Libraries tagged by further

PHP-Mock can mock built-in PHP functions (e.g. time()). PHP-Mock relies on PHP's namespace fallback policy. No further extension is needed.

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Uploadcare PHP integration handles uploads and further operations with files by wrapping Upload and REST APIs.

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Mock built-in PHP functions (e.g. time()) with PHPUnit. This package relies on PHP's namespace fallback policy. No further extension is needed.

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Mock built-in PHP functions (e.g. time()) with Mockery. This package relies on PHP's namespace fallback policy. No further extension is needed.

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[clickstorm] SEO - Extension for TYPO3. Enables important onpage features for search engine optimization (SEO). Expands the page settings and any desired records for example with a preview for Google search results (SERP) Structured Data (JSON-LD) and a Focus Keyword. Restrictive hreflang and canonical tags. Modules for metadata of records and alternative texts of images. Further features are shown in the extension manual.

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Mock built-in PHP functions (e.g. time()) with Prophecy. This package relies on PHP's namespace fallback policy. No further extension is needed.

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The package adds marketing functionalities to Contao. The Contao Marketing Suite enables dynamic playout of content to provide visitors with relevant information. Furthermore there is A/B test, SEO support, text creation tools, own tracking for links and forms. In addition, a button generator, a configurable cookie bar (already compliant with EU privacy) and many other marketing functions for professional marketing with Contao.

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Every website contains several lists of content ranging from articles on a blog, to drop down values. The KunstlaanAdminListBundles takes CRUD a step further by supplying filtering, exports to csv and editing capabilities to these content entities.

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[clickstorm] SEO - Extension for TYPO3. Enables important onpage features for search engine optimization (SEO). Expands the page settings and any desired records for example with a preview for Google search results (SERP) Structured Data (JSON-LD) and a Focus Keyword. Restrictive hreflang and canonical tags. Modules for metadata of records and alternative texts of images. Further features are shown in the extension manual.

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CSS/Javascript Minificator, Compressor And Concatenator - This extension minimizes the http requests by concatenating your css and javascript. Furthermore the result can be minified and compressed. This whole process is highly configurable and is partly based on the "minify", "jsminplus" and "jsmin" projects.

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# Introduction Welcome to the Passbase Verifications API docs. This documentation will help you understand our models and the Verification API with its endpoints. Based on this you can build your own system (i.e. verification) and hook it up to Passbase. In case of feedback or questions you can reach us under this email address: [[email protected]](mailto:[email protected]). A User submits a video selfie and valid identifying __Resources__ during a __Verification__ guided by the Passbase client-side integration. Once all the necessary __Resources__ are submitted, __Data points__ are extracted, digitized, and authenticated. These Data points then becomes part of the User's __Identity__. The User then consents to share __Resources__ and/or __Data points__ from their Identity with you. This information is passed to you and can be used to make decisions about a User (e.g. activate account). This table below explains our terminology further. | Term | Description | |-----------------------------------------|-------------| | [Identity](#tag/identity_model) | A set of Data points and Resources related to and owned by one single User. This data can be accessed by you through a Verification. | | Data points | Any data about a User extracted from a Resource (E.g. Passport Number, or Age). | | [Resource](#tag/resource_model) | A source document used to generate the Data points for a User (E.g. Passport). | | [User](#tag/user_model) | The owner of an email address associated with an Identity. | | Verification | A transaction through which a User consents to share Data points with you. If the Data points you request are not already available in the User's Identity, the Passbase client will ask the User to submit the necessary Resource required to extract them. | | Re-authentication (login) | A transaction through which a User can certify the ownership of Personal data previously shared through an Authentication. | # Authentication There are two forms of authentication for the API: • API Key • Bearer JWT Token

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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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Simple job market based on Extbase and Fluid. Basically works like dmmjobcontrol. There are list and detail views available. In addition, it is possible to set up an online application system. Furthermore, FE-Users can be enabled to add and edit jobs in the frontend, so to BE-Administration is required. Feeds (Rss091, Rss2, Atom) are also available

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Set of Migration Helpers and further Migration Tools for Pimcore Migrations.

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