docs

Doumentation, Tutorial, Information, Comparasion to another tools

Existing solutions

https://cloud-elements.com/elements/sql-server-api/

One-to-Many One API Integration to connect you to all the leading database services: MySQL, SQL Server and PostreSQL. HubSpot API

Simple Data Mapping Using Element Mapper, our drag-and-drop UI, easily map and normalize data objects and fields between leading cloud services. Marketing Cloud Services

Stay Up to Date We even manage user access and authentication, API updates, logging and monitoring, all from a consistent platform.

Make Api fast

https://nordicapis.com/making-fast-apis-lessons-learned-from-40-years-of-sql/

Another

https://carto.com/developers/sql-api/reference/#operation/postSQLStatement

Why apiSQL

This is tool, which is the first step to reach in practical some parts of goals for UnitApi which will be later the main standard to build any API

urlQuery -> sqlQuery

apiSQL

This tools is able to create meta data from SQL statement and SQL schema The way from SQL to API is possbile with one step, just for configuration

import-export generator

apisql.yaml

version: 1.1.0
  name: Import data from localhost application  
  import:
    file:
    dump:
    db:
      host:
      password          
  export:
    file:

Input

The sql file

Output

The Code, sdk

Parsing, Structure of schema

Source
    Collection
        Object
            Param

Collection
    List: 1,2,9,11
    Range: 1-11, A-M 
    Filter:
        Object,Param

Object:
    Create
    Read
    Update
    Delete

Param
    Get
    Set

output: collection | CRUD

many items Collection as model,view (one or more models)

Schema:
    source-output-model-command

Path:
    {source}/{output}/{model}/{command}    


Condition:
    where: id/1/2/3/4/5
    between: id/10/20
    where: name/to

Command
    Create - json can many create
    read - can many list
        Filter - json
        Range - json
        Param: -list of param - Which attributes show

Example:

db/collection/user/read - json
db/collection/user/delete - json
db/collection/user/update - json
db/collection/user/create - json    

output: model | RUD

one item

Schema:
    source-output-model-method-command-param-value

Path:
    {source}/{output}/{model}/{command}/{condition}/{param}/{value}/

Condition:
    where

Command:
    ReadBy
    UpdateBy -json
    DeleteBy

Example:

db/model/user/ReadBy/id/10
db/model/user/DeleteBy/login/tom

output: param | RU

one param from one item

Schema:
    source-output-model-param-param-value

Path:
    {source}/{output}/{model}/{param}/{command}/{condition}/{param}/{value}/

Condition:
    where

Command:
    Get - Read
    Set - Update

Example:

db/param/user/login/Read/id/10
db/param/user/password/read/where/login/tom
db/param/user/login/update/where/login/tom

Routing, Example

Model: User
Structure:
User:
    id
    login
    password
    created_at

Routing

{Param}  = id
{items} = 1,2,3

https://domain/{source}/User/Collection/List/{Param}/{items}
https://domain/{source}/User/Collection/Range/{Param}/{items}
https://domain/{source}/User/Object/Update/{Param}/{items}

Pattern:
https://domain/{source}/{model}/param/get/{param}/{name}/

Example:
https://domain/source/{source}/model/{model}/param/{param}/get/id/10/

Get Login

GET https://domain/{source}/{model}/{param}/{value} /param/ login /get/ where / 
GET https://domain/   db   / user  /   id / 10 /param/ login /get/ where / 
GET https://domain/source/ db /model/ user /param/ login /get/ where / id / 10 /

Set Password

PUT https://domain/source/ db /model/ user /param/ password /set/ id / 10 { "param": }

SQL Generator

Creating from Tree of model-name-type The SQL Statements for:

• Collection
• Object
• Param

SQL Inspector

Functionality

• Create metada from SQL schema
• Create REST API based on SWAGGER From Metadata
• Generate sdk for SWAGGER API

TODO

1 prototyp

zamiast pliku - zmienne w array dla modelu i konfiguracji petla parsowania wygenerowane 9 zapytan

2 prototyp

plik konfiguracyjny czytanie yaml pliku i zamiana na array plik z modelami danych i relacjami czytanie pliku z modelami petla parsowania wygenerowane wielu modeli i 9 zapytan

3 prototyp

plik konfiguracyjny czytanie yaml pliku i zamiana na array plik z modelami danych i relacjami czytanie pliku z modelami generowanie 9 zapytan do kazdego modelu dodatkowe rozpoznawanie