Libraries tagged by test data generator
edfi/resources
23543 Downloads
The Ed-Fi ODS / API enables applications to read and write education data stored in an Ed-Fi ODS through a secure REST interface. *** > *Note: Consumers of ODS / API information should sanitize all data for display and storage. The ODS / API provides reasonable safeguards against cross-site scripting attacks and other malicious content, but the platform does not and cannot guarantee that the data it contains is free of all potentially harmful content.* ***
edfi/descriptors
23540 Downloads
The Ed-Fi ODS / API enables applications to read and write education data stored in an Ed-Fi ODS through a secure REST interface. *** > *Note: Consumers of ODS / API information should sanitize all data for display and storage. The ODS / API provides reasonable safeguards against cross-site scripting attacks and other malicious content, but the platform does not and cannot guarantee that the data it contains is free of all potentially harmful content.* ***
atoum/praspel-extension
28310 Downloads
Include Praspel inside atoum.
spryker-sdk/manifest-test-data-provider
3720 Downloads
Data provider for manifests generation and integration tests
richcongress/fixture-test
37105 Downloads
Generate random and meaningful data for objects
rbone/phactory
57387 Downloads
A PHP library for generating data for tests
rewards-wise/mx-sdk-php
38 Downloads
The MX Platform API is a powerful, fully-featured API designed to make aggregating and enhancing financial data easy and reliable. It can seamlessly connect your app or website to tens of thousands of financial institutions.
neclimdul/coveo-push-api
920 Downloads
The Push API allows you to *push* items and security identities, as opposed to letting standard Coveo Cloud V2 crawlers *pull* this data from a content repository. This is especially useful when you need to index content from a cloud or on-premises system for which no dedicated source type exists in the Coveo Cloud V2 platform.
inda-hr/php_sdk
862 Downloads
# 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.
denheck/faker-context
6296 Downloads
Behat context for generating test data
joshmoody/mock-data
243 Downloads
Generate realistic test data.
prog-time/laravel-request-testdata
15 Downloads
A Laravel package for automatically generating test request data based on validation rules.
whatpulse/api-sdk-php
8 Downloads
Public API for WhatPulse user data access. This API allows authenticated users to access their own data and public data from other users, depending on privacy settings.
vigicorp/yousign-api-v3
152 Downloads
Build the best experience of digital signature through your own platform. Increase your conversion rates, leverage your data and reduce your costs with Yousign API.
umbalaconmeogia/php-test-data
3 Downloads
Utility to generate test data.