Mongo for ES2015
Large collection of predicates.
Enhance ESLint with better support for large scale monorepos
Consistent dependency versions in large JavaScript Monorepos
Big-friendly JSON. Asynchronous streaming functions for large JSON data sets.
React components for efficiently rendering large, scrollable lists and tabular data
Large object support for PostgreSQL clients (node-postgres)
A TypeScript ESLint ruleset designed for large teams and projects
TypeScript definitions for pg-large-object
A virtual scroll React component for efficiently rendering large scrollable lists, grids, tables, and feeds
Axios plugin to intercept large responses
Search and Rewrite code at large scale using precise AST pattern
Search and Rewrite code at large scale using precise AST pattern
Tokenizer for OpenAI large language models.
Web component - Large Card
Creates and manages per-zoom-level clusters for large amounts of markers.
A high-performance pure-javascript SHA1 implementation suitable for large binary data.
A mature CSV toolset with simple api, full of options and tested against large datasets.
React component for efficiently rendering large tree structures
Platform-agnostic service for storing large, infrequently accessed controller data
Search and Rewrite code at large scale using precise AST pattern
Search and Rewrite code at large scale using precise AST pattern
Upload large files from the browser with ease
Search and Rewrite code at large scale using precise AST pattern
Rust LLM inference implementation.
A high-performance viewer for large text files
A decentralized version control system for AI models and large files
Large object support for rust-postgres
A high-performance, O(P) data structure for weighted random sampling of binned probabilities, ideal for large-scale simulations.
Core library for handling large text files search and replace efficiently
command line
Search, hash, sort, fingerprint, and fuzzy-match strings faster via SWAR, SIMD, and GPGPU
Scripty - your Rust command toolkit for easy command execution and file operations
A comprehensive Rust client library for the Veracode platform (Applications, Identity, Pipeline Scan, Sandbox)
A streaming JSON‐array parser that yields one object at a time
This crate provides a complete implementation of the SQL-on-FHIR specification for Rust, enabling the transformation of FHIR resources into tabular data using declarative ViewDefinitions. It supports all major FHIR versions (R4, R4B, R5, R6) through a version-agnostic abstraction layer.
Large text fields are kept in a central table, and polymorphically associated with your models. Access and assignment should behave as if it was a column on the same table.
Store large objects in memcache or others
Large binomials
Migrate large tables without downtime by copying to a temporary table in chunks. The old table is not dropped. Instead, it is moved to timestamp_table_name for verification.
Ruby class to read large files on 32 bit Linux platforms.
Rack middleware for handling large file uploads. Integrates nicely with the Nginx upload module: http://www.grid.net.ru/nginx/upload.en.html
Large CSV builder and proccesor, it can help with creation of large csv files, reading those files and make operation over the csv data
This gem integrates the Twitter Bootstrap [LARGE]pagination component with the will_paginate pagination gem. Supports Rails and Sinatra.
Handy conversions for finance numbers to floats
Boot large ruby/rails apps faster
Lazily loads large columns on demand. By default, does this for all TEXT (:text) and BLOB (:binary) columns, but a list of specific columns to load on demand can be given. This is useful to reduce the memory taken by Rails when loading a number of records that have large columns if those particular columns are actually not required most of the time. In this situation it can also greatly reduce the database query time because loading large BLOB/TEXT columns generally means seeking to other database pages since they are not stored wholly in the record's page itself. Although this plugin is mainly used for BLOB and TEXT columns, it will actually work on all types - and is just as useful for large string fields etc.
Large-scale sparse matrix factorization for Ruby
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