《Python3 标准库》电子书和配套代码 "The Python Standard Library by Example" ebook and source code 一本又厚又全的讲解Python3标准库的书籍（1000多页）适合当作字典参考或者闲暇时慢慢阅读。
A list of Python Standard Libraries (2.6-7, 3.2-14).
Python programming basics course
Level Up Your Python skills with 200+ exercises using standard libraries.
tommy teaches tommy how to develop applications and write code in the Python programming language
GenPark AI Agent Skill - Heuristic and statistical prompt injection and jailbreak detector with semantic delimiter protection and adversarial pattern scoring.
Python Standard Library Essential Training
Flappy bird using python's tkinter and turtle
Continuous viewport to discrete UI grid cell and center click coordinate mapper for computer-use agents
High-performance PII and API secret token scrubber for prompt anonymization and data sanitization
Parses unified git diffs to detect breaking API signature changes, removed public functions, and leaked secrets
Strict heuristic and regex-based prompt injection and untrusted input guard detecting jailbreak markers, hidden instruction escapes, and indirect injection payloads
Habit loop tracking and micro-commitment accountability check-in system with partner synchronization
Safely coerces stringified primitives and mixed data types into strictly typed Python ints, floats, booleans, and lists
Jordan curve ray-casting point-in-polygon (PIP) test with polygon area and centroid Shoelace calculation
Abstract Interpretation static analyzer using the numeric Interval Domain to prove buffer bounds safety and absence of division-by-zero errors.
Repairs malformed LLM JSON outputs by stripping markdown fences and trailing commas while validating required schema keys
Real-time Tarjan SCC cycle detection on lock Wait-For-Graphs with minimal-cost victim transaction arbitrator
GenPark AI Agent Skill - Gale-Shapley deferred acceptance algorithm ensuring stable, envy-free, and Pareto-efficient bipartite matching between autonomous agents and task markets.
Verbosity penalty and length bias calibrator normalizing raw model rewards against response token lengths
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