Flask VS Plotly

Compare Flask VS Plotly and see what are their differences

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Flask

a microframework for Python based on Werkzeug, Jinja 2 and good intentions.

Plotly

Low-Code Data Apps

Landing page //
2023-07-24

Landing page //
2023-07-31

Flask

Website: flask.pocoo.org
Pricing URL: -
$ Details

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Plotly

Website: plotly.com
Pricing URL: Official Plotly Pricing
$ Details: -

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Flask features and specs

Simplicity
Flask is a micro-framework, meaning it is lightweight, easy to understand, and simple to use. It requires minimal setup to get a web application up and running.
Flexibility
Flask provides flexibility and control over the application's architecture, allowing developers to choose the components they need and avoid unnecessary bloat.
Extensibility
Flask supports various extensions to add capabilities like database integration, form validation, and authentication without compromising its core simplicity.
Documentation
Flask has comprehensive and well-organized documentation, making it easier for developers to learn and implement features effectively.
Community
Flask has a large and active community, providing ample resources like tutorials, code snippets, and third-party libraries that can help speed up development.
Testing
Flask is designed to be unit tested easily, allowing developers to test their applications and ensure reliability.

Possible disadvantages of Flask

Scalability
Flask may not be as scalable as some other frameworks for very large applications due to its minimalist design and lack of built-in features.
Boilerplate Code
Since Flask requires you to integrate and configure many components manually, codebases in Flask can sometimes contain a lot of boilerplate code.
Opinionated Architecture
While Flask provides flexibility, it also means there are fewer conventions. Developers must make more architectural decisions, which can be challenging for large team collaboration.
Limited Tools
Compared to more comprehensive frameworks, Flask offers fewer built-in tools and features, which may necessitate additional plugins or custom implementations.
Learning Curve for Complex Applications
While Flask is easy to learn for simple applications, it can become complex to manage as the application grows, requiring a good understanding of design patterns and software architecture.

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 Flask

Overall verdict

Flask is a good choice for developers looking for a lightweight and flexible framework for building web applications, particularly if they value simplicity and control over out-of-the-box features.

Why this product is good

Flask is a microframework for Python, offering simplicity and flexibility, making it a good choice for small to medium-sized applications.
It has a simple core with easy-to-add extensions, allowing developers to customize their applications as needed.
Flask's lightweight nature means it has a small overhead, leading to faster development cycles and easier debugging.
It has a strong community and excellent documentation, providing ample resources for learning and troubleshooting.

Recommended for

Developers who prefer Python and want a minimalist approach to web development.
Those working on small to medium-sized applications or microservices.
Developers who appreciate a modular and extensible architecture.
Teams that require rapid prototyping or quick deployment cycles.

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.

Flask videos

+ Add

Built To Last A Life Time - Ragproper Modern Glass Flask Review

Plotly videos

+ Add

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

Category Popularity

0-100% (relative to Flask and Plotly)

Flask

Plotly

Developer Tools

100 100%

Developer Tools

0% 0

Data Visualization

0 0%

Data Visualization

100% 100

Web Frameworks

100 100%

Web Frameworks

0% 0

Data Dashboard

0 0%

Data Dashboard

100% 100

User comments

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

Reviews

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

Flask Reviews

The 20 Best Laravel Alternatives for Web Development

Flask is the micro that’s got your back without trying to run the show. It comes with the essentials but trusts you to pick your tools — no baggage attached, truly Pythonic at heart.

Source: tms-outsource.com

Top 9 best Frameworks for web development

The best frameworks for web development include React, Angular, Vue.js, Django, Spring, Laravel, Ruby on Rails, Flask and Express.js. Each of these frameworks has its own advantages and distinctive features, so it is important to choose the framework that best suits the needs of your project.

Source: www.kiwop.com

25 Python Frameworks to Master

You’ll also have access to some extension packages like Flask-RESTful, which adds support for building powerful REST APIs, and Flask-SQLAlchemy, a convenient way to use SQLAlchemy in your flask app.

Source: kinsta.com

3 Web Frameworks to Use With Python

Flask is a micro web framework for building web applications with Python. Here is the official web page of Flask.

Source: www.stratascratch.com

Top 10 Phoenix Framework Alternatives

Flask is a micro-framework, i.e., it does not bundle tools and libraries and instead uses third party libraries to deliver functionalities.

Source: blog.back4app.com

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 that’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

Flask might be a bit more popular than Plotly. We know about 42 links to it since March 2021 and only 33 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.

Flask mentions (42)

PSET 9 Finance - What is "disable response caching" and the function they ask to notice
"After configuring Flask, notice how this file disables caching of responses (provided you’re in debugging mode, which you are by default in your code50 codespace), lest you make a change to some file but your browser not notice. ". Source: about 2 years ago
How to Send an Email in Python
Flask, which offers a simple interface for email sending— Flask Mail. (Check here how to send emails with Flask). - Source: dev.to / over 2 years ago
Plotting Bookmarks with Flask, Matplotlib, and OAuth 2.0
Lang="en"> Plot Bookmarks!{% block title %}{% endblock %} rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.2.1/css/bootstrap.min.css" /> class="container"> Plot Bookmarks by Date {% block containercontent %}{% endblock %} /> class="footer"> class="text-muted"> >This is a... - Source: dev.to / almost 3 years ago
Determining what version of Flask is installed
What's the easiest way to determine which version of Flask is installed? Source: about 3 years ago
What is the point of uWSGI?
I'm looking at the WSGI specification and I'm trying to figure out how servers like uWSGI fit into the picture. I understand the point of the WSGI spec is to separate web servers like nginx from web applications like something you'd write using Flask. What I don't understand is what uWSGI is for. Why can't nginx directly call my Flask application? Can't flask speak WSGI directly to it? Why does uWSGI need to get... Source: about 3 years ago

Plotly mentions (33)

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 / 3 months 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 / 5 months ago
Build a Stock Dashboard in less than 40 lines of Python code!🤓
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 / 7 months 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 1 year ago
Python equivalent to power bi/power query?
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago