Python Diff Checker — Compare Python Code Online
Paste two Python files and instantly see every added function, removed class, and changed logic. Syntax highlighting included. No account. No limits.
Paste text in both panels above to compare
Or to see how it works
Compare Python file versions
Paste two versions of a .py file to see exactly what changed. Great for reviewing refactors, auditing dependency upgrades, tracing regressions, or spotting what changed between two script versions before pushing to production.
Review Python pull requests
Copy the old and new versions of a function, class, or module from your editor or GitHub. The diff highlights added methods, removed logic, and changed expressions with character-level precision — faster than scanning a full file diff manually.
Python syntax highlighting
Unlike plain text diff tools, DiffCheck applies Python syntax coloring on top of the diff highlighting. Keywords, strings, decorators, and function names are color-coded — making it much easier to parse complex Python diffs at a glance, especially in heavily decorated or type-annotated code.
Indentation-aware diffing
Python's indentation is semantically meaningful — a wrong indent is a bug. DiffCheck shows indentation changes as modified lines, so accidental dedents or reindented blocks are immediately visible in the diff output, not hidden behind whitespace normalization.
Privacy-first — runs in your browser
Python scripts often contain business logic, ML model code, data pipelines, and API integrations. DiffCheck never sends your code to any server. All comparison runs locally in JavaScript — safe for internal codebases, proprietary algorithms, and sensitive scripts.
Compare data science & ML code
Paste two versions of a training script, data pipeline, or Jupyter cell to see exactly how your model or preprocessing changed. Character-level diffs make it easy to spot a changed hyperparameter, a swapped loss function, or a modified feature engineering step.
How to compare Python code online
- 1
Paste your original Python
Put the first version of your Python file or function in the left editor — this is your baseline. Works with any Python: scripts, classes, decorators, async code, type-annotated modules.
- 2
Paste your modified Python
Put the updated version in the right editor. This is what you're comparing against — a refactored class, an updated function signature, or a patched script.
- 3
Read the diff
Green lines were added; red lines were removed. Within changed lines, the exact characters that differ are highlighted more intensely. Python is selected by default for syntax coloring.
- 4
Switch views as needed
Use side-by-side to review both Python files in parallel columns, or switch to inline view for a compact unified diff. The statistics bar shows total lines added, removed, and unchanged.
Frequently asked questions
What is a Python diff checker?
A Python diff checker compares two Python files or code snippets and highlights the differences — added functions, removed classes, changed logic, and modified docstrings. It's essential for code review, debugging refactors, and comparing script versions.
Is this Python diff tool free?
Yes, completely free with no rate limits and no signup. All Python comparison runs in your browser — your code never leaves your device.
Does it handle Python indentation correctly?
Yes. The diff is line-by-line, so indentation changes are shown as modified lines. Since indentation is semantically significant in Python, even whitespace-only changes are highlighted — which is important for spotting accidental dedents or reindented blocks.
Is my Python code safe to paste here?
Yes. All diff computation runs locally in your browser using JavaScript. Your Python code is never sent to any server, never stored, and never logged. Safe to use with proprietary scripts, ML models, data pipelines, or any sensitive Python code.
Can I compare Jupyter notebook code?
Yes — paste the Python code from individual notebook cells. For full notebook comparison, copy the source from each cell and paste both versions. Character-level highlighting shows exactly which lines and expressions changed between notebook versions.
Does it work for other Python-adjacent files like requirements.txt?
Absolutely. Switch the language selector to Plain Text to compare requirements.txt, setup.cfg, pyproject.toml, or any other Python project file. The diff highlighting still works perfectly — just without Python-specific syntax coloring.