Datasets:
Clarify task examples and auxiliary tables
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README.md
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# AsynCodeBench
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AsynCodeBench evaluates coding agents under five execution protocols while holding the task set and evaluation contracts fixed.
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| `tasks` | 19 | Task statements, source revisions, tests, container digests, and manifest provenance |
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| `scenarios` | 95 | Five official protocol conditions for every task |
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| `dependencies` | 52 | Producer-consumer dependency contracts and probe tests |
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All configurations use the `test` split because this is an evaluation benchmark.
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```python
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from datasets import load_dataset
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tasks = load_dataset(
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scenarios = load_dataset("PhilipZhang/AsynCodeBench", "scenarios", split="test", revision="v0.4.2")
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dependencies = load_dataset("PhilipZhang/AsynCodeBench", "dependencies", split="test", revision="v0.4.2")
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```
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# AsynCodeBench
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AsynCodeBench evaluates coding agents under five execution protocols while holding the task set and evaluation contracts fixed. The stable **v0.4.2** release contains **19 coding tasks**. Start with the `tasks` configuration; each row is one real benchmark task.
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[**Browse the 19 task examples in Dataset Viewer →**](https://huggingface.co/datasets/PhilipZhang/AsynCodeBench/viewer/tasks/test)
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The executable harness, manifests, container references, evaluation commands, and Quick Start are versioned in the [official GitHub repository](https://github.com/KaituoZhang/AsynCodeBench/tree/2a639b049f249e79eb2031876bc06a110be9ac3a). Source repositories are materialized at each row's `base_revision` inside the recorded container image; the Parquet files therefore do not duplicate complete source checkouts or container layers.
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## Start here: one task example
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The first `tasks` row is `asyncodebench:cachetools`. It contains the full coding prompt in `problem_statement`, the immutable source revision, evaluator command, test targets, and pinned container image/digest.
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```python
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from datasets import load_dataset
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tasks = load_dataset(
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"PhilipZhang/AsynCodeBench",
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"tasks",
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split="test",
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revision="v0.4.2",
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)
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example = tasks[0]
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print(example["task_id"]) # asyncodebench:cachetools
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print(example["problem_statement"]) # complete task prompt
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print(example["container_image"]) # docker.io/wentingzhao/cachetools:v0
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print(example["dependency_count"]) # 5
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```
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## What the three configurations mean
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| Configuration | Rows | Purpose |
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| **`tasks`** | **19** | **Primary dataset. One row per coding task: prompt, source revision, tests, evaluator, and container. Most users only need this.** |
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| `scenarios` | 95 | Auxiliary protocol table: 19 tasks × 5 execution protocols. These are run conditions, not 95 additional coding tasks. |
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| `dependencies` | 52 | Auxiliary annotation table: producer-consumer contracts inside the 19 tasks, with probe tests for ADPR, DRS, CAIL, and SAD metrics. These are not additional tasks. |
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All configurations use the `test` split because every row belongs to the evaluation benchmark.
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- [Browse task examples](https://huggingface.co/datasets/PhilipZhang/AsynCodeBench/viewer/tasks/test)
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- [Browse protocol conditions](https://huggingface.co/datasets/PhilipZhang/AsynCodeBench/viewer/scenarios/test)
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- [Browse dependency annotations](https://huggingface.co/datasets/PhilipZhang/AsynCodeBench/viewer/dependencies/test)
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## Load auxiliary analysis tables
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You do not need these tables to enumerate the 19 coding tasks. Load them when comparing protocols or computing dependency-aware metrics:
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```python
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scenarios = load_dataset("PhilipZhang/AsynCodeBench", "scenarios", split="test", revision="v0.4.2")
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dependencies = load_dataset("PhilipZhang/AsynCodeBench", "dependencies", split="test", revision="v0.4.2")
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```
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checksums.json
CHANGED
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{
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"files": {
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"README.md": "
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"data/dependencies-test.parquet": "f5cd9430efaeb829bf84048dcfe34959f7400277973daa2c22b43b646938a6d1",
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"data/scenarios-test.parquet": "1e0c8aebfe2b749b3cadd8384a699ad8c3f47965146379c63391d5b863b29d6f",
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"data/tasks-test.parquet": "3d1f78c3d69281e6cf33e75d3b99e5adeecd3ba93315af6e0e5d65b902f2117b"
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{
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"files": {
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"README.md": "1cdba53b668ac408040f2e51878d97419030879b5900847d823b0ba2e6dd9c6b",
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"data/dependencies-test.parquet": "f5cd9430efaeb829bf84048dcfe34959f7400277973daa2c22b43b646938a6d1",
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"data/scenarios-test.parquet": "1e0c8aebfe2b749b3cadd8384a699ad8c3f47965146379c63391d5b863b29d6f",
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"data/tasks-test.parquet": "3d1f78c3d69281e6cf33e75d3b99e5adeecd3ba93315af6e0e5d65b902f2117b"
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