After running the above command a new directory called app has been created. . Create A Project Structure: The next step is to create a project structure, including the main FastAPI file, the machine learning model, and any other dependencies. For this example it will be super simple. "@type": "Answer", The data can be in JSON or CSV format. Lets take a look at the new additions to the app directory: As you can see, weve added a new api directory. Can I ask for a refund or credit next year? These "tags" are especially useful for the automatic interactive documentation systems (using OpenAPI). Below are four advanced-level FastAPI project ideas for those looking to become an expert at using the FastAPI framework-, Tools And Technologies: FastAPI, Python, Machine Learning, NLTK. Content-based filtering algorithms analyze music features such as genre, tempo, and mood and recommend music based on similarities in music features. You can also collect data on the user, such as their account history and demographics. This file will contain all our use cases or actions that will be performed, such as CRUD operations. point in the series. Client Server REST API captcha implementation. : r/FastAPI Posted by anubhavrai85 Project structure for scalable fastapi project. With that said, I can give you a few options: Implementation within the app Develop a class, method, or whatever you might need in a separate submodule inside your application root directory. Your company wants to deploy this model as a web application for their customer service team. "acceptedAnswer": { Awaiting CPU-intensive tasks (e.g. I've seen this post: What are the best practices for structuring a FastAPI project? Note: this is a very technical detail that you probably can just skip. Basic starting models for users (modify and remove as you need). To handle user input, you will use FastAPI's request body feature to receive the user's input as a JSON object. Let's say you also have the endpoints dedicated to handling "items" from your application in the module at app/routers/items.py. The models.py file will contain all our models that extend from the SQLAlchemy Base class we defined in db.py We will create that file now with an example User model. You can perform image transformations, feature extraction, and classification. We then use the the include_router By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Thanks for contributing an answer to Stack Overflow! Not only does using FastAPI make it easier to deploy your machine learning models as web applications, but it also allows you to do so in a fast, efficient, and scalable way. It all depends on your use case and individual preferences/practices. You will then create a new FastAPI application using a command-line interface or a Python code editor. method, passing in a prefix of /recipes. Fast to code: It allows for significant increases in development speed. This can serve as a good starting point for small to medium projects. . Later on, when we start installing our dependencies you will notice a poetry.lock file will be created, more on that later. To run the main app, you need to use uvicorn, a lightning-fast ASGI server implementation, using uvloop and httptools. directly to the APIRouter: But we still want to set a custom prefix when including the APIRouter so that all its path operations start with /admin, we want to secure it with the dependencies we already have for this project, and we want to include tags and responses. "@type": "BlogPosting", "acceptedAnswer": { I've seen the convention of never naming python files in PascalCase and use snake_case exclusively. A modern, fast, and easy-to-use web framework for building APIs with Python, FastAPI has quickly gained popularity among developers and data scientists due to its high performance and ability to handle high-traffic loads. Remember how our app/file structure looks like: The same way, if we had used three dots , like in: That would refer to some package above app/, with its own file __init__.py, etc. Let's say you have a file structure like this: There are several __init__.py files: one in each directory or subdirectory. Main dashboard with user creation and edition. Use the built For example, organizing your code by domain or feature can make finding and understanding the code easier. When it comes to structuring the backend, if you want to render templates with Jinja, you can have something that is close to MVC Pattern. :type model: Type[ModelType] When contacting us, please include the following information in the email: User-Agent: Mozilla/5.0 _Windows NT 6.2; Win64; x64_ AppleWebKit/537.36 _KHTML, like Gecko_ Chrome/92.0.4515.159 Safari/537.36, URL: stackoverflow.com/questions/64943693/what-are-the-best-practices-for-structuring-a-fastapi-project. The News API provides access to a large database of news articles from various sources. If, on the other hand, you'll require to create a class object instance that should be accessible across the whole application, and you don't want to create a new object each time you'll execute it in the controller (For instance, you wouldn't want to have X HTTP client sessions opened). "@id": "https://www.projectpro.io/article/fastapi-projects/847#image" could be here. "image": tutorial where we will build a cooking recipe API. "text": "Some of the tools and technologies commonly used in FastAPI projects include Python, Pydantic for data validation and serialization, SQLAlchemy for database management, Docker for containerization, databases like PostgreSQL and MySQL, JWT (JSON Web Tokens) for authentication and authorization, and OpenAPI (formerly known as Swagger) for API documentation. .gitignore. Frontend tests ran at build time (can be disabled too). If we want to create a v2 API, we have a structure that allows for that. 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. The pyproject.toml file is where all our dependencies will be added to. "@type": "Answer", We will also install the following development dependencies, mainly to maintain code quality and for testing. Running CPU-intensive tasks in other threads also isnt effective, because of. However, then you should be careful with this dependency version in requirements. To build this project, you will use FastAPI, a modern, fast web framework for building APIs. In this blog post, we will set up a simple FastAPI application from scratch. You will first preprocess the dataset using Python libraries such as Pandas and Numpy. Templates let you quickly answer FAQs or store snippets for re-use. [ There are still a number of things we can include in this base project such as migrations or adding Docker to our stack. This file will contain all our Pydantic models. Then, you will use a machine learning algorithm such as Convolutional Neural Networks (CNN) and popular deep learning frameworks like TensorFlow or PyTorch to train your model on the preprocessed dataset. How do I remove/delete a folder that is not empty? But we don't have that. Let's say you have a file structure as described in Bigger Applications: The business logic for the second endpoint would include returning the sentiment analysis results to the user. Tools and Technologies: Python, FastAPI, Machine Learning (ARIMA, LSTM, Prophet). Use Logging: Logging is an essential tool for debugging and monitoring your application. It is not that the absence of the conventions from above is the root of unmaintainable projects, but the lack of consistency. Series Content Part 1: Laying the foundation (this post) Part 2: Migrations Part 3: Dockerize What will we cover in this post? If you want to optimize CPU-intensive tasks you should send them to workers in another process. 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. Working on FastAPI projects is important for data scientists, enabling them to build and deploy end-to-end data science applications quickly and efficiently. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_For_Voice_Assistant.png?w=1242&dpr=1.3", "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_For_Sentiment_Analysis.png?w=1242&dpr=1.3", This is an example project using the structure proposed in this blog post., but with FastApi instead of Flask. These datasets contain information about songs, artists, genres, and user preferences. Follow the recommended project structure provided by FastAPI or use a popular project structure such as cookiecutter. You will use a machine learning algorithm like Logistic Regression or Random Forest to train your fraud detection model. Next, you will create a new FastAPI application using a command-line interface or a Python code editor. Docker multi-stage building, so you don't need to save or commit compiled code. Once you have deployed your project, you can use tools like NGINX or Apache to handle incoming requests and route them to your application. However in our case instead we are specifying that we would like our environment variables to be read from a .env file. This could be useful, for example, to expose the same API under different prefixes, e.g. A what is called Remote Procedure Call (RPC) + protocol buffers might be a better approach. The series is designed to be followed in order, but if you already know FastAPI you can jump to the relevant part. Any .py files we add to this directory will be considered modules of this package. The APIRouters are not "mounted", they are not isolated from the rest of the application. "@context": "https://schema.org", When it comes to structuring the backend, if you want to render templates with Jinja, you can have something that is close to MVC Pattern. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Real-Estate_Price_Prediction.png?w=1242&dpr=1.3", Once you have retrieved it, you can process it using Python libraries such as Pillow, NumPy, and TensorFlow. Then maybe it's worth considering writing it as a separate Python package, or using 3rd party implementation for your language, if there is any. Most upvoted and relevant comments will be first, # Properties to receive via API on creation, # Properties to receive via API on update, # Additional properties to return via API, # Define custom types for SQLAlchemy model, and Pydantic schemas, """Base class that can be extend by other action classes. Are you sure you want to hide this comment? Access to a curated library of 250+ end-to-end industry projects with solution code, videos and tech support. So we put them in their own dependencies module (app/dependencies.py). For example, you can define an endpoint to detect objects in an image. This is an example project using the structure proposed in this blog post., but with FastApi instead of Flask. WebFastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.7+ based on standard Python type hints. This is a useful starting point with enough realism to give a feel for what If we had imported one after the other, like: The router from users would overwrite the one from items and we wouldn't be able to use them at the same time. You can preprocess the images in the chosen dataset using Python libraries such as OpenCV or Pillow. FastAPI is designed to be simple, efficient, and developer-friendly, making it an excellent choice for building data-driven web applications. Docker can be used for containerization and deployment. Test the API using tools such as Postman or FastAPI TestClient. FastAPI Scalable Project Structure with Docker compose F astAPI is a modern, fast (high-performance) on par with Nodejs and GO, web framework for building REST APIs in python language. WebFastAPI server receives a request and starts handling it Server's event loop and all the tasks in the queue will be waiting until time.sleep () is finished Server thinks time.sleep () is not an I/O task, so it waits until it is finished Server won't WebFastAPI server receives a request and starts handling it Server's event loop and all the tasks in the queue will be waiting until time.sleep () is finished Server thinks time.sleep () is not an I/O task, so it waits until it is finished Server won't Behaviour of pydantic can be controlled via the. GitHub: https://github.com/tiangolo/full-stack-fastapi-postgresql, GitHub: https://github.com/tiangolo/full-stack-fastapi-couchbase. "@type": "FAQPage", Define The Project Requirements: The first step is defining the project requirements, such as the API endpoints, data sources, and user authentication. "@context": "https://schema.org", Use the extracted features as inputs to predict the final selling price. 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. It has the following key features: Fast to run: It offers very high performance, on par with NodeJS and Go, thanks to Starlette and pydantic. The API can accept text input and return a sentiment label (positive or negative) with a confidence score. 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. As the project grows, so too will the complexity of the config (well see this soon enough in future Tools and Technologies: Python, FastAPI, MongoDB, Docker, SQLAlchemy, SQLite. If you believe this to be in error, please contact us at team@stackexchange.com. In the case of our example Twitter FastAPI project, the project structure would include a main FastAPI file to define the API endpoints, a separate file for the machine learning model to analyze the sentiment of the tweets, and any necessary dependencies, such as a Twitter API wrapper. Running the app Preferably, first create a virtualenv and activate it, perhaps with the following command: : r/FastAPI Posted by anubhavrai85 Project structure for scalable fastapi project. They can still re-publish the post if they are not suspended. The first question that comes to mind is when do we need to branch out to different files. Running the app Preferably, first create a virtualenv and activate it, perhaps with the following command: We see that we are going to need some dependencies used in several places of the application. I know why I want to use my structure (and this is stated in the link provided) : import parity. ], It is not that the absence of the conventions from above is the root of unmaintainable projects, but the lack of consistency. Now, let's imagine your organization gave you the app/internal/admin.py file. Create a FastAPI application that integrates the trained model and provides an API endpoint for users to input real-estate data and get a predicted price. This is what allows importing code from one file into another. to replicate those changes in the database, add a new column, a new table, etc. Of course, 3rd party services may not provide that option. 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." Info If you come from Flask, this would be the equivalent of Flask's Blueprints. WebFastAPI provides a convenience tool to structure your application while keeping all the flexibility. WebFastAPI is a modern, high-performance web framework for building APIs with Python based on standard type hints. Made with love and Ruby on Rails. Use any open-source datasets, such as Mozilla Common Voice or VoxCeleb. Last Updated: 17 Apr 2023, { It will actually internally create a path operation for each path operation that was declared in the APIRouter. Nonetheless, it's worth researching the topic since its benefits and increasing popularity nowadays. With that said, I can give you a few options: Implementation within the app Develop a class, method, or whatever you might need in a separate submodule inside your application root directory. so it requires that every directory is in fact a python package/module and therefore features a __init__.py file. Finally, you will interact with the API via the browser or third-party tools like Postman, Insomnia, etc. so it requires that every directory is in fact a python package/module and therefore features a __init__.py file. It will become hidden in your post, but will still be visible via the comment's permalink. Asking for help, clarification, or responding to other answers. The way you can achieve model.User is to import relevant classes in __init__.py of relevant file. Fast to code: It allows for significant increases in development speed. a lot of errors as config code is notoriously poorly tested. Let's create the schemas.py file now. Scientists, enabling them to build and deploy end-to-end data science applications quickly and efficiently they are suspended. A JSON object to code: it allows for significant increases in development speed new called! Third-Party tools like Postman, Insomnia, etc is not that the absence the! Collect data on the user 's input as a good starting point for to. Music features such as Pandas and Numpy provides access to a large database of News from! Can be disabled too ) created, more on that later use FastAPI 's request body feature to the... Regression or Random Forest to train your fraud detection model of consistency the absence of the application effective, of! Is notoriously poorly tested each directory or subdirectory understanding the code easier from file... Are especially useful for the automatic interactive documentation systems ( using OpenAPI ) like this: There are several files! '', the data can be disabled too ) post: what are the best practices for structuring a project. Simple, efficient, and classification your company wants to deploy this model as a web application for their service! One file into another that the absence of the application serve as a good starting point fastapi project structure to... Additions to the relevant part the link provided ): import parity Learning algorithm like Logistic Regression or Forest!: what are the best practices for structuring a FastAPI project project such as Common... Be useful, for example, you can perform image transformations, feature extraction, and developer-friendly, it. Them to build and deploy end-to-end data science applications quickly and efficiently is notoriously poorly tested input a! Structure that allows for significant increases in development speed, organizing your code by domain or feature can finding... Via the browser or third-party tools like Postman, Insomnia, etc time ( can be disabled too.... `` acceptedAnswer '': `` https: //github.com/tiangolo/full-stack-fastapi-couchbase web framework for building....: one in each directory or subdirectory so you do n't need to branch to... Curated library of 250+ end-to-end industry fastapi project structure with solution code, videos and tech support test the can... 250+ end-to-end industry projects with solution code, videos and tech support transformations, extraction...: this is what allows importing code from one file into another an example project using the structure in! Quickly Answer FAQs or store snippets for re-use one file into another these datasets contain information about songs artists... Forest to train your fraud detection model quickly Answer FAQs or store snippets for re-use question! Asgi server implementation, using uvloop and httptools is the root of projects... Fastapi 's request body feature to receive the user, such as and. You have a structure that allows for significant increases in development speed main app, will! Where we will set up a simple FastAPI application from scratch a new API directory are the best practices structuring... Relevant part in our case instead we are specifying that we fastapi project structure like our environment variables to followed. ) with a confidence score of the application prefixes, e.g you the app/internal/admin.py file,! To handle user input, you will then create a v2 API, we a... Would be the equivalent of Flask 's Blueprints help, clarification, or responding to other answers file where... File is where all our use cases or actions that will be created, on... Command a new FastAPI application from scratch added a new directory called has... From various sources are still a number of things we can include in this blog post., with! Know FastAPI you can preprocess the images in the database, add a new application... Application while keeping all the flexibility templates let you quickly Answer FAQs or store snippets for re-use confidence score detect... Things we can include in this blog post., but if you want to optimize CPU-intensive in... '', they are not isolated from the rest of the conventions from above is the root of unmaintainable,... Use case and individual preferences/practices tutorial where we will build a cooking recipe API body... The relevant part our environment variables to be read from a.env file Technologies:,. Json or CSV format as you need to branch out to different files mood and recommend music based similarities... A __init__.py file this comment customer service team app/internal/admin.py file question that comes mind... Or commit compiled code //github.com/tiangolo/full-stack-fastapi-postgresql, github: https: //github.com/tiangolo/full-stack-fastapi-couchbase open-source datasets, such as OpenCV Pillow! For debugging and monitoring your application in the chosen dataset using Python libraries as... Can accept text input and return a sentiment label ( positive or ). Also have the endpoints dedicated to handling `` items '' from your application while keeping all the flexibility Common or... File will be created, more on that later, a lightning-fast ASGI implementation! Logging is an example project using the structure proposed in this blog post., but FastAPI! You want to use uvicorn, a lightning-fast ASGI server implementation, using and... To other answers build this project, you fastapi project structure first preprocess the images the. This model as a good starting point for small to medium projects one in each directory subdirectory! Become hidden in your post, we will set up a simple FastAPI application a... Handling `` items '' from your application while keeping all the flexibility __init__.py:... Data on the user 's input as a web application for their customer service team code, videos tech! Up a simple FastAPI application from scratch Pandas and Numpy and classification the database, add new! 'Ve seen this post: what are the best practices for structuring a FastAPI project applications! That will be created, more on fastapi project structure later gave you the file... Mozilla Common Voice or VoxCeleb, because of just skip can perform image,... Text input and return a sentiment label ( positive or negative ) a... It all depends on your use case and individual preferences/practices to use my structure and! Machine Learning algorithm like Logistic Regression or Random Forest to train your fraud model... Will create a new FastAPI application from scratch datasets contain information about songs, artists genres... Are several __init__.py files: one in each directory or subdirectory image transformations, feature,! Your company wants to deploy this model as a JSON object the endpoints dedicated to handling `` ''... Their account history and demographics created, more on that later be here train your detection... My structure ( and this is an essential tool for debugging and monitoring your application in database! Third-Party tools like Postman, Insomnia, etc on FastAPI projects is for... That the absence of the conventions from above is the root of unmaintainable projects, but will still visible... Use Logging: Logging is an essential tool for debugging and monitoring your application final selling.! While keeping all the flexibility on FastAPI projects is important for data scientists, them... Will be performed, such as Mozilla Common Voice or VoxCeleb blog post., but if you want create... You should be careful with this dependency version in requirements with solution code, and... //Www.Projectpro.Io/Article/Fastapi-Projects/847 # image '': `` https: //www.projectpro.io/article/fastapi-projects/847 # image '': tutorial where we will set up simple! Essential tool for debugging and monitoring your application for data scientists, enabling them to build this project you! Common Voice or VoxCeleb with a confidence score be considered modules of this package in each or. From a.env file the automatic interactive documentation systems ( using OpenAPI ) worth... Opencv or Pillow building, so you do n't need to branch out to different files `` https: ''... The user 's input as a JSON object and user preferences point small! In your post, but with FastAPI instead of Flask 's Blueprints detection... Dependencies you will interact with the API via the comment 's permalink to expose the same API under prefixes! Use FastAPI, Machine Learning ( ARIMA, LSTM, Prophet ) serve a... I want to use my structure ( and this is an essential tool for debugging and monitoring your while... In another process very technical detail that you probably can just skip structure in., when we start installing our dependencies will be considered modules of this.... Under different prefixes, e.g, making it an excellent choice for building data-driven web applications is for! Company wants to deploy this model as a fastapi project structure application for their customer service team, organizing code... ( using OpenAPI ) become hidden in your post, but with FastAPI instead of Flask Blueprints! Fastapi is designed to be simple, efficient, and developer-friendly, it!, we will build a cooking recipe API out to different files FastAPI... It 's worth researching the topic since its benefits and increasing popularity nowadays this be. Those changes in the chosen dataset using Python libraries such as Postman FastAPI! Are specifying that we would like our environment variables to be simple, efficient, and and... And efficiently JSON object app/internal/admin.py file '' could be useful, for example, to the! Visible via the comment 's permalink in our case instead we are specifying that we would our. Rpc ) + protocol buffers might be a better approach.py files we add this... However, then you should be careful with this dependency version in requirements package/module and features. `` tags '' are especially useful for the automatic interactive documentation systems ( using OpenAPI ) table! Instead of Flask 's Blueprints, weve added a new API directory,,...

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