explaingit

jayvdb/deepdiff

Analysis updated 2026-07-18 · repo last pushed 2019-08-01

PythonAudience · developerComplexity · 2/5DormantSetup · easy

TLDR

DeepDiff compares two Python objects of almost any type and reports exactly what changed, down to the precise nested path of each difference.

Mindmap

mindmap
  root((repo))
    What it does
      Compares two objects
      Finds nested changes
      Reports exact paths
    Tech stack
      Python library
    Use cases
      Automated testing
      Config auditing
      Debugging transforms
    Audience
      Python developers
      Test engineers
      Data auditors

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Assert that a function's output exactly matches expectations in automated tests.

USE CASE 2

Compare two versions of a config file and ignore fields you expect to differ.

USE CASE 3

Track exactly what changed between two versions of a user database object.

USE CASE 4

Search inside a deeply nested structure for where a specific value appears using DeepSearch.

What is it built with?

Python

How does it compare?

jayvdb/deepdiff0xallam/my-recipe0xhassaan/nn-from-scratch
Stars0
LanguagePythonPythonPython
Last pushed2019-08-012022-11-22
MaintenanceDormantDormant
Setup difficultyeasymoderatemoderate
Complexity2/52/54/5
Audiencedevelopergeneraldeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min
No license information is provided in the explanation.

In plain English

DeepDiff is a Python tool that compares two objects of almost any type, dictionaries, lists, strings, custom classes, and more, to tell you exactly what changed between them. Instead of just saying "these are different," it drills down into nested structures and shows you the precise path to every change, whether items were added, removed, modified, or their type changed entirely. Think of it like a very smart diff tool for your data. If you have two JSON-like objects and want to know what's different, you pass them both to DeepDiff and get back a detailed report. For example, you could compare two versions of a user database and see that root['user_42']['email'] changed from "[email protected]" to "[email protected]", or that root['items'][5] was deleted. It even handles tricky cases, like ignoring the order of items in a list or treating 1 and 1.0 as equivalent numbers. The library also includes two companion tools. DeepSearch lets you hunt for a value anywhere inside a complex nested structure, handy when you're looking for where a particular string or object appears. DeepHash creates a fingerprint of any Python object based on its actual contents, even for objects that normally can't be hashed (like dictionaries or lists), which is useful for detecting if two objects are truly identical deep down. Developers use DeepDiff most often in automated testing. Instead of manually checking that a function's output matches expectations, you can assert that DeepDiff(expected, result) returns an empty result, meaning no differences were found. It's also useful whenever you need to track changes in data, auditing, debugging complex transformations, or validating that two versions of a config file are equivalent except for specific fields you're excluding.

Copy-paste prompts

Prompt 1
Show me how to use DeepDiff to compare two nested dictionaries and list every change.
Prompt 2
Write a test that uses DeepDiff to assert two JSON objects are equivalent, ignoring list order.
Prompt 3
Explain how DeepHash lets me fingerprint an unhashable object like a dictionary or list.
Prompt 4
How do I use DeepSearch to find where a specific string appears inside a complex nested object?
Prompt 5
Help me use DeepDiff to audit differences between two versions of a config file, excluding certain fields.

Frequently asked questions

What is deepdiff?

DeepDiff compares two Python objects of almost any type and reports exactly what changed, down to the precise nested path of each difference.

What language is deepdiff written in?

Mainly Python. The stack also includes Python.

Is deepdiff actively maintained?

Dormant — no commits in 2+ years (last push 2019-08-01).

What license does deepdiff use?

No license information is provided in the explanation.

How hard is deepdiff to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is deepdiff for?

Mainly developer.

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