Results for edge-functions

Edge Functions client for supabase-client

Generators can be a bit of a pain to write. This little gem smooths out some rough edges, by letting you mirror an entire directory in one line, and providing convenience functions to add entire blocks of code to pre-existing configuration files.

Networkr is a Ruby gem inspired by the Python package NetworkX. It includes basic functionality for the creation, manipulation, and analysis of graphs. Graphs supported include undirected single-edge graphs (weighted or unweighted), directed single-edge graphs (weighted or unweighted), and undirected multi-edge graphs (weighted or unweighted). Algorithms available include Dijkstra's shortest paths, Karger's minimum cut, Kosaraju's strongly connected components, and Prim's minimum spanning tree.

Ruby client for Supabase: Auth, PostgREST, Storage, Edge Functions, and Realtime exposed through a single Supabase.create_client(supabase_url:, supabase_key:) factory, mirroring supabase-py's create_client().

Dive into the world of Python-based structured extraction, empowered by OpenAI's cutting-edge function calling API. Instructor stands out for its simplicity, transparency, and user-centric design. Whether you're a seasoned developer or just starting out, you'll find Instructor's approach intuitive and its results insightful.

JsonCanvas is a Ruby gem that provides a robust implementation of the JSONCanvas specification. This gem enables developers to easily create and manipulate JSONCanvas format. It supports functionalities such as adding text, files, links, and grouping nodes with customizable attributes like position, size, and identifiers. Additional features include connecting nodes with edges that have customizable attributes, and the ability to save and load canvas states from JSON files. This gem facilitates the easy integration of the JSONCanvas format into Ruby applications, enhancing development efficiency and user experience.

In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that keeps track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. It provides near-constant-time operations (bounded by the inverse Ackermann function) to add new sets, to merge existing sets, and to determine whether elements are in the same set. In addition to many other uses (see the Applications section), disjoint-sets play a key role in Kruskal's algorithm for finding the minimum spanning tree of a graph. A disjoint-set forest consists of a number of elements each of which stores an id, a parent pointer, and, in efficient algorithms, a value called the "rank". The parent pointers of elements are arranged to form one or more trees, each representing a set. If an element's parent pointer points to no other element, then the element is the root of a tree and is the representative member of its set. A set may consist of only a single element. However, if the element has a parent, the element is part of whatever set is identified by following the chain of parents upwards until a representative element (one without a parent) is reached at the root of the tree. Forests can be represented compactly in memory as arrays in which parents are indicated by their array index. Disjoint-set data structures model the partitioning of a set, for example to keep track of the connected components of an undirected graph. This model can then be used to determine whether two vertices belong to the same component, or whether adding an edge between them would result in a cycle. The Union–Find algorithm is used in high-performance implementations of unification. This data structure is used by the Boost Graph Library to implement its Incremental Connected Components functionality. It is also a key component in implementing Kruskal's algorithm to find the minimum spanning tree of a graph. Note that the implementation as disjoint-set forests doesn't allow the deletion of edges, even without path compression or the rank heuristic. Sharir and Agarwal report connections between the worst-case behavior of disjoint-sets and the length of Davenport–Schinzel sequences, a combinatorial structure from computational geometry.

http://www.engineyard.com/blog/2010/extending-rails-3-with-railties/ http://www.igvita.com/2010/08/04/rails-3-internals-railtie-creating-plugins/ h1. Morning Glory Morning Glory is comprised of a rake task and helper methods that manages the deployment of static assets into an Amazon CloudFront CDN's S3 Bucket, improving the performance of static assets on your Rails web applications. _NOTE: You will require an Amazon Web Services (AWS) account in order to use this gem. Specially: S3 for storing the files you wish to distribute, and CloudFront for CDN distribution of those files._ This version of Morning Glory works with Rails 3.x and Ruby 1.9.x h2. What does it do? Morning Glory provides an easy way to deploy Ruby on Rails application assets to the Amazon CloudFront CDN. It solves a number of common issues with S3/CloudFront. For instance, CloudFront won't automatically expire old assets stored on edge nodes when you redeploy new assets (the Cloudfront expiry time is 24 hours minimum). To fix this Morning Glory will automatically namespace asset releases for you, then update all references to those renamed assets within your stylesheets ensuring there are no broken asset links. It also provides a helper method to rewrite all standard Rails asset helper generated URLs to your CloudFront CDN distributions, as well as handling switching between HTTP and HTTPS. Morning Glory was also built with SASS (Syntactically Awesome Stylesheets) in mind. If you use Sass for your stylesheets they will automatically be built before deployment to the CDN. See http://sass-lang.com/ for more information on Sass.s h2. What it doesn't do Morning Glory cannot configure your CloudFront distributions for you automatically. You will manually have to login to your AWS Management Console account, "https://console.aws.amazon.com/cloudfront/home":https://console.aws.amazon.com/cloudfront/home, and set up a distribution pointing to an S3 Bucket. h2. Installation <pre> gem 'morning_glory' </pre> h2. Usage Morning Glory provides it's functionality via rake tasks. You'll need to specify the target rails environment configuration you want to deploy for by using the @RAILS_ENV={env}@ parameter (for example, @RAILS_ENV=production@). <pre> rake morning_glory:cloudfront:deploy RAILS_ENV={YOUR_TARGET_ENVIRONMENT} </pre> h2. Configuration h3. The Morning Glory configuration file, @config/morning_glory.yml@ You can specify a configuration section for every rails environment (production, staging, testing, development). This section can have the following properties defined: <pre> --- production: enabled: true # Is MorningGlory enabled for this environment? bucket: cdn.production.foo.com # The bucket to deploy your assets into s3_logging_enabled: true # Log the deployment to S3 revision: "20100317134627" # The revision prefix. This timestamp automatically generateed on deployment delete_prev_rev: true # Delete the previous asset release (save on S3 storage space) </pre> h3. The Amazon S3 authentication keys configuration file, @config/s3.yml@ This file provides the access credentials for your Amazon AWS S3 account. You can configure keys for all your environments (production, staging, testing, development). <pre> --- production: access_key_id: YOUR_ACCESS_KEY secret_access_key: YOUR_SECRET_ACCESS_KEY </pre> Note: If you are deploying your system to Heroku, you can configure your Amazon AWS S3 information with the environment variables S3_KEY and S3_SECRET instead of using a configuration file. h3. Set up an asset_host For each environment that you'd like to utilise the CloudFront CDN for you'll need to define the asset_host within the @config/environments/{ENVIRONMENT}.rb@ configuration file. As of June 2010 AWS supports HTTPS requests on the CloudFront CDN, so you no longer have to worry about switching servers. (Yay!) h4. Example config/environments/production.rb @asset_host@ snippet: Here we're targeting a CNAME domain with HTTP support. <pre> ActionController::Base.asset_host = Proc.new { |source, request| if request.ssl? "#{request.protocol}#{request.host_with_port}" else "#{request.protocol}assets.example.com" end } </pre> h3. Why do we have to use a revision-number/namespace/timestamp? Once an asset has been deployed to the Amazon Cloudfront edge servers it cannot be modified - the version exists until it expires (minimum of 24 hours). To get around this we need to prefix the asset path with a revision of some sort - in MorningGlory's case we use a timestamp. That way you can deploy many times during a 24 hour period and always have your latest revision available on your web site. h2. Dependencies h3. AWS S3 Required for uploading the assets to the Amazon Web Services S3 buckets. See "http://amazon.rubyforge.org/":http://amazon.rubyforge.org/ for more documentation on installation. h2. About the name Perhaps not what you'd expect; a "Morning Glory":http://en.wikipedia.org/wiki/Morning_Glory_cloud is a rare cloud formation observed by glider pilots in Australia (see my side project, "YourFlightLog.com for flight-logging software for paraglider and hang-glider pilots":http://www.yourflightlog.com, from which the Morning Glory plugin was originally extracted). Copyright (c) 2010 "@AdamBurmister":http://twitter.com/adamburmister/, released under the MIT license

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