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README.md

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+---
+dataset_info:
+- config_name: default
+  features:
+  - name: path
+    dtype: string
+  - name: task_binary
+    dtype: binary
+  splits:
+  - name: train
+    num_bytes: 44211099
+    num_examples: 9644
+  download_size: 44211099
+  dataset_size: 44211099
+---
+
+# CodeContests
+
+A dataset of **9,644** code contest tasks with sandbox environments and tests, formatted for [Harbor](https://github.com/open-thoughts/OpenThoughts-Agent) / [SkyRL](https://github.com/NovaSky-AI/SkyRL) agentic RL training.
+
+## Dataset Description
+
+- **Source:** [DCAgent/code-contests-sandboxes-with-tests](https://huggingface.co/datasets/DCAgent/code-contests-sandboxes-with-tests)
+
+Each row contains a task directory packed as a tar archive with instructions, environment (Dockerfile), and test verifiers.
+
+## Schema
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `path` | string | Task identifier (e.g. "code_contests-0000") |
+| `task_binary` | binary | Gzip-compressed tar archive of the task directory |
+
+## Interacting with the Data
+
+To explore the tasks locally, you can extract them into a readable format using the following commands (make sure `pyarrow` is installed):
+
+```bash
+curl -L -o extract_parquet_tasks.py \
+  "https://huggingface.co/datasets/open-thoughts/CodeContests/raw/main/extract_parquet_tasks.py"
+
+curl -L -o tasks.parquet \
+  "https://huggingface.co/datasets/open-thoughts/CodeContests/resolve/main/tasks.parquet"
+
+python extract_parquet_tasks.py tasks.parquet ./extracted_tasks
+```
+
+## Usage with SkyRL + Harbor
+
+```bash
+python examples/harbor/prepare_harbor_dataset.py --dataset open-thoughts/CodeContests
+```
+
+This will download and extract the tasks to `~/data/harbor/CodeContests/`.