Libraries tagged by equal nest

This behavior provides a way to define relations between objects that have equal hierarchy (friendship).

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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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Compute phylogenetic trees from distance matrix using BioNJ algorithm. It produce Newick file and Weighted newick if needed. There is also a render using Equal-angle algorithm and SVG output for testing. It's recommended to use a JS render like 'phylotree.js' (demo of phylotree.js here http://phylotree.hyphy.org/).

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Essa é uma classe php onde tem métodos que podem ser chamados igual no Eloquent. Serve para criar repositórios e facilitar os testes unitários sem perder o poder do Eloquent - This is a php class where it has methods that can be called equal in Eloquent. It serves to create responses and facilitate unit tests without losing the power of the Eloquent

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Provides a toEqualGolden assertion, same as toEqual, but when null is given as argument, the test file is automatically edited and null is substituted with the actual value

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Ensure that both arguments are equal

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The Nodeum API makes it easy to tap into the digital data mesh that runs across your organisation. Make requests to our API endpoints and we’ll give you everything you need to interconnect your business workflows with your storage. All production API requests are made to: http://nodeumhostname/api/ The current production version of the API is v1. **REST** The Nodeum API is a RESTful API. This means that the API is designed to allow you to get, create, update, & delete objects with the HTTP verbs GET, POST, PUT, PATCH, & DELETE. **JSON** The Nodeum API speaks exclusively in JSON. This means that you should always set the Content-Type header to application/json to ensure that your requests are properly accepted and processed by the API. **Authentication** All API calls require user-password authentication. **Cross-Origin Resource Sharing** The Nodeum API supports CORS for communicating from Javascript for these endpoints. You will need to specify an Origin URI when creating your application to allow for CORS to be whitelisted for your domain. **Pagination** Some endpoints such as File Listing return a potentially lengthy array of objects. In order to keep the response sizes manageable the API will take advantage of pagination. Pagination is a mechanism for returning a subset of the results for a request and allowing for subsequent requests to “page” through the rest of the results until the end is reached. Paginated endpoints follow a standard interface that accepts two query parameters, limit and offset, and return a payload that follows a standard form. These parameters names and their behavior are borrowed from SQL LIMIT and OFFSET keywords. **Versioning** The Nodeum API is constantly being worked on to add features, make improvements, and fix bugs. This means that you should expect changes to be introduced and documented. However, there are some changes or additions that are considered backwards-compatible and your applications should be flexible enough to handle them. These include: - Adding new endpoints to the API - Adding new attributes to the response of an existing endpoint - Changing the order of attributes of responses (JSON by definition is an object of unordered key/value pairs) **Filter parameters** When browsing a list of items, multiple filter parameters may be applied. Some operators can be added to the value as a prefix: - `=` value is equal. Default operator, may be omitted - `!=` value is different - `>` greater than - `>=` greater than or equal - `=` lower than or equal - `>

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A Codeception extension & Robo task that records test runtimes and lets you split tests into equal runtime-based groups for parallel runs

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Pagedesigner product test suite.

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A tiny framework for writing Drupal test classes in a decoupled way from the PHPUnit/Drupal framework so that they can be reused in different contexts.

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