DeepDiff v 6.3.1

Modules

• DeepDiff: Deep Difference of dictionaries, iterables, strings, and ANY other object.
• DeepSearch: Search for objects within other objects.
• DeepHash: Hash any object based on their content.
• Delta: Store the difference of objects and apply them to other objects.
• Extract: Extract an item from a nested Python object using its path.
• commandline: Use DeepDiff from commandline.

Tested on Python 3.7+ and PyPy3.

• Documentation

What is new?

Please check the ChangeLog file for the detailed information.

DeepDiff 6-3-1

This release includes many bug fixes.

• Bugfix deephash for paths by maggelus
• Bugfix deephash compiled regex maggelus
• Fix tests dependent on toml by martin-kokos
• Bugfix for include_paths for nested dictionaries by kor4ik
• Use tomli and tomli-w for dealing with tomli files by martin-kokos
• Bugfix for datetime.date by Alex Sauer-Budge

DeepDiff 6-3-0

• PrefixOrSuffixOperator: This operator will skip strings that are suffix or prefix of each other.
• include_obj_callback and include_obj_callback_strict are added by Håvard Thom.
• Fixed a corner case where numpy's np.float32 nans are not ignored when using ignore_nan_equality by Noam Gottlieb
• orjson becomes optional again.
• Fix for ignore_type_in_groups with numeric values so it does not report number changes when the number types are different.

Installation

Install from PyPi:

pip install deepdiff

If you want to use DeepDiff from commandline:

pip install "deepdiff[cli]"

If you want to improve the performance of DeepDiff with certain functionalities such as improved json serialization:

pip install "deepdiff[optimize]"

Install optional packages:

• yaml
• tomli (python 3.10 and older) and tomli-w for writing
• clevercsv for more rubust CSV parsing
• orjson for speed and memory optimized parsing
• pydantic

Documentation

https://zepworks.com/deepdiff/current/

ChangeLog

Please take a look at the CHANGELOG file.

Survey

📣 Please fill out our fast 5-question survey so that we can learn how & why you use DeepDiff, and what improvements we should make. Thank you! 👯

Contribute

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.

Or to see a more user friendly version, please run: pytest --cov=deepdiff --cov-report term-missing --runslow.

Thank you!

Citing

How to cite this library (APA style):

Dehpour, S. (2023). DeepDiff (Version 6.3.1) [Software]. Available from https://github.com/seperman/deepdiff.

How to cite this library (Chicago style):

Dehpour, Sep. 2023. DeepDiff (version 6.3.1).

Authors

Please take a look at the AUTHORS file.