def MetricSearch(dict):
db = mongoCon.AttDB()
MET = dict['metric']
mydoc4 = db.aggregate([{
'$project': {
'_id': 0,
'code': 1,
'source': 1,
'report': 1,
'metric': '$metric'
}
}, {
'$unwind': '$metric'
}, {
'$project': {
'_id': 0,
'code': 1,
'source': 1,
'report': 1,
'mstd': '$metric.value',
'mraw': '$metric.name',
'fact': '$metric.factor'
}
}, {
'$match': {
'mstd': {
'$in': [
MET,
]
}
}
}])
doc5 = []
for x in mydoc4:
doc5.append(x)
df = pd.DataFrame(data=doc5)
index = ['code', 'source', 'report', 'mraw', 'mstd', 'fact']
df = df.reindex(columns=index)
#print(df)
name = 'Metric finder for ' + MET + '.csv'
#df.to_csv(name)
#print(" CSV outputted to", os.getcwd())
d = {'name': name, 'df': df}
return d
def mnfCheck(dict):
db = mongoCon.AttDB()
CODE = dict['code']
SOURCE = dict['source']
mydoc4 = db.attributes.aggregate([
{'$project' : {'_id':0,'code':1,'source':1, 'report':1, 'manufacturer':'$manufacturer'}},
{'$unwind':'$manufacturer'},
{'$project':{'_id':0,'code':1,'source':1,'report':1,'std' : '$manufacturer.value','raw': '$manufacturer.name'}},
{'$match':{'code':{'$in':[CODE,]},'source':{'$in':[SOURCE,]}}}])
doc5 = []
for x in mydoc4:
doc5.append(x)
df = pd.DataFrame(data =doc5)
index = ['code', 'source', 'report', 'raw', 'std']
df = df.reindex(columns = index)
name= 'MNF check for '+CODE+ ' '+SOURCE+'.csv'
d = {'name':name, 'df':df}
return d
def ChannelCheck(dict):
db = mongoCon.AttDB()
CODE = dict['code']
REPORT = dict['report']
SOURCE = dict['source']
mydoc6 = db.attributes.aggregate([{'$project':{'_id':0, 'code':1, 'source':1, 'report':1, 'channel':'$channel'}},
{'$unwind':'$channel'},
{'$project':{'_id':0, 'code':1, 'source':1, 'report':1, 'std' : '$channel.value', 'raw' : '$channel.name'}}])
Channel_report = []
for x in mydoc6:
Channel_report.append(x)
df = pd.DataFrame(data =Channel_report)
index = ['source', 'code', 'raw', 'std']
header = [np.array(df['code']),np.array(index)]
df = df.reindex(columns = index)
name= 'channel check for '+CODE+ ' '+REPORT+'.csv'
d = {'name':name, 'df':df}
return d
def brandSearch(dict):
db = mongoCon.AttDB()
BRD = dict['brand']
mydoc4 = db.aggregate([{
'$project': {
'_id': 0,
'code': 1,
'source': 1,
'report': 1,
'brand': '$brand'
}
}, {
'$unwind': '$brand'
}, {
'$project': {
'_id': 0,
'code': 1,
'source': 1,
'report': 1,
'bstd': '$brand.value',
'braw': '$brand.name',
}
}, {
'$match': {
'bstd': {
'$in': [
BRD,
]
}
}
}])
doc5 = []
for x in mydoc4:
doc5.append(x)
df = pd.DataFrame(data=doc5)
index = ['code', 'source', 'report', 'braw', 'bstd']
df = df.reindex(columns=index)
#print(df)
name = 'Brand finder for ' + BRD + '.csv'
#df.to_csv(name)
#print(" CSV outputted to", os.getcwd())
d = {'name': name, 'df': df}
return d
def ChannelSearch(dict):
db = mongoCon.AttDB()
CH = dict['channel']
mydoc4 = db.aggregate([{
'$project': {
'_id': 0,
'code': 1,
'source': 1,
'report': 1,
'channel': '$channel'
}
}, {
'$unwind': '$channel'
}, {
'$project': {
'_id': 0,
'code': 1,
'source': 1,
'report': 1,
'mstd': '$channel.value',
'mraw': '$channel.name'
}
}, {
'$match': {
'mstd': {
'$in': [
CH,
]
}
}
}])
doc5 = []
for x in mydoc4:
doc5.append(x)
df = pd.DataFrame(data=doc5)
index = ['code', 'source', 'report', 'mraw', 'mstd']
df = df.reindex(columns=index)
#print(df)
name = 'Channel finder for ' + CH + '.csv'
#df.to_csv(name)
#print(" CSV outputted to", os.getcwd())
d = {'name': name, 'df': df}
return d
def attributeCheck(dict):
db = mongoCon.AttDB()
CODE = dict['code']
REPORT = dict['report']
SOURCE = dict['source']
mydoc4 = db.attributes.aggregate([{'$project' : {'_id':0,'code':1,'source':1, 'report':1, 'attribute':'$attribute'}},
{'$unwind':'$attribute'},
{'$project':{'_id':0,'code':1,'source':1,'report':1,'std' : '$attribute.value','raw': '$attribute.name'}},
{'$match':{'code':{'$in':[CODE,]},'source':{'$in':[SOURCE,]}}}])
doc5 = []
for x in mydoc4:
doc5.append(x)
print("complete3")
df = pd.DataFrame(data =doc5)
index = ['code', 'source', 'report', 'raw', 'std']
df = df.reindex(columns = index)
df =df.pivot_table(index = 'raw',columns = 'report', values= 'std', aggfunc=lambda x: ' '.join(str(v) for v in x) )
d = {'name':name, 'df':df}
return d
def recordCheck(dict):
db = mongoCon.AttDB()
CODE = dict['code']
SOURCE = dict['source']
mydoc4 = db.attributes.aggregate([{'$project' : {'_id':0,'code':1,'source':1, 'report':1, 'record':'$record'}},
{'$unwind':'$record'},
{'$project':{'_id':0,'code':1,'source':1,'report':1,'std' : '$record.value','raw': '$record.name'}},
{'$match':{'code':{'$in':[CODE,]},'source':{'$in':[SOURCE,]}}}])
recordReport= []
for x in mydoc4:
recordReport.append(x)
df = pd.DataFrame(data =recordReport)
index = ['source', 'report', 'raw', 'std','fact']
header = [np.array(df['report']),np.array(index)]
df = df.reindex(columns = index)
#df =df.pivot(index = 'raw',columns = 'report', values= ['std', 'fact'] )
df =df.pivot_table(index = 'raw',columns = 'report', values= ['std', 'fact'], aggfunc=lambda x: ' '.join(str(v) for v in x) )
name= 'record check for '+CODE+ ' '+SOURCE+'.csv'
d = {'name':name, 'df':df}
return d
