Software Alternatives, Accelerators & Startups
Register | Login

Keypirinha VS NumPy

Compare Keypirinha VS NumPy and see what are their differences

Monitask
Employee Monitoring Software with Screenshots, Internet, Activity and Time Tracking featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Keypirinha logo Keypirinha

A lightning fast and flexible keystroke launcher for Windows. No installation required (portable).

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Keypirinha Landing page
    Landing page //
    2018-09-29
  • NumPy Landing page
    Landing page //
    2023-05-13

Keypirinha features and specs

  • Speed
    Keypirinha is highly optimized for performance and speed, making it exceptionally fast in executing commands and launching applications.
  • Lightweight
    The software is very lightweight, consuming minimal system resources, which makes it suitable for machines with limited capabilities.
  • Customizability
    Keypirinha is highly customizable, allowing users to configure its behavior extensively through configuration files and plugins.
  • Plugin System
    It has a robust plugin system that allows for extending its functionality by adding new plugins. This makes it highly versatile.
  • No Installation Required
    Keypirinha does not require installation, and can be run as a portable application, which makes it easy to use across different systems.

Possible disadvantages of Keypirinha

  • Learning Curve
    Due to its extensive customization options and powerful features, new users may find Keypirinha's learning curve to be steep.
  • Limited Official Documentation
    The official documentation can sometimes be sparse, making it harder for users to find detailed guidance on advanced configurations.
  • Windows-only
    Keypirinha is only available for Windows, which limits its use for those who need cross-platform support.
  • No Graphical Interface for Settings
    Configuration is done through text files, which can be cumbersome for users who prefer a graphical user interface for settings management.
  • Dependency on Plugins
    Some functionalities heavily depend on community-contributed plugins, which may vary in quality and maintenance status.

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 Keypirinha

Overall verdict

  • Yes, Keypirinha is considered a good application by many users.

Why this product is good

  • Keypirinha is praised for its speed and efficiency as a launcher. It is lightweight, requires minimal system resources, and features a highly customizable interface. Its ability to quickly search and launch applications, documents, and URLs makes it a valuable tool for productivity enthusiasts. Additionally, its plugin support allows users to extend its functionality according to their specific needs.

Recommended for

  • Users who prioritize speed and efficiency in a launcher.
  • Individuals who prefer highly customizable software.
  • Tech-savvy users who are comfortable with configuring plugins for extended functionality.
  • People looking for a lightweight tool that has minimal impact on system performance.

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.

Keypirinha videos

+ Add

Keypirinha Tutorial - To ease your Life

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 Keypirinha and NumPy)

Keypirinha

NumPy

Productivity
100 100%
Productivity
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
App Launcher
100 100%
App Launcher
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Keypirinha and NumPy. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Keypirinha Reviews

7 Best Alfred Alternatives To Maximize Your Productivity
Keypirinha is a launcher for Windows that helps users find and launch applications, evaluate mathematical expressions, and complete other technical tasks quickly.
Source: blaze.today
Looking For Spotlight for Windows 10? Here Are Five Alternatives
The problem with KeyPirinha which bugs me the most is that you cannot select the search results with your mouse. To enable this, you have to make tons of changes in the configuration file. The app almost recognizes Windows shortcuts except for the ones in Control Panel.
Source: techwiser.com

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

Based on our record, NumPy should be more popular than Keypirinha. It has been mentiond 119 times since March 2021. 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.

Keypirinha mentions (34)

  • An Alfred workflow to open GCP services and browse resources within
    This is actually amazing. I wish there was something similar that for windows's keypirinha[1]. Specifically would be interesting to have something like that for k8s resources. 1. https://keypirinha.com/. - Source: Hacker News / 9 days ago
  • Ask HN: What tools do you recommend for working on Windows?
    I use Git bash for Windows. It brings a lot of the linux shell tools/scripting experience to Windows. There is a portable "thumbdrive edition."[1] Look for the portable versions of of other apps. PowerShell[2] is the built-in scripting language for Windows (better than BATCH scripts). I pop into gVim for quick text manipulation tasks. https://sumatrapdfreader.org is the best PDF reader. I recommend a launcher like... - Source: Hacker News / 11 months ago
  • Open-Shell: A collection of utilities bringing back classic features to Windows
    Keypirinha (a launcher) works well with Everything. Both are free. The former hasn’t been updated for a few years, but it still works for launching applications, performing quick calculations, currency conversion, etc. [1]: https://keypirinha.com/. - Source: Hacker News / about 1 year ago
  • Fluent Search
    Https://keypirinha.com/ there is no update for a long time but this one works perfectly for me. - Source: Hacker News / over 1 year ago
  • 'Screen Apnea'
    Keypirinha for me https://keypirinha.com It's been a while since it was updated last, but since it works, does that matter? - Source: Hacker News / almost 2 years ago
View more

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

What are some alternatives?

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

Alfred - Alfred is an award-winning app for macOS which boosts your efficiency with hotkeys, keywords, text expansion and more. Search your Mac and the web, and be more productive with custom actions to control your Mac.

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

Listary - Listary is a revolutionary search utility for Windows

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

Wox - An effective launcher for windows. A full-featured launcher, access programs and web contents as you type. Be more productive ever since. Wox is free for use and open-sourced at Github, Try it now! Download .

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

Loading...