Skip to main content

A lightweight python library for implementing GraphQL on Relational DB Tables in few steps using python dicts. The library is built over strawberry-graphql for creating graphQL schema from dataclasses

Project description

GoRDB - GraphQL On Relational DB

A lightweight python library for implementing GraphQL on Relational DB Tables in few steps using python dicts. The library is built over strawberry-graphql for creating graphQL schema from dataclasses

Usage Example

GoRDB makes it easy to implement graph schema and graph queries like one given below on traditional Relational DBs.
Example Graph query on Relational DB having User table and Subscriptions table implemented using GoRDB

{
    User(filterStr:" @#ROWNUM#@ <5 ")
    {
        USERID,
        USERNAME,
        Subscriptions{
            PRODUCTID
        }
    }
}

Installation Steps

Install using the following command
pip install GoRDB

Implementation Steps

Step-1:

Import GoRDB library
from GoRDB import GoRDB

Step-2:

Initialize connection configs for your DB. Here config is shown for Oracle DB, You can set this for any RDB of your choice
import cx_Oracle as orac
orac.init_oracle_client(lib_dir= "./instantclient_19_12")
import pickle
db=pickle.load(open("G:db_config.pickle","rb"))
username=db['username']
pwd=db['pwd']
db_uri=db['uri']

Step-3:

Create function which will receive an connection-id (string) and query (string) as arguments and return query results ( List of tuples) as return
connection_pools_by_connection_id={}
connection_pools_by_connection_id['CUSTOMERDB'] = orac.SessionPool(username, pwd, db_uri,min = 5, max = 20, increment = 5, threaded = True,getmode = orac.SPOOL_ATTRVAL_WAIT)

def query_executor(connection_id,query_str):
    global connection_pools_by_connection_id
    custdb=connection_pools_by_connection_id[connection_id].acquire()
    local_cursor=custdb.cursor()
    local_cursor.execute(query_str)
    query_result=local_cursor.fetchall()   
    return query_result

Step-4:

Add node definition for each node in your graph layer as dict in the format given below.
Nodes define the table in your Relational DB. Node alias is the node name which will be used in your Graph queries
Features define the columns in your RDB table. Feature type defines the column type(Default type: string)
Edges define the relation between on node to another and corresponding mapping keys. set many_mapping = True if you the edge define one-to-many relationship
Table connection id define the connection identifier which will be passed to query executor function
Query executor define the function which will be called to execute query.


Here for the example shown above we have 2 nodes.

USER_node_dict={
    'node_alias':'User',
    'tbl_name':'CUSTOMERDB.USER_TABLE',
    'tbl_connection_id':'CUSTOMERDB',
    'query_executor':query_executor,
    
    
    'features':[
        {'feature_alias':'USERID','feature_name_in_table':'USERID_SNO','feature_type':int},
        {'feature_alias':'USERNAME','feature_name_in_table':'USERNAME'},
    ],
    
    'edges':[
        {'edge_alias':'Subscriptions','node_feature_alias':'USERID','foreign_node_alias':'Subscriptions','foreignNode_feature_alias':'SUBSCRIBERID','many_mapping':True}
        
    ]
        
}


SUBSCRIPTIONS_node_dict={
    'node_alias':'Subscriptions',
    'tbl_name':'CUSTOMERDB.SUBSCRIBER_PRODUCT_TABLE',
    'tbl_connection_id':'CUSTOMERDB',
    'query_executor':query_executor,
    
    
    'features':[
        {'feature_alias':'SUBSCRIBERID','feature_name_in_table':'SUBSCRIBERID_IDX'},
        {'feature_alias':'PRODUCTID','feature_name_in_table':'PRODUCTID_IDX'},
    ],
    
    'edges':[]
}

Step-5:

Build your GraphQL Schema by passing the list of node definitions dict
schema,node_builds_compiled=GoRDB.build_scheme_from_node_dict([USER_node_dict,SUBSCRIPTIONS_node_dict])

Step-6:

Thats all! Execute your Schema, and await on the response. Now you have succesfully running Graph query engine on you RDB tables

Note: the filterstr corresponds to the "WHERE" part of your nomrmal SQL query. if you want to use some table columns which are not defined in your node definition dict you need to wrap them with ' #@' and '#@ ', but if the column is already defined in the node definition dict this is not need(for example 'USERID' used in the below query)

ding=schema.execute('{User(filterStr:" USERID > 5 and  @#ROWNUM#@ <5 "){USERID,USERNAME,Subscriptions{PRODUCTID}}}')
print(await ding)

Other features

GoRDB have helper function called show_graph which can be used to see the network diagram of your Schema

GoRDB.show_graph([USER_node_dict,SUBSCRIPTIONS_node_dict])

show_graph_example

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

GoRDB-6.3.tar.gz (21.4 kB view hashes)

Uploaded Source

Built Distribution

GoRDB-6.3-py3-none-any.whl (19.3 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page