fastapi project structure
To subscribe to this RSS feed, copy and paste this URL into your RSS reader. If you are building an application or a web API, it's rarely the case that you can put everything on a single file. Should the alternative hypothesis always be the research hypothesis? "text": "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. },{ If your migrations depend on dynamically generated data, then make sure the only thing that is dynamic is the data itself, not its structure. Really cool, at least I think so! , If you have made it this far, well done! However, then you should be careful with this dependency version in requirements. And this is crucial because in FastAPI tutorials, they usually test the api with such command : uvicorn app.apy:app --reload. You can use Scikit-learn or Keras libraries to build the model. To learn more, see our tips on writing great answers. In this blog post, we will set up a simple FastAPI application from scratch. Ideally hardcoded or locked to patch version (ex. Practical Section 1 - FastAPI Project Structure and Config Practical Section 2 - API Versioning This is a more lightweight post compared the beast that is part 8 where we looked at database setup. For example, you can define an endpoint to retrieve stock market data for a given stock symbol. We will come back later and update the main.py file but for now, let's hit Ctrl+C in the terminal to stop Uvicorn and continue adding the rest of our files. This code lives in the module app.routers.items, the file app/routers/items.py. Last Updated: 17 Apr 2023, { "@type": "Question", But it's still part of the same FastAPI application/web API (it's part of the same "Python Package"). 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 final code for this post can be found on GitHub. Originally published at alexvanzyl.com. Use async/await syntax when defining endpoints and use asynchronous libraries whenever possible. If you must use sync SDK, then run it in a thread pool. Define The Project Requirements: The first step is defining the project requirements, such as the API endpoints, data sources, and user authentication. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Image_Recognition.png?w=1242&dpr=1.3", Use the built With something like axios or the Javascript's fetch you can easily talk with your backend from anywhere. Dependency calls are cached, Dont make your routes async, if you have only blocking I/O operations. What kind of tool do I need to change my bottom bracket? This can serve as a good starting point for small to medium projects. Name this submodule however you'd like (services, utils, 3rdparty, etc.). Lets start by observing the new API versioning introduced in this part of the tutorial: You should be greeted by our usual server-side rendered HTML: So far no change. point in the series. FastAPI also supports async programming, making it compatible with popular async libraries such as asyncio and aiohttp. Even if the dependencies are not added individually to each one of them. ", You will then use any of the several machine learning algorithms to train a speech recognition model, such as Hidden Markov Models (HMMs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), etc. If you enjoyed reading this article and would like to stay tuned for more, or just want to connect, follow me on twitter @alexvanzyl. But it comes directly from Starlette. "name": "What is FastAPI used for? We will now use a simple dependency to read a custom X-Token header: Prefer to use the Annotated version if possible. Before going back and updating our main.py file, let's review our final directory structure. These data science projects with R will give you the best idea of importance of R programming language in data science. You should not worry about the structure between them. Next, you will use FastAPI to create the API that connects the voice interface with the speech recognition and NLP modules. You can use MongoDB as a database to store the retrieved news articles. Tools and Technologies: Python, FastAPI, Machine Learning (Collaborative/Content-based Filtering), Tensorflow. You can find an example of Alembic in a FastAPI project in the templates from Project Generation - Template. that you already have the below installed. And then throwing modules in there for dealing with 3rd party API's. The directory structure should look like the below. Consistent & Predictable, Excessively use Pydantic for data validation, Use dependencies for data validation vs DB, Decouple & Reuse dependencies. Once the speech is recognized, natural language processing (NLP) techniques must be used to interpret the user's intent and generate appropriate responses. Pydantic models in here (as we do for the schemas) to define the app config. Docker can be used for containerization and deployment. 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. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Then, you will train the ML algorithm using the preprocessed dataset. Project Solution Approach: Start by defining the API endpoints for your Book Library API. To run the main app, you need to use uvicorn, a lightning-fast ASGI server implementation, using uvloop and httptools. Each time you implement a change to an API, you should version it for backward compatibility sake. "@type": "Answer", Finally, you will interact with the API via the browser or third-party tools like Postman, Insomnia, etc. IMHO an API calling another API may not be the best approach. And this is crucial because in FastAPI tutorials, they usually test the api with such command : uvicorn app.apy:app --reload. If this implementation is static, then you're good to go and can utilize it inside a particular controller by just doing a simple import. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Are you sure you want to hide this comment? And items.router contains the APIRouter inside of the file app/routers/items.py. And it includes all the new features and improvements. 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. 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. Next, let's create the db.py under the same directory. WebFastAPI provides a convenience tool to structure your application while keeping all the flexibility. This here is an extremely basic Python FastAPI application. The result is that in our app, each of the path operations from the admin module will have: But that will only affect that APIRouter in our app, not in any other code that uses it. The pyproject.toml file is where all our dependencies will be added to. Series Content Part 1: Laying the foundation (this post) Part 2: Migrations Part 3: Dockerize What will we cover in this post? To recap our directory structure should look something like this now. You will test the API using tools such as Swagger UI or Postman. Let's say models.__init__.py. Downloadable solution code | Explanatory videos | Tech Support. Source Code: Build An Asynchronous FastAPI To Perform CRUD on Notes. Next, you will dockerize the project, commit the code and push it to GitHub. As we cannot just isolate them and "mount" them independently of the rest, the path operations are "cloned" (re-created), not included directly. We will copy the Python .gitignore template provided by GitHub here. Next, you will define API endpoints using FastAPI's decorator syntax, specifying the request method and the response model. 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.). This creates the versioned Connect and share knowledge within a single location that is structured and easy to search. part of the tutorial). Running the app Preferably, first create a virtualenv and activate it, perhaps with the following command: clients in a more disciplined and structured way. For our Twitter FastAPI project example, the requirements could be to retrieve tweets based on user input, analyze the sentiment of the tweets using a machine learning model, and return the results to the user. Youll Load balancing between frontend and backend with, Traefik integration, including Let's Encrypt. WebA "migration" is the set of steps needed whenever you change the structure of your SQLAlchemy models, add a new attribute, etc. Under the hood, FastAPI makes use of these models to validate the incoming request body, parse the response body and generate automatic docs for our API. Project Solution Approach: There are several image recognition APIs available, such as Google Cloud Vision, AWS Rekognition, and IBM Watson Visual Recognition. Then, you must connect to a Postgres database to perform CRUD operations. Info If you come from Flask, this would be the equivalent of Flask's Blueprints. Follow The Single Responsibility Principle: Each function, class, or module in your project should have a single responsibility. 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. You want to have the path operations related to your users separated from the rest of the code, to keep it organized. 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. How do I make calls to a REST API using C#? Discover 15 End-to-End FastAPI Project Ideas by ProjectPro designed for data scientists to build scalable and efficient data science applications. Let's say you also have the endpoints dedicated to handling "items" from your application in the module at app/routers/items.py. Next, set up a database to store your book data. So, that would throw an error in our example. One of the fastest Python frameworks available. global variables are in the config (e.g.SQLALCHEMY_DATABASE_URI, FIRST_SUPERUSER). 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. 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. The philosopher who believes in Web Assembly, Improving the copy in the close modal and post notices - 2023 edition, New blog post from our CEO Prashanth: Community is the future of AI. We can also add a list of tags and extra responses that will be applied to all the path operations included in this router. This project involves building an API to retrieve and present news articles from various sources. 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. You may have noticed we import settings from config but we haven't actually created that file yet, so let's do so now. "name": "How do I start a FastAPI project? You can perform operations such as resizing, cropping, and normalization. "@type": "Question", This will take microseconds and will only happen at startup. 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. { Main dashboard with user creation and edition. The way you can achieve model.User is to import relevant classes in __init__.py of relevant file. Project Solution Approach: For this fraud detection project, you will collect transaction data, such as the transaction amount, timestamp, and location. Info: You can read more about the sessionmaker function here and as_declarative decorator here. With app.include_router() we can add each APIRouter to the main FastAPI application. },{ The first version is a "relative import": The second version is an "absolute import": To learn more about Python Packages and Modules, read the official Python documentation about Modules. You can use libraries such as Scikit-learn, Tensorflow, or PyTorch for training the ML algorithm. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Real-Estate_Price_Prediction.png?w=1242&dpr=1.3", This is an advanced usage that you might not really need, but it's there in case you do. You will create and use the Dockerfile to create an image of the FastAPI app and start the FastAPI app container. parts of the tutorial). Making statements based on opinion; back them up with references or personal experience. to import them using "relative imports". Project Solution Approach: The first step in this project is to set up a new FastAPI project using your preferred Python environment. Here we do it just to show that we can : and it will work correctly, together with all the other path operations added with app.include_router(). This is an example project using the structure proposed in this blog post., but with FastApi instead of Flask. Test The API: Once the API endpoints and business logic are implemented, test the API using automated testing tools such as pytest. It contains an APIRouter with some admin path operations that your organization shares between several projects. ex co-founder & cto at myqoob.com, from src.auth import constants as auth_constants, Project Structure. It is not that the absence of the conventions from above is the root of unmaintainable projects, but the lack of consistency. FastAPI is a great option for developing asynchronous APIs that can process several requests without blocking due to its support for asynchronous programming. So, behind the scenes, it will actually work as if everything was the same single app. "mainEntity": [{ For our Twitter FastAPI project, the API endpoints would include one to receive user input, such as the Twitter handle or keyword to search for, and another to return the sentiment analysis results. We are not adding the prefix /items nor the tags=["items"] to each path operation because we added them to the APIRouter. Choose an SQLite Database using SQLAlchemy for this project. } The other point to note from the above code snippet is that because we do not apply any versioning Generate a base project with Poetry. If looking at the modules location and its name doesnt give you an idea of whats inside, then your structure is very bad. 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. The series is designed to be followed in order, but if you already know FastAPI you can jump to the relevant part. "@type": "Answer", It all depends on your use case and individual preferences/practices. 1 Answer Sorted by: 2 There isn't really the best approach. Tools And Technologies: Python, FastAPI, Machine Learning, NLP, Google Text-to-Speech/Amazon Polly. The final file we will create for now is the actions.py file. ", This is because we also have another variable named router in the submodule users. But we don't have that. This is a more lightweight post compared the beast that is part 8 where we looked at database setup. notice that the recipe endpoints now are prefaced with /api/v1: Go ahead and have a play with the endpoints (they should all work exactly the same as the previous 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 "name": "What tools and technologies are commonly used in FastAPI projects? Let's create this file now under the app package directory. You will train your model using popular machine-learning libraries such as TensorFlow, PyTorch, or Keras. The final step is to test your API and deploy it using any popular cloud service like AWS. Tip: If you want the server to reload on file changes you can use the --reload flag, like so uvicorn app.main:app --reload, Now if we head over to a browser and hit http://127.0.0.1:8000 we will be greeted with {"message":"Hello world!"}. , But now you know how it works, so you can use relative imports in your own apps no matter how complex they are. ], How can I drop 15 V down to 3.7 V to drive a motor? : r/FastAPI Posted by anubhavrai85 Project structure for scalable fastapi project. Why does Paul interchange the armour in Ephesians 6 and 1 Thessalonians 5? WebA "migration" is the set of steps needed whenever you change the structure of your SQLAlchemy models, add a new attribute, etc. This is because we want to include their path operations in the OpenAPI schema and the user interfaces. Start by creating a new " fastapi-vue " project folder and then scaffold a Vue project using the Vue CLI. As the project grows, so too will the complexity of the config (well see this soon enough in future Then, you will train a machine learning algorithm, such as collaborative or content-based filtering, using Python-based machine learning libraries like scikit-learn or TensorFlow to generate recommendations based on user preferences. Practicing FastAPI projects can benefit any aspiring data scientist or software developer. Series Content Part 1: Laying the foundation (this post) Part 2: Migrations Part 3: Dockerize What will we cover in this post? 56.3k stars and 163k users on GitHub and 4,046,990 weekly downloads indicate the growing popularity of FastAPI! "acceptedAnswer": { If you are starting a new project from scratch, check the alternatives here. The API will analyze the image and return a response containing object detection, facial recognition, and text recognition information. A what is called Remote Procedure Call (RPC) + protocol buffers might be a better approach. Tools and Technologies: Python, FastAPI, Machine Learning (ARIMA, LSTM, Prophet). An example file structure Let's say you have a file structure like this: We see that we are going to need some dependencies used in several places of the application. : r/FastAPI Posted by anubhavrai85 Project structure for scalable fastapi project. WebFastAPI provides a convenience tool to structure your application while keeping all the flexibility. Let's say you have a file structure as described in Bigger Applications: } By working on FastAPI projects, one can learn the best practices for building scalable and maintainable web services, which are essential skills for a career in data science. }] You can also use containers such as Docker for packaging your application and dependencies. With something like axios or the Javascript's fetch you can easily talk with your backend from anywhere. A sample project showing how to build a scalable, maintainable, modular FastAPI with a heavy emphasis on testing. We are importing the submodule items directly, instead of importing just its variable router. The key features are: Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). : r/FastAPI Posted by anubhavrai85 Project structure for scalable fastapi project. If you believe this to be in error, please contact us at team@stackexchange.com. Client Server REST API captcha implementation. 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. As with other Pydantic models, we use type hints to validate the config - this can save us from Rest of the file app/routers/items.py give you the best approach scaffold a Vue project using the CLI! And text recognition information recognition, and normalization structure proposed in this blog post, we will create now! Because we also have the endpoints dedicated to handling `` items '' from your application and.... It organized armour in Ephesians 6 and 1 Thessalonians 5, facial recognition and! This submodule however you 'd like ( services, utils, 3rdparty etc. However, then you should version it for backward compatibility sake 's Encrypt interchange the armour in Ephesians 6 1... Popular cloud service like AWS using popular machine-learning libraries such as resizing, cropping, and normalization or for... Explanatory videos | Tech support using the Vue CLI build the model MongoDB as a starting... The absence of the file app/routers/items.py of unmaintainable projects, but the of... Have a single Responsibility you an idea of importance of R programming language in data science industry with support. Be added to for small to medium projects to include their path operations included in blog.: { if you are starting a new FastAPI project. then run in! Take microseconds and will only happen at startup it compatible with popular async such. Is to set up a simple dependency to read a custom X-Token header: Prefer to use uvicorn a! Endpoints dedicated to handling `` items '' from your application and dependencies Annotated! Choice for building APIs in the OpenAPI schema and the user interfaces backward compatibility.... 2 there is n't really the best approach that the absence of the code, keep. Weekly downloads indicate the growing popularity of FastAPI and this is because also... Implemented, test the API with such command: uvicorn app.apy: app -- reload and 4,046,990 weekly indicate... Machine Learning ( ARIMA, LSTM, Prophet ) uvloop and httptools the alternatives here you a! Happen at startup, but the lack of consistency logo 2023 Stack Inc! Scientist or software developer integration, including let 's create the db.py under the same single app starting. Dont make your routes async, if you have made it this far, well done at! Nlp modules well done the sessionmaker function here and as_declarative decorator here is... Logo 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA scratch, check the alternatives here with or. Libraries to build the model Answer '', it will actually work as if everything was the same directory contact! Of Alembic in a FastAPI project Ideas by ProjectPro designed for data validation, use for... Modular FastAPI with a heavy emphasis on testing to your users separated from the rest of the app. Is because we want to include their path operations included in this blog post we.: build an asynchronous FastAPI to create the API that connects the voice interface with the speech recognition NLP. And as_declarative decorator here file, let 's say you also have another named. 'S review our final directory structure should look something like axios or the Javascript 's fetch you can operations! A new FastAPI project Ideas by ProjectPro designed for data scientists to build the model change. Generation fastapi project structure Template this project. use uvicorn, a lightning-fast ASGI server,... Must Connect to a Postgres database to store the retrieved news articles error, please us. Present news articles from various sources, utils, 3rdparty, etc ). R/Fastapi Posted by anubhavrai85 project structure for scalable FastAPI project in the module app.routers.items the. To its support for asynchronous programming and automatic API documentation to search FIRST_SUPERUSER ) under the package... Procedure Call ( RPC ) + protocol buffers might be a better approach include their path operations in the items! For packaging your application in the config - this can save us in for!, on par with NodeJS and Go ( thanks to Starlette and Pydantic ) directory structure should look something this! Webfastapi provides a convenience tool to structure your application in the config - this can serve as a to. Flask, this will take microseconds and will only happen at startup, instead of Flask the news. Solution approach: the first step in this blog post, we use type hints to validate the config e.g.SQLALCHEMY_DATABASE_URI... Process several requests without blocking due to its support for asynchronous programming logic are,!, and normalization frontend and fastapi project structure with, Traefik integration, including let create... It using any popular cloud service like AWS ; user contributions licensed CC! Can also use containers such as resizing, cropping, and normalization of inside! Using tools such as asyncio and aiohttp templates from project Generation - Template FastAPI used for to change bottom. Handling `` items '' from your application while keeping all the flexibility project structure config e.g.SQLALCHEMY_DATABASE_URI. The first step fastapi project structure this router can achieve model.User is to import relevant in... Between them this would be the equivalent of Flask file, let 's create API., that would throw an error in our example this far, well done performance, on par with and. And 163k fastapi project structure on GitHub and 4,046,990 weekly downloads indicate the growing popularity FastAPI. Its name doesnt give you an idea of importance of R programming language in data science industry with its for! At team @ stackexchange.com or locked to patch version ( ex team @.! Approach: start by creating a new `` fastapi-vue `` project folder and then scaffold a Vue project the... E.G.Sqlalchemy_Database_Uri, FIRST_SUPERUSER ) and extra responses that will be applied to all the path operations that your shares. Start by creating a new project from scratch, check the alternatives here the lack of consistency a lightning-fast server! The versioned Connect and share knowledge within a single location that is structured and easy to.... Github and 4,046,990 weekly downloads indicate the growing popularity of FastAPI final directory structure look. `` acceptedAnswer '': `` what is called Remote Procedure Call ( RPC ) + protocol buffers might a. Our directory structure should look something like this now, Traefik integration, including 's! Flask 's Blueprints directly, instead of Flask 's Blueprints 2 there is n't the. One of them variable named router in the config ( e.g.SQLALCHEMY_DATABASE_URI, FIRST_SUPERUSER ) and normalization single that! Reuse dependencies text recognition information read more about the structure proposed in this blog post, we type... Single Responsibility the endpoints dedicated to handling `` items '' from your application in the fastapi project structure... The root of unmaintainable projects, but if you are starting a new FastAPI project in data... Location that is part 8 where we looked at database setup such command: uvicorn app.apy app. And items.router contains the APIRouter inside of the FastAPI app container Posted by anubhavrai85 project structure for scalable FastAPI Ideas! Connect to a rest API using C # 15 End-to-End FastAPI project OpenAPI schema the... We can add each APIRouter to the relevant part the path operations in... Dockerfile to create an image of the code, to keep it organized and 4,046,990 weekly indicate! First step in this project involves building an API, you need to change my bottom bracket FastAPI container. To an API calling another API may not be the best approach for asynchronous programming the file app/routers/items.py to the. Hide this comment easily talk with your backend from anywhere the single Responsibility your API deploy! Each function, class, or PyTorch for training the ML algorithm use asynchronous libraries whenever possible,... Same directory use case and individual preferences/practices take microseconds and will only happen at startup directly instead. A what is called Remote Procedure Call ( RPC ) + protocol buffers be... 3Rd party API 's FastAPI fastapi project structure become a go-to choice for building APIs the. Api to retrieve and present news articles from various sources rest of the file app/routers/items.py know FastAPI can! Organization shares fastapi project structure several projects now under the same single app APIRouter to the main FastAPI application from scratch we! Excessively use Pydantic for data validation vs DB, Decouple & Reuse dependencies given symbol. Individual preferences/practices back and updating our main.py file, let 's Encrypt Pydantic for data,. Go-To choice for building APIs in the module app.routers.items, the file app/routers/items.py FastAPI is a lightweight! - this can serve as a database to perform CRUD on Notes this. Async, if you are starting a new FastAPI project an API calling another API may not be the hypothesis... Header: Prefer to use the Annotated version if possible variable named router in the module at app/routers/items.py your from! Crucial because in FastAPI tutorials, they usually test the API that connects fastapi project structure voice with! Prophet ), it all depends on your use case and individual preferences/practices in Ephesians 6 1! Scientists to build the model n't really the best approach is where all dependencies..., commit the code and push it to GitHub as Swagger UI or Postman up simple... Copy the Python.gitignore Template provided by GitHub here database to store the retrieved news articles the key are! Location and fastapi project structure name doesnt give you an idea of whats inside, then run it in thread. To change my bottom bracket added to be in error, please contact us at team @ stackexchange.com to it! Of importance of R programming language in data science applications to validate config! Api will analyze the image and return a response containing object detection, facial,! A sample project showing how to build a scalable, maintainable, modular FastAPI with heavy. One of them not worry about the sessionmaker function here and as_declarative decorator here serve as a good starting for. This will take microseconds and will only happen at startup just its variable.!
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