25 docs tagged with "programming-languages"

Names, objects, expressions, statements, indentation, imports, and conversion boundaries.

An introductory R guide to expressions, vectors, data structures, control flow, functions, and basic object-oriented systems.

Standard streams, arguments, environment variables, exit status, and composable Python CLI design.

Truth-value testing, comparisons, short-circuiting, identity, membership, and branch design.

Python decorator semantics, metadata preservation, configuration, composition, and wrapper boundaries.

Python mapping semantics, key constraints, lookup contracts, iteration, merging, and costs.

Raising, translating, handling, cleaning up, and testing Python exception contracts.

Portable pathlib usage, path resolution, discovery, file operations, and destructive-action safety.

Function contracts, parameter kinds, return values, defaults, annotations, and side-effect boundaries.

Appropriate uses of Python lambda expressions, key functions, closures, and readability boundaries.

Python list semantics, aliasing, slicing, comprehensions, mutation, and operation costs.

Iterables, for and while loops, range, enumeration, control statements, and safe mutation patterns.

Python classes, instance state, method binding, invariants, composition, and protocol-oriented design.

Type annotation contracts, modern syntax, narrowing, protocols, generics, and runtime boundaries.

Streaming, parsing, aggregating, validating, and operationalizing log-processing pipelines.

A role-oriented map connecting programming languages and platforms to common data, web, mobile, systems, and game-development work.

A compact learning map for Python's object model, control flow, functions, collections, files, and classes.

A map of the R language, its statistical-computing ecosystem, development environments, major packages, and learning resources.

Text and binary file I/O, resource lifetimes, streaming, formats, failures, and safer writes.

Base cases, progress measures, call-stack cost, recursive structures, and iteration boundaries.

Practical regex matching, extraction, replacement, Unicode semantics, escaping, and performance risks.

Python subprocess invocation, output, timeouts, environments, shell boundaries, and process lifecycle.

Immutable Unicode strings, slicing, searching, formatting, normalization, and encoding boundaries.

A map from executable examples and unit tests to integration, system, and operational confidence.

Focused test design with pytest or unittest, parametrization, fixtures, doubles, and failure assertions.