def stats_to_xlsx(inputfile, outputfile, configfile):
"""Generic function with input and output.
parameters:
inputfile - the full path to the input file
outputfile - the full path to the output file
outputfile - the full path to the config file
returns:
success - True if the task is completed, otherwise False
"""
# Check for required values
if inputfile is None or len(inputfile)==0:
logging.debug('No input file given in do_stuff()')
return False
if outputfile is None or len(outputfile)==0:
logging.debug('No output file given in do_stuff()')
return False
# load entire jason file. (Note: syntactically it is a Dictionary !!! )
with open(inputfile) as data_file:
fpAkkaOutput = json.load(data_file)
###### In this test, both normalized and non-normalized statistics are shown
origin1 = [0, 0] # Validator names, from which cell addr set below has names for non-normalized data
origin2 = [5, 0] # Validator names, from which cell addr set below has names for non-normalized data
workbook = xlsxwriter.Workbook(outputfile) # xlsxwriter model of an xlsx spreadsheet
worksheet = workbook.add_worksheet() # should supply worksheet name, else defaults
# stats = OutcomeStats(workbook,worksheet,data_file,outfile,configFile,origin1,origin2)
stats = OutcomeStats(configfile)
worksheet.set_column(0, len(stats.getOutcomes()), 3 + stats.getMaxLength())
# print(stats.getOutcomes())
outcomeFormats = OutcomeFormats({})
formats = outcomeFormats.initFormats(workbook) # shouldn't be attr of main class
###################################################
#####createStats and stats2XLSX comprise the main #
# processor filling the spreadheet cells ####
###################################################
# if stats are normalized, results are divided by number of records
# otherwise, cells show total of the number of each outcome in the appropriate column
normalized = True
validatorStats = stats.createStats(fpAkkaOutput, ~normalized)
validatorStatsNormalized = stats.createStats(fpAkkaOutput, normalized)
outcomes = stats.getOutcomes()
# print("outcomes=", outcomes)
validators = stats.getValidators()
stats.stats2XLSX(workbook, worksheet, formats, validatorStats, origin1, outcomes, validators)
stats.stats2XLSX(workbook, worksheet, formats, validatorStatsNormalized, origin2, outcomes, validators)
workbook.close()
# Success
return True
def outcomestats(inputfile, outputfile, configfile, originrow, origincolumn):
# load entire jason file. (Note: syntactically it is a Dictionary !!! )
with open(inputfile) as data_file:
fpAkkaOutput = json.load(data_file)
###### In this test, both normalized and non-normalized statistics are shown
### origin1 = [0, 0] # Validator names, from which cell addr set below has names for non-normalized data
### origin2 = [5, 0] # Validator names, from which cell addr set below has names for non-normalized data
### origin1 = [origincolumn,originrow]
origin1 = [origincolumn,originrow]
workbook = xlsxwriter.Workbook(outputfile) # xlsxwriter model of an xlsx spreadsheet
worksheet = workbook.add_worksheet() # should supply worksheet name, else defaults
# stats = OutcomeStats(workbook,worksheet,data_file,outfile,configFile,origin1,origin2)
stats = OutcomeStats(configfile)
### worksheet.set_column(0, len(stats.getOutcomes()), 3 + stats.getMaxLength())
### worksheet.set_column(origincolumn, len(stats.getOutcomes()), 3 + stats.getMaxLength())
worksheet.set_column(origincolumn, len(stats.getOutcomes()), 3 + stats.getMaxLength())
# print(stats.getOutcomes())
outcomeFormats = OutcomeFormats({})
formats = outcomeFormats.initFormats(workbook) # shouldn't be attr of main class
###################################################
#####createStats and stats2XLSX comprise the main #
# processor filling the spreadheet cells ####
###################################################
# if stats are normalized, results are divided by number of records
# otherwise, cells show total of the number of each outcome in the appropriate column
normalized = True
validatorStats = stats.createStats(fpAkkaOutput, ~normalized)
validatorStatsNormalized = stats.createStats(fpAkkaOutput, normalized)
outcomes = stats.getOutcomes()
# print("outcomes=", outcomes)
validators = stats.getValidators()
stats.stats2XLSX(workbook, worksheet, formats, validatorStats, origin1, outcomes, validators)
### stats.stats2XLSX(workbook, worksheet, formats, validatorStatsNormalized, origin2, outcomes, validators)
workbook.close()
#load entire jason file. (Note: syntactically it is a Dictionary !!! )
with open(args.getInfile()) as data_file:
fpAkkaOutput=json.load(data_file)
###### In this test, both normalized and non-normalized statistics are shown
origin1 = [0,0] #Validator names, from which cell addr set below has names for non-normalized data
origin2 = [5,0] #Validator names, from which cell addr set below has names for non-normalized data
outfile = args.getOutfile()
workbook = xlsxwriter.Workbook(outfile) #xlsxwriter model of an xlsx spreadsheet
worksheet = workbook.add_worksheet() #should supply worksheet name, else defaults
configFile= 'stats.ini'
# stats = OutcomeStats(workbook,worksheet,data_file,outfile,configFile,origin1,origin2)
stats = OutcomeStats(workbook,worksheet,args,origin1,origin2)
worksheet.set_column(0,len(stats.getOutcomes()), 3+stats.getMaxLength())
# print(stats.getOutcomes())
outcomeFormats = OutcomeFormats({})
formats = outcomeFormats.initFormats(workbook) #shouldn't be attr of main class
###################################################
#####createStats and stats2XLSX comprise the main #
# processor filling the spreadheet cells ####
###################################################
#if stats are normalized, results are divided by number of records
#otherwise, cells show total of the number of each outcome in the appropriate column
normalized = True
validatorStats = stats.createStats(fpAkkaOutput, ~normalized)
validatorStatsNormalized = stats.createStats(fpAkkaOutput, normalized)
outcomes = stats.getOutcomes()
# print("outcomes=", outcomes)
validators = stats.getValidators()
stats.stats2XLSX(workbook, worksheet, formats,validatorStats,origin1, outcomes,validators)
# load entire jason file. (Note: syntactically it is a Dictionary !!! )
with open(args.getInfile()) as data_file:
fpAkkaOutput = json.load(data_file)
###### In this test, both normalized and non-normalized statistics are shown
origin1 = [0, 0] # Validator names, from which cell addr set below has names for non-normalized data
origin2 = [5, 0] # Validator names, from which cell addr set below has names for non-normalized data
outfile = args.getOutfile()
workbook = xlsxwriter.Workbook(outfile) # xlsxwriter model of an xlsx spreadsheet
worksheet = workbook.add_worksheet() # should supply worksheet name, else defaults
configFile = "stats.ini"
# stats = OutcomeStats(workbook,worksheet,data_file,outfile,configFile,origin1,origin2)
stats = OutcomeStats(workbook, worksheet, args, origin1, origin2)
worksheet.set_column(0, len(stats.getOutcomes()), 3 + stats.getMaxLength())
# print(stats.getOutcomes())
outcomeFormats = OutcomeFormats({})
formats = outcomeFormats.initFormats(workbook) # shouldn't be attr of main class
###################################################
#####createStats and stats2XLSX comprise the main #
# processor filling the spreadheet cells ####
###################################################
# if stats are normalized, results are divided by number of records
# otherwise, cells show total of the number of each outcome in the appropriate column
normalized = True
validatorStats = stats.createStats(fpAkkaOutput, ~normalized)
validatorStatsNormalized = stats.createStats(fpAkkaOutput, normalized)
outcomes = stats.getOutcomes()
# print("outcomes=", outcomes)
validators = stats.getValidators()
stats.stats2XLSX(workbook, worksheet, formats, validatorStats, origin1, outcomes, validators)
