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Fast API for Web Development: 2025 Detailed Review - Aloa
Excerpt
### Cons of FastAPI Although FastAPI provides several benefits, developers may encounter some challenges and limitations. Here are the most significant ones: - **Cluttered Main File:** FastAPI tends to centralize everything in the main.py file, which can result in crowding and maintenance issues, especially as the project gets larger. As such, your team may need to improve code organization by creating dedicated files for exception handlers and router inclusion. - **DI Doesn't Support Singletons:** Although reliable, Dependency Injection (DI) lacks native support for singleton, enabling teams to manage shared resources through singleton classes manually or making use of third-party DI libraries. - **Syntax Learning Curve: ** Despite its many advantages, the framework uses a specific syntax that increases the learning curve for developers who are not familiar with asynchronous programming or standard Python type hints. It can take some time to learn the tool and enforce data models using Pydantic. - **Unintuitive Error Handling:** An occasionally confusing error-handling mechanism makes it challenging for developers to troubleshoot and debug issues. In complex applications with multiple error scenarios, this can lead to longer debugging times. - **Limited ORM Support:** Although there is support for ORMs (Object-Relational Mapping), such as SQLAlchemy and Tortoise ORM, other frameworks offer better integration with ORM to make the application and the database smoother. Despite these limitations, FastAPI's performance, scalability, and toolkit make it a strong contender for building high-quality web APIs. It is certainly worth considering in case any issues might be a dealbreaker for a particular project. … While the framework garners a few distinctions, there are a few instances concerning its unpolished updates and performance downgrades. One user noted a significantly lower request throughput compared to Node.js and Golang on the same machine during a benchmark test. Concerns were also raised about poor middleware performance and an almost 50% performance loss when using annotated dependencies.
Source URL
https://aloa.co/blog/fast-apiRelated Pain Points
Performance degradation from unpolished updates and middleware issues
6FastAPI shows significantly lower request throughput compared to Node.js and Golang on identical hardware during benchmarks. Users report poor middleware performance and approximately 50% performance loss when using annotated dependencies.
Code organization becomes unwieldy as projects scale
5FastAPI tends to centralize everything in the main.py file, causing crowding and maintenance issues. Teams need to manually create dedicated files for exception handlers and router inclusion to maintain code organization.
Steep learning curve for async programming and type hints
5FastAPI's specific syntax and reliance on asynchronous programming, standard Python type hints, and Pydantic increases the learning curve significantly for developers unfamiliar with these concepts, potentially slowing onboarding and adoption.
Limited ORM integration compared to other frameworks
5While FastAPI supports ORMs like SQLAlchemy and Tortoise ORM, integration is not as smooth as other frameworks. Developers must manually choose, configure, and ensure async compatibility with their ORM of choice.
Error handling mechanism is unintuitive and confusing
4FastAPI's error-handling mechanism is occasionally confusing, making troubleshooting and debugging challenging. Complex applications with multiple error scenarios experience longer debugging times as a result.
Dependency Injection lacks native singleton support
4FastAPI's DI system doesn't natively support singletons, forcing teams to manually manage shared resources through singleton classes or adopt third-party DI libraries.