    Even better, `FlatDict` support variable interpolation.
    Just set the value of one key to another key (surrounded by braces with $ at the begin, like ${xxx}),
    and calls `flat_dict.interpolate()`, `FlatDict` will interpolate their values and create `Variable` automatically.

    `FlatDict` has many other easy to use helper methods, such as `difference`, `intersect`.
    And has full support for IO operations, such as `json` and `yaml`.

    `FlatDict` also has pytorch support built-in.
    You can directly call `flat_dict.cpu()` or `flat_dict.to("cpu")` to move all `torch.Tensor` objects across devices.

    Attributes:
        indent: Indentation level in printing and dumping to json or yaml.

    Notes:
        `FlatDict` rewrite `__getattribute__` and `__getattr__` to supports attribute-style access to its members.
        Therefore, all internal attributes should be set and get through `flat_dict.setattr` and `flat_dict.getattr`.

        Although it is possible to override other internal methods, it is not recommended to do so.

        `__class__`, `__dict__`, and `getattr` are reserved and cannot be overrode in any manner.

    Examples:
        >>> d = FlatDict()
        >>> d.d = 1016
        >>> d['d']
        1016
        >>> d['i'] = 1016
        >>> d.i
        1016
        >>> d.a = Variable(1)
        >>> d.b = d.a
        >>> d.a, d.b
        (1, 1)
        >>> d.a += 1
        >>> d.a, d.b
        (2, 2)
        >>> d.a = 3
        >>> d.a, d.b
        (3, 3)
        >>> d.a = Variable('hello')
        >>> f"{d.a}, world!"
        'hello, world!'
        >>> d.a = d.a + ', world!'
        >>> d.b
        'hello, world!'
    """

    # pylint: disable=R0904

    indent = 2

    def __init__(self, *args: Any, **kwargs: Any) -> None:
        if len(args) == 1:
            arg = args[0]
            if isinstance(arg, (PathLike, str, bytes)):
                arg = self.load(arg)
            elif isinstance(arg, (Namespace,)):
                arg = vars(arg)
            args = (arg,)
        super().__init__(*args, **kwargs)
        self.move_class_attributes()

    def move_class_attributes(self, recursive: bool = True) -> Self:
        r"""
        Move class attributes to instance.

        Args:
            recursive:

        Returns:
            self:
        """

        def move_cls_attributes(cls: type) -> Mapping:
            return {k: cls.__dict__[k] for k in get_annotations(cls).keys() if k in cls.__dict__}

        if recursive:
            for cls in self.__class__.__mro__:
                self.merge(move_cls_attributes(cls), overwrite=False)
        else:
            self.merge(move_cls_attributes(self.__class__), overwrite=False)
        return self

    def __post_init__(self, *args, **kwargs) -> None:
        pass

    def __getattribute__(self, name: Any) -> Any:
        if (name not in ("getattr",) and not (name.startswith("__") and name.endswith("__"))) and name in self:
            if name in dir(self.__class__):
                value = super().__getattribute__(name)
                if isinstance(value, (property, staticmethod, classmethod)) or callable(value):
                    return value
            return self.get(name)
        return super().__getattribute__(name)

    def get(self, name: Any, default: Any = None) -> Any:
        r"""
        Get value from `FlatDict`.

        Args:
            name:
            default:

        Returns:
            value:
                If `FlatDict` does not contain `name`, return `default`.

        Raises:
            KeyError: If `FlatDict` does not contain `name` and `default` is not specified.
            TypeError: If `name` is not hashable.

        Examples:
            >>> d = FlatDict(d=1016)
            >>> d.get('d')
            1016
            >>> d['d']
            1016
            >>> d.d
            1016
            >>> d.get('d', None)
            1016
            >>> d.get('f', 2)
            2
            >>> d.get('f')
            >>> d.get('f', Null)
            Traceback (most recent call last):
            KeyError: 'f'
        """

        if name in self:
            return dict.__getitem__(self, name)
        if default is not Null:
            return default
        return self.__missing__(name)

    def __getitem__(self, name: Any) -> Any:
        return self.get(name, default=Null)

    def __getattr__(self, name: Any) -> Any:
        try:
            return self.get(name, default=Null)
        except KeyError:
            raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{name}'") from None

    def set(self, name: Any, value: Any) -> None:
        r"""
        Set value of `FlatDict`.

        Args:
            name:
            value:

        Examples:
            >>> d = FlatDict()
            >>> d.set('d', 1016)
            >>> d.get('d')
            1016
            >>> d['n'] = 'chang'
            >>> d.n
            'chang'
            >>> d.n = 'liu'
            >>> d['n']
            'liu'
        """

        if name is Null:
            raise ValueError("name must not be null")
        if name in self and isinstance(self.get(name), Variable):
            self.get(name).set(value)
        else:
            if name in get_annotations(self):
                anno = get_annotations(self)[name]
                if isinstance(anno, type) and not isinstance(value, anno):
                    value = anno(value)
            dict.__setitem__(self, name, value)

    def __setitem__(self, name: Any, value: Any) -> None:
        self.set(name, value)

    def __setattr__(self, name: Any, value: Any) -> None:
        self.set(name, value)

    def delete(self, name: Any) -> None:
        r"""
        Delete value from `FlatDict`.

        Args:
            name:

        Examples:
            >>> d = FlatDict(d=1016, n='chang')
            >>> d.d
            1016
            >>> d.n
            'chang'
            >>> d.delete('d')
            >>> d.d
            Traceback (most recent call last):
            AttributeError: 'FlatDict' object has no attribute 'd'
            >>> del d.n
            >>> d.n
            Traceback (most recent call last):
            AttributeError: 'FlatDict' object has no attribute 'n'
            >>> del d.f
            Traceback (most recent call last):
            AttributeError: 'FlatDict' object has no attribute 'f'
        """

        dict.__delitem__(self, name)

    def __delitem__(self, name: Any) -> None:
        return self.delete(name)

    def __delattr__(self, name: Any) -> None:
        try:
            self.delete(name)
        except KeyError:
            raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{name}'") from None

    def __missing__(self, name: Any) -> Any:  # pylint: disable=R1710
        raise KeyError(name)

    def validate(self) -> None:
        r"""
        Validate `FlatDict`.

        Raises:
            TypeError: If value is not of the type declared in class annotations.
            TypeError: If `Variable` has invalid type.
            ValueError: If `Variable` has invalid value.

        Examples:
            >>> d = FlatDict(d=Variable(1016, type=int), n=Variable('chang', validator=lambda x: x.islower()))
            >>> d = FlatDict(d=Variable(1016, type=str), n=Variable('chang', validator=lambda x: x.islower()))
            Traceback (most recent call last):
            TypeError: 'd' has invalid type. Value 1016 is not of type <class 'str'>.
            >>> d = FlatDict(d=Variable(1016, type=int), n=Variable('chang', validator=lambda x: x.isupper()))
            Traceback (most recent call last):
            ValueError: 'n' has invalid value. Value chang is not valid.
        """

        self._validate(self)

    @staticmethod
    def _validate(obj) -> None:
        if isinstance(obj, FlatDict):
            annotations = get_annotations(obj)
            for name, value in obj.items():
                if annotations and name in annotations and not isvalid(value, annotations[name]):
                    raise TypeError(f"'{name}' has invalid type. Value {value} is not of type {annotations[name]}.")
                if isinstance(value, Variable):
                    try:
                        value.validate()
                    except TypeError as exc:
                        raise TypeError(f"'{name}' has invalid type. {exc}") from None
                    except ValueError as exc:
                        raise ValueError(f"'{name}' has invalid value. {exc}") from None

    def getattr(self, name: str, default: Any = Null) -> Any:
        r"""
        Get attribute of `FlatDict`.

        Note that it won't retrieve value in `FlatDict`,

        Args:
            name:
            default:

        Returns:
            value: If `FlatDict` does not contain `name`, return `default`.

        Raises:
            AttributeError: If `FlatDict` does not contain `name` and `default` is not specified.

        Examples:
            >>> d = FlatDict(a=1)
            >>> d.get('a')
            1
            >>> d.getattr('a')
            Traceback (most recent call last):
            AttributeError: 'FlatDict' object has no attribute 'a'
            >>> d.getattr('b', 2)
            2
            >>> d.setattr('b', 3)
            >>> d.getattr('b')
            3
        """

        try:
            if name in self.__dict__:
                return self.__dict__[name]
            for cls in self.__class__.__mro__:
                annotations = get_annotations(cls)
                if name in cls.__dict__ and name not in annotations:
                    return cls.__dict__[name]
            return super().getattr(name, default)  # type: ignore[misc]
        except AttributeError:
            if default is not Null:
                return default
            raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{name}'") from None

    def setattr(self, name: str, value: Any) -> None:
        r"""
        Set attribute of `FlatDict`.

        Note that it won't alter values in `FlatDict`.

        Args:
            name:
            value:

        Warns:
            RuntimeWarning: If name already exists in `FlatDict`.

        Examples:
            >>> d = FlatDict()
            >>> d.setattr('attr', 'value')
            >>> d.getattr('attr')
            'value'
            >>> d.set('d', 1016)
            >>> d.setattr('d', 1031)  # RuntimeWarning: d already exists in FlatDict.
            >>> d.get('d')
            1016
            >>> d.d
            1016
            >>> d.getattr('d')
            1031
        """

        if name in self:
            warn(
                f"{name} already exists in {self.__class__.__name__}.\n"
                f"Users must call `{self.__class__.__name__}.getattr()` to retrieve conflicting attribute value.",
                RuntimeWarning,
            )
        self.__dict__[name] = value

    def delattr(self, name: str) -> None:
        r"""
        Delete attribute of `FlatDict`.

        Note that it won't delete values in `FlatDict`.

        Args:
            name:

        Examples:
            >>> d = FlatDict()
            >>> d.setattr('name', 'chang')
            >>> d.getattr('name')
            'chang'
            >>> d.delattr('name')
            >>> d.getattr('name')
            Traceback (most recent call last):
            AttributeError: 'FlatDict' object has no attribute 'name'
        """

        del self.__dict__[name]

    def hasattr(self, name: str) -> bool:
        r"""
        Determine if an attribute exists in `FlatDict`.

        Args:
            name:

        Returns:
            (bool):

        Examples:
            >>> d = FlatDict()
            >>> d.setattr('name', 'chang')
            >>> d.hasattr('name')
            True
            >>> d.delattr('name')
            >>> d.hasattr('name')
            False
        """

        try:
            if name in self.__dict__ or name in self.__class__.__dict__:
                return True
            return super().hasattr(name)  # type: ignore[misc]
        except AttributeError:
            return False

    def dict(self, flatten: bool = False) -> Mapping | Sequence | Set:
        r"""
        Convert `FlatDict` to other `Mapping`.

        Args:
            flatten: Whether to flatten [`NestedDict`][chanfig.NestedDict].

        Returns:
            (Mapping):

        See Also:
            [`to_dict`][chanfig.flat_dict.to_dict]: Implementation of `dict`.

        **Alias**:

        + `to_dict`

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> d.dict()
            {'a': 1, 'b': 2, 'c': 3}
        """

        return to_dict(self, flatten)

    def to_dict(self, flatten: bool = False) -> Mapping | Sequence | Set:
        r"""
        Alias of [`dict`][chanfig.FlatDict.dict].
        """

        return self.dict(flatten)

    @classmethod
    def from_dict(cls, obj: Mapping | Sequence) -> Any:  # pylint: disable=R0911
        r"""
        Convert `Mapping` or `Sequence` to `FlatDict`.

        Examples:
            >>> FlatDict.from_dict({'a': 1, 'b': 2, 'c': 3})
            FlatDict(
              ('a'): 1
              ('b'): 2
              ('c'): 3
            )
            >>> FlatDict.from_dict([('a', 1), ('b', 2), ('c', 3)])
            FlatDict(
              ('a'): 1
              ('b'): 2
              ('c'): 3
            )
            >>> FlatDict.from_dict([{'a': 1}, {'b': 2}, {'c': 3}])
            [FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]
            >>> FlatDict.from_dict({1, 2, 3})
            Traceback (most recent call last):
            TypeError: Expected Mapping or Sequence, but got <class 'set'>.
        """

        if obj is None:
            return cls()
        if issubclass(cls, FlatDict):
            cls = cls.empty  # type: ignore[assignment] # pylint: disable=W0642
        if isinstance(obj, Mapping):
            return cls(obj)
        if isinstance(obj, Sequence):
            try:
                return cls(obj)
            except ValueError:
                return [cls(json) for json in obj]
        raise TypeError(f"Expected Mapping or Sequence, but got {type(obj)}.")

    def sort(self, key: Callable | None = None, reverse: bool = False) -> Self:
        r"""
        Sort `FlatDict`.

        Returns:
            (FlatDict):

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> d.sort().dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> d = FlatDict(b=2, c=3, a=1)
            >>> d.sort().dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> a = [1]
            >>> d = FlatDict(z=0, a=a)
            >>> a.append(2)
            >>> d.sort().dict()
            {'a': [1, 2], 'z': 0}
        """

        items = sorted(self.items(), key=key, reverse=reverse)
        self.clear()
        for k, v in items:  # pylint: disable=C0103
            self[k] = v
        return self

    def interpolate(  # pylint: disable=R0912
        self, use_variable: bool = True, interpolators: MutableMapping | None = None, unsafe_eval: bool = False
    ) -> Self:
        r"""
        Perform Variable interpolation.

        Variable interpolation allows you to set the value of one key to be the value of another key easily.

        Args:
            use_variable: Whether to convert values to `Variable` objects.
            interpolators: Mapping contains values for interpolation. Defaults to `self`.
            unsafe_eval: Whether to evaluate interpolated values.

        Raises:
            ValueError: If value is not interpolatable.
            ValueError: If reference to itself.
            ValueError: If has circular reference.

        See Also:
            [Variable][`chanfig.Variable`]: Mutable wrapper of immutable objects.

        Examples:
            >>> d = FlatDict(a=1, b="${a}", c="${a}.${b}")
            >>> d.dict()
            {'a': 1, 'b': '${a}', 'c': '${a}.${b}'}
            >>> d.interpolate(unsafe_eval=True).dict()
            {'a': 1, 'b': 1, 'c': 1.1}
            >>> d = FlatDict(a=1, b="${a}", c="${a}.${b}")
            >>> d.dict()
            {'a': 1, 'b': '${a}', 'c': '${a}.${b}'}
            >>> d.interpolate().dict()
            {'a': 1, 'b': 1, 'c': '1.1'}
            >>> isinstance(d.a, Variable)
            True
            >>> d.a += 1
            >>> d.dict()
            {'a': 2, 'b': 2, 'c': '1.1'}
            >>> d.a is d.b
            True
            >>> d.b is d.c
            False
            >>> d = FlatDict(a=1, b="${a}", c="${b}")
            >>> d.dict()
            {'a': 1, 'b': '${a}', 'c': '${b}'}
            >>> d.interpolate(False).dict()
            {'a': 1, 'b': 1, 'c': 1}
            >>> isinstance(d.a, Variable)
            False
            >>> d.a += 1
            >>> d.dict()
            {'a': 2, 'b': 1, 'c': 1}
            >>> d = FlatDict(a=1, b="${b}", c="${b}")
            >>> d.interpolate().dict()
            Traceback (most recent call last):
            ValueError: Cannot interpolate b to itself.
            >>> d = FlatDict(a="${b}", b="${c}", c="${d}", d="${a}")
            >>> d.interpolate().dict()
            Traceback (most recent call last):
            ValueError: Circular reference found: a->b->c->d->a.
            >>> d = FlatDict(a=1, b="${a}", c="${d}")
            >>> d.interpolate().dict()
            Traceback (most recent call last):
            ValueError: d is not found in FlatDict(
              ('a'): '1'
              ('b'): '${a}'
              ('c'): '${d}'
            ).
        """
        # pylint: disable=C0103

        interpolators = interpolators or self
        placeholders: dict[str, list[str]] = {}
        for key, value in self.all_items():
            if isinstance(value, list):
                for v in value:
                    self.find_placeholders(key, v, placeholders)
            elif isinstance(value, Mapping):
                for v in value.values():
                    self.find_placeholders(key, v, placeholders)
            else:
                self.find_placeholders(key, value, placeholders)
        circular_references = find_circular_reference(placeholders)
        if circular_references:
            raise ValueError(f"Circular reference found: {'->'.join(circular_references)}.")
        if use_variable:
            placeholder_names = {i for j in placeholders.values() for i in j}
            for name in list(placeholder_names.difference(placeholders.keys())):
                if name not in interpolators:
                    raise ValueError(f"{name} is not found in {interpolators}.")
                if not isinstance(interpolators[name], Variable):
                    interpolators[name] = Variable(interpolators[name])
        for key, value in placeholders.items():
            if isinstance(self[key], list):
                for index, v in enumerate(self[key]):
                    self[key][index] = self.substitute(v, interpolators, value)
            elif isinstance(self[key], Mapping):
                for k, v in self[key].items():
                    self[key][k] = self.substitute(v, interpolators, value)
            else:
                self[key] = self.substitute(self[key], interpolators, value)
            if unsafe_eval and isinstance(self[key], str):
                with suppress(SyntaxError):
                    self[key] = eval(self[key])  # pylint: disable=W0123
        return self

    @staticmethod
    def find_placeholders(key, value, placeholders):
        placeholder = find_placeholders(value)
        if placeholder:
            for index, name in enumerate(placeholder):
                if name.startswith("."):
                    placeholder[index] = key.rsplit(".", 1)[0] + name
                if key == name:
                    raise ValueError(f"Cannot interpolate {key} to itself.")
            placeholders[key] = placeholder

    @staticmethod
    def substitute(placeholder, interpolators, value):
        try:
            if len(value) == 1 and placeholder.startswith("${") and placeholder.endswith("}"):
                return interpolators[value[0]]
            return placeholder.replace("$", "").format(**interpolators)
        except KeyError as exc:
            raise ValueError(f"{exc} is not found in {interpolators}.") from None

    def merge(self, *args: Any, overwrite: bool = True, **kwargs: Any) -> Self:
        r"""
        Merge `other` into `FlatDict`.

        Args:
            *args: `Mapping` or `Sequence` to be merged.
            overwrite: Whether to overwrite existing values.
            **kwargs: `Mapping` to be merged.

        Returns:
            self:

        **Alias**:

        + `union`

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
            >>> d.merge(n).dict()
            {'a': 1, 'b': 'b', 'c': 'c', 'd': 'd'}
            >>> l = [('c', 3), ('d', 4)]
            >>> d.merge(l).dict()
            {'a': 1, 'b': 'b', 'c': 3, 'd': 4}
            >>> FlatDict(a=1, b=1, c=1).union(FlatDict(b='b', c='c', d='d')).dict()  # alias
            {'a': 1, 'b': 'b', 'c': 'c', 'd': 'd'}
            >>> d = FlatDict()
            >>> d.merge({1: 1, 2: 2, 3:3}).dict()
            {1: 1, 2: 2, 3: 3}
            >>> d.merge(d.clone()).dict()
            {1: 1, 2: 2, 3: 3}
            >>> d.merge({1:3, 2:1, 3: 2, 4: 4, 5: 5}, overwrite=False).dict()
            {1: 1, 2: 2, 3: 3, 4: 4, 5: 5}
        """

        if len(args) == 1:
            args = args[0]
            if isinstance(args, (PathLike, str, bytes)):
                args = self.load(args)  # type: ignore[assignment]
                warn(
                    "merge file is deprecated and maybe removed in a future release. Use `merge_from_file` instead.",
                    PendingDeprecationWarning,
                )
            self._merge(self, args, overwrite=overwrite)
        elif len(args) > 1:
            self._merge(self, args, overwrite=overwrite)
        if kwargs:
            self._merge(self, kwargs, overwrite=overwrite)
        return self

    @staticmethod
    def _merge(this: FlatDict, that: Iterable, overwrite: bool = True) -> Mapping:
        if not that:
            return this
        if isinstance(that, Mapping):
            that = that.items()
        for key, value in that:
            if key in this and isinstance(this[key], Mapping):
                if isinstance(value, Mapping):
                    FlatDict._merge(this[key], value)
                elif overwrite:
                    if isinstance(value, FlatDict):
                        this.set(key, value)
                    else:
                        this[key] = value
            elif overwrite or key not in this:
                this.set(key, value)
        return this

    def union(self, *args: Any, **kwargs: Any) -> Self:
        r"""
        Alias of [`merge`][chanfig.FlatDict.merge].
        """
        return self.merge(*args, **kwargs)

    def merge_from_file(self, file: File, *args: Any, **kwargs: Any) -> Self:
        r"""
        Merge content of `file` into `FlatDict`.

        Args:
            file (File):
            *args: Passed to [`load`][chanfig.FlatDict.load].
            **kwargs: Passed to [`load`][chanfig.FlatDict.load].

        Returns:
            self:

        Examples:
            >>> d = FlatDict(a=1, b=1)
            >>> d.merge_from_file("tests/test.yaml").dict()
            {'a': 1, 'b': 2, 'c': 3}
        """

        return self.merge(self.load(file, *args, **kwargs))

    def intersect(self, other: Mapping | Iterable | PathStr) -> Self:
        r"""
        Intersection of `FlatDict` and `other`.

        Args:
            other (Mapping | Iterable | PathStr):

        Returns:
            (FlatDict):

        **Alias**:

        + `inter`

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
            >>> d.intersect(n).dict()
            {}
            >>> l = [('c', 3), ('d', 4)]
            >>> d.intersect(l).dict()
            {'c': 3}
            >>> d.merge(l).intersect("tests/test.yaml").dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> d.intersect(1)
            Traceback (most recent call last):
            TypeError: `other=1` should be of type Mapping, Iterable or PathStr, but got <class 'int'>.
            >>> d.inter(FlatDict(b='b', c='c', d='d')).dict()  # alias
            {}
        """

        if isinstance(other, (PathLike, str, bytes)):
            other = self.load(other)
        if isinstance(other, (Mapping,)):
            other = self.empty(other).items()
        if not isinstance(other, Iterable):
            raise TypeError(f"`other={other}` should be of type Mapping, Iterable or PathStr, but got {type(other)}.")
        return self.empty(**{key: value for key, value in other if key in self and self[key] == value})  # type: ignore

    def inter(self, other: Mapping | Iterable | PathStr, *args: Any, **kwargs: Any) -> Self:
        r"""
        Alias of [`intersect`][chanfig.FlatDict.intersect].
        """
        return self.intersect(other, *args, **kwargs)

    def difference(self, other: Mapping | Iterable | PathStr) -> Self:
        r"""
        Difference between `FlatDict` and `other`.

        Args:
            other:

        Returns:
            (FlatDict):

        **Alias**:

        + `diff`

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
            >>> d.difference(n).dict()
            {'b': 'b', 'c': 'c', 'd': 'd'}
            >>> l = [('c', 3), ('d', 4)]
            >>> d.difference(l).dict()
            {'d': 4}
            >>> d.merge(l).difference("tests/test.yaml").dict()
            {}
            >>> d.difference(1)
            Traceback (most recent call last):
            TypeError: `other=1` should be of type Mapping, Iterable or PathStr, but got <class 'int'>.
            >>> FlatDict(a=1, b=1, c=1).diff(FlatDict(b='b', c='c', d='d')).dict()  # alias
            {'b': 'b', 'c': 'c', 'd': 'd'}
        """

        if isinstance(other, (PathLike, str, bytes)):
            other = self.load(other)
        if isinstance(other, (Mapping,)):
            other = self.empty(other).items()
        if not isinstance(other, Iterable):
            raise TypeError(f"`other={other}` should be of type Mapping, Iterable or PathStr, but got {type(other)}.")
        return self.empty(
            **{key: value for key, value in other if key not in self or self[key] != value}  # type: ignore[misc]
        )

    def diff(self, other: Mapping | Iterable | PathStr, *args: Any, **kwargs: Any) -> Self:
        r"""
        Alias of [`difference`][chanfig.FlatDict.difference].
        """
        return self.difference(other, *args, **kwargs)

    def to(self, cls: str | TorchDevice | TorchDType) -> Self:  # pragma: no cover
        r"""
        Convert values of `FlatDict` to target `cls`.

        Args:
            cls (str | torch.device | torch.dtype):

        Returns:
            self:

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> d.to(int)
            Traceback (most recent call last):
            TypeError: to() only support torch.dtype and torch.device, but got <class 'int'>.
        """

        # pylint: disable=C0103

        if isinstance(cls, (str, TorchDevice, TorchDType)):
            for k, v in self.all_items():
                if hasattr(v, "to"):
                    self[k] = v.to(cls)
            return self

        raise TypeError(f"to() only support torch.dtype and torch.device, but got {cls}.")

    def cpu(self) -> Self:  # pragma: no cover
        r"""
        Move all tensors to cpu.

        Returns:
            self:

        Examples:
            >>> import torch
            >>> d = FlatDict(a=torch.tensor(1))
            >>> d.cpu().dict()  # doctest: +SKIP
            {'a': tensor(1, device='cpu')}
        """

        return self.to(TorchDevice("cpu"))

    def gpu(self) -> Self:  # pragma: no cover
        r"""
        Move all tensors to gpu.

        Returns:
            self:

        **Alias**:

        + `cuda`

        Examples:
            >>> import torch
            >>> d = FlatDict(a=torch.tensor(1))
            >>> d.gpu().dict()  # doctest: +SKIP
            {'a': tensor(1, device='cuda:0')}
            >>> d.cuda().dict()  # alias  # doctest: +SKIP
            {'a': tensor(1, device='cuda:0')}
        """

        return self.to(TorchDevice("cuda"))

    def cuda(self) -> Self:  # pragma: no cover
        r"""
        Alias of [`gpu`][chanfig.FlatDict.gpu].
        """
        return self.gpu()

    def tpu(self) -> Self:  # pragma: no cover
        r"""
        Move all tensors to tpu.

        Returns:
            self:

        **Alias**:

        + `xla`

        Examples:
            >>> import torch
            >>> d = FlatDict(a=torch.tensor(1))
            >>> d.tpu().dict()  # doctest: +SKIP
            {'a': tensor(1, device='xla:0')}
            >>> d.xla().dict()  # alias  # doctest: +SKIP
            {'a': tensor(1, device='xla:0')}
        """

        return self.to(TorchDevice("xla"))

    def xla(self) -> Self:  # pragma: no cover
        r"""
        Alias of [`tpu`][chanfig.FlatDict.tpu].
        """
        return self.tpu()

    def copy(self) -> Self:
        r"""
        Create a shallow copy of `FlatDict`.

        Returns:
            (FlatDict):

        Examples:
            >>> d = FlatDict(a=[])
            >>> d.setattr("name", "Chang")
            >>> c = d.copy()
            >>> c.dict()
            {'a': []}
            >>> d.a.append(1)
            >>> c.dict()
            {'a': [1]}
            >>> c.getattr("name")
            'Chang'
        """

        return copy(self)

    def __deepcopy__(self, memo: Mapping | None = None) -> Self:
        # pylint: disable=C0103

        if memo is not None and id(self) in memo:
            return memo[id(self)]
        ret = self.empty()
        ret.__dict__.update(deepcopy(self.__dict__))
        for k, v in self.items():
            if isinstance(v, FlatDict):
                ret[k] = v.deepcopy(memo=memo)
            else:
                ret[k] = deepcopy(v)
        return ret

    def deepcopy(self, memo: Mapping | None = None) -> Self:  # pylint: disable=W0613
        r"""
        Create a deep copy of `FlatDict`.

        Returns:
            (FlatDict):

        **Alias**:

        + `clone`

        Examples:
            >>> d = FlatDict(a=[])
            >>> d.setattr("name", "Chang")
            >>> c = d.deepcopy()
            >>> c.dict()
            {'a': []}
            >>> d.a.append(1)
            >>> c.dict()
            {'a': []}
            >>> c.getattr("name")
            'Chang'
            >>> d == d.clone()  # alias
            True
        """

        return deepcopy(self)

    def clone(self, memo: Mapping | None = None) -> Self:
        r"""
        Alias of [`deepcopy`][chanfig.FlatDict.deepcopy].
        """
        return self.deepcopy(memo=memo)

    def save(  # pylint: disable=W1113
        self, file: File, method: str = None, *args: Any, **kwargs: Any  # type: ignore[assignment]
    ) -> None:
        r"""
        Save `FlatDict` to file.

        Raises:
            ValueError: If save to `IO` and `method` is not specified.
            TypeError: If save to unsupported extension.

        **Alias**:

        + `save`

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> d.save("tests/test.yaml")
            >>> d.save("test.conf")
            Traceback (most recent call last):
            TypeError: `file='test.conf'` should be in ('json',) or ('yml', 'yaml'), but got conf.
            >>> with open("test.yaml", "w") as f:
            ...     d.save(f)
            Traceback (most recent call last):
            ValueError: `method` must be specified when saving to IO.
        """

        if method is None:
            if isinstance(file, (IOBase, IO)):
                raise ValueError("`method` must be specified when saving to IO.")
            method = splitext(file)[-1][1:]
        extension = method.lower()
        if extension in YAML:
            return self.yaml(file=file, *args, **kwargs)  # type: ignore[misc]  # noqa: B026
        if extension in JSON:
            return self.json(file=file, *args, **kwargs)  # type: ignore[misc]  # noqa: B026
        raise TypeError(f"`file={file!r}` should be in {JSON} or {YAML}, but got {extension}.")

    def dump(  # pylint: disable=W1113
        self, file: File, method: str = None, *args: Any, **kwargs: Any  # type: ignore[assignment]
    ) -> None:
        r"""
        Alias of [`save`][chanfig.FlatDict.save].
        """
        return self.save(file, method, *args, **kwargs)

    @classmethod
    def load(  # pylint: disable=W1113
        cls, file: File, method: str = None, *args: Any, **kwargs: Any  # type: ignore[assignment]
    ) -> Self:
        """
        Load `FlatDict` from file.

        Args:
            file: File to load from.
            method: File type, should be in `JSON` or `YAML`.

        Returns:
            (FlatDict):

        Raises:
            ValueError: If load from `IO` and `method` is not specified.
            TypeError: If dump to unsupported extension.

        Examples:
            >>> d = FlatDict.load("tests/test.yaml")
            >>> d.dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> d.load("tests/test.conf")
            Traceback (most recent call last):
            TypeError: `file='tests/test.conf'` should be in ('json',) or ('yml', 'yaml'), but got conf.
            >>> with open("tests/test.yaml") as f:
            ...     d.load(f)
            Traceback (most recent call last):
            ValueError: `method` must be specified when loading from IO.
        """

        if method is None:
            if isinstance(file, (IOBase, IO)):
                raise ValueError("`method` must be specified when loading from IO.")
            method = splitext(file)[-1][1:]
        extension = method.lower()
        if extension in JSON:
            return cls.from_json(file, *args, **kwargs)
        if extension in YAML:
            return cls.from_yaml(file, *args, **kwargs)
        raise TypeError(f"`file={file!r}` should be in {JSON} or {YAML}, but got {extension}.")

    def json(self, file: File, *args: Any, **kwargs: Any) -> None:
        r"""
        Dump `FlatDict` to json file.

        This method internally calls `self.jsons()` to generate json string.
        You may overwrite `jsons` in case something is not json serializable.

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> d.json("tests/test.json")
        """

        with self.open(file, mode="w") as fp:  # pylint: disable=C0103
            fp.write(self.jsons(*args, **kwargs))

    @classmethod
    def from_json(cls, file: File, *args: Any, **kwargs: Any) -> Self:
        r"""
        Construct `FlatDict` from json file.

        This method internally calls `self.from_jsons()` to construct object from json string.
        You may overwrite `from_jsons` in case something is not json serializable.

        Returns:
            (FlatDict):

        Examples:
            >>> d = FlatDict.from_json('tests/test.json')
            >>> d.dict()
            {'a': 1, 'b': 2, 'c': 3}
        """

        with cls.open(file) as fp:  # pylint: disable=C0103
            if isinstance(file, (IOBase, IO)):
                return cls.from_jsons(fp.getvalue(), *args, **kwargs)  # type: ignore[union-attr]
            return cls.from_jsons(fp.read(), *args, **kwargs)

    def jsons(self, *args: Any, **kwargs: Any) -> str:
        r"""
        Dump `FlatDict` to json string.

        Returns:
            (str):

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> d.jsons()
            '{\n  "a": 1,\n  "b": 2,\n  "c": 3\n}'
        """

        kwargs.setdefault("cls", JsonEncoder)
        kwargs.setdefault("indent", self.getattr("indent", 2))
        return json_dumps(self.dict(), *args, **kwargs)

    @classmethod
    def from_jsons(cls, string: str, *args: Any, **kwargs: Any) -> Self:
        r"""
        Construct `FlatDict` from json string.

        Returns:
            (FlatDict):

        Examples:
            >>> FlatDict.from_jsons('{\n  "a": 1,\n  "b": 2,\n  "c": 3\n}').dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> FlatDict.from_jsons('[["a", 1], ["b", 2], ["c", 3]]').dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> FlatDict.from_jsons('[{"a": 1}, {"b": 2}, {"c": 3}]')
            [FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]
        """

        return cls.from_dict(json_loads(string, *args, **kwargs))

    def yaml(self, file: File, *args: Any, **kwargs: Any) -> None:
        r"""
        Dump `FlatDict` to yaml file.

        This method internally calls `self.yamls()` to generate yaml string.
        You may overwrite `yamls` in case something is not yaml serializable.

        Examples:
            >>> d = FlatDict(a=1, b=2, c=3)
            >>> d.yaml("tests/test.yaml")
        """

        with self.open(file, mode="w") as fp:  # pylint: disable=C0103
            self.yamls(fp, *args, **kwargs)

    @classmethod
    def from_yaml(cls, file: File, *args: Any, **kwargs: Any) -> Self:
        r"""
        Construct `FlatDict` from yaml file.

        This method internally calls `self.from_yamls()` to construct object from yaml string.
        You may overwrite `from_yamls` in case something is not yaml serializable.

        Returns:
            (FlatDict):

        Examples:
            >>> FlatDict.from_yaml('tests/test.yaml').dict()
            {'a': 1, 'b': 2, 'c': 3}
        """

        kwargs.setdefault("Loader", YamlLoader)
        with cls.open(file) as fp:  # pylint: disable=C0103
            if isinstance(file, (IOBase, IO)):
                return cls.from_yamls(fp.getvalue(), *args, **kwargs)  # type: ignore[union-attr]
            return cls.from_dict(yaml_load(fp, *args, **kwargs))

    def yamls(self, *args: Any, **kwargs: Any) -> str:
        r"""
        Dump `FlatDict` to yaml string.

        Returns:
            (str):

        Examples:
            >>> FlatDict(a=1, b=2, c=3).yamls()
            'a: 1\nb: 2\nc: 3\n'
        """

        kwargs.setdefault("Dumper", YamlDumper)
        kwargs.setdefault("indent", self.getattr("indent", 2))
        return yaml_dump(self.dict(), *args, **kwargs)

    @classmethod
    def from_yamls(cls, string: str, *args: Any, **kwargs: Any) -> Self:
        r"""
        Construct `FlatDict` from yaml string.

        Returns:
            (FlatDict):

        Examples:
            >>> FlatDict.from_yamls('a: 1\nb: 2\nc: 3\n').dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> FlatDict.from_yamls('- - a\n  - 1\n- - b\n  - 2\n- - c\n  - 3\n').dict()
            {'a': 1, 'b': 2, 'c': 3}
            >>> FlatDict.from_yamls('- a: 1\n- b: 2\n- c: 3\n')
            [FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]
        """

        kwargs.setdefault("Loader", SafeLoader)
        return cls.from_dict(yaml_load(string, *args, **kwargs))

    @staticmethod
    @contextmanager
    def open(file: File, *args: Any, encoding: str = "utf-8", **kwargs: Any) -> Generator[IOBase | IO, Any, Any]:
        r"""
        Open file IO from file path or IO.

        This methods extends the ability of built-in `open` by allowing it to accept an `IOBase` object.

        Args:
            file: File path or IO.
            *args: Additional arguments passed to `open`.
                Defaults to ().
            **kwargs: Any
                Additional keyword arguments passed to `open`.
                Defaults to {}.

        Yields:
            (Generator[IOBase | IO, Any, Any]):

        Examples:
            >>> with FlatDict.open("tests/test.yaml") as fp:
            ...     print(fp.read())
            a: 1
            b: 2
            c: 3
            <BLANKLINE>
            >>> io = open("tests/test.yaml")
            >>> with FlatDict.open(io) as fp:
            ...     print(fp.read())
            a: 1
            b: 2
            c: 3
            <BLANKLINE>
            >>> with FlatDict.open(123, mode="w") as fp:
            ...     print(fp.read())
            Traceback (most recent call last):
            TypeError: expected str, bytes, os.PathLike, IO or IOBase, not int
        """

        if isinstance(file, (IOBase, IO)):
            yield file
        elif isinstance(file, (PathLike, str, bytes)):
            try:
                file = open(file, *args, encoding=encoding, **kwargs)  # type: ignore[call-overload] # noqa: SIM115
                yield file  # type: ignore[misc]
            finally:
                with suppress(Exception):
                    file.close()  # type: ignore[union-attr]
        else:
            raise TypeError(f"expected str, bytes, os.PathLike, IO or IOBase, not {type(file).__name__}")

    @classmethod
    def empty(cls, *args: Any, **kwargs: Any) -> Self:
        r"""
        Initialise an empty `FlatDict`.

        This method is helpful when you inheriting `FlatDict` with default values defined in `__init__()`.
        As use `type(self)()` in this case would copy all the default values, which might not be desired.

        This method will preserve everything in `FlatDict.__class__.__dict__`.

        Returns:
            (FlatDict):

        See Also:
            [`empty_like`][chanfig.FlatDict.empty_like]

        Examples:
            >>> d = FlatDict(a=[])
            >>> c = d.empty()
            >>> c.dict()
            {}
        """

        empty = cls.__new__(cls)
        empty.merge(*args, **kwargs)  # pylint: disable=W0212
        return empty

    def empty_like(self, *args: Any, **kwargs: Any) -> Self:
        r"""
        Initialise an empty copy of `FlatDict`.

        This method will preserve everything in `FlatDict.__class__.__dict__` and `FlatDict.__dict__`.

        For example, `property`s are saved in `__dict__`, they will keep their original reference after calling this
        method.

        Returns:
            (FlatDict):

        See Also:
            [`empty`][chanfig.FlatDict.empty]

        Examples:
            >>> d = FlatDict(a=[])
            >>> d.setattr("name", "Chang")
            >>> c = d.empty_like()
            >>> c.dict()
            {}
            >>> c.getattr("name")
            'Chang'
        """

        empty = self.empty(*args, **kwargs)
        empty.__dict__.update(self.__dict__)
        return empty

    def all_keys(self) -> Generator:
        r"""
        Equivalent to `keys`.

        This method is provided solely to make methods work on both `FlatDict` and `NestedDict`.

        See Also:
            [`all_keys`][chanfig.NestedDict.all_keys]
        """
        yield from self.keys()

    def all_values(self) -> Generator:
        r"""
        Equivalent to `keys`.

        This method is provided solely to make methods work on both `FlatDict` and `NestedDict`.

        See Also:
            [`all_values`][chanfig.NestedDict.all_values]
        """
        yield from self.values()

    def all_items(self) -> Generator:
        r"""
        Equivalent to `keys`.

        This method is provided solely to make methods work on both `FlatDict` and `NestedDict`.

        See Also:
            [`all_items`][chanfig.NestedDict.all_items]
        """
        yield from self.items()

    def dropnull(self) -> Self:
        r"""
        Drop key-value pairs with `Null` value.

        Returns:
            (FlatDict):

        **Alias**:

        + `dropna`

        Examples:
            >>> d = FlatDict(a=Null, b=Null, c=3)
            >>> d.dict()
            {'a': Null, 'b': Null, 'c': 3}
            >>> d.dropnull().dict()
            {'c': 3}
            >>> d.dropna().dict()  # alias
            {'c': 3}
        """

        return self.empty({k: v for k, v in self.all_items() if v is not Null})

    def dropna(self) -> Self:
        r"""
        Alias of [`dropnull`][chanfig.FlatDict.dropnull].
        """
        return self.dropnull()

    @staticmethod
    def extra_repr() -> str:  # pylint: disable=C0116
        return ""

    def __repr__(self) -> str:
        extra_lines = []
        extra_repr = self.extra_repr()
        # empty string will be split into list ['']
        if extra_repr:
            extra_lines = extra_repr.split("\n")
        child_lines = []
        for key, value in self.items():
            key_repr = repr(key)
            value_repr = repr(value)
            value_repr = self._add_indent(value_repr)
            child_lines.append(f"({key_repr}): {value_repr}")
            # child_lines.append(f"{key_repr}: {value_repr}")
        lines = extra_lines + child_lines

        main_repr = self.__class__.__name__ + "("
        if lines:
            # simple one-liner info, which most builtin Modules will use
            if len(extra_lines) == 1 and not child_lines:
                main_repr += extra_lines[0]
            elif len(child_lines) == 1 and not extra_lines and len(child_lines[0]) < 10:
                main_repr += child_lines[0]
            else:
                main_repr += "\n  " + "\n  ".join(lines) + "\n"

        main_repr += ")"
        return main_repr

    def _add_indent(self, text: str) -> str:
        lines = text.split("\n")
        # don't do anything for single-line stuff
        if len(lines) == 1:
            return text
        first = lines.pop(0)
        lines = [(self.getattr("indent", 2) * " ") + line for line in lines]
        text = "\n".join(lines)
        text = first + "\n" + text
        return text

    def __format__(self, format_spec: str) -> str:
        return repr(self.empty({k: v.__format__(format_spec) for k, v in self.all_items()}))

    def __hash__(self):
        return hash(frozenset(self.items()))

    def _ipython_display_(self):  # pragma: no cover
        return repr(self)

    def _ipython_canary_method_should_not_exist_(self):  # pragma: no cover
        return None

    def aihwerij235234ljsdnp34ksodfipwoe234234jlskjdf(self):  # pragma: no cover
        return None

    def __rich__(self):  # pragma: no cover
        return self.__repr__()

move_class_attributes

move_class_attributes(recursive: bool = True) -> Self

Move class attributes to instance.

Parameters:

Name	Type	Description	Default
recursive	bool		True

Returns:

Name	Type	Description
self	Self

Source code in chanfig/flat_dict.py

def move_class_attributes(self, recursive: bool = True) -> Self:
    r"""
    Move class attributes to instance.

    Args:
        recursive:

    Returns:
        self:
    """

    def move_cls_attributes(cls: type) -> Mapping:
        return {k: cls.__dict__[k] for k in get_annotations(cls).keys() if k in cls.__dict__}

    if recursive:
        for cls in self.__class__.__mro__:
            self.merge(move_cls_attributes(cls), overwrite=False)
    else:
        self.merge(move_cls_attributes(self.__class__), overwrite=False)
    return self

get

get(name: Any, default: Any = None) -> Any

Get value from FlatDict.

Parameters:

Name	Type	Description	Default
name	Any		required
default	Any		None

Returns:

Name	Type	Description
value	Any	If FlatDict does not contain name, return default.

Raises:

Type	Description
KeyError	If FlatDict does not contain name and default is not specified.
TypeError	If name is not hashable.

Examples:

Python Console Session

>>> d = FlatDict(d=1016)
>>> d.get('d')
1016
>>> d['d']
1016
>>> d.d
1016
>>> d.get('d', None)
1016
>>> d.get('f', 2)
2
>>> d.get('f')
>>> d.get('f', Null)
Traceback (most recent call last):
KeyError: 'f'

Source code in chanfig/flat_dict.py

def get(self, name: Any, default: Any = None) -> Any:
    r"""
    Get value from `FlatDict`.

    Args:
        name:
        default:

    Returns:
        value:
            If `FlatDict` does not contain `name`, return `default`.

    Raises:
        KeyError: If `FlatDict` does not contain `name` and `default` is not specified.
        TypeError: If `name` is not hashable.

    Examples:
        >>> d = FlatDict(d=1016)
        >>> d.get('d')
        1016
        >>> d['d']
        1016
        >>> d.d
        1016
        >>> d.get('d', None)
        1016
        >>> d.get('f', 2)
        2
        >>> d.get('f')
        >>> d.get('f', Null)
        Traceback (most recent call last):
        KeyError: 'f'
    """

    if name in self:
        return dict.__getitem__(self, name)
    if default is not Null:
        return default
    return self.__missing__(name)

set

set(name: Any, value: Any) -> None

Set value of FlatDict.

Parameters:

Name	Type	Description	Default
name	Any		required
value	Any		required

Examples:

Python Console Session

>>> d = FlatDict()
>>> d.set('d', 1016)
>>> d.get('d')
1016
>>> d['n'] = 'chang'
>>> d.n
'chang'
>>> d.n = 'liu'
>>> d['n']
'liu'

Source code in chanfig/flat_dict.py

def set(self, name: Any, value: Any) -> None:
    r"""
    Set value of `FlatDict`.

    Args:
        name:
        value:

    Examples:
        >>> d = FlatDict()
        >>> d.set('d', 1016)
        >>> d.get('d')
        1016
        >>> d['n'] = 'chang'
        >>> d.n
        'chang'
        >>> d.n = 'liu'
        >>> d['n']
        'liu'
    """

    if name is Null:
        raise ValueError("name must not be null")
    if name in self and isinstance(self.get(name), Variable):
        self.get(name).set(value)
    else:
        if name in get_annotations(self):
            anno = get_annotations(self)[name]
            if isinstance(anno, type) and not isinstance(value, anno):
                value = anno(value)
        dict.__setitem__(self, name, value)

delete

delete(name: Any) -> None

Delete value from FlatDict.

Parameters:

Name	Type	Description	Default
name	Any		required

Examples:

Python Console Session

>>> d = FlatDict(d=1016, n='chang')
>>> d.d
1016
>>> d.n
'chang'
>>> d.delete('d')
>>> d.d
Traceback (most recent call last):
AttributeError: 'FlatDict' object has no attribute 'd'
>>> del d.n
>>> d.n
Traceback (most recent call last):
AttributeError: 'FlatDict' object has no attribute 'n'
>>> del d.f
Traceback (most recent call last):
AttributeError: 'FlatDict' object has no attribute 'f'

Source code in chanfig/flat_dict.py

def delete(self, name: Any) -> None:
    r"""
    Delete value from `FlatDict`.

    Args:
        name:

    Examples:
        >>> d = FlatDict(d=1016, n='chang')
        >>> d.d
        1016
        >>> d.n
        'chang'
        >>> d.delete('d')
        >>> d.d
        Traceback (most recent call last):
        AttributeError: 'FlatDict' object has no attribute 'd'
        >>> del d.n
        >>> d.n
        Traceback (most recent call last):
        AttributeError: 'FlatDict' object has no attribute 'n'
        >>> del d.f
        Traceback (most recent call last):
        AttributeError: 'FlatDict' object has no attribute 'f'
    """

    dict.__delitem__(self, name)

validate

validate() -> None

Validate FlatDict.

Raises:

Type	Description
TypeError	If value is not of the type declared in class annotations.
TypeError	If Variable has invalid type.
ValueError	If Variable has invalid value.

Examples:

Python Console Session

>>> d = FlatDict(d=Variable(1016, type=int), n=Variable('chang', validator=lambda x: x.islower()))
>>> d = FlatDict(d=Variable(1016, type=str), n=Variable('chang', validator=lambda x: x.islower()))
Traceback (most recent call last):
TypeError: 'd' has invalid type. Value 1016 is not of type <class 'str'>.
>>> d = FlatDict(d=Variable(1016, type=int), n=Variable('chang', validator=lambda x: x.isupper()))
Traceback (most recent call last):
ValueError: 'n' has invalid value. Value chang is not valid.

Source code in chanfig/flat_dict.py

def validate(self) -> None:
    r"""
    Validate `FlatDict`.

    Raises:
        TypeError: If value is not of the type declared in class annotations.
        TypeError: If `Variable` has invalid type.
        ValueError: If `Variable` has invalid value.

    Examples:
        >>> d = FlatDict(d=Variable(1016, type=int), n=Variable('chang', validator=lambda x: x.islower()))
        >>> d = FlatDict(d=Variable(1016, type=str), n=Variable('chang', validator=lambda x: x.islower()))
        Traceback (most recent call last):
        TypeError: 'd' has invalid type. Value 1016 is not of type <class 'str'>.
        >>> d = FlatDict(d=Variable(1016, type=int), n=Variable('chang', validator=lambda x: x.isupper()))
        Traceback (most recent call last):
        ValueError: 'n' has invalid value. Value chang is not valid.
    """

    self._validate(self)

getattr

getattr(name: str, default: Any = Null) -> Any

Get attribute of FlatDict.

Note that it won’t retrieve value in FlatDict,

Parameters:

Name	Type	Description	Default
name	str		required
default	Any		Null

Returns:

Name	Type	Description
value	Any	If FlatDict does not contain name, return default.

Raises:

Type	Description
AttributeError	If FlatDict does not contain name and default is not specified.

Examples:

Python Console Session

>>> d = FlatDict(a=1)
>>> d.get('a')
1
>>> d.getattr('a')
Traceback (most recent call last):
AttributeError: 'FlatDict' object has no attribute 'a'
>>> d.getattr('b', 2)
2
>>> d.setattr('b', 3)
>>> d.getattr('b')
3

Source code in chanfig/flat_dict.py

def getattr(self, name: str, default: Any = Null) -> Any:
    r"""
    Get attribute of `FlatDict`.

    Note that it won't retrieve value in `FlatDict`,

    Args:
        name:
        default:

    Returns:
        value: If `FlatDict` does not contain `name`, return `default`.

    Raises:
        AttributeError: If `FlatDict` does not contain `name` and `default` is not specified.

    Examples:
        >>> d = FlatDict(a=1)
        >>> d.get('a')
        1
        >>> d.getattr('a')
        Traceback (most recent call last):
        AttributeError: 'FlatDict' object has no attribute 'a'
        >>> d.getattr('b', 2)
        2
        >>> d.setattr('b', 3)
        >>> d.getattr('b')
        3
    """

    try:
        if name in self.__dict__:
            return self.__dict__[name]
        for cls in self.__class__.__mro__:
            annotations = get_annotations(cls)
            if name in cls.__dict__ and name not in annotations:
                return cls.__dict__[name]
        return super().getattr(name, default)  # type: ignore[misc]
    except AttributeError:
        if default is not Null:
            return default
        raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{name}'") from None

setattr

setattr(name: str, value: Any) -> None

Set attribute of FlatDict.

Note that it won’t alter values in FlatDict.

Parameters:

Name	Type	Description	Default
name	str		required
value	Any		required

Warns:

Type	Description
RuntimeWarning	If name already exists in FlatDict.

Examples:

Python Console Session

>>> d = FlatDict()
>>> d.setattr('attr', 'value')
>>> d.getattr('attr')
'value'
>>> d.set('d', 1016)
>>> d.setattr('d', 1031)  # RuntimeWarning: d already exists in FlatDict.
>>> d.get('d')
1016
>>> d.d
1016
>>> d.getattr('d')
1031

Source code in chanfig/flat_dict.py

def setattr(self, name: str, value: Any) -> None:
    r"""
    Set attribute of `FlatDict`.

    Note that it won't alter values in `FlatDict`.

    Args:
        name:
        value:

    Warns:
        RuntimeWarning: If name already exists in `FlatDict`.

    Examples:
        >>> d = FlatDict()
        >>> d.setattr('attr', 'value')
        >>> d.getattr('attr')
        'value'
        >>> d.set('d', 1016)
        >>> d.setattr('d', 1031)  # RuntimeWarning: d already exists in FlatDict.
        >>> d.get('d')
        1016
        >>> d.d
        1016
        >>> d.getattr('d')
        1031
    """

    if name in self:
        warn(
            f"{name} already exists in {self.__class__.__name__}.\n"
            f"Users must call `{self.__class__.__name__}.getattr()` to retrieve conflicting attribute value.",
            RuntimeWarning,
        )
    self.__dict__[name] = value

delattr

delattr(name: str) -> None

Delete attribute of FlatDict.

Note that it won’t delete values in FlatDict.

Parameters:

Name	Type	Description	Default
name	str		required

Examples:

Python Console Session

>>> d = FlatDict()
>>> d.setattr('name', 'chang')
>>> d.getattr('name')
'chang'
>>> d.delattr('name')
>>> d.getattr('name')
Traceback (most recent call last):
AttributeError: 'FlatDict' object has no attribute 'name'

Source code in chanfig/flat_dict.py

def delattr(self, name: str) -> None:
    r"""
    Delete attribute of `FlatDict`.

    Note that it won't delete values in `FlatDict`.

    Args:
        name:

    Examples:
        >>> d = FlatDict()
        >>> d.setattr('name', 'chang')
        >>> d.getattr('name')
        'chang'
        >>> d.delattr('name')
        >>> d.getattr('name')
        Traceback (most recent call last):
        AttributeError: 'FlatDict' object has no attribute 'name'
    """

    del self.__dict__[name]

hasattr

hasattr(name: str) -> bool

Determine if an attribute exists in FlatDict.

Parameters:

Name	Type	Description	Default
name	str		required

Returns:

Type	Description
bool

Examples:

Python Console Session

>>> d = FlatDict()
>>> d.setattr('name', 'chang')
>>> d.hasattr('name')
True
>>> d.delattr('name')
>>> d.hasattr('name')
False

Source code in chanfig/flat_dict.py

def hasattr(self, name: str) -> bool:
    r"""
    Determine if an attribute exists in `FlatDict`.

    Args:
        name:

    Returns:
        (bool):

    Examples:
        >>> d = FlatDict()
        >>> d.setattr('name', 'chang')
        >>> d.hasattr('name')
        True
        >>> d.delattr('name')
        >>> d.hasattr('name')
        False
    """

    try:
        if name in self.__dict__ or name in self.__class__.__dict__:
            return True
        return super().hasattr(name)  # type: ignore[misc]
    except AttributeError:
        return False

dict

dict(flatten: bool = False) -> Mapping | Sequence | Set

Convert FlatDict to other Mapping.

Parameters:

Name	Type	Description	Default
flatten	bool	Whether to flatten NestedDict.	False

Returns:

Type	Description
Mapping

See Also

to_dict: Implementation of dict.

Alias:

• to_dict

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> d.dict()
{'a': 1, 'b': 2, 'c': 3}

Source code in chanfig/flat_dict.py

def dict(self, flatten: bool = False) -> Mapping | Sequence | Set:
    r"""
    Convert `FlatDict` to other `Mapping`.

    Args:
        flatten: Whether to flatten [`NestedDict`][chanfig.NestedDict].

    Returns:
        (Mapping):

    See Also:
        [`to_dict`][chanfig.flat_dict.to_dict]: Implementation of `dict`.

    **Alias**:

    + `to_dict`

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> d.dict()
        {'a': 1, 'b': 2, 'c': 3}
    """

    return to_dict(self, flatten)

to_dict

to_dict(flatten: bool = False) -> Mapping | Sequence | Set

Alias of dict.

Source code in chanfig/flat_dict.py

def to_dict(self, flatten: bool = False) -> Mapping | Sequence | Set:
    r"""
    Alias of [`dict`][chanfig.FlatDict.dict].
    """

    return self.dict(flatten)

from_dict classmethod

from_dict(obj: Mapping | Sequence) -> Any

Convert Mapping or Sequence to FlatDict.

Examples:

Python Console Session

>>> FlatDict.from_dict({'a': 1, 'b': 2, 'c': 3})
FlatDict(
  ('a'): 1
  ('b'): 2
  ('c'): 3
)
>>> FlatDict.from_dict([('a', 1), ('b', 2), ('c', 3)])
FlatDict(
  ('a'): 1
  ('b'): 2
  ('c'): 3
)
>>> FlatDict.from_dict([{'a': 1}, {'b': 2}, {'c': 3}])
[FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]
>>> FlatDict.from_dict({1, 2, 3})
Traceback (most recent call last):
TypeError: Expected Mapping or Sequence, but got <class 'set'>.

Source code in chanfig/flat_dict.py

@classmethod
def from_dict(cls, obj: Mapping | Sequence) -> Any:  # pylint: disable=R0911
    r"""
    Convert `Mapping` or `Sequence` to `FlatDict`.

    Examples:
        >>> FlatDict.from_dict({'a': 1, 'b': 2, 'c': 3})
        FlatDict(
          ('a'): 1
          ('b'): 2
          ('c'): 3
        )
        >>> FlatDict.from_dict([('a', 1), ('b', 2), ('c', 3)])
        FlatDict(
          ('a'): 1
          ('b'): 2
          ('c'): 3
        )
        >>> FlatDict.from_dict([{'a': 1}, {'b': 2}, {'c': 3}])
        [FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]
        >>> FlatDict.from_dict({1, 2, 3})
        Traceback (most recent call last):
        TypeError: Expected Mapping or Sequence, but got <class 'set'>.
    """

    if obj is None:
        return cls()
    if issubclass(cls, FlatDict):
        cls = cls.empty  # type: ignore[assignment] # pylint: disable=W0642
    if isinstance(obj, Mapping):
        return cls(obj)
    if isinstance(obj, Sequence):
        try:
            return cls(obj)
        except ValueError:
            return [cls(json) for json in obj]
    raise TypeError(f"Expected Mapping or Sequence, but got {type(obj)}.")

sort

sort(
    key: Callable | None = None, reverse: bool = False
) -> Self

Sort FlatDict.

Returns:

Type	Description
FlatDict

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> d.sort().dict()
{'a': 1, 'b': 2, 'c': 3}
>>> d = FlatDict(b=2, c=3, a=1)
>>> d.sort().dict()
{'a': 1, 'b': 2, 'c': 3}
>>> a = [1]
>>> d = FlatDict(z=0, a=a)
>>> a.append(2)
>>> d.sort().dict()
{'a': [1, 2], 'z': 0}

Source code in chanfig/flat_dict.py

def sort(self, key: Callable | None = None, reverse: bool = False) -> Self:
    r"""
    Sort `FlatDict`.

    Returns:
        (FlatDict):

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> d.sort().dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> d = FlatDict(b=2, c=3, a=1)
        >>> d.sort().dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> a = [1]
        >>> d = FlatDict(z=0, a=a)
        >>> a.append(2)
        >>> d.sort().dict()
        {'a': [1, 2], 'z': 0}
    """

    items = sorted(self.items(), key=key, reverse=reverse)
    self.clear()
    for k, v in items:  # pylint: disable=C0103
        self[k] = v
    return self

interpolate

interpolate(
    use_variable: bool = True,
    interpolators: MutableMapping | None = None,
    unsafe_eval: bool = False,
) -> Self

Perform Variable interpolation.

Variable interpolation allows you to set the value of one key to be the value of another key easily.

Parameters:

Name	Type	Description	Default
use_variable	bool	Whether to convert values to Variable objects.	True
interpolators	MutableMapping | None	Mapping contains values for interpolation. Defaults to self.	None
unsafe_eval	bool	Whether to evaluate interpolated values.	False

Raises:

Type	Description
ValueError	If value is not interpolatable.
ValueError	If reference to itself.
ValueError	If has circular reference.

See Also

[Variable][chanfig.Variable]: Mutable wrapper of immutable objects.

Examples:

Python Console Session

>>> d = FlatDict(a=1, b="${a}", c="${a}.${b}")
>>> d.dict()
{'a': 1, 'b': '${a}', 'c': '${a}.${b}'}
>>> d.interpolate(unsafe_eval=True).dict()
{'a': 1, 'b': 1, 'c': 1.1}
>>> d = FlatDict(a=1, b="${a}", c="${a}.${b}")
>>> d.dict()
{'a': 1, 'b': '${a}', 'c': '${a}.${b}'}
>>> d.interpolate().dict()
{'a': 1, 'b': 1, 'c': '1.1'}
>>> isinstance(d.a, Variable)
True
>>> d.a += 1
>>> d.dict()
{'a': 2, 'b': 2, 'c': '1.1'}
>>> d.a is d.b
True
>>> d.b is d.c
False
>>> d = FlatDict(a=1, b="${a}", c="${b}")
>>> d.dict()
{'a': 1, 'b': '${a}', 'c': '${b}'}
>>> d.interpolate(False).dict()
{'a': 1, 'b': 1, 'c': 1}
>>> isinstance(d.a, Variable)
False
>>> d.a += 1
>>> d.dict()
{'a': 2, 'b': 1, 'c': 1}
>>> d = FlatDict(a=1, b="${b}", c="${b}")
>>> d.interpolate().dict()
Traceback (most recent call last):
ValueError: Cannot interpolate b to itself.
>>> d = FlatDict(a="${b}", b="${c}", c="${d}", d="${a}")
>>> d.interpolate().dict()
Traceback (most recent call last):
ValueError: Circular reference found: a->b->c->d->a.
>>> d = FlatDict(a=1, b="${a}", c="${d}")
>>> d.interpolate().dict()
Traceback (most recent call last):
ValueError: d is not found in FlatDict(
  ('a'): '1'
  ('b'): '${a}'
  ('c'): '${d}'
).

Source code in chanfig/flat_dict.py

def interpolate(  # pylint: disable=R0912
    self, use_variable: bool = True, interpolators: MutableMapping | None = None, unsafe_eval: bool = False
) -> Self:
    r"""
    Perform Variable interpolation.

    Variable interpolation allows you to set the value of one key to be the value of another key easily.

    Args:
        use_variable: Whether to convert values to `Variable` objects.
        interpolators: Mapping contains values for interpolation. Defaults to `self`.
        unsafe_eval: Whether to evaluate interpolated values.

    Raises:
        ValueError: If value is not interpolatable.
        ValueError: If reference to itself.
        ValueError: If has circular reference.

    See Also:
        [Variable][`chanfig.Variable`]: Mutable wrapper of immutable objects.

    Examples:
        >>> d = FlatDict(a=1, b="${a}", c="${a}.${b}")
        >>> d.dict()
        {'a': 1, 'b': '${a}', 'c': '${a}.${b}'}
        >>> d.interpolate(unsafe_eval=True).dict()
        {'a': 1, 'b': 1, 'c': 1.1}
        >>> d = FlatDict(a=1, b="${a}", c="${a}.${b}")
        >>> d.dict()
        {'a': 1, 'b': '${a}', 'c': '${a}.${b}'}
        >>> d.interpolate().dict()
        {'a': 1, 'b': 1, 'c': '1.1'}
        >>> isinstance(d.a, Variable)
        True
        >>> d.a += 1
        >>> d.dict()
        {'a': 2, 'b': 2, 'c': '1.1'}
        >>> d.a is d.b
        True
        >>> d.b is d.c
        False
        >>> d = FlatDict(a=1, b="${a}", c="${b}")
        >>> d.dict()
        {'a': 1, 'b': '${a}', 'c': '${b}'}
        >>> d.interpolate(False).dict()
        {'a': 1, 'b': 1, 'c': 1}
        >>> isinstance(d.a, Variable)
        False
        >>> d.a += 1
        >>> d.dict()
        {'a': 2, 'b': 1, 'c': 1}
        >>> d = FlatDict(a=1, b="${b}", c="${b}")
        >>> d.interpolate().dict()
        Traceback (most recent call last):
        ValueError: Cannot interpolate b to itself.
        >>> d = FlatDict(a="${b}", b="${c}", c="${d}", d="${a}")
        >>> d.interpolate().dict()
        Traceback (most recent call last):
        ValueError: Circular reference found: a->b->c->d->a.
        >>> d = FlatDict(a=1, b="${a}", c="${d}")
        >>> d.interpolate().dict()
        Traceback (most recent call last):
        ValueError: d is not found in FlatDict(
          ('a'): '1'
          ('b'): '${a}'
          ('c'): '${d}'
        ).
    """
    # pylint: disable=C0103

    interpolators = interpolators or self
    placeholders: dict[str, list[str]] = {}
    for key, value in self.all_items():
        if isinstance(value, list):
            for v in value:
                self.find_placeholders(key, v, placeholders)
        elif isinstance(value, Mapping):
            for v in value.values():
                self.find_placeholders(key, v, placeholders)
        else:
            self.find_placeholders(key, value, placeholders)
    circular_references = find_circular_reference(placeholders)
    if circular_references:
        raise ValueError(f"Circular reference found: {'->'.join(circular_references)}.")
    if use_variable:
        placeholder_names = {i for j in placeholders.values() for i in j}
        for name in list(placeholder_names.difference(placeholders.keys())):
            if name not in interpolators:
                raise ValueError(f"{name} is not found in {interpolators}.")
            if not isinstance(interpolators[name], Variable):
                interpolators[name] = Variable(interpolators[name])
    for key, value in placeholders.items():
        if isinstance(self[key], list):
            for index, v in enumerate(self[key]):
                self[key][index] = self.substitute(v, interpolators, value)
        elif isinstance(self[key], Mapping):
            for k, v in self[key].items():
                self[key][k] = self.substitute(v, interpolators, value)
        else:
            self[key] = self.substitute(self[key], interpolators, value)
        if unsafe_eval and isinstance(self[key], str):
            with suppress(SyntaxError):
                self[key] = eval(self[key])  # pylint: disable=W0123
    return self

merge

merge(
    *args: Any, overwrite: bool = True, **kwargs: Any
) -> Self

Merge other into FlatDict.

Parameters:

Name	Type	Description	Default
*args	Any	Mapping or Sequence to be merged.	()
overwrite	bool	Whether to overwrite existing values.	True
**kwargs	Any	Mapping to be merged.	{}

Returns:

Name	Type	Description
self	Self

Alias:

• union

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
>>> d.merge(n).dict()
{'a': 1, 'b': 'b', 'c': 'c', 'd': 'd'}
>>> l = [('c', 3), ('d', 4)]
>>> d.merge(l).dict()
{'a': 1, 'b': 'b', 'c': 3, 'd': 4}
>>> FlatDict(a=1, b=1, c=1).union(FlatDict(b='b', c='c', d='d')).dict()  # alias
{'a': 1, 'b': 'b', 'c': 'c', 'd': 'd'}
>>> d = FlatDict()
>>> d.merge({1: 1, 2: 2, 3:3}).dict()
{1: 1, 2: 2, 3: 3}
>>> d.merge(d.clone()).dict()
{1: 1, 2: 2, 3: 3}
>>> d.merge({1:3, 2:1, 3: 2, 4: 4, 5: 5}, overwrite=False).dict()
{1: 1, 2: 2, 3: 3, 4: 4, 5: 5}

Source code in chanfig/flat_dict.py

def merge(self, *args: Any, overwrite: bool = True, **kwargs: Any) -> Self:
    r"""
    Merge `other` into `FlatDict`.

    Args:
        *args: `Mapping` or `Sequence` to be merged.
        overwrite: Whether to overwrite existing values.
        **kwargs: `Mapping` to be merged.

    Returns:
        self:

    **Alias**:

    + `union`

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
        >>> d.merge(n).dict()
        {'a': 1, 'b': 'b', 'c': 'c', 'd': 'd'}
        >>> l = [('c', 3), ('d', 4)]
        >>> d.merge(l).dict()
        {'a': 1, 'b': 'b', 'c': 3, 'd': 4}
        >>> FlatDict(a=1, b=1, c=1).union(FlatDict(b='b', c='c', d='d')).dict()  # alias
        {'a': 1, 'b': 'b', 'c': 'c', 'd': 'd'}
        >>> d = FlatDict()
        >>> d.merge({1: 1, 2: 2, 3:3}).dict()
        {1: 1, 2: 2, 3: 3}
        >>> d.merge(d.clone()).dict()
        {1: 1, 2: 2, 3: 3}
        >>> d.merge({1:3, 2:1, 3: 2, 4: 4, 5: 5}, overwrite=False).dict()
        {1: 1, 2: 2, 3: 3, 4: 4, 5: 5}
    """

    if len(args) == 1:
        args = args[0]
        if isinstance(args, (PathLike, str, bytes)):
            args = self.load(args)  # type: ignore[assignment]
            warn(
                "merge file is deprecated and maybe removed in a future release. Use `merge_from_file` instead.",
                PendingDeprecationWarning,
            )
        self._merge(self, args, overwrite=overwrite)
    elif len(args) > 1:
        self._merge(self, args, overwrite=overwrite)
    if kwargs:
        self._merge(self, kwargs, overwrite=overwrite)
    return self

union

union(*args: Any, **kwargs: Any) -> Self

Alias of merge.

Source code in chanfig/flat_dict.py

def union(self, *args: Any, **kwargs: Any) -> Self:
    r"""
    Alias of [`merge`][chanfig.FlatDict.merge].
    """
    return self.merge(*args, **kwargs)

merge_from_file

merge_from_file(
    file: File, *args: Any, **kwargs: Any
) -> Self

Merge content of file into FlatDict.

Parameters:

Name	Type	Description	Default
file	File		required
*args	Any	Passed to load.	()
**kwargs	Any	Passed to load.	{}

Returns:

Name	Type	Description
self	Self

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=1)
>>> d.merge_from_file("tests/test.yaml").dict()
{'a': 1, 'b': 2, 'c': 3}

Source code in chanfig/flat_dict.py

def merge_from_file(self, file: File, *args: Any, **kwargs: Any) -> Self:
    r"""
    Merge content of `file` into `FlatDict`.

    Args:
        file (File):
        *args: Passed to [`load`][chanfig.FlatDict.load].
        **kwargs: Passed to [`load`][chanfig.FlatDict.load].

    Returns:
        self:

    Examples:
        >>> d = FlatDict(a=1, b=1)
        >>> d.merge_from_file("tests/test.yaml").dict()
        {'a': 1, 'b': 2, 'c': 3}
    """

    return self.merge(self.load(file, *args, **kwargs))

intersect

intersect(other: Mapping | Iterable | PathStr) -> Self

Intersection of FlatDict and other.

Parameters:

Name	Type	Description	Default
other	Mapping | Iterable | PathStr		required

Returns:

Type	Description
FlatDict

Alias:

• inter

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
>>> d.intersect(n).dict()
{}
>>> l = [('c', 3), ('d', 4)]
>>> d.intersect(l).dict()
{'c': 3}
>>> d.merge(l).intersect("tests/test.yaml").dict()
{'a': 1, 'b': 2, 'c': 3}
>>> d.intersect(1)
Traceback (most recent call last):
TypeError: `other=1` should be of type Mapping, Iterable or PathStr, but got <class 'int'>.
>>> d.inter(FlatDict(b='b', c='c', d='d')).dict()  # alias
{}

Source code in chanfig/flat_dict.py

def intersect(self, other: Mapping | Iterable | PathStr) -> Self:
    r"""
    Intersection of `FlatDict` and `other`.

    Args:
        other (Mapping | Iterable | PathStr):

    Returns:
        (FlatDict):

    **Alias**:

    + `inter`

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
        >>> d.intersect(n).dict()
        {}
        >>> l = [('c', 3), ('d', 4)]
        >>> d.intersect(l).dict()
        {'c': 3}
        >>> d.merge(l).intersect("tests/test.yaml").dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> d.intersect(1)
        Traceback (most recent call last):
        TypeError: `other=1` should be of type Mapping, Iterable or PathStr, but got <class 'int'>.
        >>> d.inter(FlatDict(b='b', c='c', d='d')).dict()  # alias
        {}
    """

    if isinstance(other, (PathLike, str, bytes)):
        other = self.load(other)
    if isinstance(other, (Mapping,)):
        other = self.empty(other).items()
    if not isinstance(other, Iterable):
        raise TypeError(f"`other={other}` should be of type Mapping, Iterable or PathStr, but got {type(other)}.")
    return self.empty(**{key: value for key, value in other if key in self and self[key] == value})  # type: ignore

inter

inter(
    other: Mapping | Iterable | PathStr,
    *args: Any,
    **kwargs: Any
) -> Self

Alias of intersect.

Source code in chanfig/flat_dict.py

def inter(self, other: Mapping | Iterable | PathStr, *args: Any, **kwargs: Any) -> Self:
    r"""
    Alias of [`intersect`][chanfig.FlatDict.intersect].
    """
    return self.intersect(other, *args, **kwargs)

difference

difference(other: Mapping | Iterable | PathStr) -> Self

Difference between FlatDict and other.

Parameters:

Name	Type	Description	Default
other	Mapping | Iterable | PathStr		required

Returns:

Type	Description
FlatDict

Alias:

• diff

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
>>> d.difference(n).dict()
{'b': 'b', 'c': 'c', 'd': 'd'}
>>> l = [('c', 3), ('d', 4)]
>>> d.difference(l).dict()
{'d': 4}
>>> d.merge(l).difference("tests/test.yaml").dict()
{}
>>> d.difference(1)
Traceback (most recent call last):
TypeError: `other=1` should be of type Mapping, Iterable or PathStr, but got <class 'int'>.
>>> FlatDict(a=1, b=1, c=1).diff(FlatDict(b='b', c='c', d='d')).dict()  # alias
{'b': 'b', 'c': 'c', 'd': 'd'}

Source code in chanfig/flat_dict.py

def difference(self, other: Mapping | Iterable | PathStr) -> Self:
    r"""
    Difference between `FlatDict` and `other`.

    Args:
        other:

    Returns:
        (FlatDict):

    **Alias**:

    + `diff`

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> n = {'b': 'b', 'c': 'c', 'd': 'd'}
        >>> d.difference(n).dict()
        {'b': 'b', 'c': 'c', 'd': 'd'}
        >>> l = [('c', 3), ('d', 4)]
        >>> d.difference(l).dict()
        {'d': 4}
        >>> d.merge(l).difference("tests/test.yaml").dict()
        {}
        >>> d.difference(1)
        Traceback (most recent call last):
        TypeError: `other=1` should be of type Mapping, Iterable or PathStr, but got <class 'int'>.
        >>> FlatDict(a=1, b=1, c=1).diff(FlatDict(b='b', c='c', d='d')).dict()  # alias
        {'b': 'b', 'c': 'c', 'd': 'd'}
    """

    if isinstance(other, (PathLike, str, bytes)):
        other = self.load(other)
    if isinstance(other, (Mapping,)):
        other = self.empty(other).items()
    if not isinstance(other, Iterable):
        raise TypeError(f"`other={other}` should be of type Mapping, Iterable or PathStr, but got {type(other)}.")
    return self.empty(
        **{key: value for key, value in other if key not in self or self[key] != value}  # type: ignore[misc]
    )

diff

diff(
    other: Mapping | Iterable | PathStr,
    *args: Any,
    **kwargs: Any
) -> Self

Alias of difference.

Source code in chanfig/flat_dict.py

def diff(self, other: Mapping | Iterable | PathStr, *args: Any, **kwargs: Any) -> Self:
    r"""
    Alias of [`difference`][chanfig.FlatDict.difference].
    """
    return self.difference(other, *args, **kwargs)

to

to(cls: str | device | dtype) -> Self

Convert values of FlatDict to target cls.

Parameters:

Name	Type	Description	Default
cls	str | device | dtype		required

Returns:

Name	Type	Description
self	Self

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> d.to(int)
Traceback (most recent call last):
TypeError: to() only support torch.dtype and torch.device, but got <class 'int'>.

Source code in chanfig/flat_dict.py

def to(self, cls: str | TorchDevice | TorchDType) -> Self:  # pragma: no cover
    r"""
    Convert values of `FlatDict` to target `cls`.

    Args:
        cls (str | torch.device | torch.dtype):

    Returns:
        self:

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> d.to(int)
        Traceback (most recent call last):
        TypeError: to() only support torch.dtype and torch.device, but got <class 'int'>.
    """

    # pylint: disable=C0103

    if isinstance(cls, (str, TorchDevice, TorchDType)):
        for k, v in self.all_items():
            if hasattr(v, "to"):
                self[k] = v.to(cls)
        return self

    raise TypeError(f"to() only support torch.dtype and torch.device, but got {cls}.")

cpu

cpu() -> Self

Move all tensors to cpu.

Returns:

Name	Type	Description
self	Self

Examples:

Python Console Session

>>> import torch
>>> d = FlatDict(a=torch.tensor(1))
>>> d.cpu().dict()
{'a': tensor(1, device='cpu')}

Source code in chanfig/flat_dict.py

def cpu(self) -> Self:  # pragma: no cover
    r"""
    Move all tensors to cpu.

    Returns:
        self:

    Examples:
        >>> import torch
        >>> d = FlatDict(a=torch.tensor(1))
        >>> d.cpu().dict()  # doctest: +SKIP
        {'a': tensor(1, device='cpu')}
    """

    return self.to(TorchDevice("cpu"))

gpu

gpu() -> Self

Move all tensors to gpu.

Returns:

Name	Type	Description
self	Self

Alias:

• cuda

Examples:

Python Console Session

>>> import torch
>>> d = FlatDict(a=torch.tensor(1))
>>> d.gpu().dict()
{'a': tensor(1, device='cuda:0')}
>>> d.cuda().dict()  # alias
{'a': tensor(1, device='cuda:0')}

Source code in chanfig/flat_dict.py

def gpu(self) -> Self:  # pragma: no cover
    r"""
    Move all tensors to gpu.

    Returns:
        self:

    **Alias**:

    + `cuda`

    Examples:
        >>> import torch
        >>> d = FlatDict(a=torch.tensor(1))
        >>> d.gpu().dict()  # doctest: +SKIP
        {'a': tensor(1, device='cuda:0')}
        >>> d.cuda().dict()  # alias  # doctest: +SKIP
        {'a': tensor(1, device='cuda:0')}
    """

    return self.to(TorchDevice("cuda"))

cuda

cuda() -> Self

Alias of gpu.

Source code in chanfig/flat_dict.py

def cuda(self) -> Self:  # pragma: no cover
    r"""
    Alias of [`gpu`][chanfig.FlatDict.gpu].
    """
    return self.gpu()

tpu

tpu() -> Self

Move all tensors to tpu.

Returns:

Name	Type	Description
self	Self

Alias:

• xla

Examples:

Python Console Session

>>> import torch
>>> d = FlatDict(a=torch.tensor(1))
>>> d.tpu().dict()
{'a': tensor(1, device='xla:0')}
>>> d.xla().dict()  # alias
{'a': tensor(1, device='xla:0')}

Source code in chanfig/flat_dict.py

def tpu(self) -> Self:  # pragma: no cover
    r"""
    Move all tensors to tpu.

    Returns:
        self:

    **Alias**:

    + `xla`

    Examples:
        >>> import torch
        >>> d = FlatDict(a=torch.tensor(1))
        >>> d.tpu().dict()  # doctest: +SKIP
        {'a': tensor(1, device='xla:0')}
        >>> d.xla().dict()  # alias  # doctest: +SKIP
        {'a': tensor(1, device='xla:0')}
    """

    return self.to(TorchDevice("xla"))

xla

xla() -> Self

Alias of tpu.

Source code in chanfig/flat_dict.py

def xla(self) -> Self:  # pragma: no cover
    r"""
    Alias of [`tpu`][chanfig.FlatDict.tpu].
    """
    return self.tpu()

copy

copy() -> Self

Create a shallow copy of FlatDict.

Returns:

Type	Description
FlatDict

Examples:

Python Console Session

>>> d = FlatDict(a=[])
>>> d.setattr("name", "Chang")
>>> c = d.copy()
>>> c.dict()
{'a': []}
>>> d.a.append(1)
>>> c.dict()
{'a': [1]}
>>> c.getattr("name")
'Chang'

Source code in chanfig/flat_dict.py

def copy(self) -> Self:
    r"""
    Create a shallow copy of `FlatDict`.

    Returns:
        (FlatDict):

    Examples:
        >>> d = FlatDict(a=[])
        >>> d.setattr("name", "Chang")
        >>> c = d.copy()
        >>> c.dict()
        {'a': []}
        >>> d.a.append(1)
        >>> c.dict()
        {'a': [1]}
        >>> c.getattr("name")
        'Chang'
    """

    return copy(self)

deepcopy

deepcopy(memo: Mapping | None = None) -> Self

Create a deep copy of FlatDict.

Returns:

Type	Description
FlatDict

Alias:

• clone

Examples:

Python Console Session

>>> d = FlatDict(a=[])
>>> d.setattr("name", "Chang")
>>> c = d.deepcopy()
>>> c.dict()
{'a': []}
>>> d.a.append(1)
>>> c.dict()
{'a': []}
>>> c.getattr("name")
'Chang'
>>> d == d.clone()  # alias
True

Source code in chanfig/flat_dict.py

def deepcopy(self, memo: Mapping | None = None) -> Self:  # pylint: disable=W0613
    r"""
    Create a deep copy of `FlatDict`.

    Returns:
        (FlatDict):

    **Alias**:

    + `clone`

    Examples:
        >>> d = FlatDict(a=[])
        >>> d.setattr("name", "Chang")
        >>> c = d.deepcopy()
        >>> c.dict()
        {'a': []}
        >>> d.a.append(1)
        >>> c.dict()
        {'a': []}
        >>> c.getattr("name")
        'Chang'
        >>> d == d.clone()  # alias
        True
    """

    return deepcopy(self)

clone

clone(memo: Mapping | None = None) -> Self

Alias of deepcopy.

Source code in chanfig/flat_dict.py

def clone(self, memo: Mapping | None = None) -> Self:
    r"""
    Alias of [`deepcopy`][chanfig.FlatDict.deepcopy].
    """
    return self.deepcopy(memo=memo)

save

save(
    file: File,
    method: str = None,
    *args: Any,
    **kwargs: Any
) -> None

Save FlatDict to file.

Raises:

Type	Description
ValueError	If save to IO and method is not specified.
TypeError	If save to unsupported extension.

Alias:

• save

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> d.save("tests/test.yaml")
>>> d.save("test.conf")
Traceback (most recent call last):
TypeError: `file='test.conf'` should be in ('json',) or ('yml', 'yaml'), but got conf.
>>> with open("test.yaml", "w") as f:
...     d.save(f)
Traceback (most recent call last):
ValueError: `method` must be specified when saving to IO.

Source code in chanfig/flat_dict.py

def save(  # pylint: disable=W1113
    self, file: File, method: str = None, *args: Any, **kwargs: Any  # type: ignore[assignment]
) -> None:
    r"""
    Save `FlatDict` to file.

    Raises:
        ValueError: If save to `IO` and `method` is not specified.
        TypeError: If save to unsupported extension.

    **Alias**:

    + `save`

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> d.save("tests/test.yaml")
        >>> d.save("test.conf")
        Traceback (most recent call last):
        TypeError: `file='test.conf'` should be in ('json',) or ('yml', 'yaml'), but got conf.
        >>> with open("test.yaml", "w") as f:
        ...     d.save(f)
        Traceback (most recent call last):
        ValueError: `method` must be specified when saving to IO.
    """

    if method is None:
        if isinstance(file, (IOBase, IO)):
            raise ValueError("`method` must be specified when saving to IO.")
        method = splitext(file)[-1][1:]
    extension = method.lower()
    if extension in YAML:
        return self.yaml(file=file, *args, **kwargs)  # type: ignore[misc]  # noqa: B026
    if extension in JSON:
        return self.json(file=file, *args, **kwargs)  # type: ignore[misc]  # noqa: B026
    raise TypeError(f"`file={file!r}` should be in {JSON} or {YAML}, but got {extension}.")

dump

dump(
    file: File,
    method: str = None,
    *args: Any,
    **kwargs: Any
) -> None

Alias of save.

Source code in chanfig/flat_dict.py

def dump(  # pylint: disable=W1113
    self, file: File, method: str = None, *args: Any, **kwargs: Any  # type: ignore[assignment]
) -> None:
    r"""
    Alias of [`save`][chanfig.FlatDict.save].
    """
    return self.save(file, method, *args, **kwargs)

load classmethod

load(
    file: File,
    method: str = None,
    *args: Any,
    **kwargs: Any
) -> Self

Load FlatDict from file.

Parameters:

Name	Type	Description	Default
file	File	File to load from.	required
method	str	File type, should be in JSON or YAML.	None

Returns:

Type	Description
FlatDict

Raises:

Type	Description
ValueError	If load from IO and method is not specified.
TypeError	If dump to unsupported extension.

Examples:

Python Console Session

>>> d = FlatDict.load("tests/test.yaml")
>>> d.dict()
{'a': 1, 'b': 2, 'c': 3}
>>> d.load("tests/test.conf")
Traceback (most recent call last):
TypeError: `file='tests/test.conf'` should be in ('json',) or ('yml', 'yaml'), but got conf.
>>> with open("tests/test.yaml") as f:
...     d.load(f)
Traceback (most recent call last):
ValueError: `method` must be specified when loading from IO.

Source code in chanfig/flat_dict.py

@classmethod
def load(  # pylint: disable=W1113
    cls, file: File, method: str = None, *args: Any, **kwargs: Any  # type: ignore[assignment]
) -> Self:
    """
    Load `FlatDict` from file.

    Args:
        file: File to load from.
        method: File type, should be in `JSON` or `YAML`.

    Returns:
        (FlatDict):

    Raises:
        ValueError: If load from `IO` and `method` is not specified.
        TypeError: If dump to unsupported extension.

    Examples:
        >>> d = FlatDict.load("tests/test.yaml")
        >>> d.dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> d.load("tests/test.conf")
        Traceback (most recent call last):
        TypeError: `file='tests/test.conf'` should be in ('json',) or ('yml', 'yaml'), but got conf.
        >>> with open("tests/test.yaml") as f:
        ...     d.load(f)
        Traceback (most recent call last):
        ValueError: `method` must be specified when loading from IO.
    """

    if method is None:
        if isinstance(file, (IOBase, IO)):
            raise ValueError("`method` must be specified when loading from IO.")
        method = splitext(file)[-1][1:]
    extension = method.lower()
    if extension in JSON:
        return cls.from_json(file, *args, **kwargs)
    if extension in YAML:
        return cls.from_yaml(file, *args, **kwargs)
    raise TypeError(f"`file={file!r}` should be in {JSON} or {YAML}, but got {extension}.")

json

json(file: File, *args: Any, **kwargs: Any) -> None

Dump FlatDict to json file.

This method internally calls self.jsons() to generate json string. You may overwrite jsons in case something is not json serializable.

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> d.json("tests/test.json")

Source code in chanfig/flat_dict.py

def json(self, file: File, *args: Any, **kwargs: Any) -> None:
    r"""
    Dump `FlatDict` to json file.

    This method internally calls `self.jsons()` to generate json string.
    You may overwrite `jsons` in case something is not json serializable.

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> d.json("tests/test.json")
    """

    with self.open(file, mode="w") as fp:  # pylint: disable=C0103
        fp.write(self.jsons(*args, **kwargs))

from_json classmethod

from_json(file: File, *args: Any, **kwargs: Any) -> Self

Construct FlatDict from json file.

This method internally calls self.from_jsons() to construct object from json string. You may overwrite from_jsons in case something is not json serializable.

Returns:

Type	Description
FlatDict

Examples:

Python Console Session

>>> d = FlatDict.from_json('tests/test.json')
>>> d.dict()
{'a': 1, 'b': 2, 'c': 3}

Source code in chanfig/flat_dict.py

@classmethod
def from_json(cls, file: File, *args: Any, **kwargs: Any) -> Self:
    r"""
    Construct `FlatDict` from json file.

    This method internally calls `self.from_jsons()` to construct object from json string.
    You may overwrite `from_jsons` in case something is not json serializable.

    Returns:
        (FlatDict):

    Examples:
        >>> d = FlatDict.from_json('tests/test.json')
        >>> d.dict()
        {'a': 1, 'b': 2, 'c': 3}
    """

    with cls.open(file) as fp:  # pylint: disable=C0103
        if isinstance(file, (IOBase, IO)):
            return cls.from_jsons(fp.getvalue(), *args, **kwargs)  # type: ignore[union-attr]
        return cls.from_jsons(fp.read(), *args, **kwargs)

jsons

jsons(*args: Any, **kwargs: Any) -> str

Dump FlatDict to json string.

Returns:

Type	Description
str

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> d.jsons()
'{\n  "a": 1,\n  "b": 2,\n  "c": 3\n}'

Source code in chanfig/flat_dict.py

def jsons(self, *args: Any, **kwargs: Any) -> str:
    r"""
    Dump `FlatDict` to json string.

    Returns:
        (str):

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> d.jsons()
        '{\n  "a": 1,\n  "b": 2,\n  "c": 3\n}'
    """

    kwargs.setdefault("cls", JsonEncoder)
    kwargs.setdefault("indent", self.getattr("indent", 2))
    return json_dumps(self.dict(), *args, **kwargs)

from_jsons classmethod

from_jsons(string: str, *args: Any, **kwargs: Any) -> Self

Construct FlatDict from json string.

Returns:

Type	Description
FlatDict

Examples:

Python Console Session

>>> FlatDict.from_jsons('{\n  "a": 1,\n  "b": 2,\n  "c": 3\n}').dict()
{'a': 1, 'b': 2, 'c': 3}
>>> FlatDict.from_jsons('[["a", 1], ["b", 2], ["c", 3]]').dict()
{'a': 1, 'b': 2, 'c': 3}
>>> FlatDict.from_jsons('[{"a": 1}, {"b": 2}, {"c": 3}]')
[FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]

Source code in chanfig/flat_dict.py

@classmethod
def from_jsons(cls, string: str, *args: Any, **kwargs: Any) -> Self:
    r"""
    Construct `FlatDict` from json string.

    Returns:
        (FlatDict):

    Examples:
        >>> FlatDict.from_jsons('{\n  "a": 1,\n  "b": 2,\n  "c": 3\n}').dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> FlatDict.from_jsons('[["a", 1], ["b", 2], ["c", 3]]').dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> FlatDict.from_jsons('[{"a": 1}, {"b": 2}, {"c": 3}]')
        [FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]
    """

    return cls.from_dict(json_loads(string, *args, **kwargs))

yaml

yaml(file: File, *args: Any, **kwargs: Any) -> None

Dump FlatDict to yaml file.

This method internally calls self.yamls() to generate yaml string. You may overwrite yamls in case something is not yaml serializable.

Examples:

Python Console Session

>>> d = FlatDict(a=1, b=2, c=3)
>>> d.yaml("tests/test.yaml")

Source code in chanfig/flat_dict.py

def yaml(self, file: File, *args: Any, **kwargs: Any) -> None:
    r"""
    Dump `FlatDict` to yaml file.

    This method internally calls `self.yamls()` to generate yaml string.
    You may overwrite `yamls` in case something is not yaml serializable.

    Examples:
        >>> d = FlatDict(a=1, b=2, c=3)
        >>> d.yaml("tests/test.yaml")
    """

    with self.open(file, mode="w") as fp:  # pylint: disable=C0103
        self.yamls(fp, *args, **kwargs)

from_yaml classmethod

from_yaml(file: File, *args: Any, **kwargs: Any) -> Self

Construct FlatDict from yaml file.

This method internally calls self.from_yamls() to construct object from yaml string. You may overwrite from_yamls in case something is not yaml serializable.

Returns:

Type	Description
FlatDict

Examples:

Python Console Session

>>> FlatDict.from_yaml('tests/test.yaml').dict()
{'a': 1, 'b': 2, 'c': 3}

Source code in chanfig/flat_dict.py

@classmethod
def from_yaml(cls, file: File, *args: Any, **kwargs: Any) -> Self:
    r"""
    Construct `FlatDict` from yaml file.

    This method internally calls `self.from_yamls()` to construct object from yaml string.
    You may overwrite `from_yamls` in case something is not yaml serializable.

    Returns:
        (FlatDict):

    Examples:
        >>> FlatDict.from_yaml('tests/test.yaml').dict()
        {'a': 1, 'b': 2, 'c': 3}
    """

    kwargs.setdefault("Loader", YamlLoader)
    with cls.open(file) as fp:  # pylint: disable=C0103
        if isinstance(file, (IOBase, IO)):
            return cls.from_yamls(fp.getvalue(), *args, **kwargs)  # type: ignore[union-attr]
        return cls.from_dict(yaml_load(fp, *args, **kwargs))

yamls

yamls(*args: Any, **kwargs: Any) -> str

Dump FlatDict to yaml string.

Returns:

Type	Description
str

Examples:

Python Console Session

>>> FlatDict(a=1, b=2, c=3).yamls()
'a: 1\nb: 2\nc: 3\n'

Source code in chanfig/flat_dict.py

def yamls(self, *args: Any, **kwargs: Any) -> str:
    r"""
    Dump `FlatDict` to yaml string.

    Returns:
        (str):

    Examples:
        >>> FlatDict(a=1, b=2, c=3).yamls()
        'a: 1\nb: 2\nc: 3\n'
    """

    kwargs.setdefault("Dumper", YamlDumper)
    kwargs.setdefault("indent", self.getattr("indent", 2))
    return yaml_dump(self.dict(), *args, **kwargs)

from_yamls classmethod

from_yamls(string: str, *args: Any, **kwargs: Any) -> Self

Construct FlatDict from yaml string.

Returns:

Type	Description
FlatDict

Examples:

Python Console Session

>>> FlatDict.from_yamls('a: 1\nb: 2\nc: 3\n').dict()
{'a': 1, 'b': 2, 'c': 3}
>>> FlatDict.from_yamls('- - a\n  - 1\n- - b\n  - 2\n- - c\n  - 3\n').dict()
{'a': 1, 'b': 2, 'c': 3}
>>> FlatDict.from_yamls('- a: 1\n- b: 2\n- c: 3\n')
[FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]

Source code in chanfig/flat_dict.py

@classmethod
def from_yamls(cls, string: str, *args: Any, **kwargs: Any) -> Self:
    r"""
    Construct `FlatDict` from yaml string.

    Returns:
        (FlatDict):

    Examples:
        >>> FlatDict.from_yamls('a: 1\nb: 2\nc: 3\n').dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> FlatDict.from_yamls('- - a\n  - 1\n- - b\n  - 2\n- - c\n  - 3\n').dict()
        {'a': 1, 'b': 2, 'c': 3}
        >>> FlatDict.from_yamls('- a: 1\n- b: 2\n- c: 3\n')
        [FlatDict(('a'): 1), FlatDict(('b'): 2), FlatDict(('c'): 3)]
    """

    kwargs.setdefault("Loader", SafeLoader)
    return cls.from_dict(yaml_load(string, *args, **kwargs))

open staticmethod

open(
    file: File,
    *args: Any,
    encoding: str = "utf-8",
    **kwargs: Any
) -> Generator[IOBase | IO, Any, Any]

Open file IO from file path or IO.

This methods extends the ability of built-in open by allowing it to accept an IOBase object.

Parameters:

Name	Type	Description	Default
file	File	File path or IO.	required
*args	Any	Additional arguments passed to open. Defaults to ().	()
**kwargs	Any	Any Additional keyword arguments passed to open. Defaults to {}.	{}

Yields:

Type	Description
Generator[IOBase | IO, Any, Any]

Examples:

Python Console Session

>>> with FlatDict.open("tests/test.yaml") as fp:
...     print(fp.read())
a: 1
b: 2
c: 3

>>> io = open("tests/test.yaml")
>>> with FlatDict.open(io) as fp:
...     print(fp.read())
a: 1
b: 2
c: 3

>>> with FlatDict.open(123, mode="w") as fp:
...     print(fp.read())
Traceback (most recent call last):
TypeError: expected str, bytes, os.PathLike, IO or IOBase, not int

Source code in chanfig/flat_dict.py

@staticmethod
@contextmanager
def open(file: File, *args: Any, encoding: str = "utf-8", **kwargs: Any) -> Generator[IOBase | IO, Any, Any]:
    r"""
    Open file IO from file path or IO.

    This methods extends the ability of built-in `open` by allowing it to accept an `IOBase` object.

    Args:
        file: File path or IO.
        *args: Additional arguments passed to `open`.
            Defaults to ().
        **kwargs: Any
            Additional keyword arguments passed to `open`.
            Defaults to {}.

    Yields:
        (Generator[IOBase | IO, Any, Any]):

    Examples:
        >>> with FlatDict.open("tests/test.yaml") as fp:
        ...     print(fp.read())
        a: 1
        b: 2
        c: 3
        <BLANKLINE>
        >>> io = open("tests/test.yaml")
        >>> with FlatDict.open(io) as fp:
        ...     print(fp.read())
        a: 1
        b: 2
        c: 3
        <BLANKLINE>
        >>> with FlatDict.open(123, mode="w") as fp:
        ...     print(fp.read())
        Traceback (most recent call last):
        TypeError: expected str, bytes, os.PathLike, IO or IOBase, not int
    """

    if isinstance(file, (IOBase, IO)):
        yield file
    elif isinstance(file, (PathLike, str, bytes)):
        try:
            file = open(file, *args, encoding=encoding, **kwargs)  # type: ignore[call-overload] # noqa: SIM115
            yield file  # type: ignore[misc]
        finally:
            with suppress(Exception):
                file.close()  # type: ignore[union-attr]
    else:
        raise TypeError(f"expected str, bytes, os.PathLike, IO or IOBase, not {type(file).__name__}")

empty classmethod

empty(*args: Any, **kwargs: Any) -> Self

Initialise an empty FlatDict.

This method is helpful when you inheriting FlatDict with default values defined in __init__(). As use type(self)() in this case would copy all the default values, which might not be desired.

This method will preserve everything in FlatDict.__class__.__dict__.

Returns:

Type	Description
FlatDict

See Also

empty_like

Examples:

Python Console Session

>>> d = FlatDict(a=[])
>>> c = d.empty()
>>> c.dict()
{}

Source code in chanfig/flat_dict.py

@classmethod
def empty(cls, *args: Any, **kwargs: Any) -> Self:
    r"""
    Initialise an empty `FlatDict`.

    This method is helpful when you inheriting `FlatDict` with default values defined in `__init__()`.
    As use `type(self)()` in this case would copy all the default values, which might not be desired.

    This method will preserve everything in `FlatDict.__class__.__dict__`.

    Returns:
        (FlatDict):

    See Also:
        [`empty_like`][chanfig.FlatDict.empty_like]

    Examples:
        >>> d = FlatDict(a=[])
        >>> c = d.empty()
        >>> c.dict()
        {}
    """

    empty = cls.__new__(cls)
    empty.merge(*args, **kwargs)  # pylint: disable=W0212
    return empty

empty_like

empty_like(*args: Any, **kwargs: Any) -> Self

Initialise an empty copy of FlatDict.

This method will preserve everything in FlatDict.__class__.__dict__ and FlatDict.__dict__.

For example, propertys are saved in __dict__, they will keep their original reference after calling this method.

Returns:

Type	Description
FlatDict

See Also

empty

Examples:

Python Console Session

>>> d = FlatDict(a=[])
>>> d.setattr("name", "Chang")
>>> c = d.empty_like()
>>> c.dict()
{}
>>> c.getattr("name")
'Chang'

Source code in chanfig/flat_dict.py

def empty_like(self, *args: Any, **kwargs: Any) -> Self:
    r"""
    Initialise an empty copy of `FlatDict`.

    This method will preserve everything in `FlatDict.__class__.__dict__` and `FlatDict.__dict__`.

    For example, `property`s are saved in `__dict__`, they will keep their original reference after calling this
    method.

    Returns:
        (FlatDict):

    See Also:
        [`empty`][chanfig.FlatDict.empty]

    Examples:
        >>> d = FlatDict(a=[])
        >>> d.setattr("name", "Chang")
        >>> c = d.empty_like()
        >>> c.dict()
        {}
        >>> c.getattr("name")
        'Chang'
    """

    empty = self.empty(*args, **kwargs)
    empty.__dict__.update(self.__dict__)
    return empty

all_keys

all_keys() -> Generator

Equivalent to keys.

This method is provided solely to make methods work on both FlatDict and NestedDict.

See Also

all_keys

Source code in chanfig/flat_dict.py

def all_keys(self) -> Generator:
    r"""
    Equivalent to `keys`.

    This method is provided solely to make methods work on both `FlatDict` and `NestedDict`.

    See Also:
        [`all_keys`][chanfig.NestedDict.all_keys]
    """
    yield from self.keys()

all_values

all_values() -> Generator

Equivalent to keys.

This method is provided solely to make methods work on both FlatDict and NestedDict.

See Also

all_values

Source code in chanfig/flat_dict.py

def all_values(self) -> Generator:
    r"""
    Equivalent to `keys`.

    This method is provided solely to make methods work on both `FlatDict` and `NestedDict`.

    See Also:
        [`all_values`][chanfig.NestedDict.all_values]
    """
    yield from self.values()

all_items

all_items() -> Generator

Equivalent to keys.

This method is provided solely to make methods work on both FlatDict and NestedDict.

See Also

all_items

Source code in chanfig/flat_dict.py

def all_items(self) -> Generator:
    r"""
    Equivalent to `keys`.

    This method is provided solely to make methods work on both `FlatDict` and `NestedDict`.

    See Also:
        [`all_items`][chanfig.NestedDict.all_items]
    """
    yield from self.items()

dropnull

dropnull() -> Self

Drop key-value pairs with Null value.

Returns:

Type	Description
FlatDict

Alias:

• dropna

Examples:

Python Console Session

>>> d = FlatDict(a=Null, b=Null, c=3)
>>> d.dict()
{'a': Null, 'b': Null, 'c': 3}
>>> d.dropnull().dict()
{'c': 3}
>>> d.dropna().dict()  # alias
{'c': 3}

Source code in chanfig/flat_dict.py

def dropnull(self) -> Self:
    r"""
    Drop key-value pairs with `Null` value.

    Returns:
        (FlatDict):

    **Alias**:

    + `dropna`

    Examples:
        >>> d = FlatDict(a=Null, b=Null, c=3)
        >>> d.dict()
        {'a': Null, 'b': Null, 'c': 3}
        >>> d.dropnull().dict()
        {'c': 3}
        >>> d.dropna().dict()  # alias
        {'c': 3}
    """

    return self.empty({k: v for k, v in self.all_items() if v is not Null})

dropna

dropna() -> Self

Alias of dropnull.

Source code in chanfig/flat_dict.py

def dropna(self) -> Self:
    r"""
    Alias of [`dropnull`][chanfig.FlatDict.dropnull].
    """
    return self.dropnull()