healthcareio
/
parser
mirror of https://hiplab.mc.vanderbilt.edu/git/hiplab/parser.git
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bug fix: export import bug

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dev
Steve Nyemba 3 years ago
parent 995ea21320
commit ddddb897d0
6 changed files with 121 additions and 68 deletions
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72
healthcareio/analytics.py
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@ -192,18 +192,23 @@ class Apex :
@staticmethod
def scalar(item):
_df = item['data']
name = _df.columns.tolist()[0]
value = _df[name].values.round(2)[0]
value = '0'
unit = ''
html = '<div class="scalar"><div class="value">:value</div><div class="label">:label</div></div>'
if value > 999 and value < 1000000 :
value = " ".join([str(np.divide(value,1000).round(2)),"K"])
elif value > 999999 :
#@ Think of considering the case of a billion ...
value = " ".join([str(np.divide(value,1000000).round(2)),"M"])
else:
value = str(value)
unit = name.replace('_',' ') if 'unit' not in item else item['unit']
if _df.shape[0] > 0 :
print (_df)
print ('_____________________________________')
name = _df.columns.tolist()[0]
value = _df[name].values[0]
if value > 999 and value < 1000000 :
value = " ".join([str(np.divide(value,1000).round(2)),"K"])
elif value > 999999 :
#@ Think of considering the case of a billion ...
value = " ".join([str(np.divide(value,1000000).round(2)),"M"])
else:
value = str(value)
unit = name.replace('_',' ') if 'unit' not in item else item['unit']
return {'html':html.replace(':value',value).replace(":label",unit)}
@staticmethod
def column(item):
@ -319,8 +324,9 @@ class Apex :
values = df[x_cols].values.round(2).tolist()
else:
labels = [name.upper().replace('_',' ') for name in df.columns.tolist()]
df = df.astype(float)
values = df.values.round(2).tolist()[0] if df.shape[1] > 1 else df.values.round(2).tolist()
# df = df.astype(float)
# values = df.values.round(2).tolist()[0] if df.shape[1] > 1 else df.values.round(2).tolist()
values = df[[name for name in df.columns if df[name].dtype in [float,int]] ].values.round(2).tolist()
colors = COLORS[:len(values)]
options = {"series":values,"colors":colors,"labels":labels,"dataLabels":{"enabled":True,"style":{"colors":["#000000"]},"dropShadow":{"enabled":False}},"chart":{"type":"donut","width":200},"plotOptions":{"pie":{"customScale":.9}},"legend":{"position":"right"}}
@ -343,10 +349,10 @@ class engine :
self.store_config = _config['store']
self.info = _config['analytics']
_args = self.store_config
if self.store_config['type'] == 'mongo.MongoWriter' :
_args['type'] = 'mongo.MongoReader'
else:
_args['type'] = 'disk.SQLiteReader'
if 'type' not in self.store_config :
#
# This is the newer version of data-transport
self.store_config['context'] = 'read'
self.store_config = _args ;
def filter (self,**args):
@ -367,8 +373,8 @@ class engine :
# conn = lite.connect(self.store_config['args']['path'],isolation_level=None)
# conn.create_aggregate("stdev",1,stdev)
DB_TYPE = 'mongo' if (type(self.reader) == transport.mongo.MongoReader) else 'sql'
if DB_TYPE == 'mongo' :
self.store_config['args']['doc'] = args['type']
# if DB_TYPE == 'mongo' :
# self.store_config['args']['doc'] = args['type']
self.reader = transport.factory.instance(**self.store_config)
r = []
@ -414,20 +420,8 @@ class engine :
_analytics = [_analytics[index]]
_info = list(_analytics) if 'filter' not in args else [item for item in analytics if args['filter'] == item['id']]
# conn = lite.connect(self.store_config['args']['path'],isolation_level=None)
# conn.create_aggregate("stdev",1,stdev)
#
# @TODO: Find a better way to handle database variance
#
# DB_TYPE = 'mongo' if (type(self.reader) == transport.mongo.MongoReader) else 'sql'
if 'mongo' in self.store_config['type'] :
DB_TYPE='mongo'
else:
DB_TYPE='sql'
self.store_config['args']['table'] = args['type']
self.reader = transport.factory.instance(**self.store_config)
DB_TYPE = 'mongo' if self.store_config ['provider'] in ['mongodb','mongo'] else 'sql'
r = []
for row in _info :
pipeline = row['pipeline']
@ -440,14 +434,22 @@ class engine :
continue
if DB_TYPE == 'sql' :
query = {"sql":query}
else:
query = {DB_TYPE:query}
item['data'] = self.reader.read(**query) #item)
_df = self.reader.read(**query) #item)
print (query)
print (self.reader)
if 'serialize' in args :
# item['data'] = json.dumps(item['data'].to_dict(orient='record')) if type(item['data']) == pd.DataFrame else item['data']
item['data'] = json.dumps(item['data'].to_dict('record')) if type(item['data']) == pd.DataFrame else item['data']
item['data'] = json.dumps(_df.to_dict(orient='record'))
else:
item['data'] = (pd.DataFrame(item['data']))
# item['data'] = (pd.DataFrame(item['data']))
item['data'] = _df
pass
print (_df.head())
break
pipeline[index] = item
index += 1
#

1
healthcareio/server/__init__.py
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@ -225,6 +225,7 @@ if __name__ == '__main__' :
PATH= SYS_ARGS['config'] if 'config' in SYS_ARGS else os.sep.join([os.environ['HOME'],'.healthcareio','config.json'])
#
# Adjusting configuration with parameters (batch,folder,resume)
SYS_ARGS['config'] = json.loads(open(PATH).read())
if 'args' not in SYS_ARGS['config'] :
SYS_ARGS['config']["args"] = {"batch":1,"resume":True,"folder":"/data"}

16
healthcareio/server/index.py
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@ -6,15 +6,16 @@ import json
app = Flask(__name__)
@app.route("/favicon.ico")
def _icon():
return send_from_directory(os.path.join([app.root_path, 'static','img','logo.svg']),
return send_from_directory(os.path.join([app.root_path, 'static/img/logo.svg']),
'favicon.ico', mimetype='image/vnd.microsoft.icon')
@app.route("/")
def init():
e = SYS_ARGS['engine']
sections = {"remits":e.info['835'],"claims":e.info['837']}
_args = {"sections":sections,"store":SYS_ARGS['config']['store']}
print (SYS_ARGS['config']['store'])
return render_template("setup.html",**_args)
_args = {"sections":sections,"store":SYS_ARGS['config']['store'],'args':{'batch':5}}
return render_template("index.html",**_args)
@app.route("/format/<id>/<index>",methods=['POST'])
def _format(id,index):
@ -73,13 +74,16 @@ def reload():
if __name__ == '__main__' :
PORT = int(SYS_ARGS['port']) if 'port' in SYS_ARGS else 5500
DEBUG= int(SYS_ARGS['debug']) if 'debug' in SYS_ARGS else 0
DEBUG= int(SYS_ARGS['debug']) if 'debug' in SYS_ARGS else 1
SYS_ARGS['context'] = SYS_ARGS['context'] if 'context' in SYS_ARGS else ''
#
#
PATH= SYS_ARGS['config'] if 'config' in SYS_ARGS else os.sep.join([os.environ['HOME'],'.healthcareio','config.json'])
#
if os.path.exists(PATH) :
SYS_ARGS['config'] = json.loads(open(PATH).read())
e = healthcareio.analytics.engine(PATH)
# e.apply(type='claims',serialize=True)
SYS_ARGS['engine'] = e
app.run(host='0.0.0.0',port=PORT,debug=DEBUG,threaded=True)

46
healthcareio/server/proxy.py
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@ -37,14 +37,17 @@ class get :
@staticmethod
def processes(_args):
_info = pd.DataFrame(smart.top.read(name='healthcare-io.py'))[['name','cpu','mem']]
APP_NAME ='healthcare-io'
_info = smart.top.read(name=APP_NAME) #pd.DataFrame(smart.top.read(name='healthcare-io'))[['name','cpu','mem']]
if _info.shape[0] == 0 :
_info = pd.DataFrame({"name":["healthcare-io.py"],"cpu":[0],"mem":[0]})
_info = pd.DataFrame({"name":[APP_NAME],"cpu":[0],"mem":[0]})
# _info = pd.DataFrame(_info.groupby(['name']).sum())
# _info['name'] = ['healthcare-io.py']
m = {'cpu':'CPU','mem':'RAM','name':'name'}
_info.columns = [m[name] for name in _info.columns.tolist()]
_info = _info.rename(columns=m)
# _info.columns = [m[name] for name in _info.columns.tolist() if name in m]
_info.index = np.arange(_info.shape[0])
charts = []
@ -56,23 +59,20 @@ class get :
{"data":df, "chart":{"type":"radial","axis":{"x":label,"y":"name"}}}
)['apex']
)
#
# This will update the counts for the processes, upon subsequent requests so as to show the change
#
N = 0
lprocs = []
for proc in get.PROCS :
if proc.is_alive() :
lprocs.append(proc)
N = len(lprocs)
get.PROCS = lprocs
return {"process":{"chart":charts,"counts":N}}
return {"process":{"chart":charts,"counts":_info.shape[0]}}
@staticmethod
def files (_args):
_info = smart.folder.read(path='/data')
folder = _args['args']['folder']
_info = smart.folder.read(path=folder)
N = _info.files.tolist()[0]
if 'mongo' in _args['store']['type'] :
store_args = dict(_args['store'].copy(),**{"type":"mongo.MongoReader"})
store_args = _args['store'].copy()
store_args['context'] = 'read'
# if 'mongo' in _args['store']['type'] :
if _args['store']['provider'] in ['mongo', 'mongodb']:
# store_args = dict(_args['store'].copy(),**{"type":"mongo.MongoReader"})
# reader = transport.factory.instance(**_args)
pipeline = [{"$group":{"_id":"$name","count":{"$sum":{"$cond":[{"$eq":["$completed",True]},1,0]}} }},{"$group":{"_id":None,"count":{"$sum":"$count"}}},{"$project":{"_id":0,"status":"completed","count":1}}]
@ -83,12 +83,15 @@ class get :
else:
store_args = dict(_args['store'].copy(),**{"type":"disk.SQLiteReader"})
store_args['args']['table'] = 'logs'
# store_args = dict(_args['store'].copy(),**{"type":"disk.SQLiteReader"})
# store_args['args']['table'] = 'logs'
store_args['table'] = 'logs'
query= {"sql":"select count(distinct json_extract(data,'$.name')) as count, 'completed' status from logs where json_extract(data,'$.completed') = true"}
_query={"sql":"select json_extract(data,'$.parse') as type,count(distinct json_extract(data,'$.name')) as count from logs group by type"} #-- distribution claim/remits
reader = transport.factory.instance(**store_args)
_info = pd.DataFrame(reader.read(**query))
if not _info.shape[0] :
_info = pd.DataFrame({"status":["completed"],"count":[0]})
_info['count'] = np.round( (_info['count'] * 100 )/N,2)
@ -97,11 +100,6 @@ class get :
#
# Let us classify the files now i.e claims / remits
#
# pipeline = [{"$group":{"_id":"$parse","claims":{"$addToSet":"$name"}}},{"$project":{"_id":0,"type":"$_id","count":{"$size":"$claims"}}}]
# _args = {"aggregate":"logs","cursor":{},"allowDiskUse":True,"pipeline":pipeline}
# r = pd.DataFrame(reader.read(mongo=_args))
r = pd.DataFrame(reader.read(**_query)) #-- distribution claims/remits
r = Apex.apply({"chart":{"type":"donut","axis":{"x":"count","y":"type"}},"data":r})['apex']
r['chart']['height'] = '100%'

4
healthcareio/server/templates/setup.html
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@ -63,10 +63,10 @@
//
// We should insure the listeners are enabled
if(monitor.listen.handler == null){
monitor.listen.handler = setInterval(
/*monitor.listen.handler = setInterval(
function(){
console.log('running ...')
monitor.data()},5000)
monitor.data()},5000)*/
}
}else{

48
healthcareio/x12/__init__.py
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@ -24,6 +24,7 @@ import sys
from itertools import islice
from multiprocessing import Process
import transport
from transport import providers
import jsonmerge
import copy
@ -236,6 +237,53 @@ class Parser (Process):
_config[_id] = [_config[_id]]
config['parser'] = _config
return config
@staticmethod
def init(**_args):
"""
This function allows to initialize the database that will store the claims if need be
:path configuration file
"""
PATH = os.sep.join([os.environ['HOME'],'.healthcareio'])
filename = os.sep.join([PATH,'config.json'])
filename = _args['path'] if 'path' in _args else filename
info = None
if os.path.exists(filename):
#
# Loading the configuration file (JSON format)
file = open(filename)
info = json.loads(file.read())
OUTPUT_FOLDER = info['out-folder']
if 'output-folder' not in info and not os.path.exists(OUTPUT_FOLDER) :
os.mkdir(OUTPUT_FOLDER)
elif 'output-folder' in info and not os.path.exists(info['out-folder']) :
os.mkdir(info['out-folder'])
# if 'type' in info['store'] :
lwriter = None
IS_SQL = False
if'type' in info['store'] and info['store']['type'] == 'disk.SQLiteWriter' :
lwriter = transport.factory.instance(**info['store'])
IS_SQL = True
elif 'provider' in info['store'] and info['store']['provider'] == 'sqlite' :
lwriter = transport.instance(**info['store']) ;
IS_SQL = [providers.SQLITE,providers.POSTGRESQL,providers.NETEZZA,providers.MYSQL,providers.MARIADB]
if lwriter and IS_SQL:
for key in info['schema'] :
if key != 'logs' :
_id = 'claims' if key == '837' else 'remits'
else:
_id = key
if not lwriter.has(table=_id) :
lwriter.apply(info['schema'][key]['create'])
# [lwriter.apply( info['schema'][key]['create']) for key in info['schema'] if not lwriter.has(table=key)]
lwriter.close()
return info
def __init__(self,path):
"""

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