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NumPy VS PublicAPIs

Compare NumPy VS PublicAPIs and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

PublicAPIs logo PublicAPIs

Explore the largest API directory in the galaxy
  • NumPy Landing page
    Landing page //
    2023-05-13
Not present

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.

PublicAPIs features and specs

  • Wide Variety
    PublicAPIs provides access to a broad range of APIs across different categories, making it easier for developers to find the APIs they need for various applications.
  • Centralized Resource
    Having a centralized resource for public APIs helps developers save time by not having to search multiple sources to find the API they need.
  • Free Access
    Many of the APIs listed on PublicAPIs are free to use, making it accessible for developers who may be working with limited budgets or on hobby projects.
  • API Documentation
    PublicAPIs often includes links to detailed documentation for each API, providing developers with the information they need to integrate and utilize the APIs effectively.
  • Community Contributions
    PublicAPIs allows for community contributions, enabling a mechanism for the API repository to grow and stay up-to-date with the latest APIs.

Possible disadvantages of PublicAPIs

  • Quality Variability
    The quality of APIs listed can vary significantly, with some being well-maintained and others potentially outdated or lacking comprehensive documentation.
  • Limited Support
    PublicAPIs itself does not usually offer support for the APIs listed, which can be a disadvantage if developers encounter issues and need assistance.
  • Dependency on Third-Party Reliability
    Developers depend on third-party providers' reliability and uptime, which can affect the performance and stability of their own applications.
  • Potential Security Risks
    Using third-party APIs can introduce security vulnerabilities, especially if the APIs are not from trusted sources or if they do not follow best security practices.
  • Rate Limits
    Many public APIs impose rate limits, which can restrict the number of API calls a developer can make within a given time frame, potentially impacting application 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.

Analysis of PublicAPIs

Overall verdict

  • PublicAPIs is generally considered good due to its wide selection of APIs, ease of access, and the ability to discover new tools and services. Its open-access nature encourages creativity and rapid prototyping.

Why this product is good

  • PublicAPIs is a beneficial resource as it provides a curated list of freely available APIs for developers. It helps accelerate development by offering access to a diverse range of APIs, from weather and finance to gaming and machine learning. This can be particularly useful for both learning purposes and developing projects without the need for substantial investment in proprietary APIs.

Recommended for

  • Developers looking for free or open APIs to integrate into their projects.
  • Students and educators who need practical API examples for teaching and learning.
  • Startups and hobbyists seeking to build prototypes without incurring additional costs.

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

PublicAPIs videos

No PublicAPIs videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to NumPy and PublicAPIs)

NumPy

PublicAPIs

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
APIs
0 0%
APIs
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Web App
0 0%
Web App
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 NumPy and PublicAPIs

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

PublicAPIs Reviews

We have no reviews of PublicAPIs yet.
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Social recommendations and mentions

Based on our record, NumPy seems to be more popular. 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.

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 / 5 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

PublicAPIs mentions (0)

We have not tracked any mentions of PublicAPIs yet. Tracking of PublicAPIs recommendations started around Mar 2021.

What are some alternatives?

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

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

API List - A collective list of APIs. Build something.

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

Abstract APIs - Simple, powerful APIs for everyday dev tasks

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

The Unsplash API - No-limits, do-what-you-want API for access to 200K+ HD pics.

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