Libraries tagged by has-one

This module provides CMS field to manage data object defined in a has_one relation.

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One-To-One Relationship with Pivot for Laravel Eloquent

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Allows editing the fields of a has_one object directly in the CMS

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Allow sync method for Laravel Has Many and Morph Many Relationship.

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GridField based management of has_one , has_many , and many_many relationship selection

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SilverStripe 4 custom form element for anchor, email, telephone, file, image, internal and external links

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GridField based management of has_one , has_many , and many_many relationship selection

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A decorator for form fields that manage object relationships, to allow adding a new object on the fly through a dialog window. It can handle has_one, has_many or many_many relationships. At the moment it has been tested / works on DropdownField and ListboxField. It works both in the CMS and in the frontend.

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TYPO3 CMS extension media2click: Render external content like videos an iframes with privacy in mind: User has to click on placeholder to load the actual content.

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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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The Order Management API is used for handling an order after the customer has completed the purchase. It is used for all actions you need to manage your orders. Examples being: updating, capturing, reading and refunding an order. Read more on the [Order management](https://docs.klarna.com/order-management/) process. # Authentication

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The Cookiebot.com GDPR Compliant TYPO3 Extension aids publishers, technology vendors, and advertisers in complying with GDPR and ePrivacy Directive regulations by ensuring transparency and obtaining user consent. T3Planet has developed a TYPO3 CMS extension to seamlessly integrate Cookiebot, one of the most popular solutions for managing cookies.

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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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This library provides an API to perform binary search operations on a sorted index. The index can be a XML document, a CSV document, or an arbitrary text file where the key has a fixed position. You can easily implement your own index. This API comes handy on any sorted data structure where realtime search operations are necessary without the detour of a DBS import.

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Add a Laravel relationship where you can specify a set ID, instead of a dynamic relationship

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