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yabai VS NumPy

Compare yabai VS NumPy and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

yabai logo yabai

A tiling window manager for macOS based on binary space partitioning

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • yabai Landing page
    Landing page //
    2023-07-26
  • NumPy Landing page
    Landing page //
    2023-05-13

yabai features and specs

  • Efficient Window Management
    Yabai provides advanced tiling window management for macOS, greatly increasing productivity by allowing users to manage windows through keyboard shortcuts and layouts, minimizing the need for mouse interactions.
  • Highly Customizable
    The software offers extensive configuration options, enabling users to personalize their window management experience according to their specific workflow and preferences.
  • Open Source
    Being open source, Yabai is free to use and modify, allowing the community to contribute to its development and enhancement. This fosters a collaborative environment for improving the software.
  • Supports Scripting
    Yabai supports scripting through AppleScript or shell commands, enabling users to automate complex workflows and integrate Yabai with other tools and applications seamlessly.
  • Lightweight
    Yabai is designed to be a lightweight window manager, which means it consumes minimal system resources, ensuring that your Mac continues to run smoothly even with numerous active windows.

Possible disadvantages of yabai

  • Steep Learning Curve
    For beginners, the configuration and use of Yabai can be daunting, requiring a significant amount of time and effort to fully understand and utilize its capabilities effectively.
  • Requires SIP Disablement
    To utilize some of Yabai's more advanced features, users need to partially disable System Integrity Protection (SIP), which can reduce the overall security of the macOS system.
  • Potential Compatibility Issues
    As macOS updates and changes, compatibility issues may arise, potentially breaking functionality. Users may need to wait for updates from the developer community to resolve these issues.
  • Limited Official Support
    As an open-source project, Yabai does not come with official support channels. Users must rely on community forums and documentation, which may not always provide immediate or comprehensive assistance.
  • Complex Configurations
    Setting up Yabai to fit specific needs can be complex and time-consuming, especially for users who are not familiar with scripting or advanced configuration files.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Analysis of yabai

Overall verdict

  • Yabai is highly regarded among users who seek advanced customization and control over their macOS window management. However, it may have a steep learning curve for those unfamiliar with tiling window managers or command-line tools.

Why this product is good

  • Yabai is a popular tiling window manager for macOS, designed to streamline and enhance window management through robust keyboard shortcuts and automation features. It is particularly appreciated for its flexibility and efficiency in organizing a large number of open applications, contributing to a more productive workflow.

Recommended for

  • Developers who need efficient multitasking tools.
  • Users comfortable with the command line who enjoy customizing their environment.
  • Power users looking to optimize their macOS user experience.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

yabai videos

+ Add

Yabai Demonstration

More videos:

  • Demo - yabai macOS Tiling Window Manager Demonstration

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to yabai and NumPy)

yabai

NumPy

Window Manager
100 100%
Window Manager
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Mac Tools
100 100%
Mac Tools
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare yabai and NumPy

yabai Reviews

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NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

yabai might be a bit more popular than NumPy. We know about 138 links to it since March 2021 and only 122 links to NumPy. 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.

yabai mentions (138)

  • Supercharge your macOS workspace management with Aerospace - A guide for busy people
    Aerospace does not rely on the native spaces feature. Instead, it has the concept of virtual workspaces, all of which live in a single native macOS space. Switching between these virtual workspaces essentially means hiding all other windows and only keeping the window(s) assigned to the active workspace. This is genius, as it makes Aerospace incredibly flexible in managing windows between workspaces, without the... - Source: dev.to / 2 months ago
  • Jeff Geerling: The Framework 12 is dead. Apple killed it [video]
    Interesting. I used to daily drive for almost a year until a major macOS update broke it and I just didn't have it in me to diagnose the issue. I'll bookmark this for future adventures, thanks! - Source: Hacker News / 3 months ago
  • Show HN: Liquid Radius โ€“ Unifies macOS Tahoe's inconsistent window corners
    > Liquid Radius doesn't touch /System or modify the SSV I'm not doubting you, but by requiring users to disable SIP you are effectively opening their entire system to SSV attacks. 99% of "regular" users won't understand that tradeoff. Rounded corners are not worth disabling the operating system's major security protections, especially in today's crazy cyber environment. Yabai [0] is a good example of how... - Source: Hacker News / 3 months ago
  • From M1 MacBook to Arch Linux: A month-long experiment that became permanenent
    This. My 2013 MacBook Pro lasted just shy of 10 years no issues. My m3 max mbpro I only wish was the larger screen one and not the 13 inch one โ€ฆ oh well. But I suspect it will last me โ€” and be passed down as well โ€” 8-10 years as well. The trackpads are second to none. So are the speakers. The screen are pretty good. I wish mine got even brighter but the m4s do. The keyboard is finally awesome. The OS just works.... - Source: Hacker News / 12 months ago
  • I Used Arch, BTW: macOS, Day 1
    Aerospace is nice, but also consider checking out yabai [0] + sketchybar [1] for an i3/hyprland style tiling setup. More customizable (IMO) and perfectly suited for a terminal based workflow :~^) [0] https://github.com/koekeishiya/yabai. - Source: Hacker News / about 1 year ago
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NumPy mentions (122)

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What are some alternatives?

When comparing yabai and NumPy, you can also consider the following products

Rectangle - Window management app based on Spectacle, written in Swift.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Moom - Move your mouse over the green zoom button in any window, and Moom's mouse control overlay will appear (as seen in the above animation).

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

BTT Remote - A remote control for you Mac, using your iPhone or iPad

OpenCV - OpenCV is the world's biggest computer vision library

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