- 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.
Please check the ChangeLog file for the detailed information.
DeepDiff 6-7-1
- Support for subtracting delta objects when iterable_compare_func is used.
- Better handling of force adding a delta to an object.
- Fix for
Can't compare dicts with both single and double quotes in keys
- Updated docs for Inconsistent Behavior with math_epsilon and ignore_order = True
DeepDiff 6-7-0
- Delta can be subtracted from other objects now.
- verify_symmetry is deprecated. Use bidirectional instead.
- always_include_values flag in Delta can be enabled to include values in the delta for every change.
- Fix for Delta.add breaks with esoteric dict keys.
- You can load a delta from the list of flat dictionaries.
DeepDiff 6-6-1
- Fix for DeepDiff raises decimal exception when using significant digits
- Introducing group_by_sort_key
- Adding group_by 2D. For example
group_by=['last_name', 'zip_code']
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
https://zepworks.com/deepdiff/current/
👋 Hi there,
Thank you for using DeepDiff! As an engineer, I understand the frustration of wrestling with unruly data in pipelines. That's why I developed a new tool - Qluster to empower non-engineers to control and resolve data issues at scale autonomously and stop bugging the engineers! 🛠️
If you are going through this pain now, I would love to give you early access to Qluster and get your feedback.
Please take a look at the CHANGELOG file.
📣 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! 👯
- Please make your PR against the dev branch
- 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!
How to cite this library (APA style):
Dehpour, S. (2023). DeepDiff (Version 6.7.1) [Software]. Available from https://github.com/seperman/deepdiff.
How to cite this library (Chicago style):
Dehpour, Sep. 2023. DeepDiff (version 6.7.1).
Please take a look at the AUTHORS file.