FastAPI UploadFile Performance Compared to Flask

UploadFile performance in FastAPI can be slower than Flask due to differences in data handling. FastAPI's UploadFile utilizes asynchronous methods that may result in bottlenecks if not handled efficiently, while Flask uses synchronous methods.

Here's why FastAPI's UploadFile can be slower:

• Blocking I/O: By default, FastAPI's UploadFile methods use blocking I/O operations, which can hinder the main thread and slow down the API.
• Data Chunking: Starlette (the underlying framework for FastAPI) uses a SpooledTemporaryFile with a default max_size of 1MB. Once data exceeds this size, it's written to a temporary file on disk, adding another level of I/O overhead.

Best Practices for Efficient File Uploads in FastAPI:

Asynchronous File Writing with aiofiles

Use asynchronous file writing with the aiofiles library to write files in a non-blocking manner. This approach improves performance, especially for large files.

Reading the File in Chunks

Consider reading the file in chunks of a specified size to avoid loading the entire file into memory. This prevents memory issues and improves performance for large file uploads.

Using run_in_threadpool()

To avoid blocking the main thread, use FastAPI's run_in_threadpool() function to perform blocking I/O operations in a separate thread. This ensures non-blocking execution of file-related tasks.

Directly Accessing Request Body as a Stream

In cases where file storage on the server is not necessary, access the request body directly as a stream using request.stream(). This method allows for efficient file handling without incurring unnecessary I/O overhead.