Libraries tagged by codis
lilaconcepts/lilaconceptsbestpracticebundle
153 Downloads
Simple common, starter, empty, boilerplate-bundle to show best practice bundle development for Symfony2.1. This bundle has the right directory structure, coding standards, unittests and functional tests. It uses the Travis Continuous Integration buildbot, Composer for dependency management and Twig for templating. Read the documentation and fork/clone if you wish.
lemaur/toolbox
4004 Downloads
Toolbox full of useful packages to keep your Laravel project compliant with your coding standards.
leadtech/http-commons
18938 Downloads
A zero dependency set of definitions to help work with headers and status codes.
kdubuc/php-cs-fixer-rules
1234 Downloads
PHP Coding Standards Rules
kazemmdev/http-status
1180 Downloads
A simple Enum for http status codes responses
jparkinson1991/phpcodesniffer-standards
7588 Downloads
Custom PHP_Codesniffer standards
jbrooksuk/phpcheckstyle
399 Downloads
PHPCheckstyle is an open-source tool that helps PHP programmers adhere to certain coding conventions
janisvepris/gs1-decoder
2742 Downloads
A library for parsing GS1 codes in PHP
inda-hr/php_sdk
419 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.
ijeffro/laravel-airports
1788 Downloads
Laravel Airports is a bundle for Laravel, providing Iata Code ISO 3166 3 and country codes for all the airports.
ijeffro/laravel-airlines
6866 Downloads
Laravel Airlines is a bundle for Laravel, providing Iata Code ISO 3166 3 and country codes for all the airlines.
hayleyberryl2s/amazongiftcode
527 Downloads
Laravel Package for Amazon Gift Codes.
havvg/http-exception
11986 Downloads
A collection of exception classes to reflect HTTP status codes.
froiden/php_standard
206 Downloads
PHP coding standard to be followed at Froiden
francerz/utils
214 Downloads
Common utilities for coding