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Micro Python VS Plotly

Compare Micro Python VS Plotly and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Micro Python logo Micro Python

Python for microcontrollers

Plotly logo Plotly

Low-Code Data Apps
  • Micro Python Landing page
    Landing page //
    2023-03-16
  • Plotly Landing page
    Landing page //
    2023-07-31

Micro Python features and specs

  • Lightweight
    MicroPython is designed to be a streamlined version of Python, optimized for microcontrollers and small embedded systems. It has a smaller footprint than full Python, making it ideal for constrained environments.
  • Python Compatibility
    MicroPython is largely compatible with standard Python (Python 3.x), which allows developers who are familiar with Python to easily adapt to MicroPython for embedded applications.
  • Real-Time Capabilities
    MicroPython supports real-time operating systems and can handle tasks that require precise timing, making it suitable for controlling hardware directly.
  • Active Community
    MicroPython has a growing community of developers and enthusiasts who contribute to its development, provide support, and share resources and libraries.
  • Cross-Platform Support
    MicroPython can run on a wide range of hardware platforms, including popular boards like ESP8266, ESP32, and Raspberry Pi Pico, offering flexibility for developers.

Possible disadvantages of Micro Python

  • Limited Library Support
    Not all Python libraries are available in MicroPython, and some may require re-implementation or adaptation to work within the constraints of microcontrollers.
  • Performance Constraints
    Due to its lightweight nature and the limited resources of typical target devices, MicroPython may not perform as well as standard Python in terms of speed and processing power.
  • Learning Curve for Hardware Interfacing
    Developers who are new to embedded systems may face a learning curve when it comes to hardware interfacing and understanding the limitations and capabilities of microcontrollers.
  • Memory Limitations
    Microcontrollers have significantly less memory than computers, which can limit the complexity of programs that can be run using MicroPython.
  • Fragmented Development Environment
    Compared to standard Python, the tools and IDE support for MicroPython can be less mature and more fragmented, which may make development more challenging.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

Micro Python videos

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

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Plotly videos

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Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to Micro Python and Plotly)

Micro Python

Plotly

Education
100 100%
Education
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Charting Libraries
0 0%
Charting Libraries
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 Micro Python and Plotly

Micro Python Reviews

We have no reviews of Micro Python yet.
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Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Source: www.technotification.com
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
Source: www.geeksforgeeks.org
5 top picks for JavaScript chart libraries
Plotly is a graphing library thatโ€™s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.
Source: blog.logrocket.com

Social recommendations and mentions

Based on our record, Micro Python should be more popular than Plotly. It has been mentiond 84 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.

Micro Python mentions (84)

  • MicroPythonOS graphical operating system delivers Android-like user experience
    Reasonably, that language is MicroPython [1] which is the special pared-down version of Python for memory-constrained embedded targets. [1]: https://micropython.org/. - Source: Hacker News / 6 months ago
  • ๐Ÿ’ป MicroPython on a $3 Board: Real-Time IoT Dashboard with Zero Cloud Costs!
    In this post, weโ€™ll walk through how to use MicroPython on the popular ESP8266 microcontroller to stream sensor data (like temperature and humidity) directly to a real-time web dashboard โ€” no cloud platform, no third-party services, and no cost beyond your WiFi and coffee. - Source: dev.to / 9 months ago
  • ๐Ÿ”ฅ MicroPython on ESP32: Build a Smart Sensor in 15 Minutes Without Writing C! ๐Ÿ˜ฑ
    Welcome to the world of MicroPython, an efficient and lightweight implementation of Python 3 that runs directly on microcontrollers like the ESP32. This blog post is a deep dive into building a real-world smart sensor project in under 15 minutes using MicroPython โ€“ no Arduino IDE, no C++, and no nonsense. - Source: dev.to / 9 months ago
  • Ask HN: What less-popular systems programming language are you using?
    I'll link to it because many people don't know a version of Python runs on microcontrollers: https://micropython.org/. - Source: Hacker News / over 1 year ago
  • Tactility: OS for the ESP32 Microcontroller Family
    I'm personally working on something like this for the ESP32, but written on top of micropython [1]. A few things are written in C such as the display driver, but otherwise most things are in micropython. We chose the T-Watch 2020 V3 microphone variant as the platform [2]. Our objective is to build a modern PDA device via a mostly stand-alone watch that can be synced across devices (initially the Linux desktop). We... - Source: Hacker News / over 1 year ago
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Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 4 months ago
  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
  • Build a Stock Dashboard in less than 40 lines of Python code!๐Ÿค“
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
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What are some alternatives?

When comparing Micro Python and Plotly, you can also consider the following products

Thonny - Python IDE for beginners

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Invent With Python - Learn to program Python for free

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

Numba - Numba gives you the power to speed up your applications with high performance functions written...

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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