Software Alternatives, Accelerators & Startups

NumPy VS BrowserCat

Compare NumPy VS BrowserCat and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

BrowserCat logo BrowserCat

Easy, fast, and reliable browser automation and headless browser APIs. The web is messy, but your code shouldn't be.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • BrowserCat Home Page
    Home Page //
    2023-12-21
  • BrowserCat Metrics Dashboard
    Metrics Dashboard //
    2023-12-21
  • BrowserCat Easy Setup
    Easy Setup //
    2023-12-21

Finally, you can develop browser automation without the pain and the cost of deploying a fleet of headless browsers. Connect to BrowserCat, scale globally, and pay only for what you use. Scrape the web, automate your workflows, test your apps, generate beautiful images and pdfs from HTML, give you AI agent web access, and more.

Get started in minutes. Our forever-free plan gives you 1,000 free requests per month.

BrowserCat

$ Details
freemium $10.0 / Monthly
Platforms
Web REST API Google Chrome Firefox Safari

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.

BrowserCat features and specs

No features have been listed yet.

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

BrowserCat videos

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

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Category Popularity

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

Questions and Answers

As answered by people managing NumPy and BrowserCat.

Which are the primary technologies used for building your product?

BrowserCat's answer:

BrowserCat is built on robust open source technology that's under active development. The star of the show is Playwright, which is our recommended automation library. It's maintained by Microsoft, it officially supports JS, Python, Java, and .NET, and it's fast becoming the industry standard. BrowserCat also supports Puppeteer and numerous unofficial Playwright ports to Go, Rust, PHP, and Ruby.

What makes your product unique?

BrowserCat's answer:

Unlike other headless browser providers, BrowserCat gives you total control over your browser instances for as long as you need them. Leverage the browsers cache, cookies, and storage for bespoke browser automation jobs that truly differentiate your business from the competition.

What's the story behind your product?

BrowserCat's answer:

In previous corporate and startup gigs, I faced the challenge of developing robust, fast, and scalable browser automation. Most APIs in the space are too limiting for our needs and they were often incredibly slow. On the other hand, hosting your own headless browser fleet was a pain. I founded BrowserCat to make scaling up browser automation as easy, reliable, and affordable as deploying a serverless function.

How would you describe your primary audience?

BrowserCat's answer:

We primarily serve developers, whether the seek to develop unique browser automation jobs or radically improve the performance of their integration tests. However, we frequently work with management, biz ops, and product leaders to solve problems they can't solve any way but through automation.

Why should a person choose your product over its competitors?

BrowserCat's answer:

BrowserCat is built for performance, scalability, stability, and affordability using modern web technologies. Many of our competitors were early to market and compete on entrenchment rather than functionality. Still others are bound by their existing users to continue supporting legacy tech, rather than embrace improved, modern standards. BrowserCat is focused on supporting your for the next ten years, rather than the past ten years.

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 BrowserCat

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

BrowserCat Reviews

We have no reviews of BrowserCat 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 / 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 / 8 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 / 9 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 / 9 months ago
View more

BrowserCat mentions (0)

We have not tracked any mentions of BrowserCat yet. Tracking of BrowserCat recommendations started around Dec 2023.

What are some alternatives?

When comparing NumPy and BrowserCat, 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.

Microlink - Extract structured data from any website

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

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

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

Scrapy - Scrapy | A Fast and Powerful Scraping and Web Crawling Framework