def parse_csv_p(fp, **kw):
metadata = {}
pdata = {}
header = False
pivot_col = int(kw.get('pivot_col', 0))
results_col = [
int(i.strip()) for i in kw.get('results_col', '1').split(',')
]
for line in fp.readlines():
info = line.split(',')
if len(info) < 2:
raise Exception("Not enough fields in line:\n%s" % line.strip())
pivot = info[pivot_col]
if not header:
metadata['pivot_name'] = pivot
columns = ['Unknown'] * len(results_col)
for col in range(len(results_col)):
columns[col] = info[results_col[col]]
metadata['column_names'] = ','.join(columns)
header = True
continue
if pivot not in pdata:
pdata[pivot] = new_data(info, results_col)
else:
pdata[pivot] = add_data(pdata[group], info, results_col)
return pdata, metadata
def parse_csv_pg(fp, **kw):
metadata = {}
pgdata = {}
header = False
if 'header' in kw:
info = kw['header'].split(',')
metadata['pivot_name'] = info[0]
metadata['grouping_col'] = info[1]
metadata['column_names'] = ','.join(info[2:])
header = True
pivot_col = int(kw.get('pivot_col', 0))
grouping_col = int(kw.get('grouping_col', 1))
grouping_format = kw.get('grouping_format', False)
results_col = [
int(i.strip()) for i in kw.get('results_col', '2').split(',')
]
for line in fp.readlines():
info = line.split(',')
if len(info) < 3:
raise Exception("Not enough fields in line:\n%s" % line.strip())
pivot = info[pivot_col]
group = info[grouping_col]
if not header:
metadata['pivot_name'] = pivot
metadata['grouping_name'] = group
columns = ['Unknown'] * len(results_col)
for col in range(len(results_col)):
columns[col] = info[results_col[col]]
metadata['column_names'] = ','.join(columns)
header = True
continue
if pivot not in pgdata:
pgdata[pivot] = {}
group_dict = pgdata.get(pivot, {})
if grouping_format:
#grouping_tuple = time.strptime('080413', grouping_format)
grouping_tuple = time.strptime(group, grouping_format)
group = datetime.datetime(*grouping_tuple[:6])
if group not in group_dict:
group_dict[group] = new_data(info, results_col)
else:
group_dict[group] = add_data(group_dict[group], info, results_col)
return pgdata, metadata
def parse_csv_pg(fp, **kw):
metadata = {}
pgdata = {}
header = False
if 'header' in kw:
info = kw['header'].split(',')
metadata['pivot_name'] = info[0]
metadata['grouping_col'] = info[1]
metadata['column_names'] = ','.join(info[2:])
header = True
pivot_col = int(kw.get('pivot_col', 0))
grouping_col = int(kw.get('grouping_col', 1))
grouping_format = kw.get('grouping_format', False)
results_col = [int(i.strip()) for i in kw.get('results_col','2').split(',')]
for line in fp.readlines():
info = line.split(',')
if len(info) < 3:
raise Exception("Not enough fields in line:\n%s" % line.strip())
pivot = info[pivot_col]
group = info[grouping_col]
if not header:
metadata['pivot_name'] = pivot
metadata['grouping_name'] = group
columns = ['Unknown']*len(results_col)
for col in range(len(results_col)):
columns[col] = info[results_col[col]]
metadata['column_names'] = ','.join(columns)
header = True
continue
if pivot not in pgdata:
pgdata[pivot] = {}
group_dict = pgdata.get(pivot, {})
if grouping_format:
#grouping_tuple = time.strptime('080413', grouping_format)
grouping_tuple = time.strptime(group, grouping_format)
group = datetime.datetime(*grouping_tuple[:6])
if group not in group_dict:
group_dict[group] = new_data(info, results_col)
else:
group_dict[group] = add_data(group_dict[group], info, results_col)
return pgdata, metadata
def parse_csv_p(fp, **kw):
metadata = {}
pdata = {}
header = False
pivot_col = int(kw.get('pivot_col', 0))
results_col = [int(i.strip()) for i in kw.get('results_col','1').split(',')]
for line in fp.readlines():
info = line.split(',')
if len(info) < 2:
raise Exception("Not enough fields in line:\n%s" % line.strip())
pivot = info[pivot_col]
if not header:
metadata['pivot_name'] = pivot
columns = ['Unknown']*len(results_col)
for col in range(len(results_col)):
columns[col] = info[results_col[col]]
metadata['column_names'] = ','.join(columns)
header = True
continue
if pivot not in pdata:
pdata[pivot] = new_data(info, results_col)
else:
pdata[pivot] = add_data(pdata[group], info, results_col)
return pdata, metadata
