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Lesson
From Flask to FastAPI
Understanding the key differences between Flask and FastAPI can help developers make informed decisions on which framework to use based on their specific needs.
🚀 Performance
- FastAPI is designed to be one of the fastest web frameworks for Python, especially when it comes to I/O bound operations. It is built on top of Starlette for the web parts and Pydantic for data validation and serialization.
- Flask, on the other hand, is lightweight and flexible but does not inherently provide the same asynchronous capabilities that make FastAPI so fast.
📄 Type Annotations & Validation
- FastAPI uses Python type hints in function signatures to validate input data and serialize output data. This allows for automatic data validation, serialization, and documentation generation.
- With Flask, developers generally have to use extensions like Marshmallow to achieve similar functionality. It's more manual in comparison.
Example:
from pydantic import BaseModel
class Recipe(BaseModel):
id: int = None
name: str
ingredients: list[str]
@app.post("/recipes")
def create_recipe(recipe: Recipe):
print(recipe.id, recipe.name)
...In this example, just by using type annotations, FastAPI knows the expected shape of the data, how to validate it, and how to serialize/deserialize it. The JSON input is automatically deserialized into an object. It's similar to how ORM models define and validate the structure of the data they handle.