Libraries tagged by ACPU

Verifies that files managed by Drupal actually exist at the location where Drupal believes they are.

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Mock of Stripe's HttpClient which can be used in testing purposes in order to test your code and not to perform actual HTTP requests

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PHP_CodeSniffer integration for Acquia BLT

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Obtenga el dígito de verificación de cualquier cédula de acuerdo con la norma de la DIAN en Colombia. Una forma simple, rápida y confiable de obtener el dígito de verificación de cualquier NIT en Colombia, esto de acuerdo con la resolución expedida por la DIAN.

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Mock of Stripe's HttpClient which can be used in testing purposes in order to test your code and not to perform actual HTTP requests

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Acquire your payments using PHP with the pensopay API

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Extension for reviewing passed tests, with the display of actual and correct answers.

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Extension for actuallymab/laravel-comment package. Allow comment as guest and add other meta-info.

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A parser and validate Malaysian business registration numbers (BRN). This library ensures compliance with SSM formatting standards, accurately extracts components such as entity type and registration year, and verifies the integrity of BRNs.

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This package contains an interface used by many objects to say they can do stuff. Actually, they can perform one particular action and has been designed for that. The action performed is completely up to the implementer (sending a mail, storing a result in database, displaying something on the screen...) The concept is very simple, and very powerful at the same time.

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TYPO3 extension wrapping PHP word hyphenation using the TeX hyphenation algorithm for accurate text formatting.

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Library to replace variables and share-code placeholders in component configuration with actual values

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Use IP2Location geolocation database to lookup for accurate visitor location in Matomo. It enables the user to find the country, region, city, coordinates, zip code, time zone, ISP, domain name, connection type, area code, weather, MCC, MNC, mobile brand name, elevation and usage type that any IP address or hostname originates from. http://www.ip2location.com

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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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Parsing and formatting dates can be difficult, especially if you deal with multilingual content. Date Methods aims to simplify date output by providing page and field methods to handle points in time as well as date ranges accurately in your snippets and templates.

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