Sift out your valid inputs... functionally!
MongoDB query filtering in JavaScript
MongoDB query filtering in JavaScript
store and query json objects in redis lists
Another ingredient/recipe scraper.
MongoDB query filtering in JavaScript
MongoDB query filtering in JavaScript
MongoDB query filtering in JavaScript
Structural codebase index for LLM tooling — query definitions, call graphs, and imports without embeddings.
A paper-oriented Rust implementation of Lowe's SIFT detector, descriptor, BBF matcher, and Hough recognition helpers.
High-performance SIFT (Scale-Invariant Feature Transform) implementation in Rust with CPU and WebGPU backends.
A robust Sift telemetry streaming library
High-performance Rust core for context distillation (Studio of Two)
A convenient and opinionated way to connect to the Sift API
Context-Pipe high-performance Rust orchestrator and library
Safety-critical cognitive safety library for AI agents. 4-tier architecture (Resource Body, Kernel, Working Memory, Sifter) with formal verification primitives, detection layer, and integration primitives.
Grep-like CLI for sift-core
General Rust client library for the Sift API
Strip noise from error output. Powered by a local LLM.
Crate-specific Sift errors
Easily write arbitrary filters
Sift Ruby API. Please see http://sift.com for more details.
Parascope::Query class provides a way to dynamically apply scopes or ActiveRecord query methods based on passed params with a declarative and convenient API
Sift Science Ruby Partner API. Please see http://siftscience.com for more details.
Zen::Query class provides a way to dynamically apply scopes or ActiveRecord (or any other ORM) query methods based on passed params with a declarative and convenient API
Sift identifies certain types of emails and parses email content so you can deliver a richer experience to your users. Sift can parse emails from a variety of domains.
SolveBio is a platform for biomedical datasets. With SolveBio you can forget about parsing complex flat files and sifting through cryptic datasets. Just use the Ruby Client and API to explore massive datasets and automate just about any bioinformatics workflow. See https://www.solvebio.com/ for more information.
Deprecated. I'm planning to discontinue this gem. Although it has enormous flexibility and power, it is in my view too complex. 80% of requirements can be met through custom shell scripts which are much simpler to write and maintain. Sifts through your log files in real time, using stateful intelligence to determine what is really important. REC can alert you (by email or IM) or it can simply condense a large log file into a much shorter and more meaningful log. REC is inspired by Risto Vaarandi's brilliant *sec* (simple-evcorr.sourceforge.net) but is original code and any defects are entirely mine. While event correlation is inherently complex, REC attempts to make common tasks easy while preserving plenty of power and flexibility for ambitious tasks.
CrmFormatter is perfect for curating high-volume enterprise-scale web scraping, and integrates well with Nokogiri, Mechanize, and asynchronous jobs via Delayed_job or SideKick, to name a few. Web Scraping and Harvesting often gathers a lot of junk to sift through; presenting unexpected edge cases around each corner. CrmFormatter has been developed and refined during the past few years to focus on improving that task. It's also perfect for processing API data, Web Forms, and routine DB normalizing and scrubbing processes. Not only does it reformat Address, Phone, and Web data, it can also accept lists to scrub against, then providing detailed reports about how each piece of data compares with your criteria lists.