Software Alternatives, Accelerators & Startups

Simple Scraper VS Matplotlib

Compare Simple Scraper VS Matplotlib and see what are their differences

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Simple Scraper logo Simple Scraper

Extract data from any website in seconds โ€” download instantly, scrape in the cloud, or create an API.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Simple Scraper Landing page
    Landing page //
    2023-08-29

Simple scraper is the easiest way to scrape the web โ€” turn any website into an API in seconds and use ready-made scraping recipes to scrape popular sites with ease.

  • Matplotlib Landing page
    Landing page //
    2023-06-14

Simple Scraper

$ Details
freemium $30.0 / Monthly (6,000 credits)
Release Date
2019 November

Simple Scraper features and specs

  • Ease of Use
    SimpleScraper offers a user-friendly interface that allows even those without technical knowledge to easily extract data from websites.
  • Speed
    The tool allows for fast data extraction, reducing the time needed to gather information manually.
  • Automation
    Users can set up automated scraping tasks to run at regular intervals, which is useful for keeping data up-to-date without manual intervention.
  • API Access
    SimpleScraper provides API access, allowing developers to integrate scraping functionality into their own applications seamlessly.
  • Browser Extension
    The tool offers a browser extension, making it convenient to set up scraping tasks directly from the browser.

Possible disadvantages of Simple Scraper

  • Cost
    Advanced features and higher usage limits come with a subscription fee, which may not be feasible for all users.
  • Website Restrictions
    Some websites employ measures to prevent scraping, which may limit the effectiveness of SimpleScraper on such sites.
  • Data Quality
    Automated scraping can sometimes result in incomplete or inaccurate data, requiring manual verification.
  • Learning Curve
    Though designed to be user-friendly, there can still be a learning curve for those completely new to web scraping.
  • Resource Intensive
    Running multiple or complex scraping tasks can be resource-intensive and may affect the performance of your system.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of Simple Scraper

Overall verdict

  • Overall, Simple Scraper is a reliable and effective web scraping tool that balances ease of use with powerful features. It is well-suited for both beginners and experienced users seeking a quick and straightforward solution for extracting data from the web.

Why this product is good

  • Simple Scraper is considered a good tool primarily due to its combination of user-friendly design and robust functionality. It allows users without extensive technical skills to easily scrape data from websites with its visual point-and-click interface. Additionally, it offers features like scheduling, API access, and integration options that cater to more advanced use cases. The platform's flexibility and efficiency make it a suitable choice for many data scraping projects.

Recommended for

  • Individuals or businesses looking for a no-code solution to web scraping.
  • Marketers and researchers needing to extract and analyze web data.
  • Developers who want an API-accessible scraping solution.
  • Users who require scheduling capabilities to automate the data collection process.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

Simple Scraper videos

Super Simple Scraper Review

More videos:

  • Review - Super Simple Scraper RevieW
  • Review - Scraping with Simple Scraper in under 30 seconds

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Simple Scraper and Matplotlib)
Web Scraping
100 100%
0% 0
Data Science And Machine Learning
Data Extraction
100 100%
0% 0
Technical Computing
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 Simple Scraper and Matplotlib

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Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...

Social recommendations and mentions

Based on our record, Matplotlib should be more popular than Simple Scraper. It has been mentiond 114 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.

Simple Scraper mentions (22)

  • Ask HN: What Are You Working On? (March 2026)
    Data extraction: https://simplescraper.io A project that I launched on HN that became a business. Simplescraper rode the no-code wave of a few years back ('instant structured data without parsing html'). Now working on increasing the surface area for AI agents: MCP support, screenshots API, and (experimentally) x402^ ^ https://simplescraper.io/blog/x402-payment-protocol/. - Source: Hacker News / 5 months ago
  • Scraperr โ€“ A Self Hosted Webscraper
    1. Clicking the box programmatically โ€“ possible but inconsistent 2. Outsourcing the task to one of the many CAPTCHA-solving services (2Captcha etc) โ€“ better 3. Using a pool of reliable IP addresses so you don't encounter checkboxes or turnstiles โ€“ best I run a web scraping startup (https://simplescraper.io) and this is usually the approach. It has become more difficult, and I think a lot of the AI crawlers are... - Source: Hacker News / over 1 year ago
  • Ask HN: What Are You Working On? (October 2024)
    Making my data extraction Saas (https://simplescraper.io) more LLM friendly. Markdown extraction, improved Google search, workflows - search for this terms, visit the first N links, summarize etc. Big demand for (or rather, expectation of) this lately. - Source: Hacker News / almost 2 years ago
  • The Architecture Behind a One-Person Tech Startup
    Things are much easier for one-person startups these daysโ€”it's a gift. I remember building a todo app as my first SaaS project, and choosing something called Stormpath for authentication. It subsequently shut down, forcing me to do a last-minute migration from a hostel in Japan using Nitrous Cloud IDE (which also shut down). Just pain upon pain.[1] Now, you can just pick a full-stack cloud service and run with it.... - Source: Hacker News / about 2 years ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Simplescraper โ€” Trigger your webhook after each operation. The free plan includes 100 cloud scrape credits. - Source: dev.to / over 2 years ago
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Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 9 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 10 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 11 months ago
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What are some alternatives?

When comparing Simple Scraper and Matplotlib, you can also consider the following products

Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.

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

Scraper API - Scale Data Collection with a Simple API.

NumPy - NumPy is the fundamental package for scientific computing with Python

Diggernaut - Web scraping is just became easy. Extract any website content and turn it into datasets. No programming skills required.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.