Libraries tagged by help php
gameplayjdk/php-static-help
5318 Downloads
Common static helper classes.
seracid/php-mail-bounce-handler
450 Downloads
PHP class to help webmasters handle bounce-back, feedback loop and ARF mails in standard DSN (Delivery Status Notification, RFC-1894).
leehom1988/ios-iap-verification-php
4955 Downloads
This PHP Class is help you to verification your Apple IAP receipt-data if your server is developed by PHP.
ip2whois/ip2whois-php
163 Downloads
IP2WHOIS PHP SDK to help user to check WHOIS information for a particular domain.
suin/php-expose
6268 Downloads
Makes non-public properties and methods be testable to help your unit tests with PHPUnit.
kevinoo/laravel-phpdoc-helper
1324 Downloads
Help IDE to know the PHPDoc for classes use via Facade
thesmart/php-cli-tools
7770 Downloads
A collection of tools to help with command line development in PHP 5.3
nxu/php-nano-class-parser
3945 Downloads
A fully opinionated, extremely minimal, and very optimistic package to help add custom code to generated PHP classes.
sidz/phpstan-cakephp2
5548 Downloads
An extension to help test CakePHP 2 projects with PHPStan
ups-api/php-widget-sdk
79 Downloads
This SDK will help you generate the access token using PHP . Using this access token you will be able to connect to widgets supported by UPS.
uctoplus/uctoplus-php-api
4229 Downloads
Production environment is located at `https://api.moje.uctoplus.sk/production/`. Sandbox environment is located at `https://api.moje.uctoplus.sk/sandbox/`. All communication with API is encoded in UTF-8. This REST API is based on Open API v3 standard. For help with implementation or access to the test environment please contact our helpdesk
othyn/php-time-remaining
1393 Downloads
A tiny library that helps with simple progress output, focusing on time remaining.
myoutdeskllc/salesforce-php-query-builder
99 Downloads
library to help build soql queries for use with the rest api
keepcloud/freshdesk-php-sdk
2174 Downloads
PHP SDK for the Freshdesk API (v2)
inda-hr/php_sdk
828 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.