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To clean a Python project for distribution, run a dry-run cleanup to review targeted caches, virtual environments, build outputs, and logs before executing file deletion. This planning phase ensures only transient files are removed while preserving necessary data.

Sanitizing API keys in configuration files involves safely replacing real endpoints and keys with secure placeholders before repository handoff. This process ensures sensitive credentials are stripped from shared codebase snapshots without breaking configuration structure.

You can selectively retain data and logs during codebase packaging by reviewing the dry-run report and configuring retention rules. This allows specific files to survive the cleanup process while transient artifacts are purged.

Dry-run cleanup planning only reports planned removals without deleting files immediately. It scans for Python caches, virtual environments, build directories, and IDE settings, providing a summary for user confirmation before executing actual deletion.

Cleaning a Python codebase for release handoff targets Python caches, virtual environments, build directories, coverage files, IDE settings, and leftover test artifacts. These transient files are removed to create a minimal, reproducible project copy.

You should avoid automated cleanup scripts for project packaging when unreviewed, as accidental deletion of non-transient files may occur. Always execute a dry-run first to verify targeted caches and logs, ensuring critical data remains intact.