No, it is not possible for standard Python YAML libraries like PyYAML to preserve the original literal block format (e.g., | or >) when you load a YAML file and then dump it back. This is because the parser converts the literal block content into a standard Python string, discarding the original formatting. When you dump the string back to YAML, the dumper uses its own rules to represent the string, which typically defaults to a quoted style or a folded block style, but not necessarily the original one.

Measuring how long your Python code takes to run is a critical skill for performance optimization, benchmarking, and identifying bottlenecks in production applications. Depending on whether you are analyzing a single micro-operation, profiling a complex function, or tracking HTTP request-response lifecycles, Python offers a wide variety of tools.

This guide provides a comprehensive breakdown of how to measure execution time in vanilla Python, followed by specialized implementations for the three major web frameworks: FastAPI, Flask, and Django.

To JSON-encode a Python object using msgspec, you use the msgspec.json.encode() function. This function takes a Python object and returns a bytes object containing the JSON representation. msgspec is known for its high performance and correctness in handling data serialization.

Here's a simple guide with examples.

When building high-throughput Python backend services, I frequently rely on msgspec as a lightweight, high-performance alternative to Pydantic and standard dataclasses. While msgspec.Struct objects provide blazing-fast serialization and low memory overhead thanks to their C-extension implementation, integration with legacy libraries, database ORMs, or third-party SDKs often requires converting these structures into native Python dictionaries (dict).

In this article, I will walk through the primary techniques for converting msgspec objects to dictionaries, compare their performance characteristics, and explain when to use each method in production backend systems.

Supabase is a popular PostgreSQL-based BaaS (Backend-as-a-Service). Because it runs on a standard PostgreSQL database, you can connect to it using traditional database drivers (like psycopg2 or SQLAlchemy) or leverage its built-in REST API using client SDKs.

This guide provides a comprehensive walkthrough for integrating Supabase into your Python web applications, detailing implementations for FastAPI, Flask, and Django.

Using $ref to reference a reusable parameter in an OpenAPI specification is a key practice for keeping your API definitions clean, consistent, and maintainable. This method centralizes common parameters, like Authorization headers or a userId path parameter, in a single location and allows you to reference them from any endpoint.

Creating a mock server from a Swagger/OpenAPI file is a powerful way to decouple front-end and back-end development. It allows front-end developers to start building and testing their applications against a realistic API without waiting for the back-end to be completed.

Here's a step-by-step guide on how to set up a simple mock server using your OpenAPI specification file.

In OpenAPI, the correct way to declare a date is by using the string type along with a specific format. The format distinguishes a date from a regular string and provides a standard for validation and code generation.

Using 'Authorization: Bearer <token>' in an OpenAPI (Swagger) specification requires defining a security scheme and then applying it to the relevant API endpoints. The method for doing this varies slightly between OpenAPI versions 2.0, 3.0, and 3.1.

The meaning of required in OpenAPI (or Swagger) is consistent across all major versions: it specifies that a property must be present in the data payload. However, how you use and apply the keyword has evolved between versions.