FastAPI Interview Questions

Checkout Vskills Interview questions with answers in FastAPI to prepare for your next job role. The questions are submitted by professionals to help you to prepare for the Interview.    

Q.1 How can you test file uploads in FastAPI applications?

File uploads in FastAPI can be tested using the TestClient class provided by the fastapi.testclient module. By using the post method and providing the file in the request payload, you can simulate file uploads for testing purposes.

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Q.2 Explain the use of the FileField class in FastAPI.

The FileField class in FastAPI is a Pydantic model field specifically designed for handling file uploads. By using this class in your Pydantic models, you can easily define and validate file upload parameters in your request and response models.

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Q.3 What deployment options are available for FastAPI applications?

FastAPI applications can be deployed using various options, including traditional servers like Uvicorn or Hypercorn, containerization tools like Docker, and cloud platforms such as AWS, Google Cloud, or Azure.

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Q.4 Explain the role of Uvicorn in deploying FastAPI applications.

Uvicorn is an ASGI server that serves as the default deployment server for FastAPI. It provides high performance and supports asynchronous request handling, making it well-suited for FastAPI applications.

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Q.5 How can you containerize a FastAPI application using Docker?

To containerize a FastAPI application with Docker, you need to create a Dockerfile specifying the application dependencies, copy the source code into the container, and expose the required ports. The resulting image can then be run as a container.

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Q.6 What is the purpose of ASGI servers in the context of FastAPI deployments?

ASGI servers, such as Uvicorn and Hypercorn, are essential for deploying FastAPI applications. They handle asynchronous communication between the server and the application, ensuring efficient handling of concurrent requests.

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Q.7 Explain the concept of process management in FastAPI deployments.

Process management involves running multiple instances of a FastAPI application to handle concurrent requests. This can be achieved using tools like Gunicorn, which manage multiple worker processes and distribute incoming requests among them.

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Q.8 How can you configure environment variables for a FastAPI application?

Environment variables in FastAPI can be configured using the python-dotenv library. By creating a .env file and loading it using dotenv, developers can manage configuration settings, such as database URLs or API keys, in a secure and flexible way.

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Q.9 What is the purpose of Gunicorn in the deployment of FastAPI applications?

Gunicorn is a WSGI server that serves as a process manager for FastAPI applications. It can spawn multiple worker processes to handle incoming requests concurrently, improving the application's performance in production environments.

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Q.10 Explain the use of Docker Compose in deploying FastAPI applications.

Docker Compose is a tool for defining and running multi-container Docker applications. It simplifies the deployment of FastAPI applications by allowing developers to define the application, database, and other services in a single configuration file.

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Q.11 How can you deploy a FastAPI application on a cloud platform like AWS or Azure?

FastAPI applications can be deployed on cloud platforms by containerizing them with Docker and then utilizing container orchestration services like Amazon ECS, Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE).

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Q.12 Explain the role of reverse proxies in FastAPI deployments.

Reverse proxies, such as Nginx or Apache, act as intermediaries between the client and the FastAPI application server. They handle tasks like SSL termination, load balancing, and serving static files, improving security and performance.

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Q.13 What are the considerations for managing database connections in FastAPI deployments?

In FastAPI deployments, managing database connections involves ensuring that database connections are established and closed appropriately. Using database connection pooling tools like SQLAlchemy's create_engine with appropriate pool settings helps optimize database interactions.

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Q.14 How can you implement logging in a deployed FastAPI application?

Logging in a deployed FastAPI application can be configured using the standard logging module. Developers can define log handlers, set log levels, and customize log formats to capture relevant information for monitoring and debugging.

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Q.15 Explain the use of API versioning in FastAPI deployments.

API versioning in FastAPI deployments involves managing different versions of the API to ensure backward compatibility. This can be achieved through URL versioning, custom headers, or other strategies, allowing smooth transitions for clients.

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Q.16 What is the purpose of FastAPI's --reload option, and when should it be used in production?

The --reload option in FastAPI enables automatic code reloading during development, but it should be disabled in production. Reloading code in production can lead to downtime and increased resource usage.

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Q.17 How can you secure a FastAPI application in a production environment?

To secure a FastAPI application in production, developers should use HTTPS, configure security headers, implement proper authentication and authorization mechanisms, regularly update dependencies, and follow security best practices to protect against common vulnerabilities.

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Q.18 What is FastAPI, and how does it differ from other Python web frameworks?

FastAPI is a modern, fast web framework for building APIs with Python 3.7+ based on standard Python type hints. It differentiates itself by automatic OpenAPI and JSON Schema generation, asynchronous support, and high performance due to automatic data validation and serialization.

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Q.19 Explain the significance of type hints in FastAPI.

Type hints in FastAPI are crucial for automatic data validation, serialization, and documentation generation. They enhance code readability, enable editor support, and aid in catching potential errors early in the development process.

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Q.20 How does dependency injection work in FastAPI, and why is it useful?

Dependency injection in FastAPI involves using function parameters to declare dependencies. These dependencies can be reused across multiple routes, promoting code modularity and making it easier to test and manage complex applications.

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Q.21 What is Pydantic, and how is it used in FastAPI?

Pydantic is a data validation and settings management library. In FastAPI, Pydantic is used for request and response data validation, as well as for automatic generation of OpenAPI documentation based on Python type hints.

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Q.22 Explain the role of path parameters and query parameters in FastAPI.

Path parameters are part of the URL and are used to capture values from the URL path. Query parameters, on the other hand, are included in the URL query string. Both are essential for defining and accessing dynamic values in API endpoints.

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Q.23 How does FastAPI handle asynchronous programming, and when should it be used?

FastAPI leverages Python's native asynchronous support using async and await keywords. Asynchronous programming is beneficial for handling concurrent tasks without blocking, improving overall performance, especially in scenarios with high I/O operations.

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Q.24 What is dependency chaining in FastAPI?

Dependency chaining in FastAPI refers to the ability to chain multiple dependencies together, creating a sequence of dependencies that are executed in order. This is useful for creating reusable and modular components in the application.

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Q.25 Explain the concept of background tasks in FastAPI.

Background tasks in FastAPI allow the execution of asynchronous tasks in the background, separate from the main request-response cycle. This is useful for handling tasks like sending emails or performing time-consuming operations without affecting the API response time.

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Q.26 How does FastAPI handle request and response validation?

FastAPI uses Pydantic models for automatic validation of request and response data. It checks incoming data against the specified model, ensuring that it adheres to the defined structure and types.

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Q.27 What are middleware in FastAPI, and why are they important?

Middleware in FastAPI are functions or classes that can modify the request or response globally for all routes or specific routes. They are crucial for tasks such as authentication, logging, or modifying headers consistently across the application.

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Q.28 Explain OAuth2 authentication in FastAPI.

FastAPI supports OAuth2 authentication, allowing developers to secure their APIs. OAuth2 flow involves the use of tokens for authentication, and FastAPI provides built-in support for generating and validating these tokens.

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Q.29 How does FastAPI handle file uploads?

FastAPI handles file uploads through the UploadFile class, which is a Pydantic model. It automatically validates file types, sizes, and provides easy-to-use methods for handling uploaded files in API routes.

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Q.30 Discuss the role of dependency overrides in FastAPI.

Dependency overrides in FastAPI allow developers to replace or override dependencies on a per-request basis. This is useful for testing, debugging, or modifying behavior without changing the core application code.

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Q.31 What is the purpose of the FastAPI class in FastAPI applications?

The FastAPI class is the main entry point for FastAPI applications. It is used to create instances of the FastAPI framework, define routes, configure middleware, and start the application server.

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Q.32 How can automatic documentation be generated for FastAPI projects?

FastAPI automatically generates API documentation using Swagger UI and ReDoc, based on the OpenAPI standard. The documentation is accessible at the /docs and /redoc endpoints, providing a user-friendly interface for exploring and testing the API.

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Q.33 What is Pytest, and how does it differ from other testing frameworks in Python?

Pytest is a testing framework for Python that simplifies test writing and execution. It stands out for its concise syntax, fixtures, and powerful features like parameterized testing. It requires less boilerplate code compared to other testing frameworks.

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Q.34 Explain the purpose of fixtures in Pytest.

Fixtures in Pytest are functions marked with the @pytest.fixture decorator. They provide a way to set up preconditions or resources needed for tests. Fixtures make it easy to share common setup code across multiple tests.

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Q.35 How does Pytest handle test discovery?

Pytest automatically discovers and runs tests based on naming conventions. Test files and functions should be named with test_ prefixes, and Pytest will discover and execute them without the need for explicit configuration.

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Q.36 What is the significance of the assert statement in Pytest?

The assert statement in Pytest is used to validate whether a given condition is True. When a test contains an assert statement, Pytest captures the result and reports it in a detailed manner, making it easy to identify the cause of test failures.

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Q.37 Explain the concept of fixtures scope in Pytest.

Fixtures in Pytest can have different scopes: function, class, module, or session. The scope determines how long the fixture persists. For example, a function-scoped fixture is re-executed for each test function, while a session-scoped fixture is created once for the entire test session.

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Q.38 How can you parameterize tests in Pytest?

Tests can be parameterized in Pytest using the @pytest.mark.parametrize decorator. It allows you to run the same test function with different sets of input parameters, making it easy to cover multiple scenarios in a single test.

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Q.39 What is the purpose of the conftest.py file in Pytest?

The conftest.py file is used to share fixtures, hooks, and configuration across multiple test files. It acts as a container for common testing components, making them accessible to tests in the same directory and its subdirectories.

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Q.40 How does Pytest handle test fixtures teardown?

Pytest provides fixture finalization through the yield statement. If a fixture function uses yield, the code before the yield is the setup, and the code after the yield is the teardown. Resources acquired during setup are automatically released at the end of the test.

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Q.41 What is the purpose of the pytest.mark module?

The pytest.mark module is used for marking tests with metadata or attributes. It allows you to categorize and filter tests based on specific criteria, such as marks for slow tests, smoke tests, or specific environments.

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Q.42 How can you skip or mark a test as expected to fail in Pytest?

To skip a test, use the @pytest.mark.skip decorator. To mark a test as expected to fail, use the @pytest.mark.xfail decorator. Marking a test as expected to fail allows it to run and report the failure without causing the entire test suite to fail.

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Q.43 What is the purpose of the -k option in Pytest?

The -k option in Pytest allows you to selectively run tests that match a given string expression. It provides a flexible way to filter and execute specific tests based on their names or other attributes.

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Q.44 How can you generate code coverage reports with Pytest?

Pytest can generate code coverage reports using plugins like pytest-cov. By installing the plugin and running Pytest with the --cov option, it calculates and displays coverage metrics for the tested code.

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Q.45 Explain the concept of fixtures autouse in Pytest.

Fixtures with the autouse=True parameter are automatically invoked for all tests without explicit dependency injection. This is useful for setting up global preconditions or performing actions before and after each test.

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Q.46 What is the purpose of the capsys and caplog fixtures in Pytest?

The capsys fixture captures the standard output and standard error streams, allowing you to test or inspect printed output. The caplog fixture captures log messages, enabling tests for proper logging behavior.

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Q.47 How can you run Pytest in parallel?

Pytest supports parallel test execution using plugins like pytest-xdist. By installing the plugin and using options like -n or --dist, tests can be distributed and run in parallel across multiple processes or machines.

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Q.48 What is asynchronous programming in Python, and how does it benefit FastAPI applications?

Asynchronous programming in Python, marked by the use of async and await keywords, allows non-blocking execution of tasks. FastAPI leverages asynchronous programming to handle concurrent operations efficiently, improving overall application performance.

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Q.49 Explain the role of asynchronous databases in FastAPI applications.

Asynchronous databases in FastAPI support non-blocking database operations, allowing the application to continue processing other tasks while waiting for database queries to complete. This is crucial for maintaining responsiveness in applications with high I/O operations.

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Q.50 Which libraries in Python are commonly used for asynchronous database access in FastAPI?

Libraries like databases and SQLAlchemy with an asynchronous driver such as asyncpg or aiomysql are commonly used for asynchronous database access in FastAPI applications.

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Q.51 Explain the purpose of the Session and AsyncSession in SQLAlchemy for FastAPI applications.

In SQLAlchemy, Session is used for synchronous database operations, while AsyncSession is designed for asynchronous database operations. FastAPI applications use AsyncSession to execute asynchronous queries and transactions.

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Q.52 How does FastAPI handle database dependency injection?

FastAPI uses dependency injection to manage database connections. Database sessions or connections can be defined as dependencies, and FastAPI ensures that the correct session or connection is passed to the route functions.

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Q.53 What is connection pooling in the context of asynchronous databases, and why is it important?

Connection pooling involves reusing existing database connections instead of creating new ones for each query. It is crucial for performance optimization as it reduces the overhead of establishing new connections, especially in applications with high concurrency.

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Q.54 Explain the concept of CRUD operations in the context of asynchronous databases in FastAPI.

CRUD stands for Create, Read, Update, and Delete operations. In the context of asynchronous databases in FastAPI, CRUD operations refer to the basic database operations performed on data entities. FastAPI routes often implement these operations to interact with the database.

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Q.55 How can you handle database transactions asynchronously in FastAPI?

FastAPI supports asynchronous database transactions using the async with statement. By using the await database.transaction() context manager, you can ensure that a series of database operations are executed atomically. async with database.transaction(): # perform asynchronous database operations.

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Q.56 Discuss the use of Pydantic models in FastAPI when working with asynchronous databases.

Pydantic models are used for data validation and serialization in FastAPI. When working with asynchronous databases, Pydantic models can be used to define the structure of data entities, ensuring consistency between the API and the database schema.

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Q.57 How can you handle database migrations in FastAPI applications with asynchronous databases?

Database migrations in FastAPI applications with asynchronous databases are often managed using tools like alembic. Alembic provides a way to define and apply database schema changes, keeping the database structure in sync with the application code.

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Q.58 Explain the purpose of the execute and fetch_all methods in asynchronous database queries with FastAPI.

In asynchronous database queries, the execute method is used to execute a query, while the fetch_all method retrieves all results. These methods are often utilized with the database object to perform database operations asynchronously.

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Q.59 How does FastAPI handle database connection cleanup?

FastAPI ensures that database connections are properly cleaned up by using dependency injection. When a request is processed, the database connection is automatically closed or returned to the connection pool, preventing resource leaks.

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Q.60 Discuss the benefits of using an ORM (Object-Relational Mapping) like SQLAlchemy with asynchronous databases in FastAPI.

Using an ORM like SQLAlchemy with asynchronous databases simplifies database interactions by allowing developers to work with Python objects instead of raw SQL. It provides an abstraction layer that facilitates database operations, making code more readable and maintainable.

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Q.61 How can you test asynchronous database operations in FastAPI applications?

Testing asynchronous database operations in FastAPI can be done using tools like httpx for making asynchronous HTTP requests and by using test databases or fixtures. Pytest fixtures can be used to create, migrate, and seed test databases for conducting unit and integration tests on asynchronous database operations.

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Q.62 Why is logging important in FastAPI applications?

Logging is crucial for understanding the behavior of an application, diagnosing issues, and monitoring its performance. It provides a way to record information, warnings, errors, and other relevant details during runtime.

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Q.63 How can you enable logging in a FastAPI application?

FastAPI uses Python's built-in logging module. To enable logging in a FastAPI application, you can import the logging module and configure it as needed. Additionally, FastAPI itself logs information related to request handling, which can be controlled through the application's settings.

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Q.64 Explain the different log levels in the logging module.

The logging module defines several log levels, including DEBUG, INFO, WARNING, ERROR, and CRITICAL. These levels allow developers to categorize log messages based on their severity. During runtime, log messages with a level equal to or higher than the configured level are recorded.

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Q.65 How can you configure logging in a FastAPI application?

Logging configuration in FastAPI can be done using the standard logging module. Developers can set the desired log level, specify log handlers (e.g., console, file), and define a log format. This configuration is typically done in the application's startup event.

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Q.66 What is the purpose of loggers in the logging module?

Loggers in the logging module are used to organize and categorize log messages. They act as named entities that can be configured individually, allowing developers to control the logging behavior for different parts of the application.

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Q.67 How can you log messages in FastAPI routes or dependencies?

FastAPI allows you to use the standard logging module to log messages within routes or dependencies. You can obtain a logger using logging.getLogger(__name__) and then use methods like debug(), info(), etc., to log messages at different levels.

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Q.68 Explain the use of context-specific logging in FastAPI.

FastAPI provides a context-specific logger accessible through fastapi.logger. This logger is automatically configured during the application startup and can be used within routes, dependencies, or other parts of the application to log messages specific to FastAPI components.

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Q.69 What is request logging in FastAPI, and how can you customize it?

FastAPI automatically logs information related to incoming requests, including method, path, and response status. Developers can customize this logging by configuring the logging level and format for request-related logs during the application setup.

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Q.70 How can you handle log rotation in a FastAPI application?

Log rotation can be achieved using Python's RotatingFileHandler or TimedRotatingFileHandler in the logging configuration. These handlers allow log files to be rotated based on size or time, preventing them from becoming too large.

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Q.71 Explain the concept of structured logging in FastAPI.

Structured logging involves logging data in a structured format, such as JSON, making it easier to analyze log entries. FastAPI supports structured logging by allowing developers to include additional data in log messages using the extra parameter.

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Q.72 How can you integrate external logging services with FastAPI?

FastAPI can integrate with external logging services by configuring appropriate log handlers. For example, developers can use the SysLogHandler or third-party handlers compatible with services like Elasticsearch, Splunk, or cloud-based logging solutions.

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Q.73 What is the purpose of logging middleware in FastAPI?

Logging middleware in FastAPI allows developers to capture information about requests and responses, including timing, status codes, and other relevant details. This can be valuable for performance monitoring and auditing.

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Q.74 How can you suppress FastAPI's default access log messages?

Developers can configure the uvicorn ASGI server to suppress access log messages by setting the --no-access-log option when starting the server. This is useful when customizing logging to better suit the application's requirements.

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Q.75 Explain how to use exception logging in FastAPI.

FastAPI provides an exception handler that can be used to log exceptions globally. By defining an exception handler in the application settings, developers can capture and log unhandled exceptions that occur during request processing.

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Q.76 How can you use logging to track the execution flow in FastAPI middleware?

Logging can be used in FastAPI middleware by obtaining a logger and adding log messages at various points in the middleware execution flow. This helps developers track the sequence of events and debug issues in the middleware processing logic.

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Q.77 What is user authentication, and why is it important in web applications?

User authentication is the process of verifying the identity of a user, typically through credentials like username and password. It is essential for securing web applications by ensuring that only authorized users can access protected resources.

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Q.78 How does FastAPI handle user authentication?

FastAPI supports user authentication through a variety of methods, including API keys, OAuth2, and dependency injection for session-based authentication. Developers can choose the authentication method that best fits their application's requirements.

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Q.79 Explain the role of OAuth2 in user authentication with FastAPI.

OAuth2 is a secure and widely used protocol for user authentication and authorization. FastAPI provides built-in support for OAuth2, making it easy to implement authentication with services like Google, Facebook, or custom OAuth2 providers.

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Q.80 What is the purpose of the Depends class in FastAPI?

The Depends class in FastAPI is used for dependency injection, allowing developers to declare dependencies for route functions. It is commonly used to handle user authentication by injecting authentication dependencies into route functions.

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Q.81 How can you implement password hashing for user authentication in FastAPI?

FastAPI recommends using a library like passlib for password hashing. Developers can use the library to hash and verify passwords securely, enhancing the security of user authentication.

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Q.82 Explain the concept of bearer tokens in FastAPI.

Bearer tokens are a type of access token commonly used in OAuth2 authentication. In FastAPI, they are often used to authenticate users by including the token in the Authorization header of HTTP requests.

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Q.83 How can you implement API key-based authentication in FastAPI?

FastAPI allows developers to implement API key-based authentication by using dependencies with the APIKey class. This involves extracting the API key from the request and validating it against a set of known keys.

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Q.84 What is the purpose of the HTTPBearer class in FastAPI?

The HTTPBearer class is a FastAPI dependency specifically designed for handling OAuth2 bearer tokens. It extracts and verifies bearer tokens from the Authorization header, simplifying the implementation of OAuth2 authentication.

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Q.85 How can you secure routes in FastAPI to require authentication?

Routes in FastAPI can be secured by using dependencies that handle user authentication. By adding authentication dependencies to route functions using the Depends class, developers can enforce authentication requirements for specific routes.

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Q.86 Explain the difference between session-based and token-based authentication.

Session-based authentication involves storing user credentials on the server after successful login and issuing a session cookie to the client. Token-based authentication, on the other hand, relies on the client presenting a token (like a JWT) with each request, eliminating the need to store session data on the server.

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Q.87 How can you handle user roles and permissions in FastAPI?

FastAPI allows developers to implement user roles and permissions by adding custom logic to authentication dependencies. By checking user roles during authentication, developers can control access to specific routes or resources based on user privileges.

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Q.88 Explain the purpose of the security parameter in FastAPI route decorators.

The security parameter in FastAPI route decorators is used to specify the authentication dependencies required for a particular route. It allows developers to define the authentication methods needed to access a specific route.

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Q.89 How does FastAPI handle token expiration and refreshing?

FastAPI supports token expiration and refreshing in OAuth2 by using the expires_in and refresh_token parameters during token creation. This enables the implementation of secure token-based authentication with automatic token renewal.

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Q.90 What is the purpose of the OAuth2PasswordBearer class in FastAPI?

The OAuth2PasswordBearer class in FastAPI is a specialized dependency for handling OAuth2 password flow. It extracts the username and password from the request and validates them to generate an access token.

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Q.91 How can you handle user authentication in WebSocket connections with FastAPI?

FastAPI allows user authentication in WebSocket connections by extracting and validating authentication information from the WebSocket's initial connection request. This ensures that WebSocket connections are secure and associated with authenticated users.

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Q.92 What is the significance of file uploads in FastAPI applications?

File uploads in FastAPI allow clients to send files to the server, enabling functionalities such as image uploads, document submissions, or any use case where transferring binary data is necessary.

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Q.93 How can you handle file uploads in FastAPI?

FastAPI handles file uploads through the use of the UploadFile class from the fastapi module. This class provides an easy and standardized way to work with uploaded files in request payloads.

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Q.94 Explain the role of Form and File in handling file uploads.

The Form class in FastAPI is used to define form fields, while the File class is used specifically for handling file uploads. When creating a route, you can use both classes to define form fields and handle uploaded files in the request payload.

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Q.95 How does FastAPI validate and limit file uploads?

FastAPI automatically validates file uploads based on their content type and size. You can use parameters like upload_file: UploadFile = File(...) in your route definition to enforce validation rules such as maximum file size.

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Q.96 Explain the process of handling multiple file uploads in a single request.

To handle multiple file uploads, you can use a list of UploadFile objects in the route parameters. FastAPI will automatically process multiple files sent in the request payload, making it convenient to handle bulk file uploads.

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Q.97 What role does Pydantic play in validating file uploads?

Pydantic models, used in FastAPI, can be employed to define the structure and validation rules for file uploads. By incorporating Pydantic models, developers can ensure that uploaded files adhere to specific requirements, such as file type or size.

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Q.98 Explain how to save and store uploaded files in FastAPI.

FastAPI provides methods to save and store uploaded files. You can use the file attribute of the UploadFile class to access the file data and save it to a desired location, such as a local directory or a cloud storage service.

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Q.99 How can you implement file response handling in FastAPI?

FastAPI allows you to return files in responses using the FileResponse class. By creating an instance of FileResponse and returning it from a route, you can efficiently serve files to clients.

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Q.100 What is the purpose of the max_length parameter in handling file uploads?

The max_length parameter is used to limit the size of file uploads in FastAPI. By setting a maximum length, developers can prevent excessively large files from being processed, helping to manage server resources.

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Q.101 Explain the use of asynchronous file uploads in FastAPI.

FastAPI supports asynchronous file uploads by using asynchronous request handlers (async def). This is particularly useful when dealing with large file uploads or when integrating with asynchronous storage systems.

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Q.102 How can you implement client-side file validation in FastAPI?

Client-side file validation can be implemented using JavaScript on the frontend. FastAPI can then enforce additional server-side validation to ensure the security and integrity of the uploaded files.

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Q.103 What role does the background_tasks parameter play in handling file uploads?

The background_tasks parameter in FastAPI allows you to perform background tasks, such as processing or saving files, asynchronously. This ensures that file handling operations do not block the main request-response cycle.

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Q.104 Explain the use of the dependant parameter in handling file uploads.

The dependant parameter in FastAPI allows you to define dependencies for your route. This can be useful when handling file uploads, as you may have dependencies, such as authentication, that need to be resolved before processing the uploaded files.

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