reduce-without
Isomorphic map-reduce function to flatten an array into the supplied array
JavaScript's functional programming helper library.
Map Reduce without eval()
A best-practices CSS foundation
Reduce transform functions with PostCSS.
Reduce initial definitions to the actual initial value, where possible.
High quality image resize in browser.
Reduce CSS calc() function to the maximum
Reduce function calls in a string, using a callback
Reduce a list of values using promises into a promise for a value
Reduce custom identifiers with PostCSS.
Reduce multiple reducers into a single reducer
Types for the TypeScript-ESTree AST spec
`[].reduce()` for old browsers
High quality image resizing for blobs in browsers (`pica` wrapper with some sugar)
Reduce any JSON value by traversing depth first and visiting each node
Safe defaults for cssnano which require minimal configuration.
Utility for creating Universal macOS applications from two x64 and arm64 Electron applications
A scheduler based on requestAnimationFrame
A zero-config, fast and small (~3kB) virtual list (and grid) component for React, Vue, Solid and Svelte.
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Reduce an array to unique values, optionally into a separate array.
A better [].reduce
Slim is a template language whose goal is reduce the syntax to the essential parts without becoming cryptic.
Rubydoop embeds a JRuby runtime in Hadoop, letting you write map reduce code in Ruby without using the streaming APIs
To help with reading the results of grep without further reducing the output, hl will highlight terms in the output
CLI json processor for Rubyists. jrq enable you to filter/map/reduce json without studying new syntax.
Cloud Data Fusion is a fully managed, cloud-native, enterprise data integration service for quickly building and managing data pipelines. Note that google-cloud-data_fusion-v1 is a version-specific client library. For most uses, we recommend installing the main client library google-cloud-data_fusion instead. See the readme for more details.
Orders ActiveRecord items by floating ranks for spaces in-between items. Influenced by gem ActsAsList. The floating rank allows inserting items at arbitrary positions without reordering items. Thus, reducing the number of WRITE queries.
A collection of diverse simple utilities without much anything to do with one another. The main rationale is to reduce the time spent on boilerplate like checking whether the arguments have the right type, or introducing some basic internationalization. More detail in the README.
Extends standard Enumerator with a "enumerate_yields" method. Just add a one-liner piece of code to your yield method and your method can be called with or without a block. Recursion and some meta-magic greatly reduce coding.
Link renderer for use with [will_paginate](https://github.com/mislav/will_paginate). When paginated results are loaded asyncronously, it is not ideal to output fully fleshed-out html for the links; there is too much redundancy in doing so. Additionally, if you're requesting pagination asyncronously, you don't want links anyway, because you'd want to allow users to view results on other pages without a page reload. This gem reduces each link to its minimal form: a page number.
Lazy As Json A simple and concise way to use as_json with “only”, “except” and other options without using them literally. Instead of using this - `User.as_json(only: [:id, :first_name, profiles: [:company, :location]])` You can perhaps use this - `User.as_json(only_keys: ‘_,first_name,profiles(p),p.company,p.location’)` As simple as this. You can control what your API response should include through a flexible parameter string. i.e. - “/api/v1/users/me?_keys=_,last_name,profiles(p),p.company,p.location” This parameter string could dig through the nested objects and their nesting too. Just to reduce the API response size significantly, you can use this parameter control over wherever it is used. However it might seems quite trivial but frankly speaking it saves lot in response data hence faster loading time at client side. Moreover as it uses Hash.new and constructs attribute on runtime, you can throttle calling from the expensive method by using this parameter string.
A simple elaboration on Ruby's native SizedQueue which allows using the queue object to re-awaken a blocked thread and cause it to abandon its blocking enqueue/dequeue operation. Useful for simplifying program logic, reducing the need for external flags/Muteces (yes, I said Muteces), and for cleanly resolving queues on program termination without risk of data loss or deadlock. Why use this queue? There are two reasons. For one thing, under several circumstances it is _considerably_ faster than Ruby's native SizedQueue. I admit I'm not entirely sure why, but I have tested this on multiple platforms and it seems to hold true as a generality. You can feel free to confirm or dispel that this advantage holds for your use case at your own leisure. The second reason is the aforementioned simplification of program logic. In the case that all data passing through the queues must be preserved on program termination, SizedQueue can require some elaborate trickery to ensure that even the most remote possibility of deadlock is removed. ImprovedSizedQueue solves this problem by making it possible to use the queue to pass control messages between threads, irrespective of the queue's actual content.
E11y (Easy Telemetry) - Observability for Rails developers who hate noise. UNIQUE FEATURES: • Request-scoped debug buffering - buffers debug logs in memory, flushes ONLY on errors • Zero-config SLO tracking - automatic Service Level Objectives for HTTP endpoints and jobs • Schema-validated events - catch bugs before production with dry-schema DEVELOPER EXPERIENCE: • Minimal setup — one config block, works with stdout out of the box • Auto-metrics from events (no manual Yabeda.increment) • Rails-first design (follows Rails conventions) • Pluggable adapters (Loki, Sentry, OpenTelemetry, custom backends) COST SAVINGS: • Reduce log storage costs by 90% (request-scoped buffering) • Replace expensive APM SaaS ($500-5k/month → infra costs only) • Own your observability data (no vendor lock-in) PRODUCTION-READY: • Thread-safe for multi-threaded Rails + Sidekiq • Adaptive sampling (error-based, load-based, value-based) • PII filtering (GDPR-compliant masking/hashing) • Performance optimized (hash-based events, minimal allocations) Perfect for Rails 7.0+ teams who need observability without complexity or high costs.
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