:doc:`/index`

F.A.Q
=====

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.. admonition:: DeepDiff is now part of |qluster_link|.

    *If you're building workflows around data validation and correction,* `Qluster </qluster>`__ *gives your team a structured way to manage rules, review failures, approve fixes, and reuse decisions—without building the entire system from scratch.*

.. Note::
    |:mega:| **Please fill out our** `fast 5-question survey <https://forms.gle/E6qXexcgjoKnSzjB8>`__ so that we can learn how & why you use DeepDiff, and what improvements we should make. Thank you! |:dancers:|


Q: DeepDiff report is not precise when ignore_order=True
--------------------------------------------------------

    >>> from deepdiff import DeepDiff
    >>> from pprint import pprint
    >>> t1 = [
    ...     {
    ...         "key": "some/pathto/customers/foo/",
    ...         "flags": 0,
    ...         "value": ""
    ...     },
    ...     {
    ...         "key": "some/pathto/customers/foo/account_number",
    ...         "flags": 0,
    ...         "value": "somevalue1"
    ...     }
    ... ]
    >>>
    >>> t2 = [
    ...     {
    ...         "key": "some/pathto/customers/foo/account_number",
    ...         "flags": 0,
    ...         "value": "somevalue2"
    ...     },
    ...     {
    ...         "key": "some/pathto/customers/foo/",
    ...         "flags": 0,
    ...         "value": "new"
    ...     }
    ... ]
    >>>
    >>> pprint(DeepDiff(t1, t2))
    {'values_changed': {"root[0]['key']": {'new_value': 'some/pathto/customers/foo/account_number',
                                           'old_value': 'some/pathto/customers/foo/'},
                        "root[0]['value']": {'new_value': 'somevalue2',
                                             'old_value': ''},
                        "root[1]['key']": {'new_value': 'some/pathto/customers/foo/',
                                           'old_value': 'some/pathto/customers/foo/account_number'},
                        "root[1]['value']": {'new_value': 'new',
                                             'old_value': 'somevalue1'}}}

**Answer**

This is explained in :ref:`cutoff_distance_for_pairs_label` and :ref:`cutoff_intersection_for_pairs_label`

Bump up these 2 parameters to 1 and you get what you want:

    >>> pprint(DeepDiff(t1, t2, ignore_order=True, cutoff_distance_for_pairs=1, cutoff_intersection_for_pairs=1))
    {'values_changed': {"root[0]['value']": {'new_value': 'new', 'old_value': ''},
                        "root[1]['value']": {'new_value': 'somevalue2',
                                             'old_value': 'somevalue1'}}}


Q: The report of changes in a nested dictionary is too granular
---------------------------------------------------------------

**Answer**

Use :ref:`threshold_to_diff_deeper_label`

    >>> from deepdiff import DeepDiff
    >>> t1 = {"veggie": "carrots"}
    >>> t2 = {"meat": "carrots"}
    >>>
    >>> DeepDiff(t1, t2, threshold_to_diff_deeper=0)
    {'dictionary_item_added': ["root['meat']"], 'dictionary_item_removed': ["root['veggie']"]}
    >>> DeepDiff(t1, t2, threshold_to_diff_deeper=0.33)
    {'values_changed': {'root': {'new_value': {'meat': 'carrots'}, 'old_value': {'veggie': 'carrots'}}}}



Q: TypeError: Object of type type is not JSON serializable
----------------------------------------------------------

I'm trying to serialize the DeepDiff results into json and I'm getting the TypeError.

    >>> diff=DeepDiff(1, "a")
    >>> diff
    {'type_changes': {'root': {'old_type': <class 'int'>, 'new_type': <class 'str'>, 'old_value': 1, 'new_value': 'a'}}}
    >>> json.dumps(diff)
    Traceback (most recent call last):
      File "<stdin>", line 1, in <module>
      File ".../json/__init__.py", line 231, in dumps
        return _default_encoder.encode(obj)
      File ".../json/encoder.py", line 199, in encode
        chunks = self.iterencode(o, _one_shot=True)
      File ".../json/encoder.py", line 257, in iterencode
        return _iterencode(o, 0)
      File ".../json/encoder.py", line 179, in default
        raise TypeError(f'Object of type {o.__class__.__name__} '
    TypeError: Object of type type is not JSON serializable

**Answer**

In order to serialize DeepDiff results into json, use to_json()

    >>> diff.to_json()
    '{"type_changes": {"root": {"old_type": "int", "new_type": "str", "old_value": 1, "new_value": "a"}}}'


Q: How do I parse DeepDiff result paths?
----------------------------------------

**Answer**

Use parse_path:

    >>> from deepdiff import parse_path
    >>> parse_path("root[1][2]['age']")
    [1, 2, 'age']
    >>> parse_path("root[1][2]['age']", include_actions=True)
    [{'element': 1, 'action': 'GET'}, {'element': 2, 'action': 'GET'}, {'element': 'age', 'action': 'GET'}]
    >>>
    >>> parse_path("root['joe'].age")
    ['joe', 'age']
    >>> parse_path("root['joe'].age", include_actions=True)
    [{'element': 'joe', 'action': 'GET'}, {'element': 'age', 'action': 'GETATTR'}]

Or use the tree view so you can use path(output_format='list'):

    >>> t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2, 3, 4]}}
    >>> t2 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2]}}
    >>> ddiff = DeepDiff(t1, t2, view='tree')
    >>> ddiff
    {'iterable_item_removed': [<root[4]['b'][2] t1:3, t2:not present>, <root[4]['b'][3] t1:4, t2:not present>]}
    >>> # Note that the iterable_item_removed is a set. In this case it has 2 items in it.
    >>> # One way to get one item from the set is to convert it to a list
    >>> # And then get the first item of the list:
    >>> removed = list(ddiff['iterable_item_removed'])[0]
    >>> removed
    <root[4]['b'][2] t1:3, t2:not present>
    >>>
    >>> parent = removed.up
    >>> parent
    <root[4]['b'] t1:[1, 2, 3, 4], t2:[1, 2]>
    >>> parent.path()  # gives you the string representation of the path
    "root[4]['b']"
    >>> parent.path(output_format='list')  # gives you the list of keys and attributes that make up the path
    [4, 'b']


Q: Why my datetimes are reported in UTC?
----------------------------------------

**Answer**

DeepDiff converts all datetimes into UTC. If a datetime is timezone naive, we assume it is in UTC too.
That is different than what Python does. Python assumes your timezone naive datetime is in your local timezone. However, you can override it to any other time zone such as your :ref:`default_timezone_label`.

    >>> from deepdiff import DeepDiff
    >>> from datetime import datetime, timezone
    >>> d1 = datetime(2020, 8, 31, 13, 14, 1)
    >>> d2 = datetime(2020, 8, 31, 13, 14, 1, tzinfo=timezone.utc)
    >>> d1 == d2
    False
    >>> DeepDiff(d1, d2)
    {}

    >>> d3 = d2.astimezone(pytz.timezone('America/New_York'))
    >>> DeepDiff(d1, d3)
    {}
    >>> d1 == d3
    False


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