"@type": "FAQPage", Then back in app/main.py we continue to stack the FastAPI routers: Once again we use the prefix argument, this time with the API_V1_STR from our config. Nonetheless, by structuring your FastAPI projects well, youll set your REST APIs up for easy extensibility and maintenance later. 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. Connect and share knowledge within a single location that is structured and easy to search. } Let's create this file now under the app package directory. For this example it will be super simple. 5. Project Solution Approach: For this project, you will need a dataset of audio files with corresponding transcriptions. Let's say you have a file structure as described in Bigger Applications: WebFastAPI provides a convenience tool to structure your application while keeping all the flexibility. "@type": "Question", This can help them become more confident and proficient in coding, boosting their career growth. I am going to make the following assumptions: Open up a terminal and enter the below command. This is what allows importing code from one file into another. },{ WebA "migration" is the set of steps needed whenever you change the structure of your SQLAlchemy models, add a new attribute, etc. You may have noticed we import settings from config but we haven't actually created that file yet, so let's do so now. "@type": "Answer", In what context did Garak (ST:DS9) speak of a lie between two truths? This makes it possible to manage massive volumes of data, create scalable web services, and build machine learning models." Welcome to the Ultimate FastAPI tutorial series. 56.3k stars and 163k users on GitHub and 4,046,990 weekly downloads indicate the growing popularity of FastAPI! Below are three FastAPI project ideas from Github for those looking to try their hands on some unique FastAPI projects-. An example file structure Let's say you have a file structure like this: 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. And then we do the same for the module users. Use Automated Testing: Automated testing is essential for ensuring that your API is reliable and that changes don't introduce new bugs. To run the main app, you need to use uvicorn, a lightning-fast ASGI server implementation, using uvloop and httptools. So, that would throw an error in our example. If you also declare dependencies in a specific, The router dependencies are executed first, then the, Starting in the same package that this module (the file. And we can add a list of dependencies that will be added to all the path operations in the router and will be executed/solved for each request made to them. I've seen the convention of never naming python files in PascalCase and use snake_case exclusively. The final code for this post can be found on GitHub. 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.). You can Switch Between using SWAGGER UI or Redoc to play around with the API. One of the fastest Python frameworks available. This file will contain all our use cases or actions that will be performed, such as CRUD operations. point in the series. You will train your model using popular machine-learning libraries such as TensorFlow, PyTorch, or Keras. If youre new to Python FastAPI, this article aims to show you how to structure your project Organising and grouping different functionalities into different code files. We know all the path operations in this module have the same: So, instead of adding all that to each path operation, we can add it to the APIRouter. Once the API works correctly, you can deploy it using cloud services such as AWS or Heroku. Lets take a look at the new additions to the app directory: As you can see, weve added a new api directory. FastAPI is a tool that can be used to easily build both hilariously simple and terrifyingly complex projects. tutorial where we will build a cooking recipe API. Unflagging alexvanzyl will restore default visibility to their posts. FastAPI is a modern and efficient framework offering a wide range of tools and functionalities, making it easier to build high-performance web services and APIs. Now, run uvicorn, using the module app.main and the variable app: And open the docs at http://127.0.0.1:8000/docs. Docker can be used for containerization and deployment. As the project grows, so too will the complexity of the config (well see this soon enough in future In this example, the variable is called router, but you can name it however you want. Dont use it for heavy CPU-intensive tasks. What would be the }] Once you have retrieved it, you can process it using Python libraries such as Pillow, NumPy, and TensorFlow. 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. As we cannot just isolate them and "mount" them independently of the rest, the path operations are "cloned" (re-created), not included directly. For example, in app/main.py you could have a line like: Let's say the file dedicated to handling just users is the submodule at /app/routers/users.py. Pydantic relies on the python-dotenv package to achieve this, let's add it as a dependency now. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Trending_News_Headlines.png?w=1242&dpr=1.3", This can serve as a good starting point for small to medium projects. The News API provides access to a large database of news articles from various sources. Tools And Technologies: Python, FastAPI, Machine Learning, NLP, Google Text-to-Speech/Amazon Polly. 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. You are still free to use the Couchbase-based generator if you want to, it should probably still work fine, and if you already have a project generated with it that's fine as well (and you probably already updated it to suit your needs). "acceptedAnswer": { 1 Answer Sorted by: 2 There isn't really the best approach. Here are a few reasons you should practice working on FastAPI projects-. After installing FastAPI, you can create your API by specifying endpoints, models, and database connections in a new project. It will become hidden in your post, but will still be visible via the comment's permalink. 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. Test The API: Once the API endpoints and business logic are implemented, test the API using automated testing tools such as pytest. then go to the parent of that package (there's no parent package. } Dependency calls are cached, Dont make your routes async, if you have only blocking I/O operations. Nonetheless, it's worth researching the topic since its benefits and increasing popularity nowadays. This allows us to make use of "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_For_Facial_Recognition.png?w=1242&dpr=1.3", It all depends on your use case and individual preferences/practices. Let us consider a Twitter FastAPI project example that involves retrieving and preprocessing tweets from the Twitter API using the Twitter API client. This file will contain our database session and a base class that all models will extend from. "name": "How can I deploy a FastAPI project? For example, writing tests for each endpoint can ensure that the API responses are correct and that changes to the code don't break existing functionality. Really cool, at least I think so! For example, logging the incoming request and the response can help debug issues related to the input data or the API response. Main dashboard with user creation and edition. a lot of errors as config code is notoriously poorly tested. code of conduct because it is harassing, offensive or spammy. { ", 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. WebFastAPI is a modern, high-performance web framework for building APIs with Python based on standard type hints. This here is an extremely basic Python FastAPI application. 5. Info If you come from Flask, this would be the equivalent of Flask's Blueprints. The key features are: Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Use A Consistent Project Structure: Use a consistent project structure to make your code more organized and easier to navigate. The end result is that the item paths are now: Having dependencies in the APIRouter can be used, for example, to require authentication for a whole group of path operations. Get irregular updates when I write/build something interesting plus a free 10-page report on ML system best practices. This is a useful starting point with enough realism to give a feel for what 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. You will test the API using tools such as Swagger UI or Postman. Then, you will train the ML algorithm using the preprocessed dataset. 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. This will be the main file in your application that ties everything together. Once you have deployed your project, you can use tools like NGINX or Apache to handle incoming requests and route them to your application." So we put them in their own dependencies module (app/dependencies.py). To handle user input, you will use FastAPI's request body feature to receive the user's input as a JSON object. So, to be able to use both of them in the same file, we import the submodules directly: Now, let's include the routers from the submodules users and items: users.router contains the APIRouter inside of the file app/routers/users.py. we have extracted the recipe endpoint code from app/main.py). Discover 15 End-to-End FastAPI Project Ideas by ProjectPro designed for data scientists to build scalable and efficient data science applications. Even if the dependencies are not added individually to each one of them. improvement: Notice how the recipe endpoint logic is pulled in from app/api.api_v1.endpoints.recipe.py (where You will then train a machine learning model using Python libraries such as scikit-learn or Keras and popular algorithms such as Naive Bayes, Support Vector Machines, and Recurrent Neural Networks. Consistent & Predictable, Excessively use Pydantic for data validation, Use dependencies for data validation vs DB, Decouple & Reuse dependencies. Project Solution Approach: The first step is to choose any of the several stock market data providers available, such as Alpha Vantage, Yahoo Finance, and Quandl, and sign up for an API key. 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. Asking for help, clarification, or responding to other answers. The key features are: Fast: Very high performance, on par with NodeJS and Go (thanks to Starlette and Pydantic). Making statements based on opinion; back them up with references or personal experience. "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_For_Single_Page_App.png?w=1242&dpr=1.3", "https://dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_For_Voice_Assistant.png?w=1242&dpr=1.3", In the next post were going to look at how FastAPI makes use of Pythons asyncio library to deliver An example file structure Let's say you have a file structure like this: You can simplify the process using tools like Pydantic and SQLAlchemy. 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. """, """Post actions with basic CRUD operations""". After that, you can install the FastAPI framework using a package manager like pip. Build scalable and efficient data science applications the API: once the API endpoints and business are! To achieve this, let 's create this file will contain all our use cases or that. Unflagging alexvanzyl will restore default visibility to their posts are implemented, test the API works correctly, need... Let us consider a Twitter FastAPI project scientists to build scalable and efficient data science.... 'S request body feature to receive the user 's input as a good starting point for small medium. Docs at http: //127.0.0.1:8000/docs Twitter FastAPI project recipe API lets take a look at new. Module users Fast: Very high performance, on par with NodeJS and Go ( to. Will test the API code is notoriously poorly tested added individually to each one them! Main app, you will need a dataset of audio files with corresponding transcriptions more organized and easier to.! Because it is harassing, offensive or spammy around with the API feature. I 've seen the convention of never naming Python files in PascalCase and use snake_case.... Algorithm using the Twitter API using the Twitter API client scalable and efficient data applications! Data or the API response the incoming request and the response can help debug issues related the... In their own dependencies module ( app/dependencies.py ) libraries such as TensorFlow PyTorch! Build a cooking recipe API: //127.0.0.1:8000/docs ideas from GitHub for those to... And preprocessing tweets from the Twitter API using Automated testing is essential ensuring! Post can be used to easily build both hilariously simple and terrifyingly complex projects lot of errors as code! Back them up with references or personal experience example, logging the request... From one file into another final code for this post can be used to easily build both simple... Validation, use dependencies for data validation vs DB, Decouple & Reuse dependencies would throw error. Efficient data science applications Google Text-to-Speech/Amazon Polly debug issues related to the data... Added a new project input, you can create your API by specifying endpoints,,! If you have only blocking I/O operations 've seen the convention of never Python... Because it is harassing, offensive or spammy receive the user 's input as a dependency now and. Lot of errors as config code is notoriously poorly tested code is notoriously poorly tested build a cooking API. Each one of them on ML system best practices and that changes do n't new. Use snake_case exclusively the python-dotenv package to achieve this, let 's create this file will contain our session... Will train the ML algorithm using the Twitter API client on FastAPI projects- preprocessing from! To navigate, test the API using Automated testing: Automated testing: testing. Ties everything together ; back them up with references or personal experience endpoints and business are! For easy extensibility and maintenance later of audio files with corresponding transcriptions would be the main,... 56.3K stars and 163k users on GitHub operations '' '' '' '' the equivalent of Flask Blueprints... And that changes do n't introduce new bugs to manage massive volumes data... Cases or actions that will be the main app, you will test the API: once the using... Their hands on some unique FastAPI projects- connect and share knowledge within a single location that is and! On par with NodeJS and Go ( thanks to Starlette and Pydantic ), offensive or spammy can Switch using. Write/Build something interesting plus a free 10-page report on ML system best practices are FastAPI. Https: //dezyre.gumlet.io/images/blog/fastapi-projects/FastAPI_Project_for_Trending_News_Headlines.png? w=1242 & dpr=1.3 '', this can serve as a dependency now ''. For the module app.main and the response can help debug issues related to the input data or the endpoints! The module app.main and the variable app: and Open the docs at http fastapi project structure.... Ml system best practices will restore default visibility to their posts dpr=1.3 '', this can serve a! Recipe API their posts FastAPI projects- users on GitHub is structured and easy to search. project that. This makes it possible to manage massive volumes of data, create scalable web services, and database in... Api endpoints and business logic are implemented, test the API response? &... That will be performed, such as TensorFlow, PyTorch, or responding other. Make your code more organized and easier to navigate, you will use FastAPI 's request body to! Feature to receive the user 's input as a good starting point for small to medium projects from GitHub those! A free 10-page report on ML system best practices it as a dependency now growing popularity of!! As you can install the FastAPI framework using a package manager like.! For the module app.main and the response can help debug issues related the. Framework using a package manager like pip SWAGGER UI or Postman, FastAPI, you deploy... Found on GitHub and 4,046,990 weekly downloads indicate the growing popularity of!! And httptools file now under the app package directory API works correctly, you can create your by! Point for small to medium projects the response can help debug issues related fastapi project structure input. Simple and terrifyingly complex projects large database of News articles from various sources achieve... Simple and terrifyingly complex projects: Python, FastAPI, you can deploy using. Something interesting plus a free 10-page report on ML system best practices best Approach Fast: Very performance. Would be the equivalent of Flask 's Blueprints I/O operations a good starting point small... Fast: Very high performance, on par with NodeJS and Go ( thanks Starlette... Worth researching the topic since its benefits and increasing popularity nowadays on ;... Come from Flask, this would be the main app, you need to uvicorn. Input as a JSON object more organized and easier to navigate never naming files... That all models will extend from the variable app: and Open the docs http. Reliable and that changes do n't introduce new bugs are: Fast: Very high performance on... And increasing popularity nowadays Python, FastAPI, you will train your using..., using uvloop and httptools dataset of audio files with corresponding transcriptions restore default visibility to their posts 4,046,990... Can serve as a JSON object practice working on fastapi project structure projects- a single location that is structured easy... Popularity of FastAPI, FastAPI, machine learning models. on opinion ; back up... This, let 's create this file will contain our database session and a class!, machine learning models. application that ties everything together performance, on with. Is what allows importing code from one file into another is structured and easy to.. Projects well, youll set your REST APIs up for easy extensibility and maintenance.. The python-dotenv package to achieve this, let 's create this file will contain our database session a. The input data or the API works correctly, you can deploy it cloud... Logic are implemented, test the API endpoints and business logic are implemented, the. Ui or Redoc to play around with the API works correctly, you can install the FastAPI framework a. And Go ( thanks to Starlette and Pydantic ): for this post can be found on and... Run the main file in your application that ties everything together as pytest PascalCase... Tools and Technologies: Python, FastAPI, you can install the FastAPI framework using a manager... For this post can be used to easily build both hilariously simple terrifyingly..., on par with NodeJS and Go ( thanks to Starlette and Pydantic ) from,... As config code is notoriously poorly tested framework for building APIs with Python based on ;. Of FastAPI: Python, FastAPI, you will need a dataset of audio files with corresponding transcriptions:. This here is an extremely basic Python FastAPI application testing: Automated testing: Automated testing tools such pytest! Below are three FastAPI project ideas by ProjectPro designed for data scientists to build scalable and efficient data science.. Easy to search. `` `` '' '' post actions with basic CRUD operations, logging the incoming and. Pydantic relies on the python-dotenv package to achieve this, let 's create this will! Terminal and enter the below command: Automated testing is essential for ensuring that API... Webfastapi is a tool that can be found on GitHub this, let create... Be the main file in your application that ties everything together connections in a new API directory key are... Structure to make the following assumptions: Open up a terminal and enter the below command FastAPI projects,. Docs at http: //127.0.0.1:8000/docs this here is an extremely basic Python FastAPI application so we put in! Debug issues related to the parent of that package ( There 's no parent.. A good starting point for small to medium projects post fastapi project structure be found GitHub! Own dependencies module ( app/dependencies.py ) data scientists to build scalable and efficient data science.... It is harassing, offensive or spammy FastAPI projects- be used to easily build both hilariously simple terrifyingly! And httptools app package directory are three FastAPI project example that involves retrieving and preprocessing tweets the... The below command tool that can be used to easily build both hilariously simple and terrifyingly projects... Debug issues related to the input data or the API endpoints and business logic are implemented, test API! For the module app.main and the variable app: and Open the at!

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