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https://issues.apache.org/jira/browse/BEAM-12803?focusedWorklogId=653213&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-653213
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ASF GitHub Bot logged work on BEAM-12803:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 20/Sep/21 21:20
Start Date: 20/Sep/21 21:20
Worklog Time Spent: 10m
Work Description: JonathanHourany commented on a change in pull request
#15539:
URL: https://github.com/apache/beam/pull/15539#discussion_r712501402
##########
File path: sdks/python/apache_beam/typehints/native_type_compatibility.py
##########
@@ -107,7 +107,7 @@ def _match_is_exactly_iterable(user_type):
def match_is_named_tuple(user_type):
return (
_safe_issubclass(user_type, typing.Tuple) and
- hasattr(user_type, '_field_types'))
+ hasattr(user_type, '__annotations__'))
Review comment:
Good catch. The only other object I know of off the top of my head that
has `__annotations__` are `dataclasses`, but dataclasses aren't a subclass of
`typing.Tuple` so this function should still return `false` for those
instances. AFIAK it'll only return true if the dataclass sublcasses
`typing.Tuple` or `typing.NamedTuple`
```python
>>> from dataclasses import dataclass
>>> from apache_beam.typehints.native_type_compatibility import
match_is_named_tuple
>>> @dataclass
...: class TestDS():
...: foo: int
>>> match_is_named_tuple(TestDS)
False
```
However
```python
>>> from apache_beam.typehints.native_type_compatibility import
match_is_named_tuple
>>> @dataclass
...: class TestDS(typing.NamedTuple):
...: foo: int
>>> match_is_named_tuple(TestDS)
True
```
edit: updated example
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Issue Time Tracking
-------------------
Worklog Id: (was: 653213)
Time Spent: 1h 40m (was: 1.5h)
> SqlTransform doesn't work on python 3.9
> ---------------------------------------
>
> Key: BEAM-12803
> URL: https://issues.apache.org/jira/browse/BEAM-12803
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Reporter: sean teeling
> Assignee: Brian Hulette
> Priority: P2
> Time Spent: 1h 40m
> Remaining Estimate: 0h
>
> Working example below -(Is there no way to paste pre-formatted code into
> jira?!)- (EDIT: I added the appropriate "code" block)
> {code:python}
> import itertools
> import csv
> import io
> import apache_beam as beam
> from apache_beam.dataframe.io import read_csv
> from apache_beam.transforms.sql import SqlTransform
> def parse_csv(val):
> deflower_headers(iterator):
> return itertools.chain([next(iterator).lower()], iterator)
> return csv.DictReader(lower_headers(io.TextIOWrapper(val.open())))
> class BeamTransformBuilder():
> def build(self, pipeline):
> practices = (
> pipeline
> | beam.io.fileio.MatchFiles("data.csv")
> | beam.io.fileio.ReadMatches()
> | beam.Reshuffle()
> | beam.FlatMap(parse_csv)
> | beam.Map(lambda x: beam.Row(id="test-id"))
> | SqlTransform("""
> SELECT
> id
> FROM PCOLLECTION""")
> )
> practices | beam.Map(print)
> def main():
> builder = BeamTransformBuilder()
> with beam.Pipeline('DirectRunner') as p:
> builder.build(p)
> if __name__ == '__main__':
> main()
> {code}
>
> Results in the error:
>
> {code:java}
> File
> "/usr/local/lib/python3.9/site-packages/apache_beam/typehints/schemas.py",
> line 185, in typing_to_runner_api
> element_type = typing_to_runner_api(_get_args(type_)[0])
> IndexError: tuple index out of range
> {code}
>
>
> Tested on Python 3.9.6.
>
> Annoyingly, it is difficult to test this out on other python versions.
> There's no documentation for how to setup a docker container using
> DirectRunner and running it locally. There's barely any documentation on what
> python versions are supported. And using pyenv, and pip install apache-beam
> requires a lot of other downloads that have conflicts when other versions are
> already installed.
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