Reference

XCODX

Reference

Precise, runnable documentation for the language and platform features you use every day.

All 8
JavaScript

Array.prototype.filter()

filter() builds a new array containing only the elements that pass a test you provide. The original array is left unchanged.

 JavaScript

Array.prototype.map()

map() builds a new array by running a function on every element of an existing one. It never changes the original — it returns a transformed copy of exactly the same length. This is the standard way to turn one array into another in JavaScript.

 JavaScript

Array.prototype.reduce()

reduce() collapses an array into a single value — a sum, a lookup object, a grouped structure — by running a function that carries an accumulator across every element.

 JavaScript

Array.prototype.sort()

sort() orders an array in place. By default it sorts elements as strings; pass a compare function to sort numbers or objects correctly.

 JavaScript

Object.entries()

Object.entries() returns an array of an object's own [key, value] pairs — the cleanest way to iterate an object when your loop needs both the key and the value.

 JavaScript

Object.keys()

Object.keys() returns an array of an object's own enumerable string keys — the standard way to count properties or iterate over an object by turning it into an array first.
All 6
Python

dict.get()

dict.get(key, default=None) reads a value by key and returns a fallback instead of raising KeyError when the key is missing — the safe way to read a dictionary.

 Python

dict.items()

dict.items() returns a live view of a dictionary's (key, value) pairs — the cleanest way to iterate when your loop needs both the key and the value.

 Python

enumerate()

enumerate() wraps any iterable and yields (index, item) pairs, giving you a running count alongside each value. It is the Pythonic replacement for looping over range(len(...)) and indexing back in.

 Python

range()

range() produces a lazy, memory-efficient sequence of integers — the standard way to count in a Python loop. It never builds a list; it computes each value on demand from its start, stop and step.

 Python

str.replace()

str.replace() returns a new string with occurrences of a substring swapped for another. By default it replaces every match; a count argument caps how many are changed. The original string is never modified.

 Python

str.split()

str.split() breaks a string into a list of substrings around a separator. With no separator it splits on any run of whitespace and drops empty pieces; with one it cuts on that literal, and maxsplit caps how many cuts it makes.

A reference page has one job: tell you exactly what a feature does and how to use it correctly, in as little time as possible. Every page here follows the same shape — a plain-language definition, the exact syntax, a table of parameters and return values, the mistakes people actually make, and live examples you can edit and run without leaving the page.

That last part is what sets these pages apart from a static spec. Instead of reading what map() or reduce() returns, you run it, change the input, and watch the output update — the fastest way to build a real mental model. Everything runs in the online editor; there is nothing to install and nothing to configure.

Browse a language below, or jump straight to a page from search. Each language's reference is organised into clusters (arrays, strings, and so on) so related pages stay linked and easy to explore.

Frequently asked questions

What is the XCODX reference?
A growing set of focused documentation pages for programming-language and platform features — one page per method, property or concept. Each gives the syntax, parameters, return value, common pitfalls and runnable examples.
Are the examples actually runnable?
Yes. Every example runs live in the embedded editor — edit the code and see the output change. You can also open any snippet in the full online editor or the language's online compiler.
How is this different from MDN or the official docs?
The facts are the same and verified against authoritative sources, but each page is written to be read quickly and — crucially — every example is interactive, so you learn by running code rather than only reading it.
Which languages are covered?
Coverage is expanding cluster by cluster. JavaScript is the most complete today; more languages are added continuously, each held to the same standard.