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Graph/pandas

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pandas

pandas

pandas

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Updated4/30/2026

PageRank0.0007

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14 linked nodes

WRITTEN_INLanguage

RELATES_TODomain

AFFECTSRootCause

Outcome: The trace really does have that much impact.

AFFECTSRootCause

could not find way how to provide this file pattern in python script. Outcome: Convert DynamicFrame to Pandas DataFrame.

AFFECTSRootCause

when I test the Lambda function using the S3-put option. Tension: This is not the expected result. Outcome: I suspect there might be an issue with my Lambda function.

AFFECTSRootCause

The Pandas data frame (df) is fully loaded in memory then pushed to S3 by wrangler. Tension: The Pandas data frame (df) is fully loaded in memory.

AFFECTSRootCause

`DataFrame.query()` evaluates user-supplied `expr` similarly to `eval()`/Python expression evaluation, so untrusted input can execute unintended code within the evaluation context.

AFFECTSRootCause

read_pickle performs pickle deserialization and security scanners treat it as a code-execution surface

AFFECTSRootCause

"SELECT * FROM df_data WHERE id={}".format(user_input) — duckdb.query("SELECT * FROM df_data WHERE id={}".format(user_input)). Tension: the version with f-strings seems insecure to me. Outcome: duckdb.execute("""SELECT * FROM df_data WHERE id=?""", (user_input,)).df().

REQUIRESSolution

Simply turning off the monitoring (the SQL trace) on production decreased a prod script from 8 minutes to 40 seconds — If monitoring is still required (for auditing or other reasons). Outcome: there is a workaround provided by @gordthompson which uses OPENJSON.

REQUIRESSolution

Use pandas : — Convert DynamicFrame to Pandas DataFrame. Tension: Define the S3 path for the output file. Outcome: Upload the buffer to S3.

REQUIRESSolution

Please review my Lambda function code and help me identify the issue? — I have verified the environment variables, IAM permissions, and the input event JSON. Outcome: I suspect there might be an issue with my Lambda function.

REQUIRESSolution

It is possible to read the data in small chunks as it is available in `read_sql` function. — I would like to chunk the data frame and pass those chunks to a process. Tension: I don't think it's possible with parquet. Outcome: for i, chunk in enumerate(chunks): print(f"Processing chunk {i+1}") write_parquet_chunk(chunk, path).

REQUIRESSolution

Use Fortify exclusions or a fork that disables read_pickle() if your enterprise policy requires removing the flagged surface

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