Libraries tagged by maybe

Determine if a page may be crawled from robots.txt and robots meta tags

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The extension provides support for sending notifications across a variety of delivery channels, including mail, SMS, Slack etc. Notifications may also be stored in a database so they may be displayed in your web interface.

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To build your perfect website you probably need images, video's or maybe even a presentation too. The Kunstmaan Media Bundle handles all those media assets and centralizes them so you can find your content just the way you like it: fast and efficiently. No central asset management module is useful without some pretty advanced image editing functionality. To provide this we have integrated the Aviary image editing service right from the interface.

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Simplify the way your editors may upload their images: no complex local procedure needed, let TYPO3 automatically resize down their huge images/pictures on-the-fly during upload (or using a command for batch processing) and according to your own business rules (directory/groups). This will highly reduce the footprint on your server and speed-up response time if lots of images are rendered (e.g., in a gallery). Features an EXIF/IPTC extractor to ensure metadata may be used by the FAL indexer even if not preserved upon resizing.

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A simple functional programming library.

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Send notifications across a variety of delivery channels, including mail and Slack. Notifications may also be stored in a database so they may be displayed in your web interface.

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Sets of digits or characters that may be used for base conversions, encoding and decoding tasks, and input validation

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Send notifications across a variety of delivery channels, including mail and Slack. Notifications may also be stored in a database so they may be displayed in your web interface.

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Send notifications across a variety of delivery channels, including mail and Slack. Notifications may also be stored in a database so they may be displayed in your web interface.

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An implementation of the Maybe monad in PHP.

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OwlCarousel2 assets for Yii PHP framework 2.0

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Big file creation helper. May be used for sitemap.xml or YML files creation.

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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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Option & Result types

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TinyMCE widget for Yii PHP framework 2.0

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