Comprehensive graduate-level Python coding questions. Each record pairs a question with a worked solution and a final answer.
Available Now · Sample Available
Python Coding QSA
Graduate-level Python in the HumanEval / DS-1000 lane.
Volume
0
Volume
Scalable Volume
Coverage
Grad, PhD, Python, Coding
Model Benchmark
0.0
%
Codex GPT-5.4 · Pass at k
Targets
LiveCodeBench, HumanEval, MBPP, BigCodeBench
Modality & Delivery
Text→Text
Formats
Excel (.xlsx)
What You Receive
Coverage
Complexity theory, algorithmic analysis, and proof-based reasoning, aligned to the reasoning measured by LiveCodeBench and similar algorithmic benchmarks.
Package Structure
Differentiators
- Structured question, worked solution, and final answer record format.
Record Schema
| Field | Description |
|---|---|
answer | The concise final answer associated with the question. |
question | The question or task presented in the dataset record. |
solution | The worked solution or supporting reasoning for the question. |
Results
| Model | Metric | Result |
|---|---|---|
| Codex GPT-5.4 | Pass@3 |
Methodology & Quality
Methodology
Questions are expert-authored, then split across an SME pool for complexity validation before benchmarking.
SME involvement
Domain-expert curated with up to L2 review
Stressors
Design criteria
- Keep the question, supporting solution, and final answer as distinct record components.
Build assumptions
Quality approach
Known limitations
Customization & Scalability
Custom sets available. Additional volume in progress