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Glasp VS NumPy

Compare Glasp VS NumPy and see what are their differences

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Glasp logo Glasp

Social web highlighter

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Glasp Landing page
    Landing page //
    2022-09-14

Highlight the web and share the gist with peers. Learn from like-minded people. Glasp is an easier and faster way to highlight text and leave notes on the web. With one click, the content youโ€™ve collected appears across all your devices. ๐Ÿ“š

Glasp beautifully organizes your collection of highlights, so that you can easily come back to what truly matters to you anytime. By following like-minded people, you will discover useful content that expands your knowledge and thoughts. Collective learning is how humans got smarter across generations.ใ€€

โ€”โ€”

Key Features: โœ… Highlight text on the web โœ… Take notes on saved content and highlights โœ… Add tags to your highlights โœ… Discover useful content from like-minded people

โ€”โ€”

How to Use Glasp: 1. Click "Add to Chrome". 2. Log in to Glasp from the extension menu. 3. Select text and click your favorite color from a pop-up color tip. 4. You can see your highlights and notes on your profile page and/or Glasp home feed. 5. Add tags or leave comments on your saved content 6. Developing your collection of ideas and thoughts will help you connect the dots with like-minded people ;)

โ€”โ€” Benefits of Using Glasp: + Retain more information and easy to look back ๐Ÿ“š + Extract only important parts and use them for the future citation ๐Ÿ”— + Discover useful information from like-minded people ๐Ÿ” + Share your highlights & notes with friends and peers with one click ๐Ÿš€ + Leave your digital legacy for future generations (contribute to human history) ๐Ÿ™Œ

  • NumPy Landing page
    Landing page //
    2023-05-13

Glasp

Website
glasp.co
$ Details
freemium $15.0 / Monthly
Platforms
Web Windows Google Chrome Safari Edge Opera Vivaldi
Release Date
2021 December
Startup details
Country
United States
State
California
Founder(s)
Kazuki Nakayashiki, Kei Watanabe
Employees
1 - 9

Glasp features and specs

  • Highlight web articles
  • Kindle's notes & highlights import
  • Highlight YouTube transcripts
  • Highlight PDFs
  • Export highlights & notes
  • Find top highlights of articles
  • See other people's highlights & notes
  • Showcase reading list

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 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.

Glasp videos

Glasp - Tutorial Video

More videos:

  • Tutorial - Glasp User Profile Page
  • Tutorial - How to use Glasp browser extension (Chrome Extension)
  • Tutorial - Create and take a note on the Atomic Note
  • Tutorial - Highlight Web Pages with Glasp

NumPy videos

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 Glasp and NumPy)
Productivity
100 100%
0% 0
Data Science And Machine Learning
Bookmark Manager
100 100%
0% 0
Data Science Tools
0 0%
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 Glasp and NumPy

Glasp Reviews

Best AI YouTube Summarizers in 2025 (Free & Paid)
Glasp is a user-friendly tool for straightforward summaries of YouTube videos. It uses typical natural language processing algorithms to ensure that the summaries are simple and coherent. The simplicity of its interface makes it accessible to users of all ages, from tech novices to seasoned professionals. Users can also copy summaries, as in Scripsy, allowing for easy...
Source: www.scripsy.ai

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.
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 seems to be a lot more popular than Glasp. While we know about 122 links to NumPy, we've tracked only 9 mentions of Glasp. 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.

Glasp mentions (9)

  • Improve your learning with Glasp: A Comprehensive Guide.
    To sign up, visit the Glasp website and click the Sign-up button in the top right corner, or log in if you already have an account. - Source: dev.to / over 2 years ago
  • Unlock Your Full Learning Potential with Glasp: The Ultimate Study Tool
    You can install the Glasp browser extension to your web browser from its website or as an app on Play Store. - Source: dev.to / over 2 years ago
  • Daily Thread / June 29
    For no reason at all, if you wanted to read the transcript of their dumb podcast without giving them views or listens, you can use the Glasp extension on chrome or safari to give you a summary instead of sitting through the video. Source: about 3 years ago
  • How to improve my workflow? Need help.
    Also glasp.co and https://roamresearch.com/ look interesting. I haven't tried them yet. Source: about 3 years ago
  • Whatโ€™s a 100 dollar item you use every day that really boost productivity?
    These ones are free (since im a cheap person) but I use: - This for youtube summaries. Source: about 3 years ago
View more

NumPy mentions (122)

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What are some alternatives?

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

AdCreative.ai - Give your business an unfair advantage with creatives / banners generated by highly trained Artificial Intelligence.

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

Raindrop.io - All your articles, photos, video & content from web & apps in one place.

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

My Mind - All your notes, bookmarks, inspiration, articles, and images in one single, private place, enhanced with artificial intelligence.

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