sorensenjs commented on issue #31152:
URL: https://github.com/apache/beam/issues/31152#issuecomment-2094493983
That workaround code example doesn't work, because ReadFromCsv and
WriteToCsv both produce/require schemas.
Even if you were to use a ._asdict() like so
```
( pipeline | beam.io.ReadFromCsv('/tmp/input.csv', dtype=str)
| beam.Map(lambda x: x._asdict())
| beam.Map(print)
```
Conversion to str element by element will result in 'None' values instead of
empty strings. Values interpreted as floating point may loose precision.
```
{'a': 'text', 'b': 1, 'c': 21, 'd': 5945023, 'e': 376974, 'f': 0, 'g': 0,
'h': 0, 'i': 1, 'j': 2, 'k': 0, 'l': 4, 'm': None, 'n': None, 'o': None, 'p':
None, 'q': None, 'r': None}
Elapsed time 0:00:00.878320
{'a': 'text', 'b': '1', 'c': '21', 'd': '5945023', 'e': '376974', 'f': '0',
'g': '0', 'h': '0', 'i': '1', 'j': '2', 'k': '0', 'l': '4', 'm': None, 'n':
None, 'o': None, 'p': None, 'q': None, 'r': None}
Elapsed time 0:00:24.243182
```
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