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Ninja Build VS iPython

Compare Ninja Build VS iPython and see what are their differences

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Ninja Build logo Ninja Build

Ninja is a small build system with a focus on speed.

iPython logo iPython

iPython provides a rich toolkit to help you make the most out of using Python interactively.
  • Ninja Build Landing page
    Landing page //
    2021-09-14
  • iPython Landing page
    Landing page //
    2021-10-07

Ninja Build features and specs

  • Speed
    Ninja is designed for high performance, making it one of the fastest build systems available. It minimizes the time spent on tasks such as parsing, dependency resolution, and build command execution.
  • Simplicity
    Ninjaโ€™s configuration syntax is straightforward and concise, reducing the complexity involved in setting up builds and allowing for a clear overview of build rules.
  • Parallelism
    Ninja excels at handling parallel builds, leveraging multiple cores effectively to decrease overall build times.
  • Incremental Builds
    Ninja efficiently handles incremental builds by only recompiling what is necessary, which significantly speeds up iterative development processes.
  • Integration
    Ninja is often used as the backend for more complex build systems (e.g., CMake), making it a versatile tool within a larger toolchain.

Possible disadvantages of Ninja Build

  • Limited Features
    Ninja is deliberately minimalist, lacking many of the features found in other build systems, such as built-in support for complex dependency management and custom build steps.
  • Learning Curve
    While Ninja itself has a simple syntax, the learning curve can be steep for those unfamiliar with how build systems work or for those coming from more feature-rich environments.
  • Dependency on Generators
    Ninja often requires an external generator (like CMake) to create its build files, which can add to the setup complexity and introduce dependencies on other tools.
  • Limited Scripting Capabilities
    Unlike some build systems that offer extensive scripting support (e.g., Python in SCons), Ninja's functionality is largely limited to what its syntax and predefined rules allow.
  • Less Flexibility
    Due to its minimalist nature, Ninja may not be as flexible as other build systems, potentially limiting its use in more complex or unusual build scenarios.

iPython features and specs

  • Interactive Computing
    IPython provides a rich toolkit to help you make the most out of using Python interactively. This includes powerful introspection, rich media display, session logging, and more.
  • Ease of Use
    IPython includes features like syntax highlighting, tab completion, and easy access to the help system, which make writing and understanding code easier for users.
  • Rich Display System
    It supports rich media like images, videos, LaTeX, and HTML, making it very useful for data visualization and educational purposes.
  • Extensibility
    IPython is highly extensible and can be customized with a range of plugins, extensions, and different backends to suit various needs.
  • Enhanced Debugging
    It features enhanced debugging capabilities, including an improved traceback support and better handling of exceptions.

Possible disadvantages of iPython

  • Learning Curve
    For beginners, the extensive feature set of IPython may be overwhelming and have a steep learning curve.
  • Resource Intensive
    IPython, particularly Jupyter notebooks, can be resource-intensive, leading to slow performance on large datasets or complex computations.
  • Dependency Management
    Managing dependencies can be challenging, especially when using multiple packages in the same environment, which can lead to conflicts.
  • Limited IDE Features
    While IPython has many interactive features, it lacks some of the more advanced IDE features such as comprehensive code refactoring tools and integrated version control.
  • Exporting and Sharing
    Although you can export notebooks in various formats, sharing them in a way that preserves full interactivity can be complex compared to traditional scripts.

Analysis of Ninja Build

Overall verdict

  • Ninja Build is considered a strong choice for users seeking a fast, reliable, and efficient build system. Its simplicity and focus on performance make it appealing to developers working on projects where build speed is critical.

Why this product is good

  • Ninja Build is a high-performance build system designed to handle complex build processes efficiently. It is known for its minimalistic yet powerful design, which allows for faster build times compared to traditional build systems like Make. Its approach to dependency tracking and parallelism is optimized for modern build environments, making it suitable for large codebases and incremental builds.

Recommended for

    Ninja Build is recommended for developers working on large-scale projects with complex build processes, particularly in environments where build speed and efficiency are prioritized. It is especially beneficial for projects that are continuously integrated or require frequent incremental builds.

Analysis of iPython

Overall verdict

  • Yes, iPython is highly regarded for its flexibility, powerful features, and ability to enhance productivity in data analysis and scientific computing. It serves as an integral tool for many professionals in technical fields.

Why this product is good

  • iPython, which forms the backbone of the Jupyter ecosystem, is favored for its interactive capabilities, integration with various data science libraries, and support for visualizations. It allows seamless execution of code in a web-based environment, making it highly effective for experiments, rapid prototyping, and sharing insights.

Recommended for

  • Data Scientists
  • Researchers
  • Educators
  • Software Developers
  • Anyone interested in interactive and exploratory computing

Ninja Build videos

FORTNITE STW: HERE IS THE BEST NINJA BUILD (AFTER MONTHS OF TESTING)

iPython videos

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Category Popularity

0-100% (relative to Ninja Build and iPython)
Front End Package Manager
Text Editors
0 0%
100% 100
JS Build Tools
100 100%
0% 0
Python IDE
0 0%
100% 100

User comments

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Social recommendations and mentions

Ninja Build might be a bit more popular than iPython. We know about 23 links to it since March 2021 and only 20 links to iPython. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Ninja Build mentions (23)

  • CMake Made Simple: A Reusable Template for Your First C++ Project
    On Windows, download the binaries from the cmake and Ninja websites. After that, add the executables to your PATH. - Source: dev.to / 11 months ago
  • TypeScript's Successor is Waiting, and You'll Never Want to Turn Back
    Under the hood, Rescript uses a build system called Ninja. Ninja is similar to Make, but cross-platform and more minimal/performant. - Source: dev.to / over 2 years ago
  • Using Make โ€“ writing less Makefile
    Ninja was super easy to pick up even after using make for some time (10+ years). GN is just a ninja generator that is optional. https://gn.googlesource.com/gn/+/main/docs/quick_start.md https://ninja-build.org/. - Source: Hacker News / over 2 years ago
  • Ask HN: What outdated tech are you still using and are perfectly happy with?
    Really? I thought most new projects were switching to ninja[^1] and have never used it. [^1]: https://ninja-build.org/. - Source: Hacker News / over 2 years ago
  • What was used to build C++ programs before Cmake?
    Ninja showed real promise for a while, but then CMake grew up and people stopped seeing a reason to leave it behind. Source: almost 3 years ago
View more

iPython mentions (20)

  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
  • Modern Python REPL in Emacs using VTerm
    As alluded to in Poetry2Nix Development Flake with Matplotlib GTK Support, Iโ€™m currently in the process of getting my โ€œnewโ€ python workflow up to speed. My second problem, after dependency and environment management, was that fancy REPLs like ipython or ptpython donโ€™t jazz well with the standard comint based inferior python repl that comes with python-mode. One can basically only run ipython with the... - Source: dev.to / about 2 years ago
  • Wanting to learn how to code, but completely lost.
    Third, if possible use a command line interpreter to test things out. I recommend ipython for this purpose. You can use your browser's developer console this way if you are learning Javascript. Source: about 3 years ago
  • IJulia: The Julia Notebook
    IJulia is an interactive notebook environment powered by the Julia programming language. Its backend is integrated with that of the Jupyter environment. The interface is web-based, similar to the iPython notebook. It is open-source and cross-platform. - Source: dev.to / over 3 years ago
  • How to "end" a loop in the REPL?
    Also, take a look at installing iPthon to give you a much richer shell environment. This underpins Jupyter Notebooks, so is well known, proven and trusted. Source: over 3 years ago
View more

What are some alternatives?

When comparing Ninja Build and iPython, you can also consider the following products

GNU Make - GNU Make is a tool which controls the generation of executables and other non-source files of a program from the program's source files.

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

SCons - SCons is an Open Source software construction toolโ€”that is, a next-generation build tool.

PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...

npm - npm is a package manager for Node.

Spyder - The Scientific Python Development Environment