Day.js is a lightweight JavaScript date/time library (approximately 2 kB gzipped) designed as a drop-in alternative to Moment.js. It provides immutable, chainable parsing, validation, manipulation, formatting, and comparison APIs, along with extensive internationalization support via over 100 locale files. The library is built as a modular core with a plugin system that extends functionality without bloating the base bundle. It runs in both browsers and Node.js, includes TypeScript definitions, and has a comprehensive test suite that ensures behavioral parity with Moment.js. This is a library, not an application or data pipeline—there are no server components, CLI tools, or data analysis artifacts. The architecture is intentionally small and focused, with a constant-driven unit system and a clean separation between core, plugins, and locales.
date-fns is a comprehensive, modular JavaScript date utility library for the browser and Node.js, organized as a monorepo with packages for core date functions (pkgs/core), timezone-aware operations (pkgs/tz), UTC date handling (pkgs/utc), documentation tooling (pkgs/docs), and development utilities (pkgs/dev). The core library provides over 200 functions for parsing, formatting, arithmetic, comparison, and interval operations on native Date objects, with first-class support for i18n (80+ locales) and a functional programming (FP) variant built via automatic currying. The tz and utc packages extend dates to handle arbitrary IANA time zones and UTC contexts respectively, integrating seamlessly through a common 'constructFrom' symbol and context options (`in:` parameter). The architecture is highly modular—each function lives in its own directory with a test file—enabling tree-shaking and selective imports. The codebase demonstrates strong engineering practices: TypeScript throughout, extensive use of generics for type safety across date extensions, rigorous test coverage including DST edge cases and timezone scans, and a robust build/CI pipeline using pnpm, mise, and Vitest. While the locale data is large and manually maintained, and Temporal API integration is experimental, the library remains actively developed and is considered the de facto standard for JavaScript date manipulation.
Arrow is a Python library providing enhanced date and time manipulation capabilities, serving as a drop-in replacement for datetime with improved usability. It offers timezone-aware objects, human-readable time deltas, flexible parsing/formatting, and time span generation. The architecture centers around an immutable Arrow class with factory methods for creation, supplemented by dedicated modules for parsing, formatting, localization, and utilities. The library follows Python best practices with type hints, comprehensive testing, and clear separation of concerns. Its locale system supports over 60 languages for internationalized date representation.
pandas_market_calendars is a Python library that provides market and exchange trading calendars for over 50 global financial exchanges, including equities, futures, and OTC markets. It generates accurate trading schedules (open/close times, holidays, early closes, late opens, and breaks) as pandas DatetimeIndex objects, enabling developers and quantitative analysts to align time series data, backtest strategies, and check market status. The library is a fork of Quantopian/Zipline's exchange_calendars module, extended with additional calendars, utility functions, and source documentation. Architecturally, the library uses a base MarketCalendar class with a metaclass-based registry pattern that automatically registers all calendar subclasses by name and alias. Individual exchange calendars (e.g., NYSE, CME, LSE, JPX) are implemented as subclasses in the `calendars/` directory, with holiday rules defined in separate `holidays/` modules. Market times are stored in a ProtectedDict (immutable dictionary) to prevent accidental modification. The library also provides a mirror module that wraps calendars from the external `exchange_calendars` package, ensuring backward compatibility. Key entry points include `get_calendar()` to retrieve a calendar instance, `date_range()` to generate intraday timestamps, `merge_schedules()` to combine multiple exchange schedules, and `mark_session()` to classify timestamps into pre-market, regular, and post-market sessions. The library depends on pandas for data structures and timezone handling via zoneinfo, and optionally on exchange-calendars for mirrored calendars. It is designed for production use with extensive test coverage, CI/CD pipelines, and semantic versioning. The library's primary data flow is static: holiday rules and market time definitions are hardcoded in Python code and updated via new releases. There is no runtime data fetching, which ensures reproducibility but requires manual updates when exchanges change their calendars. The changelog shows frequent updates for holiday corrections and new exchange support, indicating active maintenance.
This repository is a curated 'awesome' list of falsehoods programmers believe in. It is not a software application or data pipeline; it is a markdown-based collection of links to external articles, libraries, and resources organized by topic (dates, names, geography, etc.). The repository contains no executable code, no API endpoints, no CLI tools, and no data transformations. Its value lies in the curation and editorial quality of the links, along with a well-documented contribution guide and automated linting workflows (lychee for link checking, typos for spelling, awesome-lint for list formatting). The infrastructure includes GitHub Actions for autofix, autolock, docs, labels, and linting, all reused from a shared workflow repository (kdeldycke/repomatic). The pyproject.toml provides reusable configuration for link exclusion patterns and typo detection. While not a software project, the repository demonstrates high standards for maintaining a community-curated resource.