Snippets

This is the site where the "magic buttons" live ✨

Originally, "code" referred to sequences of 0s and 1s. Over time, it evolved to describe the text of programs. Today, the industry embraces the concept of "everything as code", making coding an essential skill for everyone. Everyone needs the code now.

Snippets play a special role and importance among all code kinds: isolated parts of the code that demonstrate an example of using a tool to solve a problem or a ready-to-use (possibly with limitations) solution to a specific task.

Key characteristics of a snippet include:

High frequency: The problem addressed by the snippet should occur often.
Problem-solving: Ideally, the snippet must solve a specific issue.
Strict solution or limited solution: Ideally, the snippet should provide a universal strict solution. If that’s not feasible, it should offer a solution with some limitations.
Interpretability as-is: Ideally, the snippet must be in a ready-to-use format, either as a complete code or a module for the interpreter.
Demonstration: If it's difficult to create as-is interpretable snippet, demonstrational snippet can be useful.
Code unit or fragment: If a complete code is difficult to present, the snippet can be presented as a fragment of code.
Minimality: The snippet should focus on a specific functionality that cannot be broken down into sequence of smaller snippets.
Tools usage: The snippet can use external utilities.
Target system: If the snippet is intended for a specific target system, it must be specified.

Our service is designed to help users find the perfect code snippets with ease:

Precise Search: Quickly locate snippets using known parameters.
Smart Search: Discover solutions based on natural language descriptions.
Explore Collections: Browse curated sets of snippets for inspiration.

To ensure the snippets database remains highly consistent and fully optimized for semantic search, we focus on curating snippets in the following key areas:

Bash cheatsheet
OS administration cheatsheet
DevOps tools cheatsheets (including Docker, Kubernetes, and more)
Python cheatsheet
Node.js cheatsheet.

Once a user finds the desired snippet, they can either copy the text to the clipboard or download the raw code via a provided link. This enhances convenience and is especially valuable for running snippets directly (in-line), for example to calculate string length of a string (see https://code-magic.com/snippets/1):


curl -s https://api.code-magic.com/api/snippet-raws/1/316a711f9df18cc5146c13588065a3a2 | bash -s "1234567890"
# => 10

To guarantee that the code returned by code-magic matches the request, the raw URL includes an MD5 hash of the code. This hash is verified when the code is fetched via the API, ensuring users receive the exact code they requested—or an error if the snippet has been altered since the raw URL was generated.

Do we really need a snippet database in the era of LLM models that can generate the necessary snippets at the user's request? Our response is yes:

high-quality code, code guarantee: LLM models, by their architecture, since they are neural networks, are not able to guarantee that the generated code really works and really does what the user wanted
fast search, simplicity of search and accuracy of search: LLM model is unable to understand that the user's task is often specific, which means that the user will have to describe their problem in great detail.

Let's go!