FastAPI VS EyeOnTask

• 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.

• Instant Invoice and Billing
  Quickly generate invoices
• Custom forms
  Built-in support to custom forms
• Dashboard
  Easy to use dashboard
• Report & Analytics
  Create insightful reports
• Job Card
  Digitalized job card
• Recurring Jobs
  Schedule recurring job calender
• Mobile app
  Available on both Android and iOS
• Communication
  Seamless channel to share messages, documents and live locations
• Clean UI
  Simple and easy to understand UI
• Automated workflow
  Customize workflow management
• Inventory Management
  Industry leading Inventory management
• Payment
  Integrated payment system
• Location Tracking
  Powerful live location tracking
• Work Orders
  Ability to manage heavy work orders
• Employee Management
  Impressive employee management system
• Equipment Management
  Hassle-free equipment and inventory management
• Easy to Use
  Very easy setup and use
• Timesheets
  Dynamic job timesheets for time tracking
• Attendance Monitoring
  Intuitive attendance management
• eSign
  On-field signature
• Scheduling
  Automated scheduling
• Customer Portal
  Impressive customer portal
• Notifications
  Real-time notifications
• Multi Language
  Supports more than 16 languages
• No Credit Needed
  easily use free version without inserting credit card details
• Free setup
  No Setup Cost
• 24/7 Support
  Round the clock support available
• Free Trial
  Free trial available for 15 days

FastAPI from the ground up

More videos

Introduction EyeOnTask

More videos

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• 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 / 2 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 / 8 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 / 16 days ago

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Tracking EyeOnTask since May 2021.