Streaming File Uploads and Downloads with FastAPI: A Practical Guide

Handling large files efficiently when uploading or downloading is a common requirement for modern APIs. FastAPI, built on top of Starlette, provides excellent support for streaming file uploads and downloads, which helps minimize memory usage, improve responsiveness, and enable scalable file handling.

This article covers how to implement streaming file uploads and downloads in FastAPI, best practices to handle large files without loading everything into memory at once, and practical code examples.

Why Streaming File Uploads and Downloads?

When dealing with large files, reading the entire content into memory can lead to:

• High memory consumption, possibly crashing your server
• Increased latency, as the server waits for the entire file before responding
• Poor scalability under concurrent requests

Streaming solves this by processing data chunks as they arrive or as they are sent, reducing memory footprint and accelerating response times.

Streaming File Uploads with FastAPI

Using UploadFile for Efficient Uploads

FastAPI’s UploadFile uses Starlette’s UploadFile internally, which wraps a SpooledTemporaryFile object allowing efficient access to uploaded file data without loading it fully into memory.

Basic Streaming Upload Example

Here’s how to write an endpoint that saves an uploaded file by reading it in manageable chunks asynchronously:

from fastapi import FastAPI, File, UploadFile, HTTPException, status
import aiofiles  # Async file IO library
import os
app = FastAPI()
CHUNK_SIZE = 1024 * 1024  # 1 MB chunks
@app.post("/upload/")
async def upload_file(file: UploadFile = File(...)):
    filename = os.path.basename(file.filename)
    file_location = f"./uploaded_files/{filename}"
    os.makedirs(os.path.dirname(file_location), exist_ok=True)
try:
        async with aiofiles.open(file_location, "wb") as out_file:
            while True:
                chunk = await file.read(CHUNK_SIZE)  # Read chunk
                if not chunk:
                    break
                await out_file.write(chunk)  # Write chunk
    except Exception:
        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
                            detail=f"Error uploading file {filename}")
    finally:
        await file.close()
return {"filename": filename, "message": "Upload successful"}

Key Points:

• UploadFile.read() reads asynchronously in chunks.
• aiofiles allows writing files asynchronously, so the event loop stays responsive.
• The file is never fully loaded in memory.
• Proper error handling and resource cleanup with finally is used.

Handling Large Files (>3GB)

To upload very large files (e.g., ≥3GB) without buffering:

• Use streaming form data parsers like streaming_form_data for advanced fine-grained control.
• Limit and validate max file sizes by counting bytes as data streams in.
• Avoid synchronous/blocking code in upload handlers to keep FastAPI’s event loop healthy.

An example implementation using streaming_form_data allows streaming directly to disk as data arrives, avoiding loading the full file even into temporary memory.

Streaming File Downloads with FastAPI

For downloading large files, FastAPI provides StreamingResponse, which streams file content in chunks to the client.

Basic Streaming File Download Example

from fastapi import FastAPI, Response
from fastapi.responses import StreamingResponse
import aiofiles
import os
app = FastAPI()
CHUNK_SIZE = 1024 * 1024  # 1 MB
async def file_iterator(file_path: str):
    async with aiofiles.open(file_path, "rb") as f:
        while True:
            chunk = await f.read(CHUNK_SIZE)
            if not chunk:
                break
            yield chunk
@app.get("/download/{filename}")
async def download_file(filename: str):
    file_path = f"./uploaded_files/{os.path.basename(filename)}"
    if not os.path.exists(file_path):
        return Response(content="File not found", status_code=404)
return StreamingResponse(file_iterator(file_path), 
                             media_type="application/octet-stream",
                             headers={"Content-Disposition": f"attachment; filename={filename}"})

How this works:

• file_iterator is an async generator reading file chunks.
• StreamingResponse consumes this iterator, sending data chunk-by-chunk.
• The client starts receiving data immediately, no need to wait for full file read.
• Proper Content-Disposition header triggers browser download.

Additional Tips and Best Practices

• Set reasonable chunk sizes (e.g., 1MB to 4MB) to optimize throughput and memory use.
• Use async I/O libraries like `aiofiles` to avoid blocking the event loop.
• Validate file names and avoid directory traversal security issues by sanitizing inputs.
• Handle client disconnects gracefully during uploads/downloads.
• For very large production-grade file uploads, consider specialized streaming libraries and middlewares that support upload progress and rich validation.
• Use content length limits via reverse proxies (e.g., Nginx) and FastAPI middleware for security.
• Implement upload resumption and chunked uploads if your clients require fail-safe large file uploads.

Streaming file uploads and downloads with FastAPI help build scalable and memory-efficient APIs for handling large files without blocking or crashing your server. Leveraging async streaming patterns and smart chunking techniques is essential for production-grade file handling.

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