Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10K - 100K
License:
| 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]) |