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CREATE TABLE sys_batch (

    batch_id        INTEGER PRIMARY KEY AUTOINCREMENT,

    batch_name      VARCHAR2 ( 100 ) );



CREATE TABLE sys_batch_tgt (

    batch_id        INTEGER PRIMARY KEY,

    name_of_batch   VARCHAR2 ( 100 ) );

import sqlalchemy

from sqlalchemy.ext.automap import automap_base

from sqlalchemy.sql import select

from sqlalchemy.orm import Session



import bonobo

#import bonobo_sqlalchemy



engine = sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/coolstuff.db')

Base = automap_base()

Base.prepare(engine, reflect=True)



# Tables

sys_batch = Base.classes.sys_batch

sys_batch_tgt = Base.classes.sys_batch_tgt



#def get_services():

#   return {'sqlalchemy.pgengine': sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/carauction.db')}



def extract_sys_batch():

    conn = engine.connect()

    s = select([sys_batch])

    result = conn.execute(s)

    #conn.close()

    row = result.fetchone()

    yield row



# convert incoming SQLAlchemy "ProxyRow" to a dict, so we can manipulate it.

def tfm_0(row):

    tgt_row = {}

    tgt_row['batch_id'] = row['batch_id']

    tgt_row['name_of_batch'] = row['batch_name']

    return tgt_row



def tfm_1(row):

    row['batch_id'] = row['batch_id'] + 100

    return row



def ldr_1(row):

    # write to target

    session = Session(engine)

    thing = sys_batch_tgt(**row)

    session.add(thing)

    session.commit()



def get_graph(**options):



    return bonobo.Graph(

        extract_sys_batch,

        tfm_0,

        tfm_1,

        ldr_1,

        bonobo.PrettyPrinter(),

    )



# The __main__ block actually execute the graph.

if __name__ == '__main__':

    parser = bonobo.get_argument_parser()



    #each transformation is its own thread, so we have to open/close in there.

    #conn = engine.connect()



    with bonobo.parse_args(parser) as options:

        bonobo.run(get_graph(**options)) #, services=get_services(**options)



    #conn.close()

CREATE TABLE sys_batch (

    batch_id        INTEGER PRIMARY KEY AUTOINCREMENT,

    batch_name      VARCHAR2 ( 100 ) );



CREATE TABLE sys_batch_tgt (

    batch_id        INTEGER PRIMARY KEY,

    name_of_batch   VARCHAR2 ( 100 ) );

import sqlalchemy

from sqlalchemy.ext.automap import automap_base

from sqlalchemy.sql import select

from sqlalchemy.orm import Session



import bonobo

#import bonobo_sqlalchemy



engine = sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/coolstuff.db')

Base = automap_base()

Base.prepare(engine, reflect=True)



# Tables

sys_batch = Base.classes.sys_batch

sys_batch_tgt = Base.classes.sys_batch_tgt



#def get_services():

#   return {'sqlalchemy.pgengine': sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/carauction.db')}



def extract_sys_batch():

    conn = engine.connect()

    s = select([sys_batch])

    result = conn.execute(s)

    #conn.close()

    row = result.fetchone()

    yield row



# convert incoming SQLAlchemy "ProxyRow" to a dict, so we can manipulate it.

def tfm_0(row):

    tgt_row = {}

    tgt_row['batch_id'] = row['batch_id']

    tgt_row['name_of_batch'] = row['batch_name']

    return tgt_row



def tfm_1(row):

    row['batch_id'] = row['batch_id'] + 100

    return row



def ldr_1(row):

    # write to target

    session = Session(engine)

    thing = sys_batch_tgt(**row)

    session.add(thing)

    session.commit()



def get_graph(**options):



    return bonobo.Graph(

        extract_sys_batch,

        tfm_0,

        tfm_1,

        ldr_1,

        bonobo.PrettyPrinter(),

    )



# The __main__ block actually execute the graph.

if __name__ == '__main__':

    parser = bonobo.get_argument_parser()



    #each transformation is its own thread, so we have to open/close in there.

    #conn = engine.connect()



    with bonobo.parse_args(parser) as options:

        bonobo.run(get_graph(**options)) #, services=get_services(**options)



    #conn.close()

CREATE TABLE sys_batch (

    batch_id        INTEGER PRIMARY KEY AUTOINCREMENT,

    batch_name      VARCHAR2 ( 100 ) );



CREATE TABLE sys_batch_tgt (

    batch_id        INTEGER PRIMARY KEY,

    name_of_batch   VARCHAR2 ( 100 ) );

import sqlalchemy

from sqlalchemy.ext.automap import automap_base

from sqlalchemy.sql import select

from sqlalchemy.orm import Session



import bonobo

#import bonobo_sqlalchemy



engine = sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/coolstuff.db')

Base = automap_base()

Base.prepare(engine, reflect=True)



# Tables

sys_batch = Base.classes.sys_batch

sys_batch_tgt = Base.classes.sys_batch_tgt



#def get_services():

#   return {'sqlalchemy.pgengine': sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/carauction.db')}



def extract_sys_batch():

    conn = engine.connect()

    s = select([sys_batch])

    result = conn.execute(s)

    #conn.close()

    row = result.fetchone()

    yield row



# convert incoming SQLAlchemy "ProxyRow" to a dict, so we can manipulate it.

def tfm_0(row):

    tgt_row = {}

    tgt_row['batch_id'] = row['batch_id']

    tgt_row['name_of_batch'] = row['batch_name']

    return tgt_row



def tfm_1(row):

    row['batch_id'] = row['batch_id'] + 100

    return row



def ldr_1(row):

    # write to target

    session = Session(engine)

    thing = sys_batch_tgt(**row)

    session.add(thing)

    session.commit()



def get_graph(**options):



    return bonobo.Graph(

        extract_sys_batch,

        tfm_0,

        tfm_1,

        ldr_1,

        bonobo.PrettyPrinter(),

    )



# The __main__ block actually execute the graph.

if __name__ == '__main__':

    parser = bonobo.get_argument_parser()



    #each transformation is its own thread, so we have to open/close in there.

    #conn = engine.connect()



    with bonobo.parse_args(parser) as options:

        bonobo.run(get_graph(**options)) #, services=get_services(**options)



    #conn.close()

CREATE TABLE sys_batch (

    batch_id        INTEGER PRIMARY KEY AUTOINCREMENT,

    batch_name      VARCHAR2 ( 100 ) );



CREATE TABLE sys_batch_tgt (

    batch_id        INTEGER PRIMARY KEY,

    name_of_batch   VARCHAR2 ( 100 ) );

import sqlalchemy

from sqlalchemy.ext.automap import automap_base

from sqlalchemy.sql import select

from sqlalchemy.orm import Session



import bonobo

#import bonobo_sqlalchemy



engine = sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/coolstuff.db')

Base = automap_base()

Base.prepare(engine, reflect=True)



# Tables

sys_batch = Base.classes.sys_batch

sys_batch_tgt = Base.classes.sys_batch_tgt



#def get_services():

#   return {'sqlalchemy.pgengine': sqlalchemy.create_engine('sqlite:///C:/Py/bonobo/carauction.db')}



def extract_sys_batch():

    conn = engine.connect()

    s = select([sys_batch])

    result = conn.execute(s)

    #conn.close()

    row = result.fetchone()

    yield row



# convert incoming SQLAlchemy "ProxyRow" to a dict, so we can manipulate it.

def tfm_0(row):

    tgt_row = {}

    tgt_row['batch_id'] = row['batch_id']

    tgt_row['name_of_batch'] = row['batch_name']

    return tgt_row



def tfm_1(row):

    row['batch_id'] = row['batch_id'] + 100

    return row



def ldr_1(row):

    # write to target

    session = Session(engine)

    thing = sys_batch_tgt(**row)

    session.add(thing)

    session.commit()



def get_graph(**options):



    return bonobo.Graph(

        extract_sys_batch,

        tfm_0,

        tfm_1,

        ldr_1,

        bonobo.PrettyPrinter(),

    )



# The __main__ block actually execute the graph.

if __name__ == '__main__':

    parser = bonobo.get_argument_parser()



    #each transformation is its own thread, so we have to open/close in there.

    #conn = engine.connect()



    with bonobo.parse_args(parser) as options:

        bonobo.run(get_graph(**options)) #, services=get_services(**options)



    #conn.close()

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