Libraries tagged by url rule

Laravel package to sanitize and validate usernames, emails, phones, names, Ghana IDs, and URLs beyond default validation rules

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Configure rewrite rules for arbitrary (available) URLs.

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Texy converts plain text in easy to read Texy syntax into structurally valid (X)HTML. It supports adding of images, links, nested lists, tables and has full support for CSS. Texy supports hyphenation of long words (which reflects language rules), clickable emails and URL (emails are obfuscated against spambots), national typographic single and double quotation marks, ellipses, em dashes, dimension sign, nonbreakable spaces (e.g. in phone numbers), acronyms, arrows and many others. Texy code can optionally contain HTML tags. Minified version.

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WordPress equivalent of drupal_cache_protection. Strips/redirects tracking params so Varnish caches canonical URLs, augments robots.txt with bot-throttling rules, and exposes filters for site-specific extension.

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Generate smarter XML sitemaps for your Magento store with config-driven rules, CLI control, and built-in Google Search Console diff analysis. SEO Sitemaps Plus collects catalog and CMS URLs automatically and publishes sitemap files your GSC connector can compare against live index coverage.

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Publish fully compliant Google Merchant Center feeds with automated scheduling. Map Magento attributes to Google product schema using presets or custom rules. Produce supplemental feeds for promotions, sale pricing, and inventory. Validate feed output with warnings before pushing to Merchant Center. Automate uploads via SFTP, Content API, or downloadable URLs. Fully compatible with Magento 2.4.x Open Source and Adobe Commerce. Need feed setup or ongoing support? See our Magento development services, Magento maintenance services, and Magento hosting solutions.

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Generic Composer plugin that downloads platform-specific binaries — FFI shared libraries, CLI tools, WASM modules — from GitHub releases or any URL, driven by composer.json extra configuration

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Laravel Admin Panel

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# Introduction **INDA (INtelligent Data Analysis)** is an [Intervieweb](https://www.intervieweb.it/hrm/) AI solution provided as a RESTful API. The INDA pricing model is *credits-based*, which means that a certain number of credits is associated to each API request. Hence, users have to purchase a certain amount of credits (established according to their needs) which will be reduced at each API call. INDA accepts and processes a user's request only if their credits quota is grater than - or, at least, equal to - the number of credits required by that request. To obtain further details on the pricing, please visit our [site](https://inda.ai) or contact us. INDA HR embraces a wide range of functionalities to manage the main elements of a recruitment process: + [**candidate**](https://api.inda.ai/hr/docs/v2/#tag/Resume-Management) (hereafter also referred to as **resume** or **applicant**), or rather a person looking for a job; + [**job advertisement**](https://api.inda.ai/hr/docs/v2/#tag/JobAd-Management) (hereafter also referred to as **job ad**), which is a document that collects all the main information and details about a job vacancy; + [**application**](https://api.inda.ai/hr/docs/v2/#tag/Application-Management), that binds candidates to job ads; it is generated whenever a candidate applies for a job. Each of them has a specific set of methods that grants users the ability to create, read, update and delete the relative documents, plus some special features based on AI approaches (such as *document parsing* or *semantic search*). They can be explored in their respective sections. Data about the listed document types can be enriched by connecting them to other INDA supported entities, such as [**companies**](https://api.inda.ai/hr/docs/v2/#tag/Company-Management) and [**universities**](https://api.inda.ai/hr/docs/v2/#tag/Universities), so that recruiters may get a better and more detailed idea on the candidates' experiences and acquired skills. All the functionalities mentioned above are meant to help recruiters during the talent acquisition process, by exploiting the power of AI systems. Among the advantages a recruiter has by using this kind of systems, tackling the bias problem is surely one of the most relevant. Bias in recruitment is a serious issue that affect both recruiters and candidates, since it may cause wrong hiring decisions. As we care a lot about this problem, we are constantly working on reduce the bias in original data so that INDA results may be as fair as possible. As of now, in order to tackle the bias issue, INDA automatically ignores specific fields (such as name, gender, age and nationality) during the initial processing of each candidate data. Furthermore, we decided to let users collect data of various types, including personal or sensitive details, but we do not allow their usage if it is different from statistical purposes; our aim is to discourage recruiters from focusing on candidates' personal information, and to put their attention on the candidate's skills and abilities. We want to help recruiters to prevent any kind of bias while searching for the most valuable candidates they really need. The following documentation is addressed both to developers, in order to provide all technical details for INDA integration, and to managers, to guide them in the exploration of the implementation possibilities. The host of the API is [https://api.inda.ai/hr/v2/](https://api.inda.ai/hr/v2/). We recommend to check the API version and build (displayed near the documentation title). You can contact us at [email protected] in case of problems, suggestions, or particular needs. The search panel on the left can be used to navigate through the documentation and provides an overview of the API structure. On the right, you can find (*i*) the url of the method, (*ii*) an example of request body (if present), and (*iii*) an example of response for each response code. Finally, in the central section of each API method, you can find (*i*) a general description of the purpose of the method, (*ii*) details on parameters and request body schema (if present), and (*iii*) details on response schema, error models, and error codes.

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Provides simple functionality to manage SEO tags based on URL path within your Laravel application.

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create a menu that support page (multiLocale 'title/ url/ prefix', nesting, template, static/dynamic, roles & permissions).

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Allows to associate a social media post URL with each post, and optionally to display a link to it in the frontend.

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Allows to associate a social media post URL with each post, and optionally to display a link to it in the frontend.

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Bitly PHP SDK by Codehaveli uses the functionality of Bitly API version 4. This package is in initial release and have very less feature compared to main Bitly API.

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The Engine API is an HTTP API served by Docker Engine. It is the API the Docker client uses to communicate with the Engine, so everything the Docker client can do can be done with the API. Most of the client's commands map directly to API endpoints (e.g. `docker ps` is `GET /containers/json`). The notable exception is running containers, which consists of several API calls. # Errors The API uses standard HTTP status codes to indicate the success or failure of the API call. The body of the response will be JSON in the following format: ``` { "message": "page not found" } ``` # Versioning The API is usually changed in each release, so API calls are versioned to ensure that clients don't break. To lock to a specific version of the API, you prefix the URL with its version, for example, call `/v1.30/info` to use the v1.30 version of the `/info` endpoint. If the API version specified in the URL is not supported by the daemon, a HTTP `400 Bad Request` error message is returned. If you omit the version-prefix, the current version of the API (v1.40) is used. For example, calling `/info` is the same as calling `/v1.40/info`. Using the API without a version-prefix is deprecated and will be removed in a future release. Engine releases in the near future should support this version of the API, so your client will continue to work even if it is talking to a newer Engine. The API uses an open schema model, which means server may add extra properties to responses. Likewise, the server will ignore any extra query parameters and request body properties. When you write clients, you need to ignore additional properties in responses to ensure they do not break when talking to newer daemons. # Authentication Authentication for registries is handled client side. The client has to send authentication details to various endpoints that need to communicate with registries, such as `POST /images/(name)/push`. These are sent as `X-Registry-Auth` header as a Base64 encoded (JSON) string with the following structure: ``` { "username": "string", "password": "string", "email": "string", "serveraddress": "string" } ``` The `serveraddress` is a domain/IP without a protocol. Throughout this structure, double quotes are required. If you have already got an identity token from the [`/auth` endpoint](#operation/SystemAuth), you can just pass this instead of credentials: ``` { "identitytoken": "9cbaf023786cd7..." } ```

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