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Adolessence101-ally/python-logic-assertions

Deterministic Synthetic Python Logic & Assertion Dataset ⚡ Full Production Release Available: Looking for commercial licensing or larger training volume?📦 Download the Full 100,000 Verified Dataset (.Parquet + .JSONL) with Commercial Rights → A high-entropy, 100% syntactically verified synthetic dataset of Python conditional logic, multi-variable state mutations, and ground-truth unit test assertions. Dataset Overview Rows (Free Preview): 10,000 verified… See the full description on the dataset page: https://huggingface.co/datasets/Adolessence101-ally/python-logic-assertions.

sourceHugging Facecc-by-nc-4.0updated 1mo agoView on Hugging Face
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Dataset Card

Deterministic Synthetic Python Logic & Assertion Dataset

⚡ Full Production Release Available: Looking for commercial licensing or larger training volume? 📦 [Download the Full 100,000 Verified Dataset (.Parquet + .JSONL) with Commercial Rights →](https://buy.polar.sh/polar_cl_mJTc4TkjMmibI1h1DxoQaiDWf4Pu8NKAxYIG93QXYB0)

A high-entropy, 100% syntactically verified synthetic dataset of Python conditional logic, multi-variable state mutations, and ground-truth unit test assertions.

Dataset Overview

  • —Rows (Free Preview): 10,000 verified execution pairs
  • —Full Commercial Corpus: 100,000 samples (Dual Parquet + JSONL)
  • —Format: Apache Parquet (Snappy Compressed)
  • —Zero Hallucination: Every function includes closed-form deterministic unit test assertions.
  • —Purpose: Designed to fine-tune code LLMs on multi-variable boundary reasoning and execution state tracking.

Commercial vs. Research Access

Feature10k Hugging Face Sample100k Full Production Corpus
Sample Count10,000 rows100,000 rows
Formats Included.parquet.parquet + .jsonl
Algorithmic VarietyBaseline relational logic4 Distinct Algorithmic Templates
LicenseCC-BY-NC 4.0 (Non-Commercial)Full Commercial License
AccessFree Download[Purchase ($24) →](https://buy.polar.sh/polar_cl_mJTc4TkjMmibI1h1DxoQaiDWf4Pu8NKAxYIG93QXYB0)

Schema

ColumnTypeDescription
idstringUnique deterministic sample identifier
instructionstringNatural language code generation prompt
codestringExecutable Python function implementation
unit_teststringGround-truth unit test suite (assert statements)

Quickstart

python
from datasets import load_dataset

dataset = load_dataset("adolessence101-ally/python-logic-assertions")
print(dataset["train"][0])