Columns and DataType Not Explicitly Set on line 137 of utils.py

[CodeSmileBot]

Hello!

I found an AI-Specific Code smell in your project.
The smell is called: Columns and DataType Not Explicitly Set

You can find more information about it in this paper: https://dl.acm.org/doi/abs/10.1145/3522664.3528620.

According to the paper, the smell is described as follows:

Problem	If the columns are not selected explicitly, it is not easy for developers to know what to expect in the downstream data schema. If the datatype is not set explicitly, it may silently continue the next step even though the input is unexpected, which may cause errors later. The same applies to other data importing scenarios.
Solution	It is recommended to set the columns and DataType explicitly in data processing.
Impact	Readability

Example:

### Pandas Column Selection
import pandas as pd
df = pd.read_csv('data.csv')
+ df = df[['col1', 'col2', 'col3']]

### Pandas Set DataType
import pandas as pd
- df = pd.read_csv('data.csv')
+ df = pd.read_csv('data.csv', dtype={'col1': 'str', 'col2': 'int', 'col3': 'float'})

You can find the code related to this smell in this link:

beam/sdks/python/apache_beam/runners/interactive/utils.py

Lines 127 to 147 in 34a1796

	using_dataframes = isinstance(element_type, pd.DataFrame)
	using_series = isinstance(element_type, pd.Series)
	if using_dataframes or using_series:
	rows_df = pd.concat(rows)
	else:
	rows_df = pd.DataFrame(rows, columns=columns_names)
	if include_window_info and not using_series:
	windowed_info_df = pd.DataFrame(
	windowed_info, columns=['event_time', 'windows', 'pane_info'])
	final_df = pd.concat([rows_df, windowed_info_df], axis=1)
	else:
	final_df = rows_df
	return final_df
	def register_ipython_log_handler():
	# type: () -> None
	"""Adds the IPython handler to a dummy parent logger (named

.

I also found instances of this smell in other files, such as:

File: https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/per_entity_training.py#L63-L73 Line: 68
File: https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/inference/milk_quality_prediction_windowing.py#L100-L110 Line: 105
File: https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/inference/milk_quality_prediction_windowing.py#L119-L129 Line: 124
File: https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/inference/milk_quality_prediction_windowing.py#L120-L130 Line: 125
File: https://github.com/apache/beam/blob/master/sdks/python/apache_beam/examples/inference/milk_quality_prediction_windowing.py#L187-L197 Line: 192
.

I hope this information is helpful!