fixing text for typos and English grammer

seperman · seperman · commit 8c7561b3e29e · 2026-03-27T12:11:40.000-07:00
diff --git a/AUTHORS.md b/AUTHORS.md
@@ -34,7 +34,7 @@ Authors in order of the timeline of their contributions:
 - Stian Jensen [stianjensen](https://github.com/stianjensen) for improving ignoring of NoneType in diff 
 - Florian Klien [flowolf](https://github.com/flowolf) for adding math_epsilon
 - Tim Klein [timjklein36](https://github.com/timjklein36) for retaining the order of multiple dictionary items added via Delta.
-- Wilhelm Schürmann[wbsch](https://github.com/wbsch) for fixing the typo with yml files.
+- Wilhelm Schürmann [wbsch](https://github.com/wbsch) for fixing the typo with yml files.
 - [lyz-code](https://github.com/lyz-code) for adding support for regular expressions in DeepSearch and strict_checking feature in DeepSearch.
 - [dtorres-sf](https://github.com/dtorres-sf) for adding the option for custom compare function
 - Tony Wang [Tony-Wang](https://github.com/Tony-Wang) for bugfix: verbose_level==0 should disable values_changes.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -36,7 +36,7 @@
     - Added support for memoryview serialization
     - Added support for bytes serialization (non-UTF8 compatible)
     - Fixed bug where group_by with numbers would leak type info into group path reports
-    - Fixed bug in `_get_clean_to_keys_mapping without` explicit significant digits
+    - Fixed bug in `_get_clean_to_keys_mapping` without explicit significant digits
     - Added support for python dict key serialization
     - Enhanced support for IP address serialization with safe module imports
     - Added development tooling improvements (pyright config, .envrc example)
@@ -45,7 +45,7 @@
 - v8-5-0
     - Updating deprecated pydantic calls
     - Switching to pyproject.toml
-    - Fix for moving nested tables when using iterable_compare_func.  by 
+    - Fix for moving nested tables when using iterable_compare_func.
     - Fix recursion depth limit when hashing numpy.datetime64
     - Moving from legacy setuptools use to pyproject.toml
 
@@ -231,7 +231,7 @@
 - v1-0-2: Checking for ImmutableMapping type instead of dict
 - v1-0-1: Better ignore order support
 - v1-0-0: Restructuring output to make it more useful. This is NOT backward compatible.
-- v0-6-1: Fixiing iterables with unhashable when order is ignored
+- v0-6-1: Fixing iterables with unhashable when order is ignored
 - v0-6-0: Adding unicode support
 - v0-5-9: Adding decimal support
 - v0-5-8: Adding ignore order of unhashables support
diff --git a/README.md b/README.md
@@ -138,7 +138,7 @@ Please take a look at the [CHANGELOG](CHANGELOG.md) file.
 1. Please make your PR against the dev branch
 2. Please make sure that your PR has tests. Since DeepDiff is used in many sensitive data driven projects, we strive to maintain around 100% test coverage on the code.
 
-Please run `pytest --cov=deepdiff --runslow` to see the coverage report. Note that the `--runslow` flag will run some slow tests too. In most cases you only want to run the fast tests which so you wont add the `--runslow` flag.
+Please run `pytest --cov=deepdiff --runslow` to see the coverage report. Note that the `--runslow` flag will run some slow tests too. In most cases you only want to run the fast tests which so you won't add the `--runslow` flag.
 
 Or to see a more user friendly version, please run: `pytest --cov=deepdiff --cov-report term-missing --runslow`.
 
diff --git a/deepdiff/deephash.py b/deepdiff/deephash.py
@@ -349,7 +349,7 @@ def get(self, key: Any, default: Any = None, extract_index: Optional[int] = 0) -
         """
         Get method for the hashes dictionary.
         It can extract the hash for a given key that is already calculated when extract_index=0
-        or the count of items that went to building the object whenextract_index=1.
+        or the count of items that went to building the object when extract_index=1.
         """
         return self.get_key(self.hashes, key, default=default, extract_index=extract_index,
                             ignore_numeric_type_changes=self.ignore_numeric_type_changes)
@@ -360,7 +360,7 @@ def get_key(hashes: Dict[Any, Any], key: Any, default: Any = None, extract_index
         """
         get_key method for the hashes dictionary.
         It can extract the hash for a given key that is already calculated when extract_index=0
-        or the count of items that went to building the object whenextract_index=1.
+        or the count of items that went to building the object when extract_index=1.
         """
         try:
             result = DeepHash._getitem(hashes, key, extract_index=extract_index,
diff --git a/deepdiff/distance.py b/deepdiff/distance.py
@@ -45,7 +45,7 @@ def _get_rough_distance(self: "DistanceProtocol"):
         Gives a numeric value for the distance of t1 and t2 based on how many operations are needed to convert
         one to the other.
 
-        This is a similar concept to the Levenshtein Edit Distance but for the structured data and is it is designed
+        This is a similar concept to the Levenshtein Edit Distance but for the structured data and it is designed
         to be between 0 and 1.
 
         A distance of zero means the objects are equal and a distance of 1 is very far.
diff --git a/deepdiff/helper.py b/deepdiff/helper.py
@@ -496,10 +496,10 @@ def cartesian_product(a: Iterable[Tuple[Any, ...]], b: Iterable[Any]) -> Iterato
 
 def cartesian_product_of_shape(dimentions: Iterable[int], result: Optional[Tuple[Tuple[Any, ...], ...]] = None) -> Iterator[Tuple[Any, ...]]:
     """
-    Cartesian product of a dimentions iterable.
+    Cartesian product of a dimensions iterable.
     This is mainly used to traverse Numpy ndarrays.
 
-    Each array has dimentions that are defines in ndarray.shape
+    Each array has dimensions that are defined in ndarray.shape
     """
     if result is None:
         result = ((),)  # a tuple with an empty tuple
diff --git a/deepdiff/model.py b/deepdiff/model.py
@@ -919,7 +919,7 @@ def stringify_param(self, force: Optional[str] = None) -> Optional[str]:
                         Will return '(unrepresentable)' instead of None if there is no string representation
 
         TODO: stringify_param has issues with params that when converted to string via repr,
-        it is not straight forward to turn them back into the original object.
+        it is not straightforward to turn them back into the original object.
         Although repr is meant to be able to reconstruct the original object but for complex objects, repr
         often does not recreate the original object.
         Perhaps we should log that the repr reconstruction failed so the user is aware.
diff --git a/docs/changelog.rst b/docs/changelog.rst
@@ -43,7 +43,7 @@ DeepDiff Changelog
    - Added support for bytes serialization (non-UTF8 compatible)
    - Fixed bug where group_by with numbers would leak type info into group
      path reports
-   - Fixed bug in ``_get_clean_to_keys_mapping without`` explicit
+   - Fixed bug in ``_get_clean_to_keys_mapping`` without explicit
      significant digits
    - Added support for python dict key serialization
    - Enhanced support for IP address serialization with safe module imports
@@ -328,7 +328,7 @@ DeepDiff Changelog
 - v1-0-2: Checking for ImmutableMapping type instead of dict
 - v1-0-1: Better ignore order support
 - v1-0-0: Restructuring output to make it more useful. This is NOT backward compatible.
-- v0-6-1: Fixiing iterables with unhashable when order is ignored
+- v0-6-1: Fixing iterables with unhashable when order is ignored
 - v0-6-0: Adding unicode support
 - v0-5-9: Adding decimal support
 - v0-5-8: Adding ignore order for unhashables support
diff --git a/docs/commandline.rst b/docs/commandline.rst
@@ -238,7 +238,7 @@ Imagine if we have the following files:
    :header-rows: 1
 
 .. csv-table:: t2.csv
-   :file: ../tests/fixtures/t1.csv
+   :file: ../tests/fixtures/t2.csv
    :header-rows: 1
 
 
diff --git a/docs/custom.rst b/docs/custom.rst
@@ -178,7 +178,7 @@ Define A Custom Operator
 ------------------------
 
 
-To define an custom operator, you just need to inherit *BaseOperator* or *BaseOperatorPlus*.
+To define a custom operator, you just need to inherit *BaseOperator* or *BaseOperatorPlus*.
 
     - *BaseOperatorPlus* is our new base operator that can be subclassed and provides the structure to build any custom operator.
     - *BaseOperator* is our older base class for creating custom operators. It was designed mainly for simple string based regex comparison.
diff --git a/docs/deep_distance.rst b/docs/deep_distance.rst
@@ -8,7 +8,7 @@ Deep Distance
 
 Deep Distance is the distance between 2 objects. It is a floating point number between 0 and 1. Deep Distance in concept is inspired by `Levenshtein Edit Distance <https://en.wikipedia.org/wiki/Levenshtein_distance>`_.
 
-At its core, the Deep Distance is the number of operations needed to convert one object to the other divided by the sum of the sizes of the 2 objects capped at 1. Note that unlike Levensthtein Distance, the Deep Distance is based on the number of operations and NOT the “minimum” number of operations to convert one object to the other. The number is highly dependent on the granularity of the diff results. And the granularity is controlled by the parameters passed to DeepDiff.
+At its core, the Deep Distance is the number of operations needed to convert one object to the other divided by the sum of the sizes of the 2 objects capped at 1. Note that unlike Levenshtein Distance, the Deep Distance is based on the number of operations and NOT the “minimum” number of operations to convert one object to the other. The number is highly dependent on the granularity of the diff results. And the granularity is controlled by the parameters passed to DeepDiff.
 
 .. _get_deep_distance_label:
 
diff --git a/docs/deephash_doc.rst b/docs/deephash_doc.rst
@@ -9,7 +9,7 @@ The main usage of DeepHash is to calculate the hash of otherwise unhashable obje
 For example you can use DeepHash to calculate the hash of a set or a dictionary!
 
 At the core of it, DeepHash is a deterministic serialization of your object into a string so it
-can be passed to a hash function. By default it uses SHA256. You have the option to pass any another hashing function to be used instead.
+can be passed to a hash function. By default it uses SHA256. You have the option to pass any other hashing function to be used instead.
 
 **Import**
     >>> from deepdiff import DeepHash
@@ -31,15 +31,15 @@ exclude_types: list, default = None
 
 
 exclude_paths: list, default = None
-    List of paths to exclude from the report. If only one item, you can path it as a string instead of a list containing only one path.
+    List of paths to exclude from the report. If only one item, you can pass it as a string instead of a list containing only one path.
 
 
 include_paths: list, default = None
-    List of the only paths to include in the report. If only one item, you can path it as a string.
+    List of the only paths to include in the report. If only one item, you can pass it as a string.
 
 
 exclude_regex_paths: list, default = None
-    List of string regex paths or compiled regex paths objects to exclude from the report. If only one item, you can path it as a string instead of a list containing only one regex path.
+    List of string regex paths or compiled regex paths objects to exclude from the report. If only one item, you can pass it as a string instead of a list containing only one regex path.
 
 
 exclude_obj_callback
diff --git a/docs/delta.rst b/docs/delta.rst
@@ -202,7 +202,7 @@ Delta Deserializer
 
 DeepDiff by default uses a restricted Python pickle function to deserialize the Delta dumps. Read more about :ref:`delta_dump_safety_label`.
 
-The user of Delta can decide to switch the serializer and deserializer to their custom ones. The serializer and deserializer parameters can be used exactly for that reason. The best way to come up with your own serializer and deserialier is to take a look at the `pickle_dump and pickle_load functions in the serializer module <https://github.com/seperman/deepdiff/serialization.py>`_
+The user of Delta can decide to switch the serializer and deserializer to their custom ones. The serializer and deserializer parameters can be used exactly for that reason. The best way to come up with your own serializer and deserializer is to take a look at the `pickle_dump and pickle_load functions in the serializer module <https://github.com/seperman/deepdiff/serialization.py>`_
 
 .. _delta_json_deserializer_label:
 
diff --git a/docs/diff_doc.rst b/docs/diff_doc.rst
@@ -131,7 +131,7 @@ ignore_uuid_types: Boolean, default = False
 
 ignore_string_case: Boolean, default = False
     :ref:`ignore_string_case_label`
-    Whether to be case-sensitive or not when comparing strings. By settings ignore_string_case=False, strings will be compared case-insensitively.
+    Whether to be case-sensitive or not when comparing strings. By setting ignore_string_case=True, strings will be compared case-insensitively.
 
 ignore_nan_inequality: Boolean, default = False
     :ref:`ignore_nan_inequality_label`
diff --git a/docs/exclude_paths.rst b/docs/exclude_paths.rst
@@ -21,7 +21,7 @@ Also for root keys you don't have to pass as "root['key']". You can instead just
 Example
     >>> t1 = {"for life": "vegan", "ingredients": ["no meat", "no eggs", "no dairy"]}
     >>> t2 = {"for life": "vegan", "ingredients": ["veggies", "tofu", "soy sauce"]}
-    >>> print (DeepDiff(t1, t2, exclude_paths="ingredients))  # one item pass it as a string
+    >>> print (DeepDiff(t1, t2, exclude_paths="ingredients"))  # one item pass it as a string
     {}
     >>> print (DeepDiff(t1, t2, exclude_paths=["ingredients", "ingredients2"]))  # multiple items pass as a list or a set.
     {}
diff --git a/docs/ignore_order.rst b/docs/ignore_order.rst
@@ -9,7 +9,7 @@ DeepDiff by default compares objects in the order that it iterates through them
 In other words if you have 2 lists, then the first item of the lists are compared to each other, then the 2nd items and so on.
 That makes DeepDiff be able to run in linear time.
 
-However, There are often times when you don't care about the order in which the items have appeared.
+However, there are often times when you don't care about the order in which the items have appeared.
 In such cases DeepDiff needs to do way more work in order to find the differences.
 
 There are a couple of parameters provided to you to have full control over.
diff --git a/docs/ignore_types_or_values.rst b/docs/ignore_types_or_values.rst
@@ -77,7 +77,7 @@ Example
     >>> DeepDiff(t1, t2, ignore_numeric_type_changes=True)
     {}
 
-Note that this parameter only works for comparing numbers with numbers. If you compare a number to a string value of the number, this parameter does not solver your problem:
+Note that this parameter only works for comparing numbers with numbers. If you compare a number to a string value of the number, this parameter does not solve your problem:
 
 Example:
     >>> t1 = Decimal('10.01')
@@ -382,7 +382,7 @@ include_obj_callback_strict: function, default = None
     ...         return True if isinstance(obj, int) and obj > 10 else False
     ...
     >>> t1 = {"x": 10, "y": "b", "z": "c"}
-    >>> t1 = {"x": 12, "y": "b", "z": "c"}
+    >>> t2 = {"x": 12, "y": "b", "z": "c"}
     >>> DeepDiff(t1, t2, include_obj_callback=include_obj_callback_strict)
     {'values_changed': {"root['x']": {'new_value': 12, 'old_value': 10}}}
     >>> DeepDiff(t1, t2, include_obj_callback_strict=include_obj_callback_strict)
diff --git a/docs/index.rst b/docs/index.rst
@@ -15,7 +15,7 @@ The DeepDiff library includes the following modules:
 
 - **DeepDiff** For Deep Difference of 2 objects. :doc:`/diff`
 
-    It return the deep Difference of python objects. It can also be used to take the distance between objects. :doc:`/deep_distance`
+    It returns the deep difference of python objects. It can also be used to take the distance between objects. :doc:`/deep_distance`
 
 - **DeepSearch** Search for objects within other objects. :doc:`/dsearch`
 
diff --git a/docs/numbers.rst b/docs/numbers.rst
@@ -28,7 +28,7 @@ If ignore_numeric_type_changes is set to True and you have left significant_digi
     For Decimals, Python's format rounds 2.5 to 2 and 3.5 to 4 (to the closest even number)
 
 .. note::
-    To override what significant digits mean and switch it to scientific notation, use number_format_notation="e
+    To override what significant digits mean and switch it to scientific notation, use number_format_notation="e"
     Behind the scene that switches DeepDiff to use "{:.Xe}".format(Your Number) where X=significant_digits.
 
 **Examples:**
diff --git a/docs/optimizations.rst b/docs/optimizations.rst
@@ -102,7 +102,7 @@ With a cache size of 500, we set the :ref:`cache_tuning_sample_size_label` to be
 
     {'PASSES COUNT': 3960, 'DIFF COUNT': 19469, 'DISTANCE CACHE HIT COUNT': 11847, 'MAX PASS LIMIT REACHED': False, 'MAX DIFF LIMIT REACHED': False, 'DURATION SEC': 2}
 
-As you can see in this case none of the stats have not changed compared to the previous stats.
+As you can see in this case none of the stats have changed compared to the previous stats.
 
 .. figure:: _static/benchmark_deeply_nested_a__3.8__ignore_order=True__cache_size=500__cache_tuning_sample_size=500__cutoff_intersection_for_pairs=1.png
    :alt: cache_size=500 cache_tuning_sample_size=500
@@ -221,7 +221,7 @@ And then we run it in Pypy3.6-7.3.0. It takes 12 seconds now but around 110Mb of
    Nested blob of text diffed in Pypy3.6-7.3.0
 
 .. note::
-    Note that if you diffing numbers, and have Numpy installed as recommended, cPython will have a better performance than Pypy. But if you are diffing blobs of mixed strings and some numbers, Pypy will have a better CPU performance and worse memory usage.
+    Note that if you are diffing numbers, and have Numpy installed as recommended, cPython will have a better performance than Pypy. But if you are diffing blobs of mixed strings and some numbers, Pypy will have a better CPU performance and worse memory usage.
 
 
 Cutoff Intersection For Pairs
diff --git a/docs/other.rst b/docs/other.rst
@@ -25,7 +25,7 @@ Comparing bytes that have non UTF-8 encoding:
         raise UnicodeDecodeError(
     UnicodeDecodeError: 'utf-8' codec can't decode byte 0xbc in position 0: Can not produce a hash for root: invalid start byte in 'p of flo...'. Please either pass ignore_encoding_errors=True or pass the encoding via encodings=['utf-8', '...'].
 
-Let's try to pass both 'utf-8' and 'latin-1' as encodings to be tries:
+Let's try to pass both 'utf-8' and 'latin-1' as encodings to be tried:
     >>> DeepDiff([b'foo'], [item], encodings=['utf-8', 'latin-1'], ignore_order=True)
     {'values_changed': {'root[0]': {'new_value': b'\xbc cup of flour', 'old_value': b'foo'}}}
 
diff --git a/docs/serialization.rst b/docs/serialization.rst
@@ -227,7 +227,7 @@ Delta Serialize To Flat Dictionaries
 
 Sometimes, it is desired to serialize a :ref:`delta_label` object to a list of flat dictionaries. For example, to store them in relation databases. In that case, you can use the Delta.to_flat_dicts to achieve the desired outcome.
 
-Since None is a valid value, we use a special hard-coded string to signify "unkown": 'unknown___'
+Since None is a valid value, we use a special hard-coded string to signify "unknown": 'unknown___'
 
 .. note::
     Many new keys are added to the flat dicts in DeepDiff 7.0.0
diff --git a/docs/troubleshoot.rst b/docs/troubleshoot.rst
@@ -16,7 +16,7 @@ If you are running into this issue, you are using an older version of DeepDiff.
 
 DeepDiff prefers to use Murmur3 for hashing. However you have to manually install murmur3 by running: `pip install mmh3`
 
-On MacOS Mojave some user experience difficulty when installing Murmur3.
+On MacOS Mojave, some users experience difficulty when installing Murmur3.
 
 The problem can be solved by running:
 
diff --git a/docs/view.rst b/docs/view.rst
@@ -328,7 +328,7 @@ The ``diff`` given will be the ``DeepDiff`` that ``pretty`` was called on; this
     Diff #3: Item root[1] removed from set.
 
 
-Text view vs. Tree view vs. vs. pretty() method
+Text view vs. Tree view vs. pretty() method
 -----------------------------------------------
 
 Views are just different format of results. Each comes with its own set of features. At the end of the day the user can choose the right format based on the use case.
