17 docs tagged with "Python"

A reusable pattern for time based sliding window uniqueness problems — combining a deque for order (window) and a hash map for O(1) insertions/lookups/deletes

A practical guide for Poetry users importing a local lib that they are actively developing and want "hot reloading".

Comparisons of DS&A tasks across different languages"

A clean, reusable approach to sliding window problems — starting at the first valid state, removing conditional complexity, and focusing on window validity instead of index juggling.

Explore multiple techniques for converting flat or semi-structured data into trees in Python, including recursive, map-based, and bottom-up builds like Merkle trees.

A pragmatic exploration of Go, JavaScript, Python, and C++ in the high-stakes context of technical interviews. This living guide compares syntax, performance, paradigms, and practical usability to help you pick the right tool for the job.

A quick reference for tracking the top N largest or smallest values in a stream — using heaps

This section isn’t about data structures and algorithms — it’s about surviving the system. Tips and patterns to help you finish implementation before time runs out, even when your engineering instincts are working against you.

Why VS Code and modern Python tooling often show multiple Python versions simultaneously, and how different subsystems each run their own interpreter.

A complete guide to label-based selection and assignment in pandas, with real-world recipes.

Handy Python snippets and patterns for working with 2D grids and matrices: initialization, bounds checking, neighbor offsets, and n-distance neighbors.

Quick syntax and language reference for experienced developers returning to Python. Covers list comprehensions, lambda, unpacking, reflection, scoping, and more.

A timed problem-solver's guide to efficient sorting in Python

Existence checks, containment, and elegant branching

Compare recursive tree traversal with and without generators, highlighting performance and readability tradeoffs.

Explanation of how Python’s * and ** argument patterns work, including keyword-only arguments and flexible function signatures.

A personal and technical reflection on how Python became my default language for MVPs — despite my early frustrations.