Finally, we have our tests directory that contains all the unit tests. Start by creating a new " fastapi-vue " project folder and then scaffold a Vue project using the Vue CLI. This here is an extremely basic Python FastAPI application. # Create all tables in the database. If you want to optimize CPU-intensive tasks you should send them to workers in another process. We can also add path operations directly to the FastAPI app. This post is part 8. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Music_Recommendation.png?w=1242&dpr=1.3", You will define API endpoints using FastAPI's decorator syntax, specifying the request method and the response model. Then, you must connect to a Postgres database to perform CRUD operations. We then use the the include_router For example, using the aiohttp library for asynchronous HTTP requests can help improve performance. No matter what rules you have the only rule that should be followed is being consistent with your rules. These "tags" are especially useful for the automatic interactive documentation systems (using OpenAPI). : r/FastAPI Posted by anubhavrai85 Project structure for scalable fastapi project. You can deploy a FastAPI project using any cloud provider or hosting service, such as AWS, Google Cloud, Microsoft Azure, etc., that supports Python and provides a WSGI server such as Gunicorn or Uvicorn. Series Content Part 1: Laying the foundation (this post) Part 2: Migrations Part 3: Dockerize What will we cover in this post? In this section, we will install only the required dependencies to get a basic CRUD ( Create, Read, Update, Delete) application going. One of the fastest Python frameworks available. You can also use pre-trained TTS models from open-source libraries such as Mozilla TTS or DeepSpeech. For example, the project generator Full Stack FastAPI PostgreSQL might be a better alternative, as it is actively maintained and used. A Basic Python FastAPI Backend App. Project structure for scalable fastapi project. Of course, 3rd party services may not provide that option. Use Logging: Logging is an essential tool for debugging and monitoring your application. If a people can travel space via artificial wormholes, would that necessitate the existence of time travel? Once unpublished, this post will become invisible to the public and only accessible to Alexander van Zyl. Project Solution Approach: To build the Movie Recommendation API project, you would need a dataset containing information about movies, such as the MovieLens dataset, IMDb dataset, or TMDB dataset. A project generator will always have a very opinionated setup that you should update and adapt for your own needs, but it might be a good starting point for your project. You will implement time-series forecasting algorithms such as ARIMA, LSTM, or Prophet to predict future stock market trends using Python libraries such as statsmodels, Keras, or Prophet. FastAPI has become a go-to choice for building APIs in the data science industry with its support for asynchronous programming and automatic API documentation. For example, organizing your code by domain or feature can make finding and understanding the code easier. Here is what you can do to flag alexvanzyl: alexvanzyl consistently posts content that violates DEV Community's I know why I want to use my structure (and this is stated in the link provided) : import parity. For example, defining a dependency for a database connection allows you to easily switch to a different database implementation without changing the code in the endpoint that uses the database. Use the Vue Router to create routes, render components, and manage user auth with token-based authentication. This code lives in the module app.routers.items, the file app/routers/items.py. With something like axios or the Javascript's fetch you can easily talk with your backend from anywhere. Later on, when we start installing our dependencies you will notice a poetry.lock file will be created, more on that later. WebFastAPI is a modern, high-performance web framework for building APIs with Python based on standard type hints. WebFastAPI is a modern, high-performance web framework for building APIs with Python based on standard type hints. This will take microseconds and will only happen at startup. And this is crucial because in FastAPI tutorials, they usually test the api with such command : uvicorn app.apy:app --reload. parts of the tutorial). We will now use a simple dependency to read a custom X-Token header: Prefer to use the Annotated version if possible. No matter what rules you have the only rule that should be followed is being consistent with your rules. And we can even declare global dependencies that will be combined with the dependencies for each APIRouter: Now we import the other submodules that have APIRouters: As the files app/routers/users.py and app/routers/items.py are submodules that are part of the same Python package app, we can use a single dot . "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Image_Recognition.png?w=1242&dpr=1.3", Source Code: Build Real Estate Price Prediction Model with NLP and FastAPI, Tools And Technologies: FastAPI, Python (NLTK, SpaCy), Machine Learning (Naive Bayes, SVM, etc.). Once you have deployed your project, you can use tools like NGINX or Apache to handle incoming requests and route them to your application. If you are building an application or a web API, it's rarely the case that you can put everything on a single file. Test the API using tools such as Postman or FastAPI TestClient. Finally, you can test your API using tools like pytest, Swagger UI or Postman and deploy it to a server using platforms like Heroku or AWS. Project Solution Approach: Start working on this sentiment analysis project by choosing a suitable dataset for sentiment analysis, such as the IMDB Movie Reviews dataset or the Amazon Product Reviews dataset. Once the API works correctly, you can deploy it using cloud services such as AWS or Heroku. These data science projects with R will give you the best idea of importance of R programming language in data science. Tools and Technologies: Python, FastAPI, Tensorflow, Google Cloud Vision. At this point, nothing has really changed in our directory structure but you will notice that the pyproject.toml file has been updated and a new poetry.lock file has been created. The APIRouters are not "mounted", they are not isolated from the rest of the application. "name": "How do I start a FastAPI project? With a wide range of Python projects and expert guidance from industry professionals, ProjectPro can help you build the skills and experience you need to succeed in the data science industry. Have a look into the FastAPI's creator template for FastAPI-Postgres App. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Real-Estate_Price_Prediction.png?w=1242&dpr=1.3", For our project example, the business logic for the first endpoint would include retrieving the tweets from the Twitter API, preprocessing the text data, and passing it to the sentiment analysis model. These datasets contain information about songs, artists, genres, and user preferences. You can also use containers such as Docker for packaging your application and dependencies. Follow The Single Responsibility Principle: Each function, class, or module in your project should have a single responsibility. We are using an invented header to simplify this example. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_For_Single_Page_App.png?w=1242&dpr=1.3", Would creating a services folder inside the v1 folder here make sense. For example, organizing your code by domain or feature can make finding and understanding the code easier. Here are a few reasons you should practice working on FastAPI projects-. The first file we will create is the main.py file, it will serve as the entry point to our application and house all our routes. so it requires that every directory is in fact a python package/module and therefore features a __init__.py file. We will also install the following development dependencies, mainly to maintain code quality and for testing. If looking at the project structure doesnt give you an idea of what the project is about, then the structure might be unclear. 5. For example, organizing your code by domain or feature can make finding and understanding the code easier. To give you a better example in my fastapi-mvc-template on startup event, I'm creating Redis and Aiohttp class object instance: which then can be used inside any controller without the need of creating them each time API method gets called: If the implementation for dealing with 3rd party APIs is bigger than a few files/classes. This is post borrows heavily from the official full-stack FastAPI postgresql cookie-cutter repo. Info If you come from Flask, this would be the equivalent of Flask's Blueprints. How do I remove/delete a folder that is not empty? But we want to be smarter and simplify the code a bit. In the end, it doesn't really matter that much as long it's a meaningful name to you and other people involved in the project. This can serve as a good starting point for small to medium projects. Containerize the application using Docker and deploy it to a cloud platform such as AWS. Note that, much like dependencies in path operation decorators, no value will be passed to your path operation function. I know why I want to use my structure (and this is stated in the link provided) : import parity. Let's create this file now under the app package directory. It will include all the routes from that router as part of it. Nonetheless, by structuring your FastAPI projects well, youll set your REST APIs up You want to have the path operations related to your users separated from the rest of the code, to keep it organized. Use A Database Abstraction Layer: If your API requires data persistence, use a database abstraction layer such as SQLAlchemy or Tortoise-ORM to make it easier to interact with the database and write maintainable code. If looking at the modules location and its name doesnt give you an idea of whats inside, then your structure is very bad. Generate a base project with Poetry. Content Discovery initiative 4/13 update: Related questions using a Machine How do you test that a Python function throws an exception? After that, you can install the FastAPI framework using a package manager like pip. In this blog post, we will set up a simple FastAPI application from scratch. This blog will walk you through the essential steps to structure a FastAPI project and explore 15 FastAPI project ideas to help you learn how to build APIs using this robust framework. },{ From building a movie recommendation API to a book library API and even a voice assistant API, this section will cover various FastAPI project ideas that showcase the power and versatility of FastAPI. Define The Project Requirements: The first step is defining the project requirements, such as the API endpoints, data sources, and user authentication. Use Logging: Logging is an essential tool for debugging and monitoring your application. 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