two version of R2R are hereHEADmaster

1 files changed, 837 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/deepdiff/helper.py b/.venv/lib/python3.12/site-packages/deepdiff/helper.py
new file mode 100644
index 00000000..63a4e315
--- /dev/null
+++ b/.venv/lib/python3.12/site-packages/deepdiff/helper.py
@@ -0,0 +1,837 @@
+import sys
+import re
+import os
+import datetime
+import uuid
+import logging
+import warnings
+import string
+import time
+import enum
+import ipaddress
+from typing import NamedTuple, Any, List, Optional, Dict, Union, TYPE_CHECKING, Tuple
+from ast import literal_eval
+from decimal import Decimal, localcontext, InvalidOperation as InvalidDecimalOperation
+from itertools import repeat
+from orderly_set import StableSetEq as SetOrderedBase  # median: 1.0867 s for cache test, 5.63s for all tests
+from threading import Timer
+
+if TYPE_CHECKING:
+    from pytz.tzinfo import BaseTzInfo
+
+
+class np_type:
+    pass
+
+
+class pydantic_base_model_type:
+    pass
+
+
+class SetOrdered(SetOrderedBase):
+    def __repr__(self):
+        return str(list(self))
+
+
+try:
+    import numpy as np
+except ImportError:  # pragma: no cover. The case without Numpy is tested locally only.
+    np = None  # pragma: no cover.
+    np_array_factory = 'numpy not available'  # pragma: no cover.
+    np_ndarray = np_type  # pragma: no cover.
+    np_bool_ = np_type  # pragma: no cover.
+    np_int8 = np_type  # pragma: no cover.
+    np_int16 = np_type  # pragma: no cover.
+    np_int32 = np_type  # pragma: no cover.
+    np_int64 = np_type  # pragma: no cover.
+    np_uint8 = np_type  # pragma: no cover.
+    np_uint16 = np_type  # pragma: no cover.
+    np_uint32 = np_type  # pragma: no cover.
+    np_uint64 = np_type  # pragma: no cover.
+    np_intp = np_type  # pragma: no cover.
+    np_uintp = np_type  # pragma: no cover.
+    np_float32 = np_type  # pragma: no cover.
+    np_float64 = np_type  # pragma: no cover.
+    np_double = np_type  # pragma: no cover.
+    np_floating = np_type  # pragma: no cover.
+    np_complex64 = np_type  # pragma: no cover.
+    np_complex128 = np_type  # pragma: no cover.
+    np_cdouble = np_type  # pragma: no cover.
+    np_complexfloating = np_type  # pragma: no cover.
+else:
+    np_array_factory = np.array
+    np_ndarray = np.ndarray
+    np_bool_ = np.bool_
+    np_int8 = np.int8
+    np_int16 = np.int16
+    np_int32 = np.int32
+    np_int64 = np.int64
+    np_uint8 = np.uint8
+    np_uint16 = np.uint16
+    np_uint32 = np.uint32
+    np_uint64 = np.uint64
+    np_intp = np.intp
+    np_uintp = np.uintp
+    np_float32 = np.float32
+    np_float64 = np.float64
+    np_double = np.double  # np.float_ is an alias for np.double and is being removed by NumPy 2.0
+    np_floating = np.floating
+    np_complex64 = np.complex64
+    np_complex128 = np.complex128
+    np_cdouble = np.cdouble  # np.complex_ is an alias for np.cdouble and is being removed by NumPy 2.0
+    np_complexfloating = np.complexfloating
+
+numpy_numbers = (
+    np_int8, np_int16, np_int32, np_int64, np_uint8,
+    np_uint16, np_uint32, np_uint64, np_intp, np_uintp,
+    np_float32, np_float64, np_double, np_floating, np_complex64,
+    np_complex128, np_cdouble,)
+
+numpy_complex_numbers = (
+    np_complexfloating, np_complex64, np_complex128, np_cdouble,
+)
+
+numpy_dtypes = set(numpy_numbers)
+numpy_dtypes.add(np_bool_)  # type: ignore
+
+numpy_dtype_str_to_type = {
+    item.__name__: item for item in numpy_dtypes
+}
+
+try:
+    from pydantic.main import BaseModel as PydanticBaseModel  # type: ignore
+except ImportError:
+    PydanticBaseModel = pydantic_base_model_type
+
+
+logger = logging.getLogger(__name__)
+
+py_major_version = sys.version_info.major
+py_minor_version = sys.version_info.minor
+
+py_current_version = Decimal("{}.{}".format(py_major_version, py_minor_version))
+
+py2 = py_major_version == 2
+py3 = py_major_version == 3
+py4 = py_major_version == 4
+
+
+NUMERICS = frozenset(string.digits)
+
+
+class EnumBase(str, enum.Enum):
+    def __repr__(self):
+        """
+        We need to add a single quotes so we can easily copy the value when we do ipdb.
+        """
+        return f"'{self.name}'"
+
+    def __str__(self):
+        return self.name
+
+
+def _int_or_zero(value):
+    """
+    Tries to extract some number from a string.
+
+    12c becomes 12
+    """
+    try:
+        return int(value)
+    except Exception:
+        result = []
+        for char in value:
+            if char in NUMERICS:
+                result.append(char)
+        if result:
+            return int(''.join(result))
+        return 0
+
+
+def get_semvar_as_integer(version):
+    """
+    Converts:
+
+    '1.23.5' to 1023005
+    """
+    version = version.split('.')
+    if len(version) > 3:
+        version = version[:3]
+    elif len(version) < 3:
+        version.extend(['0'] * (3 - len(version)))
+
+    return sum([10**(i * 3) * _int_or_zero(v) for i, v in enumerate(reversed(version))])
+
+
+# we used to use OrderedDictPlus when dictionaries in Python were not ordered.
+dict_ = dict
+
+if py4:
+    logger.warning('Python 4 is not supported yet. Switching logic to Python 3.')  # pragma: no cover
+    py3 = True  # pragma: no cover
+
+if py2:  # pragma: no cover
+    sys.exit('Python 2 is not supported anymore. The last version of DeepDiff that supported Py2 was 3.3.0')
+
+pypy3 = py3 and hasattr(sys, "pypy_translation_info")
+
+
+if np and get_semvar_as_integer(np.__version__) < 1019000:
+    sys.exit('The minimum required Numpy version is 1.19.0. Please upgrade your Numpy package.')
+
+strings = (str, bytes)  # which are both basestring
+unicode_type = str
+bytes_type = bytes
+only_complex_number = (complex,) + numpy_complex_numbers
+only_numbers = (int, float, complex, Decimal) + numpy_numbers
+datetimes = (datetime.datetime, datetime.date, datetime.timedelta, datetime.time)
+ipranges = (ipaddress.IPv4Interface, ipaddress.IPv6Interface, ipaddress.IPv4Network, ipaddress.IPv6Network)
+uuids = (uuid.UUID, )
+times = (datetime.datetime, datetime.time)
+numbers: Tuple = only_numbers + datetimes
+booleans = (bool, np_bool_)
+
+basic_types = strings + numbers + uuids + booleans + (type(None), )
+
+class IndexedHash(NamedTuple):
+    indexes: List
+    item: Any
+
+current_dir = os.path.dirname(os.path.abspath(__file__))
+
+ID_PREFIX = '!>*id'
+
+KEY_TO_VAL_STR = "{}:{}"
+
+TREE_VIEW = 'tree'
+TEXT_VIEW = 'text'
+DELTA_VIEW = '_delta'
+
+ENUM_INCLUDE_KEYS = ['__objclass__', 'name', 'value']
+
+
+def short_repr(item, max_length=15):
+    """Short representation of item if it is too long"""
+    item = repr(item)
+    if len(item) > max_length:
+        item = '{}...{}'.format(item[:max_length - 3], item[-1])
+    return item
+
+
+class ListItemRemovedOrAdded:  # pragma: no cover
+    """Class of conditions to be checked"""
+    pass
+
+
+class OtherTypes:
+    def __repr__(self):
+        return "Error: {}".format(self.__class__.__name__)  # pragma: no cover
+
+    __str__ = __repr__
+
+
+class Skipped(OtherTypes):
+    pass
+
+
+class Unprocessed(OtherTypes):
+    pass
+
+
+class NotHashed(OtherTypes):
+    pass
+
+
+class NotPresent:  # pragma: no cover
+    """
+    In a change tree, this indicated that a previously existing object has been removed -- or will only be added
+    in the future.
+    We previously used None for this but this caused problem when users actually added and removed None. Srsly guys? :D
+    """
+
+    def __repr__(self):
+        return 'not present'  # pragma: no cover
+
+    __str__ = __repr__
+
+
+class CannotCompare(Exception):
+    """
+    Exception when two items cannot be compared in the compare function.
+    """
+    pass
+
+
+unprocessed = Unprocessed()
+skipped = Skipped()
+not_hashed = NotHashed()
+notpresent = NotPresent()
+
+# Disabling remapping from old to new keys since the mapping is deprecated.
+RemapDict = dict_
+
+
+# class RemapDict(dict_):
+#     """
+#     DISABLED
+#     Remap Dictionary.
+
+#     For keys that have a new, longer name, remap the old key to the new key.
+#     Other keys that don't have a new name are handled as before.
+#     """
+
+#     def __getitem__(self, old_key):
+#         new_key = EXPANDED_KEY_MAP.get(old_key, old_key)
+#         if new_key != old_key:
+#             logger.warning(
+#                 "DeepDiff Deprecation: %s is renamed to %s. Please start using "
+#                 "the new unified naming convention.", old_key, new_key)
+#         if new_key in self:
+#             return self.get(new_key)
+#         else:  # pragma: no cover
+#             raise KeyError(new_key)
+
+
+class indexed_set(set):
+    """
+    A set class that lets you get an item by index
+
+    >>> a = indexed_set()
+    >>> a.add(10)
+    >>> a.add(20)
+    >>> a[0]
+    10
+    """
+
+
+def add_to_frozen_set(parents_ids, item_id):
+    return parents_ids | {item_id}
+
+
+def convert_item_or_items_into_set_else_none(items):
+    if items:
+        if isinstance(items, strings):
+            items = {items}
+        else:
+            items = set(items)
+    else:
+        items = None
+    return items
+
+
+def add_root_to_paths(paths):
+    """
+    Sometimes the users want to just pass
+    [key] instead of root[key] for example.
+    Here we automatically add all sorts of variations that might match
+    the path they were supposed to pass. 
+    """
+    if paths is None:
+        return
+    result = SetOrdered()
+    for path in paths:
+        if path.startswith('root'):
+            result.add(path)
+        else:
+            if path.isdigit():
+                result.add(f"root['{path}']")
+                result.add(f"root[{path}]")
+            elif path[0].isdigit():
+                result.add(f"root['{path}']")
+            else:
+                result.add(f"root.{path}")
+                result.add(f"root['{path}']")
+    return result
+
+
+RE_COMPILED_TYPE = type(re.compile(''))
+
+
+def convert_item_or_items_into_compiled_regexes_else_none(items):
+    if items:
+        if isinstance(items, (strings, RE_COMPILED_TYPE)):
+            items = [items]
+        items = [i if isinstance(i, RE_COMPILED_TYPE) else re.compile(i) for i in items]
+    else:
+        items = None
+    return items
+
+
+def get_id(obj):
+    """
+    Adding some characters to id so they are not just integers to reduce the risk of collision.
+    """
+    return "{}{}".format(ID_PREFIX, id(obj))
+
+
+def get_type(obj):
+    """
+    Get the type of object or if it is a class, return the class itself.
+    """
+    if isinstance(obj, np_ndarray):
+        return obj.dtype.type  # type: ignore
+    return obj if type(obj) is type else type(obj)
+
+
+def numpy_dtype_string_to_type(dtype_str):
+    return numpy_dtype_str_to_type[dtype_str]
+
+
+def type_in_type_group(item, type_group):
+    return get_type(item) in type_group
+
+
+def type_is_subclass_of_type_group(item, type_group):
+    return isinstance(item, type_group) \
+        or (isinstance(item, type) and issubclass(item, type_group)) \
+        or type_in_type_group(item, type_group)
+
+
+def get_doc(doc_filename):
+    try:
+        with open(os.path.join(current_dir, '../docs/', doc_filename), 'r') as doc_file:
+            doc = doc_file.read()
+    except Exception:  # pragma: no cover
+        doc = 'Failed to load the docstrings. Please visit: https://zepworks.com/deepdiff/current/'  # pragma: no cover
+    return doc
+
+
+number_formatting = {
+    "f": r'{:.%sf}',
+    "e": r'{:.%se}',
+}
+
+
+def number_to_string(number, significant_digits, number_format_notation="f"):
+    """
+    Convert numbers to string considering significant digits.
+    """
+    try:
+        using = number_formatting[number_format_notation]
+    except KeyError:
+        raise ValueError("number_format_notation got invalid value of {}. The valid values are 'f' and 'e'".format(number_format_notation)) from None
+
+    if not isinstance(number, numbers):  # type: ignore
+        return number
+    elif isinstance(number, Decimal):
+        with localcontext() as ctx:
+            # Precision = number of integer digits + significant_digits
+            # Using number//1 to get the integer part of the number
+            ctx.prec = len(str(abs(number // 1))) + significant_digits
+            try:
+                number = number.quantize(Decimal('0.' + '0' * significant_digits))
+            except InvalidDecimalOperation:
+                # Sometimes rounding up causes a higher precision to be needed for the quantize operation
+                # For example '999.99999999' will become '1000.000000' after quantize
+                ctx.prec += 1
+                number = number.quantize(Decimal('0.' + '0' * significant_digits))
+    elif isinstance(number, only_complex_number):  # type: ignore
+        # Case for complex numbers.
+        number = number.__class__(
+            "{real}+{imag}j".format(  # type: ignore
+                real=number_to_string(
+                    number=number.real,  # type: ignore
+                    significant_digits=significant_digits,
+                    number_format_notation=number_format_notation
+                ),
+                imag=number_to_string(
+                    number=number.imag,  # type: ignore
+                    significant_digits=significant_digits,
+                    number_format_notation=number_format_notation
+                )
+            )  # type: ignore
+        )
+    else:
+        number = round(number=number, ndigits=significant_digits)  # type: ignore
+
+        if significant_digits == 0:
+            number = int(number)
+
+    if number == 0.0:
+        # Special case for 0: "-0.xx" should compare equal to "0.xx"
+        number = abs(number)  # type: ignore
+
+    # Cast number to string
+    result = (using % significant_digits).format(number)
+    # https://bugs.python.org/issue36622
+    if number_format_notation == 'e':
+        # Removing leading 0 for exponential part.
+        result = re.sub(
+            pattern=r'(?<=e(\+|\-))0(?=\d)+',
+            repl=r'',
+            string=result
+        )
+    return result
+
+
+class DeepDiffDeprecationWarning(DeprecationWarning):
+    """
+    Use this warning instead of DeprecationWarning
+    """
+    pass
+
+
+def cartesian_product(a, b):
+    """
+    Get the Cartesian product of two iterables
+
+    **parameters**
+
+    a: list of lists
+    b: iterable to do the Cartesian product
+    """
+
+    for i in a:
+        for j in b:
+            yield i + (j,)
+
+
+def cartesian_product_of_shape(dimentions, result=None):
+    """
+    Cartesian product of a dimentions iterable.
+    This is mainly used to traverse Numpy ndarrays.
+
+    Each array has dimentions that are defines in ndarray.shape
+    """
+    if result is None:
+        result = ((),)  # a tuple with an empty tuple
+    for dimension in dimentions:
+        result = cartesian_product(result, range(dimension))
+    return result
+
+
+def get_numpy_ndarray_rows(obj, shape=None):
+    """
+    Convert a multi dimensional numpy array to list of rows
+    """
+    if shape is None:
+        shape = obj.shape
+
+    dimentions = shape[:-1]
+    for path_tuple in cartesian_product_of_shape(dimentions):
+        result = obj
+        for index in path_tuple:
+            result = result[index]
+        yield path_tuple, result
+
+
+class _NotFound:
+
+    def __eq__(self, other):
+        return False
+
+    __req__ = __eq__
+
+    def __repr__(self):
+        return 'not found'
+
+    __str__ = __repr__
+
+
+not_found = _NotFound()
+
+warnings.simplefilter('once', DeepDiffDeprecationWarning)
+
+
+class RepeatedTimer:
+    """
+    Threaded Repeated Timer by MestreLion
+    https://stackoverflow.com/a/38317060/1497443
+    """
+
+    def __init__(self, interval, function, *args, **kwargs):
+        self._timer = None
+        self.interval = interval
+        self.function = function
+        self.args = args
+        self.start_time = time.time()
+        self.kwargs = kwargs
+        self.is_running = False
+        self.start()
+
+    def _get_duration_sec(self):
+        return int(time.time() - self.start_time)
+
+    def _run(self):
+        self.is_running = False
+        self.start()
+        self.function(*self.args, **self.kwargs)
+
+    def start(self):
+        self.kwargs.update(duration=self._get_duration_sec())
+        if not self.is_running:
+            self._timer = Timer(self.interval, self._run)
+            self._timer.start()
+            self.is_running = True
+
+    def stop(self):
+        duration = self._get_duration_sec()
+        if self._timer is not None:
+            self._timer.cancel()
+        self.is_running = False
+        return duration
+
+
+def _eval_decimal(params):
+    return Decimal(params)
+
+
+def _eval_datetime(params):
+    params = f'({params})'
+    params = literal_eval(params)
+    return datetime.datetime(*params)
+
+
+def _eval_date(params):
+    params = f'({params})'
+    params = literal_eval(params)
+    return datetime.date(*params)
+
+
+LITERAL_EVAL_PRE_PROCESS = [
+    ('Decimal(', ')', _eval_decimal),
+    ('datetime.datetime(', ')', _eval_datetime),
+    ('datetime.date(', ')', _eval_date),
+]
+
+
+def literal_eval_extended(item):
+    """
+    An extended version of literal_eval
+    """
+    try:
+        return literal_eval(item)
+    except (SyntaxError, ValueError):
+        for begin, end, func in LITERAL_EVAL_PRE_PROCESS:
+            if item.startswith(begin) and item.endswith(end):
+                # Extracting and removing extra quotes so for example "Decimal('10.1')" becomes "'10.1'" and then '10.1'
+                params = item[len(begin): -len(end)].strip('\'\"')
+                return func(params)
+        raise
+
+
+def time_to_seconds(t:datetime.time) -> int:
+    return (t.hour * 60 + t.minute) * 60 + t.second
+
+
+def datetime_normalize(
+    truncate_datetime:Union[str, None],
+    obj:Union[datetime.datetime, datetime.time],
+    default_timezone: Union[
+        datetime.timezone, "BaseTzInfo"
+    ] = datetime.timezone.utc,
+) -> Any:
+    if truncate_datetime:
+        if truncate_datetime == 'second':
+            obj = obj.replace(microsecond=0)
+        elif truncate_datetime == 'minute':
+            obj = obj.replace(second=0, microsecond=0)
+        elif truncate_datetime == 'hour':
+            obj = obj.replace(minute=0, second=0, microsecond=0)
+        elif truncate_datetime == 'day':
+            obj = obj.replace(hour=0, minute=0, second=0, microsecond=0)
+    if isinstance(obj, datetime.datetime):
+        if has_timezone(obj):
+            obj = obj.astimezone(default_timezone)
+        else:
+            obj = obj.replace(tzinfo=default_timezone)
+    elif isinstance(obj, datetime.time):
+        return time_to_seconds(obj)
+    return obj
+
+
+def has_timezone(dt):
+    """
+    Function to check if a datetime object has a timezone
+
+    Checking dt.tzinfo.utcoffset(dt) ensures that the datetime object is truly timezone-aware
+    because some datetime objects may have a tzinfo attribute that is not None but still
+    doesn't provide a valid offset.
+
+    Certain tzinfo objects, such as pytz.timezone(None), can exist but do not provide meaningful UTC offset information.
+    If tzinfo is present but calling .utcoffset(dt) returns None, the datetime is not truly timezone-aware.
+    """
+    return dt.tzinfo is not None and dt.tzinfo.utcoffset(dt) is not None
+
+
+def get_truncate_datetime(truncate_datetime) -> Union[str, None]:
+    """
+    Validates truncate_datetime value
+    """
+    if truncate_datetime not in {None, 'second', 'minute', 'hour', 'day'}:
+        raise ValueError("truncate_datetime must be second, minute, hour or day")
+    return truncate_datetime
+
+
+def cartesian_product_numpy(*arrays):
+    """
+    Cartesian product of Numpy arrays by Paul Panzer
+    https://stackoverflow.com/a/49445693/1497443
+    """
+    la = len(arrays)
+    dtype = np.result_type(*arrays)  # type: ignore
+    arr = np.empty((la, *map(len, arrays)), dtype=dtype)  # type: ignore
+    idx = slice(None), *repeat(None, la)
+    for i, a in enumerate(arrays):
+        arr[i, ...] = a[idx[:la - i]]
+    return arr.reshape(la, -1).T
+
+
+def diff_numpy_array(A, B):
+    """
+    Numpy Array A - B
+    return items in A that are not in B
+    By Divakar
+    https://stackoverflow.com/a/52417967/1497443
+    """
+    return A[~np.isin(A, B)]  # type: ignore
+
+
+PYTHON_TYPE_TO_NUMPY_TYPE = {
+    int: np_int64,
+    float: np_float64,
+    Decimal: np_float64
+}
+
+
+def get_homogeneous_numpy_compatible_type_of_seq(seq):
+    """
+    Return with the numpy dtype if the array can be converted to a non-object numpy array.
+    Originally written by mgilson https://stackoverflow.com/a/13252348/1497443
+    This is the modified version.
+    """
+    iseq = iter(seq)
+    first_type = type(next(iseq))
+    if first_type in {int, float, Decimal}:
+        type_ = first_type if all((type(x) is first_type) for x in iseq) else False
+        return PYTHON_TYPE_TO_NUMPY_TYPE.get(type_, False)
+    else:
+        return False
+
+
+def detailed__dict__(obj, ignore_private_variables=True, ignore_keys=frozenset(), include_keys=None):
+    """
+    Get the detailed dictionary of an object.
+
+    This is used so we retrieve object properties too.
+    """
+    if include_keys:
+        result = {}
+        for key in include_keys:
+            try:
+                value = getattr(obj, key)
+            except Exception:
+                pass
+            else:
+                if not callable(value) or key == '__objclass__':  # We don't want to compare functions, however for backward compatibility, __objclass__ needs to be reported.
+                    result[key] = value
+    else:
+        result = obj.__dict__.copy()  # A shallow copy
+        private_var_prefix = f"_{obj.__class__.__name__}__"  # The semi private variables in Python get this prefix
+        for key in ignore_keys:
+            if key in result or (
+                ignore_private_variables and key.startswith('__') and not key.startswith(private_var_prefix)
+            ):
+                del result[key]
+        for key in dir(obj):
+            if key not in result and key not in ignore_keys and (
+                    not ignore_private_variables or (
+                        ignore_private_variables and not key.startswith('__') and not key.startswith(private_var_prefix)
+                    )
+            ):
+                value = getattr(obj, key)
+                if not callable(value):
+                    result[key] = value
+    return result
+
+
+def named_tuple_repr(self):
+    fields = []
+    for field, value in self._asdict().items():
+        # Only include fields that do not have their default value
+        if field in self._field_defaults:
+            if value != self._field_defaults[field]:
+                fields.append(f"{field}={value!r}")
+        else:
+            fields.append(f"{field}={value!r}")
+
+    return f"{self.__class__.__name__}({', '.join(fields)})"
+
+
+class OpcodeTag(EnumBase):
+    insert = 'insert'
+    delete = 'delete'
+    equal = 'equal'
+    replace = 'replace'  # type: ignore
+    # swapped = 'swapped'  # in the future we should support reporting of items swapped with each other
+
+
+class Opcode(NamedTuple):
+    tag: str
+    t1_from_index: int
+    t1_to_index: int
+    t2_from_index: int
+    t2_to_index: int
+    old_values: Optional[List[Any]] = None
+    new_values: Optional[List[Any]] = None
+
+    __repr__ = __str__ = named_tuple_repr
+
+
+class FlatDataAction(EnumBase):
+    values_changed = 'values_changed'
+    type_changes = 'type_changes'
+    set_item_added = 'set_item_added'
+    set_item_removed = 'set_item_removed'
+    dictionary_item_added = 'dictionary_item_added'
+    dictionary_item_removed = 'dictionary_item_removed'
+    iterable_item_added = 'iterable_item_added'
+    iterable_item_removed = 'iterable_item_removed'
+    iterable_item_moved = 'iterable_item_moved'
+    iterable_items_inserted = 'iterable_items_inserted'  # opcode
+    iterable_items_deleted = 'iterable_items_deleted'  # opcode
+    iterable_items_replaced = 'iterable_items_replaced'  # opcode
+    iterable_items_equal = 'iterable_items_equal'  # opcode
+    attribute_removed = 'attribute_removed'
+    attribute_added = 'attribute_added'
+    unordered_iterable_item_added = 'unordered_iterable_item_added'
+    unordered_iterable_item_removed = 'unordered_iterable_item_removed'
+    initiated = "initiated"
+
+
+OPCODE_TAG_TO_FLAT_DATA_ACTION = {
+    OpcodeTag.insert: FlatDataAction.iterable_items_inserted,
+    OpcodeTag.delete: FlatDataAction.iterable_items_deleted,
+    OpcodeTag.replace: FlatDataAction.iterable_items_replaced,
+    OpcodeTag.equal: FlatDataAction.iterable_items_equal,
+}
+
+FLAT_DATA_ACTION_TO_OPCODE_TAG = {v: i for i, v in OPCODE_TAG_TO_FLAT_DATA_ACTION.items()}
+
+
+UnkownValueCode: str = 'unknown___'
+
+
+class FlatDeltaRow(NamedTuple):
+    path: List
+    action: FlatDataAction
+    value: Optional[Any] = UnkownValueCode
+    old_value: Optional[Any] = UnkownValueCode
+    type: Optional[Any] = UnkownValueCode
+    old_type: Optional[Any] = UnkownValueCode
+    new_path: Optional[List] = None
+    t1_from_index: Optional[int] = None
+    t1_to_index: Optional[int] = None
+    t2_from_index: Optional[int] = None
+    t2_to_index: Optional[int] = None
+
+    __repr__ = __str__ = named_tuple_repr
+
+
+JSON = Union[Dict[str, str], List[str], List[int], Dict[str, "JSON"], List["JSON"], str, int, float, bool, None]
+
+
+class SummaryNodeType(EnumBase):
+    dict = 'dict'
+    list = 'list'
+    leaf = 'leaf'