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+# Scientific Coding SWE Dataset (JSONL Format)
+
+## Dataset Description
+
+This dataset contains 244 samples extracted from the [xinshuo/Scientific_Coding_SWE_dataset](https://huggingface.co/datasets/xinshuo/Scientific_Coding_SWE_dataset), specifically the `json_dump` field from each sample. The data is provided in JSONL (JSON Lines) format for easy streaming and processing.
+
+### Dataset Summary
+
+The Scientific Coding SWE (Software Engineering) dataset focuses on real-world code issues and fixes from prominent scientific computing projects. Each sample represents a complete software engineering task including:
+
+- Issue descriptions
+- Code patches (fixes)
+- Test cases
+- Metadata about the changes
+- Execution results
+
+### Supported Tasks
+
+- **Software Engineering Task Resolution**: Understanding and resolving code issues in scientific computing contexts
+- **Code Generation**: Generating fixes for missing or incorrect code
+- **Test-Driven Development**: Working with test cases and validation
+- **Documentation Generation**: Understanding code documentation needs
+
+### Languages
+
+The dataset covers two primary programming languages:
+- **C++**: 159 samples (65.2%)
+- **Python**: 85 samples (34.8%)
+
+## Dataset Structure
+
+### Data Format
+
+The dataset is provided as a single JSONL file (`dataset_json_dumps.jsonl`), where each line is a complete JSON object representing one sample.
+
+### Data Fields
+
+Each sample contains the following fields:
+
+- `org` (string): Organization name (e.g., "einsteintoolkit", "Qiskit", "openmm")
+- `repo` (string): Repository name
+- `number` (int): Issue/PR number
+- `state` (string): State of the issue (e.g., "open", "closed")
+- `title` (string): Title of the issue/PR
+- `body` (string): Description of the issue
+- `base` (dict): Base branch information with keys:
+  - `label`: Branch label
+  - `ref`: Branch reference
+  - `sha`: Commit SHA
+- `resolved_issues` (list): List of related issues with:
+  - `number`: Issue number
+  - `title`: Issue title
+  - `body`: Issue description
+- `fix_patch` (string): Git diff/patch for the fix
+- `test_patch` (string): Git diff/patch for tests
+- `doc_patch` (string): Git diff/patch for documentation
+- `tag` (string): Additional tags
+- `number_interval` (string): Number interval information
+- `lang` (string): Programming language (cpp, python)
+- `language` (string): Same as lang
+- `instance_id` (string): Unique instance identifier
+- `fixed_tests` (dict): Test results for fixed code
+- `p2p_tests` (dict): Patch-to-pass tests
+- `f2p_tests` (dict): Fail-to-pass tests
+- `s2p_tests` (dict): Skip-to-pass tests
+- `n2p_tests` (dict): None-to-pass tests
+- `run_result` (dict): Execution results with counts of passed/failed/skipped tests
+- `test_patch_result` (dict): Test patch execution results
+- `fix_patch_result` (dict): Fix patch execution results
+- `hints` (string): Hints for solving the issue
+- `count_new_files` (int): Number of new files added
+- `count_new_entities` (int): Number of new code entities
+- `workdir` (string): Working directory path
+- `fix_meta_info` (dict): Metadata about the fix
+- `test_meta_info` (dict): Metadata about tests
+- `doc_meta_info` (dict): Metadata about documentation
+- `meta_info` (dict): General metadata
+- `pre_commands` (list): Commands to run before testing
+
+### Data Instances
+
+An example instance (truncated for brevity):
+
+```json
+{
+  "org": "einsteintoolkit",
+  "repo": "Cactus",
+  "number": 1,
+  "state": "open",
+  "title": "Add missing LinearExtrapBnd.c in CactusExamples/SampleBoundary",
+  "body": "This PR adds the missing source file LinearExtrapBnd.c to complete the CactusExamples/SampleBoundary thorn implementation.",
+  "language": "cpp",
+  "instance_id": "einsteintoolkit__cactus_1",
+  "fix_patch": "diff --git a/arrangements/CactusExamples/SampleBoundary/src/LinearExtrapBnd.c ...",
+  "run_result": {
+    "passed_count": 1,
+    "failed_count": 0,
+    "skipped_count": 0
+  }
+}
+```
+
+### Data Splits
+
+This dataset contains a single split with all 244 samples.
+
+## Source Projects
+
+The dataset includes samples from the following scientific computing projects:
+
+| Organization | Count | Description |
+|-------------|-------|-------------|
+| openmm | 54 | High-performance molecular dynamics simulation |
+| pyscf | 47 | Python-based Simulations of Chemistry Framework |
+| rdkit | 46 | Cheminformatics and machine learning software |
+| einsteintoolkit | 40 | Computational infrastructure for numerical relativity and astrophysics |
+| Qiskit | 38 | Open-source quantum computing framework |
+| AMReX-Codes | 19 | Block-structured adaptive mesh refinement framework |
+
+## Dataset Creation
+
+### Source Data
+
+This dataset is derived from the [xinshuo/Scientific_Coding_SWE_dataset](https://huggingface.co/datasets/xinshuo/Scientific_Coding_SWE_dataset), which curates software engineering tasks from real GitHub issues and pull requests in scientific computing projects.
+
+### Data Collection Process
+
+The data was extracted by:
+1. Loading the original dataset using the HuggingFace `datasets` library
+2. Extracting only the `json_dump` field from each sample
+3. Converting to JSONL format for efficient streaming and processing
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+This dataset can be used to:
+- Train and evaluate AI models for scientific software engineering tasks
+- Improve automated code generation and bug fixing in scientific computing
+- Understand common patterns in scientific software development
+
+### Discussion of Biases
+
+The dataset may have the following biases:
+- Overrepresentation of certain programming languages (C++ and Python)
+- Focus on specific scientific domains (physics, chemistry, quantum computing)
+- Representation limited to open-source projects with public GitHub repositories
+
+## Additional Information
+
+### Dataset Curators
+
+This JSONL version was created from the original xinshuo/Scientific_Coding_SWE_dataset.
+
+### Licensing Information
+
+Please refer to the original dataset for licensing information.
+
+### Citation Information
+
+If you use this dataset, please cite the original source:
+
+```bibtex
+@dataset{scientific_coding_swe_dataset,
+  title={Scientific Coding SWE Dataset},
+  author={xinshuo},
+  year={2024},
+  url={https://huggingface.co/datasets/xinshuo/Scientific_Coding_SWE_dataset}
+}
+```
+
+### Contributions
+
+For questions or issues with this JSONL format, please refer to the dataset repository.
+
+## Usage Example
+
+```python
+import json
+
+# Read and process the dataset
+with open('dataset_json_dumps.jsonl', 'r') as f:
+    for line in f:
+        sample = json.loads(line)
+        print(f"Issue: {sample['title']}")
+        print(f"Language: {sample['language']}")
+        print(f"Organization: {sample['org']}")
+        print("---")
+```
+
+Or use with HuggingFace datasets:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("xinshuo/test_jsonl", data_files="dataset_json_dumps.jsonl")
+```
+