def parse_CADTechData(file):
try:
# This gets the workbook and the tap
wb = open_workbook(filename=file)
ws = wb.sheet_by_index(0)
columndic = generateExcelColumns(counterbegin=0, sizeOfColumns=1)
data = []
for row in range(4, ws.nrows):
CADTechData_row = CADTechData(
customerName = ws.cell(row, columndic['E']).value,
forecastName = ws.cell(row, columndic['Z']).value,
mfgPartno = ws.cell(row, columndic['J']).value,
reservedQuantity = ws.cell(row, columndic['O']).value,
availQuantity = ws.cell(row, columndic['Q']).value,
boQty = ws.cell(row, columndic['R']).value,
age = ws.cell(row, columndic['N']).value,
poEta = xlrdFuntionTime(excelCell = ws.cell(row, columndic['S']).value, wb = wb),
oemPo = ws.cell(row, columndic['T']).value
)
if CADTechData_row.nonempty():
# CADTechData_row.customerId = customerNameLinearSearch(CADTechData_row.customerName.upper(), sorted_by_value)
data.append(CADTechData_row.__dict__)
del CADTechData_row
except Exception as e:
print(e)
else:
ws = None
wb = None
fileNameOutput = 'DBI_LOAD_0001_TECHDATA_CAD_'+(str(datetime.date.today()))+'.csv'
to_csv(fileNameOutput, data, CADTechDataOG.keys())
def parse_ingramCAD(file):
try:
# This gets the workbook and the tap
wb = open_workbook(filename=file)
ws = wb.sheet_by_index(0)
columndic = generateExcelColumns(counterbegin=0, sizeOfColumns=1)
data = []
for row in range(2, ws.nrows):
ingramCAD_row = IngramCAD(
customerName = ws.cell(row, columndic['B']).value,
mfgPartno = ws.cell(row, columndic['D']).value,
availQuantity = ws.cell(row, columndic['H']).value
)
if ingramCAD_row.nonempty():
# ingramCAD_row.customerId = customerNameLinearSearch(ingramCAD_row.customerName.upper(), sorted_by_value)
data.append(ingramCAD_row.__dict__)
del ingramCAD_row
except Exception as e:
print(e)
else:
# After reading the wb it manages the memory
ws = None
wb = None
fileNameOutput = 'DBI_LOAD_0008_CAD_INGRAM_MICRO_'+(str(datetime.date.today()))+'.csv'
to_csv(fileNameOutput, data, IngramCAD.keys())
def parse_ingram(file):
try:
# This gets the workbook and the tap
wb = load_workbook(filename=file, read_only=True, data_only=True)
ws = wb.worksheets[0]
columndic = generateExcelColumns(counterbegin=1, sizeOfColumns=1)
data = []
for row in range(2, ws.max_row+1):
ingram_row = Ingram(
customerName = '', #ws.cell(row = row, column = columndic['K']).value,
mfgPartno = ws.cell(row = row, column = columndic['C']).value,
reservedQuantity = ws.cell(row = row, column = columndic['H']).value,
availQuantity = ws.cell(row = row, column = columndic['J']).value
)
if ingram_row.nonempty():
# ingram_row.customerId = customerNameLinearSearch(ingram_row.customerName.upper(), sorted_by_value)
data.append(ingram_row.__dict__)
del ingram_row
except Exception as e:
print(e)
else:
ws = None
wb = None
fileNameOutput = 'DBI_LOAD_0005_INGRAM_MICRO_'+(str(datetime.date.today()))+'.csv'
to_csv(fileNameOutput, data, Ingram.keys())
def parse_techdata(file):
try:
# This gets the workbook and the tap
wb = load_workbook(filename=file, read_only=True, data_only=True)
ws = wb.worksheets[0]
columndic = generateExcelColumns(counterbegin=1, sizeOfColumns=2)
data = []
for row in range(4, ws.max_row+1):
techdata_row = TechData(
customerName = ws.cell(row = row, column = columndic['I']).value,
forecastName = ws.cell(row = row, column = columndic['I']).value, #This has to be parse out
mfgPartno = ws.cell(row = row, column = columndic['N']).value,
availQuantity = ws.cell(row = row, column = columndic['Z']).value,
boQty = ws.cell(row = row, column = columndic['AA']).value
)
if techdata_row.nonempty():
# techdata_row.customerId = customerNameLinearSearch(techdata_row.customerName.upper(), sorted_by_value)
data.append(techdata_row.__dict__)
del techdata_row
except Exception as e:
print(e)
else:
ws = None
wb = None
fileNameOutput = 'DBI_LOAD_0007_TECHDATA_'+(str(datetime.date.today()))+'.csv'
to_csv(fileNameOutput, data, TechData.keys())
def parse_synnex(file):
try:
wb = open_workbook(filename=file)
ws = wb.sheet_by_index(0)
columndic = generateExcelColumns(counterbegin=0, sizeOfColumns=1)
data = []
for row in range(1, ws.nrows):
synnex_row = Synnex(
customerName = ws.cell(row, columndic['I']).value,
forecastName = ws.cell(row, columndic['H']).value,
mfgPartno = ws.cell(row, columndic['F']).value,
reservedQuantity = ws.cell(row, columndic['J']).value,
availQuantity = ws.cell(row, columndic['O']).value,
boQty = ws.cell(row, columndic['P']).value,
age = ws.cell(row, columndic['S']).value,
poEta = xlrdFuntionTime(excelCell = ws.cell(row, columndic['T']).value, wb = wb),
oemPo = ws.cell(row, columndic['U']).value
)
if synnex_row.nonempty():
# synnex_row.customerId = customerNameLinearSearch(synnex_row.customerName.upper(), sorted_by_value)
data.append(synnex_row.__dict__)
del synnex_row
except Exception as e:
print(e)
else:
# After reading the wb it manages the memory
ws = None
wb = None
fileNameOutput = 'DBI_LOAD_0004_SYNNEX_'+(str(datetime.date.today()))+'.csv'
to_csv(fileNameOutput, data, Synnex.keys())