Data Streaming with FastAPI

In this tutorial, we will explore how to implement streaming data in FastAPI, a modern web framework for building APIs with Python.

Streaming data involves transferring data in a continuous flow, rather than sending it all at once. This can be useful for handling large amounts of data, such as audio or video files, and can also improve the performance of your API.

To get started, make sure you have FastAPI installed. You can install it using pip:

pip install fastapi uvicorn

Now, let’s create a new Python file for our FastAPI application. In this example, I’ll create a file called main.py. Import the necessary modules:

from fastapi import FastAPI, Response
from fastapi.responses import StreamingResponse

Next, create an instance of the FastAPI class:

app = FastAPI()

Now, let’s define a route that will stream data. In this example, we’ll create a route that streams a large file line by line:

@app.get("/stream-data")
async def stream_data():
    def generate_data():
        with open("large_file.txt", "r") as file:
            for line in file:
                yield line

    return StreamingResponse(generate_data())

In the code above, we define a function generate_data() that reads a large text file line by line and yields each line. We then return a StreamingResponse object that streams the data using the generate_data() function.

You can now run the FastAPI application using Uvicorn:

uvicorn main:app --reload

Now, if you navigate to http://127.0.0.1:8000/stream-data in your browser, you should see the data being streamed line by line from the file.

Streaming data can be useful for various applications, such as real-time data processing, video streaming, or any scenario where handling large amounts of data efficiently is required.

In this tutorial, we’ve covered the basics of streaming data in FastAPI. You can further customize and optimize your streaming endpoints based on your specific requirements and data sources. Happy coding!