FastAPI VS HeavyM

• High Performance
  Built on Starlette and Pydantic, FastAPI is one of the fastest frameworks for Python, providing high performance due to its asynchronous request handling.
• Automatic Interactive API Documentation
  FastAPI automatically generates interactive API documentation via Swagger UI and ReDoc, which are very helpful for development and testing.
• Type Checking and Validation
  With Pydantic models and Python type hints, FastAPI provides automatic data validation and type checking, reducing the chance of runtime errors.
• Ease of Use
  Its syntax and design make it easy to learn for Python developers, offering a smooth development experience while reducing boilerplate code.
• Asynchronous Support
  FastAPI supports asynchronous programming, allowing for better performance for I/O-bound operations, making it optimal for handling many simultaneous connections.
• Extensive Documentation
  It has comprehensive and well-structured documentation, which is very useful for both beginners and advanced users.
• Community and Ecosystem
  FastAPI has a growing community and ecosystem, with many plugins and integrations available to extend its functionality.

Possible disadvantages

• Learning Curve for Asynchronous Programming
  Although FastAPI itself is easy to learn, grasping the concepts of asynchronous programming in Python can be challenging for beginners.
• Complex Dependencies
  Using Pydantic for advanced validation can make the request models complex, requiring a deeper understanding of Pydantic and its functionalities.
• Early Stage Libraries
  Some third-party libraries and extensions specifically tailored for FastAPI might still be in early stages of development and lack long-term stability.
• Limited Real-World Examples
  Although the documentation is extensive, there might be limited real-world examples and case studies readily available compared to more mature frameworks.
• Deployment Complexity
  Deploying FastAPI applications might be more complex in comparison to traditional synchronous frameworks, mainly due to the need for asynchronous server setups.

• User-Friendly Interface
  HeavyM offers an intuitive and easy-to-navigate interface, allowing users of all skill levels to create impressive visual projections without a steep learning curve.
• Real-Time Projection Mapping
  The software provides real-time projection mapping capabilities, enabling users to see instant results and make adjustments on the fly for live events and performances.
• Wide Range of Effects
  HeavyM includes a diverse collection of built-in effects and animations, allowing users to enhance their projections with creative visuals easily.
• Compatibility with Multiple Projectors
  The software supports multiple projectors, making it suitable for complex setups requiring seamless integration and coordination between different projection sources.
• Regular Updates and Support
  HeavyM is frequently updated with new features and improvements, and the development team provides reliable customer support for troubleshooting and guidance.

Possible disadvantages

• Limited Advanced Features
  While suitable for basic and intermediate projection mapping, HeavyM may lack some advanced features available in more professional software, which could be a limitation for experienced users seeking complex functionalities.
• Performance on Older Hardware
  The software may experience performance issues on older or less powerful hardware, potentially limiting its usability for users without up-to-date computer systems.
• Cost Considerations
  For individual artists or smaller organizations, the cost of HeavyM may be a concern, particularly if they require additional licenses or features available only in higher-tier packages.
• Learning Curve for Advanced Use
  Despite its user-friendly design, mastering more advanced projection mapping techniques using HeavyM might still require a learning curve, which could be a barrier for some users.
• Limited Export Options
  Export options in HeavyM might be limited compared to other software, which could be a drawback for users needing specific formats or integrations with other tools and workflows.

FastAPI from the ground up

More videos

HeavyM Review

More videos

• Rated 5/5 by Kurslog team
  SaaSHub review

  · Apr 2026

  When our backend team needs to build services for data parsing, aggregators, or high-load APIs, FastAPI is our absolute go-to choice. It completely lives up to its name-development speed is outstanding. The...

• The 20 Best Laravel Alternatives for Web Development
  tms-outsource.com · Jan 2024

  FastAPI, as the name hints, is a swift mover. Built on Starlette, it’s all about speed and performance with Python. Crafting API masterpieces at the speed of light, now that’s something.

• 25 Python Frameworks to Master
  kinsta.com · Oct 2023

  Since its release in 2018, it has rapidly gained popularity due to its great performance and simplicity. In fact, according to PyPi Stats, FastAPI has over 9 million monthly downloads, surpassing even full-stack...

View more

• 7 Best Projection Mapping Software 2024 (#1 Video Mapper)
  contentmavericks.com · Nov 2023

  Other options include Resolume Arena, which excels in live performances and offers an ultra-fast video player for real-time video mixing. Resolume Avenue, a sister program to Arena, also provides a reliable visual...

• Exploring the top 10 World of LCD Projector Mapping Softwares
  www.sam-inspire.com · Oct 2023

  HeavyM is another popular choice for professional projection mapping. With a range of customizable effects, this software allows users to dynamically transform static objects into dynamic canvases. Its user-friendly...

• Top 7 Alternatives to MadMapper – Amplify Your Projection Mapping Projects!
  www.uubyte.com · Sep 2023

  HeavyM is a projection mapping software specifically designed for creating captivating visuals and light shows. It offers a user-friendly interface and a wide range of effects and filters to enhance your projection...

View more

• Clean Architecture in Python with FastAPI, FastStream, and Dishka

  Using FastAPI, FastStream, and dishka lets us follow Clean Architecture principles and almost avoid leaky abstractions. The prototype also used Pydantic and SQLAlchemy. I do not focus on them because these technologies are already... - Source: dev.to / 7 days ago

• QueuePool Limit Reached - When FastAPI Runs Out of Database Connections

  If your FastAPI app talks to a database through SQLAlchemy, chances are high you will meet it sooner or later. Not on your machine, of course. It shows up in production, after a few quiet hours, under load. And the reflex is always the... - Source: dev.to / 13 days ago

• ContexteTech is now open source: a hub for everything that adapts an AI model

  API: FastAPI with async SQLAlchemy, PostgreSQL 17 for data, Redis for caching and rate limits. The cache is invalidated by a single version counter bumped on every write: no fine-grained purging to manage. - Source: dev.to / 21 days ago

View more

Tracking HeavyM since Mar 2021.