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# fileparse.py

import csv

def parse_csv(lines, select=None, types=None, has_headers=True, delimiter=',', silence_errors=False):

'''

Parse a CSV file into a list of records with type conversion.

'''

if select and not has_headers:

raise RuntimeError('select requires column headers')

rows = csv.reader(lines, delimiter=delimiter)

# Read the file headers (if any)

headers = next(rows) if has_headers else []

# If specific columns have been selected, make indices for filtering and set output columns

if select:

indices = [ headers.index(colname) for colname in select ]

headers = select

records = []

for rowno, row in enumerate(rows, 1):

if not row: # Skip rows with no data

continue

# If specific column indices are selected, pick them out

if select:

row = [ row[index] for index in indices]

# Apply type conversion to the row

if types:

try:

row = [func(val) for func, val in zip(types, row)]

except ValueError as e:

if not silence_errors:

print(f"Row {rowno}: Couldn't convert {row}")

print(f"Row {rowno}: Reason {e}")

continue

# Make a dictionary or a tuple

if headers:

record = dict(zip(headers, row))

else:

record = tuple(row)

records.append(record)

return records