Libraries tagged by create table

envms/fluentpdo

929 Favers
383161 Downloads

FluentPDO is a quick and light PHP library for rapid query building. It features a smart join builder, which automatically creates table joins.

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lichtner/fluentpdo

935 Favers
235673 Downloads

FluentPDO is a quick and light PHP library for rapid query building. It features a smart join builder, which automatically creates table joins.

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fpdo/fluentpdo

929 Favers
219442 Downloads

FluentPDO is a quick and light PHP library for rapid query building. It features a smart join builder, which automatically creates table joins.

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repat/laravel-job-models

8 Favers
22755 Downloads

Eloquent Models for the tables job and job_fails as created by artisan queue:table and queue:failed-table

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rmitesh/filament-action

12 Favers
3280 Downloads

Creates a Filament table action.

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dynamic/silverstripe-elemental-tabset

3 Favers
15314 Downloads

Create a tabbed interface that uses elements

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starcitizentools/tabber-neue

14 Favers
82 Downloads

Allows to create tabs within a page. Forked from Extension:Tabber

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repat/laravel-database-session-model

1 Favers
11110 Downloads

Eloquent Model for the sessions table as created by artisan session:table

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typisttech/wp-admin-tabs

17 Favers
12496 Downloads

Create tabbed navigation for WordPress admin dashboard, the OOP way

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level-2/maphper

53 Favers
744 Downloads

A lightweight ORM using the DataMapper pattern, creates database tables on the fly.

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sgalinski/df-tabs

1 Favers
3778 Downloads

Tabbed Content and Pages - Create tab based content elements and pages easily and flexible with configurable mouseover handling, animations and autoplay features! It requires jquery.

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pkeidel/dbtolaravel

0 Favers
430 Downloads

Reads a database and creates the migrations, models, controllers and blades for the tables

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inda-hr/php_sdk

6 Favers
494 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.

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phphackes/zend-tablegateway-factory

1 Favers
580 Downloads

Creates TableGateways according to schema and table name provided.

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wikifab/tabber

0 Favers
3572 Downloads

This is a mediawiki extension to create tabs in mediawiki pages

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