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Streamlit VS gitmbed

Compare Streamlit VS gitmbed and see what are their differences

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Streamlit logo Streamlit

Turn python scripts into beautiful ML tools

gitmbed logo gitmbed

Social media better with gitmbed! Embeds in your posts/READMEs where they would normally be blocked!
  • Streamlit Landing page
    Landing page //
    2023-10-07
  • gitmbed Landing page
    Landing page //
    2023-07-25

Streamlit features and specs

  • Ease of Use
    Streamlit's API is extremely intuitive and easy to learn, which makes it accessible for developers of varying experience levels. The simplicity allows for rapid development and less time spent on complex front-end coding.
  • Interactive Widgets
    It provides a set of interactive widgets that make it simple to add complex functionalities like sliders, buttons, and file uploaders to your application with minimal code.
  • Real-time Feedback
    Streamlit supports real-time data updates, allowing users to see changes instantly. This is particularly useful for data analysis and machine learning applications where live data visualization is crucial.
  • Integration with Machine Learning Libraries
    Streamlit integrates seamlessly with popular machine learning libraries like TensorFlow, PyTorch, and scikit-learn, making it a great tool for showcasing machine learning models and results.
  • Open Source
    Being an open-source project, Streamlit is free to use and comes with the support and contributions of an active community. This means continuous improvements and a wealth of shared resources.

Possible disadvantages of Streamlit

  • Limited Customization
    Streamlit offers limited customization options compared to traditional web frameworks. This can be a hindrance if you need a highly customized UI/UX for your application.
  • Performance Issues
    For more complex or resource-intensive applications, Streamlit may suffer from performance drawbacks. It is not designed for high-performance computing out of the box.
  • Scalability
    Streamlit is not well-suited for large-scale applications requiring major backend architecture or for scenarios demanding high scalability and concurrency.
  • Limited Widget Style Options
    The styling and customization options for widgets are somewhat limited, meaning your application's look and feel might be more constrained compared to using other front-end frameworks.
  • Deployment Complexity
    While Streamlit provides some deployment options, deploying Streamlit apps in a production environment can sometimes require additional effort and knowledge, especially for those unfamiliar with web deployment practices.

gitmbed features and specs

  • Seamless Integration
    Gitmbed allows for easy embedding of GitHub repositories into various platforms, providing seamless integration with different environments.
  • User-Friendly
    The tool is designed to be intuitive, making it accessible for users with varying levels of technical expertise.
  • Real-Time Updates
    Gitmbed provides real-time updates from the source repository, ensuring that embedded content is always current.
  • Customizable
    Users can customize the appearance and functionality of embedded repositories to suit their specific needs.

Possible disadvantages of gitmbed

  • Dependency on GitHub
    The effectiveness of Gitmbed relies heavily on GitHub's API and availability, which could be a limitation if issues arise with GitHub.
  • Limited Use Cases
    While Gitmbed is great for embedding repositories, its use cases are somewhat limited to platforms and situations where such a feature is needed.
  • Potential Security Risks
    Embedding repositories from GitHub could pose security risks, especially if the embedded content is not thoroughly reviewed.
  • Performance Concerns
    Depending on the size and complexity of the repository, embedding it could lead to performance issues on platforms with limited resources.

Analysis of Streamlit

Overall verdict

  • Overall, Streamlit is well-regarded for its ease of use, speed of development, and ability to create clean and professional-looking applications without in-depth web development knowledge. It provides a seamless bridge between complex data analysis and user-friendly presentation, which can be highly beneficial for a wide range of use cases.

Why this product is good

  • Streamlit is a popular choice for quickly building and deploying data applications and interactive dashboards with minimal code. It is designed to be user-friendly, allowing data scientists and engineers to transform their scripts into shareable web apps. It supports real-time updates, is highly customizable, and integrates well with Python libraries like NumPy, Pandas, and Matplotlib, making it an attractive option for many developers working within the Python ecosystem.

Recommended for

    Streamlit is ideal for data scientists, analysts, and developers looking to rapidly prototype and deploy data-driven applications. It is recommended for those who prioritize simplicity, quick deployment, and seamless integration with Python code. Individuals or teams interested in building dashboards, ML model sharing platforms, or interactive reports will find Streamlit particularly useful.

Analysis of gitmbed

Overall verdict

  • GitHub is a solid, industry-standard platform for hosting Git repositories and collaborating on code, backed by robust infrastructure, extensive integrations, and a massive community.

Why this product is good

  • Widely adopted, industry-standard platform trusted by millions of developers and organizations
  • Excellent Git repository hosting with strong performance and reliability
  • Rich ecosystem including GitHub Actions for CI/CD, Issues, Projects, and Wikis
  • Strong collaboration features like pull requests, code review tools, and discussions
  • Free tier available for public and private repositories with generous limits
  • Large community and marketplace of third-party integrations and apps
  • Good security features including Dependabot, secret scanning, and code scanning
  • Well-documented API for automation and custom tooling

Recommended for

  • Individual developers hosting personal or open-source projects
  • Teams and organizations needing collaborative code management
  • Companies wanting integrated CI/CD pipelines via GitHub Actions
  • Open-source maintainers seeking community visibility and contributions
  • Educational institutions teaching version control and collaboration
  • Enterprises requiring scalable, secure code hosting with compliance options

Streamlit videos

My thoughts on web frameworks in Python and R (PyWebIO vs Streamlit vs R Shiny)

More videos:

  • Review - 1/4: What is Streamlit
  • Tutorial - How to Build a Streamlit App (Beginner level Streamlit tutorial) - Part 1

gitmbed videos

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

Add video

Category Popularity

0-100% (relative to Streamlit and gitmbed)
Developer Tools
100 100%
0% 0
JS
0 0%
100% 100
Productivity
100 100%
0% 0
JavaScript
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Streamlit seems to be a lot more popular than gitmbed. While we know about 220 links to Streamlit, we've tracked only 1 mention of gitmbed. 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.

Streamlit mentions (220)

  • How I Bypassed Reddit's Unauthenticated RSS Rate Limits (Without an API Key)
    I wrapped the logic in a small, single-process Streamlit app that pulls the newest posts from Hacker News, Reddit, and Lemmy into one sortable table. A few implementation details worth mentioning:. - Source: dev.to / 15 days ago
  • Adding Authentication and SSO to a Streamlit App
    Streamlit makes it simple to turn Python scripts into shareable data apps. As these apps move from personal notebooks to team and company use, adding secure authentication and single sign-on (SSO) becomes essential. Authentication protects sensitive data and gates features by user identity. SSO lets people sign in once and move across apps without repeating logins. - Source: dev.to / 5 months ago
  • How I trained a computer vision model on the AWS Free Tier
    The app I built to explore that question is a Streamlit app with two modes. Standard mode sends your image to the DetectLabels API and checks if it returns "Egg" or "Easter Egg" in the labels. Custom Labels mode uses a custom model I trained on my own images. Both draw bounding boxes around any eggs they find. - Source: dev.to / 5 months ago
  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Once you've completed your analysis, consider building a dashboard to visualize your findings. Tools like Streamlit make it easy to create interactive web apps:. - Source: dev.to / 6 months ago
  • [TIL][Python] Python Tool for Online PDF Viewing, Comparison, and Data Import
    Title: [TIL][Python] Online PDF Page-by-Page Viewing and Comparison Tool for Importing Data (Python online PDF Viewer and comparison) and Python Snippets Published: false Date: 2023-08-04 00:00:00 UTC Tags: Canonical_url: http://www.evanlin.com/til-python-tips/ --- ## Small Project: Online PDF Viewer and Parse Data compare: -... - Source: dev.to / about 3 years ago
View more

gitmbed mentions (1)

  • Submit Your Design Here and I will review it (Youtube video)
    In terms of HTML/CSS, I have https://github.com/flancast90/The-Vault (local serverless and encrypted file storage), https://github.com/flancast90/gitmbed (chrome extension for a better GitHub), https://github.com/flancast90/PennyPriceJS (price-finder tool), and my resume site/template (www.finnsoftware.net). Source: almost 5 years ago

What are some alternatives?

When comparing Streamlit and gitmbed, you can also consider the following products

Anvil.works - Build seriously powerful web apps with all the flexibility of Python. No web development experience required.

FastAPI - FastAPI is an Open Source, modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.

Gradio - Build & share machine learning apps delightfully.

Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.

Flet - Build internal web apps quickly in the language you already know.

Apache Superset - modern, enterprise-ready business intelligence web application