@ -37,14 +37,17 @@ class get :
@staticmethod
@staticmethod
def processes ( _args ) :
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 :
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 = pd.DataFrame(_info.groupby(['name']).sum())
# _info['name'] = ['healthcare-io.py']
# _info['name'] = ['healthcare-io.py']
m = { ' cpu ' : ' CPU ' , ' mem ' : ' RAM ' , ' name ' : ' name ' }
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 ] )
_info . index = np . arange ( _info . shape [ 0 ] )
charts = [ ]
charts = [ ]
@ -56,23 +59,20 @@ class get :
{ " data " : df , " chart " : { " type " : " radial " , " axis " : { " x " : label , " y " : " name " } } }
{ " data " : df , " chart " : { " type " : " radial " , " axis " : { " x " : label , " y " : " name " } } }
) [ ' apex ' ]
) [ ' apex ' ]
)
)
#
# This will update the counts for the processes, upon subsequent requests so as to show the change
return { " process " : { " chart " : charts , " counts " : _info . shape [ 0 ] } }
#
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 } }
@staticmethod
@staticmethod
def files ( _args ) :
def files ( _args ) :
_info = smart . folder . read ( path = ' /data ' )
folder = _args [ ' args ' ] [ ' folder ' ]
_info = smart . folder . read ( path = folder )
N = _info . files . tolist ( ) [ 0 ]
N = _info . files . tolist ( ) [ 0 ]
if ' mongo ' in _args [ ' store ' ] [ ' type ' ] :
store_args = _args [ ' store ' ] . copy ( )
store_args = dict ( _args [ ' store ' ] . copy ( ) , * * { " type " : " mongo.MongoReader " } )
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)
# 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 } } ]
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 :
else :
store_args = dict ( _args [ ' store ' ] . copy ( ) , * * { " type " : " disk.SQLiteReader " } )
# store_args = dict(_args['store'].copy(),**{"type":"disk.SQLiteReader"})
store_args [ ' args ' ] [ ' table ' ] = ' logs '
# 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 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
_query = { " sql " : " select json_extract(data, ' $.parse ' ) as type,count(distinct json_extract(data, ' $.name ' )) as count from logs group by type " } #-- distribution claim/remits
reader = transport . factory . instance ( * * store_args )
reader = transport . factory . instance ( * * store_args )
_info = pd . DataFrame ( reader . read ( * * query ) )
_info = pd . DataFrame ( reader . read ( * * query ) )
if not _info . shape [ 0 ] :
if not _info . shape [ 0 ] :
_info = pd . DataFrame ( { " status " : [ " completed " ] , " count " : [ 0 ] } )
_info = pd . DataFrame ( { " status " : [ " completed " ] , " count " : [ 0 ] } )
_info [ ' count ' ] = np . round ( ( _info [ ' count ' ] * 100 ) / N , 2 )
_info [ ' count ' ] = np . round ( ( _info [ ' count ' ] * 100 ) / N , 2 )
@ -97,11 +100,6 @@ class get :
#
#
# Let us classify the files now i.e claims / remits
# Let us classify the files now i.e claims / remits
#
#
# pipeline = [{"$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 = pd . DataFrame ( reader . read ( * * _query ) ) #-- distribution claims/remits
r = Apex . apply ( { " chart " : { " type " : " donut " , " axis " : { " x " : " count " , " y " : " type " } } , " data " : r } ) [ ' apex ' ]
r = Apex . apply ( { " chart " : { " type " : " donut " , " axis " : { " x " : " count " , " y " : " type " } } , " data " : r } ) [ ' apex ' ]
r [ ' chart ' ] [ ' height ' ] = ' 100 % '
r [ ' chart ' ] [ ' height ' ] = ' 100 % '
Steve Nyemba
2 years ago