Metadata-Version: 2.1
Name: DDLJ
Version: 0.0.3
Summary: JSON Utils for generating DDL from JSON Schema
Home-page: https://github.com/deepstartup/jsonutils
Author: Arghadeep Chaudhury,Siddhartha Bhattacharya
Author-email: siddhbhatt@gmail.com,arghadeep.chaudhury@gmail.com
License: UNKNOWN
Description: # JSON Utils Package (DDLj)
        This is a python package having multiple utilities for handling JSON Files. 
        
        Module1 - DDLj : Converts JSON Schema Files into ANSI SQL DDLs
        Supports foll databases: 
        A.PostgreSQL
        B.MYSQL
        C.DB2
        D.MariaDB
        E.Oracle
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        Usage:
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        pip install DDLJ
        
        python
        
        >>> from DDLj import genddl
        
        >>> genddl(*param1,param2,*param3,*param4)
        
        Where 
        
        param1= JSON Schema File
        
        param2=Database (Default Oracle)
        
        Param3= Glossary file
        
        Param4= DDL output script
        
        Note : * indicates mandatory parameters
        
        It also includes a Flask module for front-end if used as a standalone tool. Refer to App directory.
        *******************************************
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        Example:
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        Input JSON schema as:
        {
        	"schema": "Http://Json-Schema.Org/Draft-07/Schema#",
        	"type": "object",
        	"title": "TableNameTest",
        	"additionalProperties": false,
        	"properties": {
        		"ColumnNameOne": {
        			"type": "string",
        			"maxLength": 10
        		},
        		"ColumnNameTwo": {
        			"type": "string",
        			"format": "date-time"
        		},
        		"ColumnNameThree": {
        			"type": "string",
        			"maxLength": 200
        		},
        		"ColumnNameFour": {
        			"type": "string",
        			"maxLength": 300
        		},
        		"ColumnNameFive": {
        			"type": "string",
        			"format": "date"
        		},
        		"ColumnNameSix": {
        			"type": "number"
        		},
        		"ColumnNameSeven": {
        			"type": "number"
        		},
        		"ColumnNameEight": {
        			"type": "string",
        			"maxLength": 1000
        		},
        		"ColumnNameNine": {
        			"type": "string",
        			"maxLength": 2000
        		},
        		"ColumnNameTen": {
        			"type": "number"
        		}
        	}
        }
        
        Code Usage:
        >>> from DDLj import genddl
        >>> genddl('TestJsonSchema.json','Oracle','GlossaryTestFile.csv','GenDDLGlossary.sql')
        
        Output:
        Create Table TableNameTest (COL_NAM_One Varchar2(10),
        COL_NAM_Two Timestamp(6),
        COL_NAM_Three Varchar2(200),
        COL_NAM_Four Varchar2(300),
        COL_NAM_Five Date,
        COL_NAM_Six Number(38,10),
        COL_NAM_Seven Number(38,10),
        COL_NAM_Eight Varchar2(1000),
        COL_NAM_Nine Varchar2(2000),
        COL_NAM_Ten Number(38,10));
        
        Please see the Test Folder for JSON schema, glossary file and output.
        ****************************
        
        Note: Other modules to come soon.
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
