16 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.

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.