---
license: cc-by-nc-4.0
language:
- en
tags:
- synthetic
- code
- reasoning
- python
- assertions
- verified
size_categories:
- 10K<n<100K
task_categories:
- text-generation
pretty_name: PyLogic-Verified-10k
---

# 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

| Feature | 10k Hugging Face Sample | 100k Full Production Corpus |
| :--- | :--- | :--- |
| **Sample Count** | 10,000 rows | 100,000 rows |
| **Formats Included** | `.parquet` | `.parquet` + `.jsonl` |
| **Algorithmic Variety** | Baseline relational logic | 4 Distinct Algorithmic Templates |
| **License** | CC-BY-NC 4.0 (Non-Commercial) | **Full Commercial License** |
| **Access** | Free Download | **[Purchase ($24) →](https://buy.polar.sh/polar_cl_mJTc4TkjMmibI1h1DxoQaiDWf4Pu8NKAxYIG93QXYB0)** |

## Schema

| Column | Type | Description |
| :--- | :--- | :--- |
| `id` | string | Unique deterministic sample identifier |
| `instruction` | string | Natural language code generation prompt |
| `code` | string | Executable Python function implementation |
| `unit_test` | string | Ground-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])