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🔄 Worth Revisiting

Python 3.14: Type-Safe String Interpolation with t-strings

Problem

Building SQL queries with f-strings directly embeds user input into the query string, allowing attackers to inject malicious SQL commands.

Parameterized queries are secure but require you to maintain query templates and value lists separately.

Solution

Python 3.14 introduces template string literals (t-strings). Instead of returning strings, they return Template objects that safely expose interpolated values.

This lets you validate and sanitize interpolated values before building the final query.

Build Self-Documenting Regex with Pregex

Problem

Regex patterns like [a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,} are difficult to read and intimidating.

Team members without regex expertise might struggle to understand and modify these validation patterns.

Solution

Team members without regex expertise might struggle to understand and modify these validation patterns.

Pregex transforms regex into readable Python code using descriptive components.

Key benefits:

• Code that explains its intent without comments
• Easy modification without regex expertise
• Composable patterns for complex validation
• Export to regex format when needed

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Visualize Machine Learning Results with Yellowbrick – Learn to visualize ML model performance with Yellowbrick. Create confusion matrices, ROC curves, and feature importance plots in scikit-learn pipelines.

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