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Plotly VS PyInstaller

Compare Plotly VS PyInstaller and see what are their differences

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

Plotly logo Plotly

Low-Code Data Apps

PyInstaller logo PyInstaller

PyInstaller is a program that freezes (packages) Python programs into stand-alone executables...
  • Plotly Landing page
    Landing page //
    2023-07-31
  • PyInstaller Landing page
    Landing page //
    2021-10-20

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.

PyInstaller features and specs

  • Cross-Platform Support
    PyInstaller supports Windows, macOS, and Linux, allowing developers to create executables for multiple platforms from a single codebase.
  • Single Executable
    PyInstaller can bundle a Python application and all its dependencies into a single executable, simplifying distribution as users do not need to install Python separately.
  • Easy to Use
    PyInstaller has straightforward commands and a simple configuration process, making it accessible even for those with limited experience in creating executables.
  • Customizable
    PyInstaller provides various options for customization, allowing developers to specify which files to include or exclude, add data files, and more.
  • Active Community
    PyInstaller benefits from an active community that contributes to its development and provides support through forums and other platforms.

Possible disadvantages of PyInstaller

  • Executable Size
    The executable files generated by PyInstaller can be large since they include the Python interpreter and all dependencies, which may not be ideal for applications with size constraints.
  • Compatibility Issues
    While PyInstaller supports many third-party Python packages, some packages may not work out of the box, requiring additional configuration or adjustments.
  • Occasional Bugs
    Like any software tool, PyInstaller can have bugs, especially with new or less common Python features, which may require troubleshooting or code workarounds.
  • Limited Optimization
    The executables produced by PyInstaller may not be as optimized in terms of performance as those created by more complex methods or tools specifically designed for performance enhancements.
  • Dynamic Module Loading
    Handling dynamic imports can be challenging with PyInstaller, requiring developers to manually specify hidden imports to ensure all dependencies are included.

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.

Plotly videos

+ Add

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

PyInstaller videos

+ Add

Archivo ejecutable en Python | Windows| PyInstaller |PyQT5| Python | ยกMuy fรกcil!

More videos:

  • Review - python hack #8 reverse shell espionage cmd fichier py en exe pyinstaller part2
  • Review - python hack #8 reverse shell espionage cmd fichier py en exe pyinstaller part1

Category Popularity

0-100% (relative to Plotly and PyInstaller)

Plotly

PyInstaller

Data Visualization
100 100%
Data Visualization
0% 0
Website Builder
0 0%
Website Builder
100% 100
Charting Libraries
100 100%
Charting Libraries
0% 0
Development
0 0%
Development
100% 100

User comments

Share your experience with using Plotly and PyInstaller. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Plotly and PyInstaller

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

PyInstaller Reviews

We have no reviews of PyInstaller yet.
Be the first one to post

Social recommendations and mentions

Plotly might be a bit more popular than PyInstaller. We know about 34 links to it since March 2021 and only 33 links to PyInstaller. 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.

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
View more

PyInstaller mentions (33)

  • Show HN: Halloy โ€“ the modern IRC client I hope will outlive me
    I don't say it is best, but there are solutions like pyinstaller [0] to produce a binary from python code. [0] https://pyinstaller.org/en/stable/. - Source: Hacker News / 9 months ago
  • ReproZip โ€“ reproducible experiments from command-line executions
    Https://news.ycombinator.com/item?id=43553198 : > auditwheel show > auditwheel repair: copies these external shared libraries into the wheel itself, and automatically modifies the appropriate RPATH entries such that these libraries will be picked up at runtime. This accomplishes a similar result as if the libraries had been statically linked without requiring changes to the build system. Packagers are... - Source: Hacker News / 12 months ago
  • Cosmopolitan v3.5.0
    Looking forward toward somebody hooking together Python in APE [0], something like pex [1]/shiv[2]/pyinstaller[3], and the pants build system [4] to have a toolchain which spits out single-file python executables with baked-in venv and portable across mainstream OSes with native (or close enough) performance. 0 - https://news.ycombinator.com/item?id=40040342 2 - https://shiv.readthedocs.io/en/latest/ 3 -... - Source: Hacker News / about 2 years ago
  • Playable Sandbox Now Available
    Normally games made with pygame are not playable from the web. They can only be run from the command line or use PyInstaller or cx_Freeze to create a standalone executable. - Source: dev.to / over 2 years ago
  • Python GUIs
    I have found PyInstaller [1] to work well for packaging everything into a single ZIP file that unzips to a folder with an executable binary and all accompanying files (or even a single EXE file that self-extracts when run, but that increases startup time). It knows how to package PyQt and its associated Qt libraries (or PySide, which I actually prefer) so that they can be shipped with your application. [1... - Source: Hacker News / about 3 years ago
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What are some alternatives?

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

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.

cx_Freeze - cx_Freeze is a set of scripts and modules for freezing Python scripts into executables in much the...

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

bbfreeze - create stand-alone executables from python scripts

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.

PyPy - PyPy is a fast, compliant alternative implementation of the Python language (2.7.1).

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