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Based on our record, NumPy seems to be a lot more popular than pngcrush. While we know about 107 links to NumPy, we've tracked only 3 mentions of pngcrush. 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.
Did you compare to PNG crush and optipng? Those are what I used to use because they're easily installable Linux/brew packages. Source: about 1 year ago
My god running pngcrush on the 2x and 3x files takes ages. I run the thing overnight because it takes hours. Source: over 1 year ago
I've always just used this (it's more old school but def solid): https://pmt.sourceforge.io/pngcrush/. - Source: Hacker News / almost 3 years ago
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 2 months ago
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 2 months ago
Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 7 months ago
A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
ImageOptim - Faster web pages and apps.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
TinyPNG - Make your website faster and save bandwidth. TinyPNG optimizes your PNG images by 50-80% while preserving full transparency!
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
pngquant - command-line utility and library for lossy compression of PNG images
OpenCV - OpenCV is the world's biggest computer vision library