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9Proxy VS NumPy

Compare 9Proxy VS NumPy and see what are their differences

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9Proxy logo 9Proxy

Clean. Fast. Unlimited Bandwidth. Premium Residential Proxies, Starting from $0.04/IP.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • 9Proxy Pricing
    Pricing //
    2024-02-27
  • 9Proxy Home
    Home //
    2024-02-27

9Proxy provides reliable residential proxies with clean, fast connections and unlimited bandwidth, starting from $0.04/IP. Benefit from our flexible replacement policy and exclusive advantages for affiliates, resellers, and partners for enhanced online activities and mutual benefits.

  • NumPy Landing page
    Landing page //
    2023-05-13

9Proxy

Website
9proxy.com
$ Details
paid Free Trial $0.04 / One-off ($0.04/IP)
Platforms
Amazon eBay Zonnolab Multilogin RBtools Steam Twitter Telegram Yandex Facebook Messenger Facebook Instagram TikTok LinkedIn Viber YouTube Twitch Windows Linux
Release Date
2023 November

9Proxy features and specs

  • Price Aggregation
    Compare prices and find better deals easily
  • SERP & SEO
    Optimize for success in search engine rankings
  • Multi-Accounting
    Efficiently manage multiple accounts
  • Data Scraping
    Collect and analyze web data effectively
  • Ad Tech
    Campaign success through advanced ad tech
  • Market Research
    In-depth insights for informed business decisions

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 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.

9Proxy videos

Introducing 9Proxy | Premium Residential Proxies - 2024 Commercial

More videos:

  • Tutorial - 9Proxy | How To Set Up 9Proxy
  • Review - Datacenter vs. Residential Proxies: Which One to Choose? | 9Proxy | Premium Residential Proxies
  • Review - Proxy giá rẻ, tốc độ cao với 9Proxy

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 9Proxy and NumPy)
Residential Proxies
100 100%
0% 0
Data Science And Machine Learning
Proxy
100 100%
0% 0
Data Science Tools
0 0%
100% 100

Questions and Answers

As answered by people managing 9Proxy and NumPy.

Why should a person choose your product over its competitors?

9Proxy's answer

Individuals should opt for 9Proxy due to its extensive pool of over 9 million residential proxies, competitive pricing starting at just $0.04 per IP, and unique offerings such as unlimited bandwidth and a distinct replacement policy. Additionally, 9Proxy's commitment to high anonymity and customer support availability 24/7 across various platforms ensures a superior user experience compared to other services.

What makes your product unique?

9Proxy's answer

9Proxy stands out with its over 9 million clean residential proxies, ensuring high anonymity and security for its users. Its unique replacement policy guarantees that users receive functioning proxies at all times, enhancing reliability. Furthermore, 9Proxy offers unlimited bandwidth without additional charges, setting it apart from competitors who often impose data limits.

How would you describe your primary audience?

9Proxy's answer

9Proxy's primary audience includes SEO professionals, market researchers, and data analysts who require reliable and anonymous internet access for data scraping, SERP analysis, and market research. It also caters to businesses involved in ad tech, multi-accounting, and price aggregation, providing them with the necessary tools to perform their tasks efficiently and securely.

What's the story behind your product?

9Proxy's answer

We are a group of professionals identifying a gap in the market for reliable, affordable, and anonymous proxy services. We then leverage our expertise in network technology and security to create a solution that addresses these needs, leading to the establishment of 9Proxy. The company has grown by focusing on customer needs, technological advancements, and quality service.

Who are some of the biggest customers of your product?

9Proxy's answer

Our biggest customers generally include: Digital marketing agencies SEO and SEM professionals Big data analytics firms E-commerce companies Cybersecurity companies Academic and research institutions

Which are the primary technologies used for building your product?

9Proxy's answer

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User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare 9Proxy and NumPy

9Proxy 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.
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 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.

9Proxy mentions (0)

We have not tracked any mentions of 9Proxy yet. Tracking of 9Proxy recommendations started around Feb 2024.

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

What are some alternatives?

When comparing 9Proxy and NumPy, you can also consider the following products

ABC S5 Proxy - ABCProxy is the top residential ip proxy service provider, with more than 200 million IP addresses covering more than 190 countries, providing elite anonymity, high connection rate IP, etc.

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

922 S5 proxy - 922S5 is one of the best and cheapest proxy service provider with 200M+ residential proxies and many other proxy types! Start using it NOW!

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

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

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