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Embedly VS NumPy

Compare Embedly VS NumPy and see what are their differences

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Embedly logo Embedly

Embedly helps publishers and consumers manage embed codes from websites and APIs.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Embedly Landing page
    Landing page //
    2021-09-21
  • NumPy Landing page
    Landing page //
    2023-05-13

Embedly features and specs

  • Ease of Use
    Embedly provides a simple API that allows developers to embed content from a wide variety of sources with minimal effort.
  • Content Versatility
    Supports embedding content from many major providers such as YouTube, Instagram, Twitter, and more, enhancing the versatility of web content.
  • Customization
    Offers customizable embed options so developers can tailor the appearance and behavior of the embedded content to fit their needs.
  • Aggregated Data
    Provides enriched metadata from embedded content, which could be useful for SEO and content analysis.
  • Cross-Platform Support
    Embeds are responsive and work well across different devices and platforms, providing a consistent user experience.

Possible disadvantages of Embedly

  • Cost
    Embedly offers a freemium model, but the free tier has limitations, and the premium plans can be expensive for small businesses or individual developers.
  • Dependency
    Relying on a third-party service means developers are dependent on Embedly for uptime and performance, which could be a potential risk if the service experiences issues.
  • Privacy Concerns
    Using Embedly means sharing data with a third-party service, which could raise privacy concerns depending on the type of content being embedded.
  • Limitations in Custom Sources
    While Embedly supports many major providers, it may not support lesser-known or niche content sources, which could be a drawback for certain use cases.
  • API Rate Limits
    The API has rate limits even on premium plans, which could be restrictive for high-traffic websites or applications requiring extensive embedding.

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 Embedly

Overall verdict

  • Embedly is generally considered a good option for content embedding due to its comprehensive API and ease of use.

Why this product is good

  • Embedly provides a robust platform that allows developers to easily embed multimedia content from a wide range of sources. The service simplifies the process of extracting and displaying content such as images, videos, and articles by providing a unified API. It supports a vast number of providers and offers customization options, making it a flexible tool for developers. Additionally, Embedly delivers content in a mobile-optimized way, ensuring a better user experience across different devices.

Recommended for

  • Developers looking to integrate multimedia content into websites or applications
  • Content creators and publishers who want to enrich their platforms with external content
  • Web and mobile app developers needing a simple solution for embedding content from multiple sources

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.

Embedly videos

+ Add

Tips On Embedding In Blogs And Websites Using Embedly

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 Embedly and NumPy)

Embedly

NumPy

Advertising
100 100%
Advertising
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Content Marketing
100 100%
Content Marketing
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Embedly and NumPy

Embedly Reviews

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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.
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 Embedly. 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.

Embedly mentions (13)

  • Automod remove videos less than 1second long?
    You can see what kinds of properties you can see for media - I fed the URL of a video into embed.ly as that document suggested, but none of the fields returned gave me a video length... You may want to try with one of the images posted to your sub and see what properties you get. Maybe there's something else in the metadata you can search for that is common across the short videos. Source: over 1 year ago
  • Embedding videos on reddit
    Some people report success with getting approved by https://embed.ly/, others report that service never responded to them. Source: almost 2 years ago
  • free-for.dev
    Embed.ly — Provides APIs for embedding media in a webpage, responsive image scaling, extracting elements from a webpage. Free for up to 5,000 URLs/month at 15 requests/second. - Source: dev.to / over 2 years ago
  • How to ban specific YouTube links?
    Use https://embed.ly to extract the MEDIA_AUTHoR or MEDIA_AUTHOR_URL from the link and add it to either of the 2 rules below. Source: over 2 years ago
  • How does Reddit embed “unavailable” Youtube videos? (example included)
    If you pull up that script, it references "cdn.embedly.com", a third-party content delivery network. See their home page at https://embed.ly/. Source: about 3 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 / 8 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 Embedly and NumPy, you can also consider the following products

uberflip - Organize and Centralize ALL of your Content in minutes

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

CoSchedule - CoSchedule is the #1 marketing calendar that helps you stay organized and get sh*t done. Plan, produce, publish and promote your content.

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

Rocketium - A DIY video creation platform. Make videos in minutes using preset themes and templates.

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

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