Software Alternatives, Accelerators & Startups

devenv VS Plotly

Compare devenv VS Plotly and see what are their differences

devenv logo devenv

Fast, Declarative, Reproducible, and Composable dev envs

Plotly logo Plotly

Low-Code Data Apps
  • devenv Landing page
    Landing page //
    2023-10-09
  • Plotly Landing page
    Landing page //
    2023-07-31

devenv features and specs

  • Ease of Use
    Devenv provides a straightforward interface that simplifies setting up and managing development environments, reducing setup time.
  • Scalability
    It allows for easy scaling of environments, whether it's a small project or a larger enterprise application, making it adaptable to different needs.
  • Environment Consistency
    Ensures that all team members have a consistent development environment, minimizing discrepancies and facilitating smoother collaboration.
  • Integration Capabilities
    Seamless integration with various tools and platforms, enhancing workflows without significant disruption to existing processes.

Possible disadvantages of devenv

  • Learning Curve
    Despite its ease of use, new users might encounter a learning curve while familiarizing themselves with its specific functionalities and features.
  • Platform Limitations
    Certain advanced features may be limited to specific platforms, potentially restricting its applicability for some users or organizations.
  • Resource Intensive
    Running complex development environments can be resource-intensive, which might be a concern on lower-specification machines.
  • Dependency Management
    Managing dependencies and configurations can become complex in larger projects, potentially leading to overhead in maintaining environments.

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.

devenv videos

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Plotly videos

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 devenv and Plotly)
Productivity
100 100%
0% 0
Data Visualization
0 0%
100% 100
Password Management
100 100%
0% 0
Charting Libraries
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 devenv and Plotly

devenv Reviews

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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.
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...
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.

Social recommendations and mentions

devenv might be a bit more popular than Plotly. We know about 50 links to it since March 2021 and only 34 links to Plotly. 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.

devenv mentions (50)

  • Where .env Went Wrong
    While there are absolutely a million of these env tools popping up which are absolutely vibe-coded slop, secretspec is not one of them. It's from the creator of https://devenv.sh and has been around for a while. - Source: Hacker News / 4 days ago
  • Better pre-commit, re-engineered in Rust
    Probably not relevant to you, since it is yet another tool for managing your development environment, but maybe have a look at devenv (https://devenv.sh). it's main purpose is managing the development environment, but it has integration for pre-commit (or pmeven prek iirc) that let's pre-commit do it's thing, but takes over the dependency management. - Source: Hacker News / 9 months ago
  • fnox, a secret manager that pairs well with mise
    Pretty sad to see almost verbatim copy of https://secretspec.dev :) I'm glad mise is catching up on https://devenv.sh features though. - Source: Hacker News / 9 months ago
  • Mise: Monorepo Tasks
    There's a tool that makes the Nix way a lot more approachable: https://devenv.sh/ e.g. `languages.rust.enable = true` and you're off to the races. - Source: Hacker News / 10 months ago
  • Easy development environments with Nix and Nix flakes!
    If writing a devshell on your own seems more complicated than necessary, you can use tools like Devenv or Devbox (by the same team that built NixHub), which are both built on Nix. Devenv provides nice wrappers to automatically add languages, services (like postgres or redis), etc. On top of your flake, without having to do the shenanigans we had to do with Valkey. Devbox on the other hand, lets you skip writing... - Source: dev.to / 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 / 5 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

What are some alternatives?

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

Flox - Manage and share development environments with all the frameworks and libraries you need, then publish artifacts anywhere. Harness the power of Nix.

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.

NixOS - 25 Jun 2014 . All software components in NixOS are installed using the Nix package manager. Packages in Nix are defined using the nix language to create nix expressions.

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

Podman - Simple debugging tool for pods and images

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.