2023-12-01 03:43:52 +00:00
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import copy
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from . import util
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import transport
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import numpy as np
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import time
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import pandas as pd
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from multiprocessing import Process
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def build (**_args):
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"""
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This function will build SQL statements to create a table (perhaps not needed)
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:plugins loaded plugins
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:x12 837|835 file types
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"""
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_plugins=_args['plugins']
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_x12 = _args['x12']
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_template = util.template(plugins=_plugins)[_x12]
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_primaryKey = util.getPrimaryKey(plugins=_plugins,x12=_x12)
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_tables = []
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_main = {}
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for _name in _template :
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_item = _template[_name] #copy.deepcopy(_template[_name])
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if _primaryKey not in _item and type(_item) == dict:
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_item[_primaryKey] = ''
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_tables.append({_name:_item})
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else:
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_main[_name] = ''
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_name = getContext(_x12)
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_tables += [{_name:_main}]
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_template[_name] = _main
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return _template #_tables
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def getContext(_x12) :
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return 'claims' if _x12 == '837' else 'remits'
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def format(**_args) :
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"""
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:rows rows for the
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:primary_key primary_key field name
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:x12 file format
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"""
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# _name = _args['table']
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_rows = _args['rows']
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_primary_key = _args['primary_key']
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_x12 = _args['x12']
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_mainTableName = getContext(_x12)
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_tables = {_mainTableName:[]}
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for _claim in _rows :
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# #
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# # Turn the claim into a relational model ...
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# #
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_main = {}
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_pkvalue = None
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if _primary_key in _claim :
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_pkvalue = _claim[_primary_key]
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for _attrName in _claim :
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_item = _claim[_attrName]
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_item = update(_item,_primary_key,_pkvalue)
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if _attrName not in _tables and type(_item) in [dict,list]:
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_tables[_attrName] = []
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if type(_item) in [dict,list] :
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_tables[_attrName] += _item if type(_item) == list else [_item]
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else:
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#
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# This section suggests we found a main table attribute
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_main[_attrName] = _item
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_tables[_mainTableName].append(_main)
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return _tables
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def update (_item,key,value):
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if type(_item) not in [dict,list] :
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return _item
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if type(_item) == dict :
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_item[key] = value
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else:
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#
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# List, we will go through every item and update accordingly
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_index = 0
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for _row in _item :
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if type(_row) == dict :
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_row['_index'] = _index
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_row[key] = value
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return _item
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def init(**_args):
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"""
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This function will kick off the export process provided claims/remits and the loaded plugins (not sure why)
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It requires the data it is pulling to be consistently formatted (otherwise nothing can be done)
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:plugins
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:store data store information i.e {source,target} specifications for data-transport
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:x12 file type i.e 837|835
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"""
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_file_type = _args['x12']
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_plugins = _args['plugins']
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_store = _args['store']
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_default = build(plugins=_plugins,x12=_file_type)
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_df = read(store = _store['source'],x12=_file_type)
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_pkey = util.getPrimaryKey(plugins = _plugins, x12=_file_type)
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SEGMENTS = 4 # arbitrary choice
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_indexes = np.array_split(np.arange(_df.shape[0]),SEGMENTS)
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jobs = []
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for _ii in _indexes :
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2023-12-07 19:00:16 +00:00
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try:
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_data = format(rows= _df.iloc[_ii].to_dict(orient='records'),x12=_file_type,primary_key=_pkey)
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_thread = Process(target=post,args=({'store':_store['target'],'data':_data,'default':_default,'x12':_file_type},))
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jobs.append(_thread)
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except Exception as e:
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#
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# Log: sigment,
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pass
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2023-12-01 03:43:52 +00:00
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if jobs :
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jobs[0].start()
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jobs[0].join()
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while jobs :
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jobs = [thread for thread in jobs if thread.is_alive()]
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time.sleep(1)
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def read (**_args):
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_store = copy.copy(_args['store'])
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_x12 = _args['x12']
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_store['table'] = getContext(_x12) #'claims' if _x12 == '837' else 'remits'
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reader = transport.factory.instance(**_store)
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#
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# @TODO: reading should support streaming (for scalability)
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_df = reader.read()
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return _df
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def post(_args):
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_data = _args['data']
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_store = _args['store']
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_default = _args['default']
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2023-12-01 18:16:10 +00:00
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_prefix = 'clm_' if _args['x12'] == '837' else 'rem_'
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2023-12-01 03:43:52 +00:00
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for _name in _data :
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2023-12-01 18:16:10 +00:00
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_tablename = _prefix+_name
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_store['table'] = _tablename if _name not in ['remits','claims'] else _name
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2023-12-01 03:43:52 +00:00
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_store['context']='write'
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writer = transport.factory.instance(**_store)
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2023-12-01 18:16:10 +00:00
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if len(_data[_name]) == 0 and _name in _default and not writer.has(table=_tablename):
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2023-12-01 03:43:52 +00:00
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_rows = [_default[_name]]
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else:
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_rows = _data[_name]
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2023-12-01 18:16:10 +00:00
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writer.write(pd.DataFrame(_rows).fillna(''))
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2023-12-01 03:43:52 +00:00
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if hasattr(writer,'close') :
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writer.close()
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# _xwriter = trasnport.factory.instance(**_store)
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# _xwriter.write(_df)
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# _info = format()
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pass
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