Software Alternatives & Reviews

Cython VS NumPy

Compare Cython VS NumPy and see what are their differences

Cython logo Cython

Cython is a language that makes writing C extensions for the Python language as easy as Python...

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Cython Landing page
    Landing page //
    2023-10-15
  • NumPy Landing page
    Landing page //
    2023-05-13

Cython

Categories
  • Website Builder
  • Website Design
  • Programming Language
  • CMS
Website cython.org
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NumPy

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Python Tools
  • Software Libraries
Website numpy.org
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Cython videos

Stefan Behnel - Get up to speed with Cython 3.0

More videos:

  • Review - Cython: A First Look
  • Review - Simmi Mourya - Scientific computing using Cython: Best of both Worlds!

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 Cython and NumPy)
Website Builder
100 100%
0% 0
Data Science And Machine Learning
Website Design
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 Cython and NumPy

Cython Reviews

We have no reviews of Cython yet.
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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.
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 Cython. It has been mentiond 107 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.

Cython mentions (46)

  • How to make a c++ python extension?
    The approach that I favour is to use Cython. The nice thing with this approach is that your code is still written as (almost) Python, but so long as you define all required types correctly it will automatically create the C extension for you. Early versions of Cython required using Cython specific typing (Python didn't have type hints when Cython was created), but it can now use Python's type hints. Source: 10 months ago
  • Codon: Python Compiler
    Just for reference, * Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11." * Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles. * Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... Makes writing C... - Source: Hacker News / 11 months ago
  • Any faster Python alternatives?
    Profile and optimize the hotspots with cython (or whatever the cool kids are using these days... It's been a while.). Source: 12 months ago
  • What exactly is 'JIT'?
    JIT essentially means generating machine code for the language on the fly, either during loading of the interpreter (method JIT), or by profiling and optimizing hotspots (tracing JIT). The language itself can be statically or dynamically typed. You could also compile a dynamic language ahead of time, for example, cython. Source: 12 months ago
  • Been using Python for 3 years, never used a Class.
    There are also just-in-time compilers available for some Python features, that compile those parts to machine code. That includes Numba (usable as a library within CPython) and Pypy (an alternative Python implementation that includes a JIT compiler to improve performance). There’s also Cython, which is a superset of Python that allows more directly interfacing with C and C++ functions, and compiling the resulting... Source: about 1 year ago
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NumPy mentions (107)

  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 14 days ago
  • JSON in data science projects: tips & tricks
    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 / 22 days ago
  • Introducing Flama for Robust Machine Learning APIs
    Numpy: A library for scientific computing in Python. - Source: dev.to / 3 months ago
  • A Comprehensive Guide to NumPy Arrays
    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 / 5 months ago
  • Beginning Python: Project Management With PDM
    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 / 6 months ago
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What are some alternatives?

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

Numba - Numba gives you the power to speed up your applications with high performance functions written...

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

PyInstaller - PyInstaller is a program that freezes (packages) Python programs into stand-alone executables...

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

nuitka - Nuitka is a Python compiler.

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