Added solution code

Solutions/6_15/fileparse.py

@@ -0,0 +1,47 @@
+# 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