From a819212b4ccf5ea3b2cb597a1ebbf4939a6daae2 Mon Sep 17 00:00:00 2001 From: David Kunzmann Date: Mon, 3 Feb 2025 11:35:18 +0100 Subject: [PATCH] Fix after release --- rules/S7195/python/metadata.json | 1 - rules/S7195/python/rule.adoc | 4 ++-- 2 files changed, 2 insertions(+), 3 deletions(-) diff --git a/rules/S7195/python/metadata.json b/rules/S7195/python/metadata.json index db85439bfdd..d858e9c6653 100644 --- a/rules/S7195/python/metadata.json +++ b/rules/S7195/python/metadata.json @@ -18,7 +18,6 @@ "quickfix": "unknown", "code": { "impacts": { - "MAINTAINABILITY": "MEDIUM", "RELIABILITY": "MEDIUM" }, "attribute": "CONVENTIONAL" diff --git a/rules/S7195/python/rule.adoc b/rules/S7195/python/rule.adoc index a083b611422..e8edfd9af26 100644 --- a/rules/S7195/python/rule.adoc +++ b/rules/S7195/python/rule.adoc @@ -2,7 +2,7 @@ This rule raises an issue when a column of a PySpark DataFrame is populated with == Why is this an issue? -In PySpark, when populating a DataFrame columns with empty or null values, it is recommended to use `lit(None)`. +In PySpark, when populating a DataFrame column with empty or null values, it is recommended to use `lit(None)`. Using literals such as `lit('')` as a placeholder for absent values can lead to data misinterpretation and inconsistencies. The usage of `lit(None)` ensures clarity and consistency in the codebase, making it explicit that the column is intentionally populated with null values. @@ -10,7 +10,7 @@ Using `lit(None)` also preserves the ability to use functions such as `isnull` o == How to fix it -To fix this issue, replace `lit('')` with `lit(None)` when populating a DataFrame columns with empty/null values. +To fix this issue, replace `lit('')` with `lit(None)` when populating a DataFrame column with empty/null values. === Code examples