Merge pull request #52 from mwisnowski/chore/cleanup-debug-workflow

chore: comment out debug step in similarity cache workflow
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mwisnowski 2026-02-20 11:49:53 -08:00 committed by GitHub
commit 65680fb920
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@ -89,44 +89,45 @@ jobs:
exit 1
fi
- name: Debug - Inspect Parquet file after tagging
if: steps.check_cache.outputs.needs_build == 'true'
run: |
python -c "
import pandas as pd
from pathlib import Path
from code.path_util import get_processed_cards_path
parquet_path = Path(get_processed_cards_path())
print(f'Reading Parquet file: {parquet_path}')
print(f'File exists: {parquet_path.exists()}')
if not parquet_path.exists():
raise FileNotFoundError(f'Parquet file not found: {parquet_path}')
df = pd.read_parquet(parquet_path)
print(f'Loaded {len(df)} rows from Parquet file')
print(f'Columns: {list(df.columns)}')
print('')
# Show first 5 rows completely
print('First 5 complete rows:')
print('=' * 100)
for idx, row in df.head(5).iterrows():
print(f'Row {idx}:')
for col in df.columns:
value = row[col]
if isinstance(value, (list, tuple)) or hasattr(value, '__array__'):
# For array-like, show type and length
try:
length = len(value)
print(f' {col}: {type(value).__name__}[{length}] = {value}')
except:
print(f' {col}: {type(value).__name__} = {value}')
else:
print(f' {col}: {value}')
print('-' * 100)
"
# Debug step - uncomment if needed to inspect Parquet file contents
# - name: Debug - Inspect Parquet file after tagging
# if: steps.check_cache.outputs.needs_build == 'true'
# run: |
# python -c "
# import pandas as pd
# from pathlib import Path
# from code.path_util import get_processed_cards_path
#
# parquet_path = Path(get_processed_cards_path())
# print(f'Reading Parquet file: {parquet_path}')
# print(f'File exists: {parquet_path.exists()}')
#
# if not parquet_path.exists():
# raise FileNotFoundError(f'Parquet file not found: {parquet_path}')
#
# df = pd.read_parquet(parquet_path)
# print(f'Loaded {len(df)} rows from Parquet file')
# print(f'Columns: {list(df.columns)}')
# print('')
#
# # Show first 5 rows completely
# print('First 5 complete rows:')
# print('=' * 100)
# for idx, row in df.head(5).iterrows():
# print(f'Row {idx}:')
# for col in df.columns:
# value = row[col]
# if isinstance(value, (list, tuple)) or hasattr(value, '__array__'):
# # For array-like, show type and length
# try:
# length = len(value)
# print(f' {col}: {type(value).__name__}[{length}] = {value}')
# except:
# print(f' {col}: {type(value).__name__} = {value}')
# else:
# print(f' {col}: {value}')
# print('-' * 100)
# "
- name: Generate theme catalog
if: steps.check_cache.outputs.needs_build == 'true'