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NumPy VS Zyte

Compare NumPy VS Zyte and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Zyte logo Zyte

We're Zyte (formerly Scrapinghub), the central point of entry for all your web data needs.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Zyte Landing page
    Landing page //
    2022-01-09

We are the leader in web data extraction technology and services. We're obsessed with data. And what it can do for businesses.

We help thousands of companies and millions of developers to get their hands on clean, accurate data. Quickly, reliably & at scale. Every day, for more than a decade.

From price intelligence, news and media, job listings and entertainment trends, brand monitoring, and more, our customers rely on us to obtain dependable data from over 13 billion web pages each month.

Zyte (formerly Scrapinghub) serves over 2,000 companies and 1 million developers from across the globe who value accurate, reliable web data to help them run their business.

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.

Zyte features and specs

  • High-Quality Data Extraction
    Zyte provides powerful web scraping capabilities, allowing for reliable and high-quality data extraction from various websites.
  • Ease of Use
    The platform offers a user-friendly interface and comprehensive documentation, making it easier for both beginners and experienced users to navigate and utilize its features.
  • Compliance and Ethical Scraping
    Zyte emphasizes ethical scraping practices and compliance with website terms of service, helping users avoid legal and ethical issues.
  • Custom Solutions
    Zyte offers tailored data extraction solutions to meet specific business needs, providing customization and flexibility.
  • Scalability
    The platform supports scalable data extraction operations, suitable for both small projects and large-scale enterprise needs.

Possible disadvantages of Zyte

  • Cost
    The pricing for Zyte's services can be relatively high, which may be a barrier for small businesses or individual users with limited budgets.
  • Learning Curve
    Despite its user-friendly design, mastering all the advanced features of Zyte may require a learning curve, particularly for users new to web scraping.
  • Rate Limiting
    Some users may encounter rate limiting or blocking from target websites, which can hinder the data extraction process and require additional strategies to manage.
  • Dependency on Third-Party Websites
    As with any web scraping tool, Zyte's effectiveness can be impacted by changes in the HTML structure of target websites or their policies, requiring constant adaptation.
  • Ethical and Legal Restrictions
    While Zyte promotes ethical scraping, users must still navigate complex legal landscapes, which can vary by region and website, adding operational challenges.

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 Zyte

Overall verdict

  • Zyte is considered a good choice for businesses and individuals looking for reliable and efficient web scraping solutions. Its strong customer support, extensive documentation, and user-friendly platform make it well-regarded in the industry.

Why this product is good

  • Zyte (formerly Scrapinghub) is regarded as a good platform because it provides a comprehensive set of tools and services for web data extraction and web scraping. It offers easy-to-use APIs, a robust infrastructure for large-scale data scraping, and services like automated data retrieval and storage. Additionally, Zyte is recognized for its ability to handle complex scraping tasks, such as data extraction from dynamic websites using AJAX or JavaScript.

Recommended for

  • Data scientists and analysts needing web data for research and insights
  • Developers seeking APIs for efficient and scalable data extraction
  • Business professionals requiring market and competitor insights
  • Companies looking for automated and reliable data extraction services

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

Zyte videos

What is data exraction?

More videos:

  • Review - Scraping and sentiment analysis using Scrapinghub and Amazon Comrehend

Category Popularity

0-100% (relative to NumPy and Zyte)
Data Science And Machine Learning
Web Scraping
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Data Extraction
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 NumPy and Zyte

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

Zyte Reviews

Creating an Automated Text Extraction Workflow — Part 1
The 600 lbs gorilla, Diffbot, comes with a swath of solid APIs but starts at $300, which is ridiculous if you’re just extracting text. Scrapinghub’s News API, Extractor API, and plenty more are better priced if you want an affordable alternative; plus, Extractor API includes a visual online tool for extracting hundreds of articles at once, if you want to do things via UI.
Source: medium.com

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Zyte. While we know about 119 links to NumPy, we've tracked only 1 mention of Zyte. 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 / 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

Zyte mentions (1)

What are some alternatives?

When comparing NumPy and Zyte, 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.

Bright Data - World's largest proxy service with a residential proxy network of 72M IPs worldwide and proxy management interface for zero coding.

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

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

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

Smartproxy - Smartproxy is perhaps the most user-friendly way to access local data anywhere. It has global coverage with 195 locations, offers more than 55M residential proxies worldwide and a great deal of scraping solutions.