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Deep Difference and Search of any Python object/data. Recreate objects by adding adding deltas to each other.

Project description

DeepDiff v 7.0.1

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  • 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 3.8+ and PyPy3.

What is new?

Please check the ChangeLog file for the detailed information.

DeepDiff 7-0-1

  • Fixes the translation between Difflib opcodes and Delta flat rows.

DeepDiff 7-0-0

  • DeepDiff 7 comes with an improved delta object. Delta to flat dictionaries have undergone a major change. We have also introduced Delta serialize to flat rows.
  • Subtracting delta objects have dramatically improved at the cost of holding more metadata about the original objects.
  • When verbose=2, and the "path" of an item has changed in a report between t1 and t2, we include it as new_path.
  • path(use_t2=True) returns the correct path to t2 in any reported change in the tree view
  • Python 3.7 support is dropped and Python 3.12 is officially supported.

DeepDiff 6-7-1

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


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:


A message from Sep, the creator of DeepDiff

👋 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.


:mega: 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! :dancers:


  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!


Please take a look at the AUTHORS file.

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