Tools for diffing and merging of Jupyter notebooks.

Overview

Installation | Documentation | Contributing | Development Install | Testing | License | Getting help

nbdime Jupyter Notebook Diff and Merge tools

Build Status codecov.io Documentation Status Google Group

nbdime provides tools for diffing and merging of Jupyter Notebooks.

  • nbdiff compare notebooks in a terminal-friendly way
  • nbmerge three-way merge of notebooks with automatic conflict resolution
  • nbdiff-web shows you a rich rendered diff of notebooks
  • nbmerge-web gives you a web-based three-way merge tool for notebooks
  • nbshow present a single notebook in a terminal-friendly way

Diffing notebooks in the terminal:

terminal-diff

Merging notebooks in a browser:

web-merge

Installation

Install nbdime with pip:

pip install nbdime

See the installation docs for more installation details and development installation instructions.

Documentation

See the latest documentation at https://nbdime.readthedocs.io.

See also description and discussion in the Jupyter Enhancement Proposal.

Contributing

If you would like to contribute to the project, please read our contributor documentation and the CONTRIBUTING.md.

Development Install

To install a development version of nbdime, you will need npm installed and available on your PATH while installing.

For a development install, enter on the command line:

pip install -e git+https://github.com/jupyter/nbdime#egg=nbdime

See installation documentation for additional detail, particularly related to performing a dev install for working on the browser script code.

Testing

Install the test requirements:

pip install nbdime[test]

To run Python tests locally, enter on the command line: pytest

To run Javascript tests locally, enter: npm test

Install the codecov browser extension to view test coverage in the source browser on github.

See testing documentation for additional detail.

License

We use a shared copyright model that enables all contributors to maintain the copyright on their contributions.

All code is licensed under the terms of the revised BSD license.

Getting help

We encourage you to ask questions on the mailing list.

Resources

Owner
Project Jupyter
Interactive Computing
Project Jupyter
Project to deploy a machine learning model based on Titanic dataset from Kaggle

kaggle_titanic_deploy Project to deploy a machine learning model based on Titanic dataset from Kaggle In this project we used the Titanic dataset from

Vivian Yamassaki 8 May 23, 2022
Repository for DCA0305, an undergraduate course about Machine Learning Workflows and Pipelines

Federal University of Rio Grande do Norte Technology Center Department of Computer Engineering and Automation Machine Learning Based Systems Design Re

Ivanovitch Silva 81 Oct 18, 2022
Projeto: Machine Learning: Linguagens de Programacao 2004-2001

Projeto: Machine Learning: Linguagens de Programacao 2004-2001 Projeto de Data Science e Machine Learning de análise de linguagens de programação de 2

Victor Hugo Negrisoli 0 Jun 29, 2021
Stacked Generalization (Ensemble Learning)

Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea

Ikki Tanaka 192 Dec 23, 2022
Python library for multilinear algebra and tensor factorizations

scikit-tensor is a Python module for multilinear algebra and tensor factorizations

Maximilian Nickel 394 Dec 09, 2022
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

alkaline-ml 1.3k Dec 22, 2022
MIT-Machine Learning with Python–From Linear Models to Deep Learning

MIT-Machine Learning with Python–From Linear Models to Deep Learning | One of the 5 courses in MIT MicroMasters in Statistics & Data Science Welcome t

2 Aug 23, 2022
Transpile trained scikit-learn estimators to C, Java, JavaScript and others.

sklearn-porter Transpile trained scikit-learn estimators to C, Java, JavaScript and others. It's recommended for limited embedded systems and critical

Darius Morawiec 1.2k Jan 05, 2023
Tools for diffing and merging of Jupyter notebooks.

nbdime provides tools for diffing and merging of Jupyter Notebooks.

Project Jupyter 2.3k Jan 03, 2023
pywFM is a Python wrapper for Steffen Rendle's factorization machines library libFM

pywFM pywFM is a Python wrapper for Steffen Rendle's libFM. libFM is a Factorization Machine library: Factorization machines (FM) are a generic approa

João Ferreira Loff 251 Sep 23, 2022
Data Version Control or DVC is an open-source tool for data science and machine learning projects

Continuous Machine Learning project integration with DVC Data Version Control or DVC is an open-source tool for data science and machine learning proj

Azaria Gebremichael 2 Jul 29, 2021
Test symmetries with sklearn decision tree models

Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro

Rupert Tombs 2 Jul 19, 2022
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

152 Jan 02, 2023
ELI5 is a Python package which helps to debug machine learning classifiers and explain their predictions

A library for debugging/inspecting machine learning classifiers and explaining their predictions

154 Dec 17, 2022
Python based GBDT implementation

Py-boost: a research tool for exploring GBDTs Modern gradient boosting toolkits are very complex and are written in low-level programming languages. A

Sberbank AI Lab 20 Sep 21, 2022
Houseprices - Predict sales prices and practice feature engineering, RFs, and gradient boosting

House Prices - Advanced Regression Techniques Predicting House Prices with Machine Learning This project is build to enhance my knowledge about machin

1 Jan 01, 2022
Scikit learn library models to account for data and concept drift.

liquid_scikit_learn Scikit learn library models to account for data and concept drift. This python library focuses on solving data drift and concept d

7 Nov 18, 2021
This is the code repository for Interpretable Machine Learning with Python, published by Packt.

Interpretable Machine Learning with Python, published by Packt

Packt 299 Jan 02, 2023
A collection of neat and practical data science and machine learning projects

Data Science A collection of neat and practical data science and machine learning projects Explore the docs » Report Bug · Request Feature Table of Co

Will Fong 2 Dec 10, 2021
A modular active learning framework for Python

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

modAL 1.9k Dec 31, 2022