Update README.md

README.md

@@ -90,9 +90,11 @@ configs:
 ---
 
 # Overview
+We are extremely delighted to release Multi-SWE-Bench.
+Multi-SWE-Bench aims to build a multi-language benchmark dataset containing real software engineering scenarios for evaluating the ability of LLM to solve real software engineering problems. 
+The dataset supports multiple languages, currently including C, C++, Java, Javascript, Typescript, Rust, Go.
 
-# Dataset 
-## Data Instances Structure
+# Data Instances Structure
 An example of a Multi-SWE-bench datum is as follows:
 ```
 org: (str) - Organization name identifier from Github.
@@ -116,4 +118,98 @@ fix_patch_result: (dict) - The result after all the patches were applied.
 instance_id: (str) - A formatted instance identifier, usually as org__repo_PR-number.
 ```
 
-## Usage
+# Usage
+Because huggingface's dataset library does not support complex nested structures, 
+there are nested structures within these fields that have been serialized in the original dataset（huggingface）, 
+and you'll have to deserialize these if you want to use this dataset.
+```python
+SERIALIZATION_FIELDS = [
+    'base', 'fixed tests', 'p2p_tests', 'f2p_tests',
+    's2p_tests', 'n2p_tests', 'run_result',
+    'test_patch_result', 'fix_patch_result'
+]
+```
+
+## sample
+```python
+from datasets import load_dataset, config
+import pandas as pd
+import os
+import json
+
+# Constant definitions
+# There are nested structures within these fields, which were serialized in the original dataset, and now these need to be deserialized
+SERIALIZATION_FIELDS = [
+    'base', 'fixed tests', 'p2p_tests', 'f2p_tests',
+    's2p_tests', 'n2p_tests', 'run_result',
+    'test_patch_result', 'fix_patch_result'
+]
+CACHE_DIR = 'D:/huggingface_cache'
+
+def safe_deserialize(value):
+    """Safely deserialize a JSON string"""
+    try:
+        if value in (None, ''):
+            return None
+        return json.loads(value)
+    except (TypeError, json.JSONDecodeError) as e:
+        print(f"Deserialization failed: {str(e)}")
+        return value
+
+def load_hf_dataset():
+    """Load a HuggingFace dataset"""
+    os.environ['HF_HOME'] = CACHE_DIR
+    config.HF_DATASETS_CACHE = CACHE_DIR
+    return load_dataset("Hagon/test2", split='cpp')
+
+def analyze_dataset_structure(dataset):
+    """Analyze and print the dataset structure"""
+    print(f"Dataset size: {len(dataset)}")
+    print("\nDataset structure analysis: " + "-" * 50)
+    print("Field names and types:")
+    for name, dtype in dataset.features.items():
+        print(f"  {name}: {str(dtype)}")
+
+def print_data_types(dataset, sample_count=3):
+    """Print the data types of sample data"""
+    print(f"\nData types of the first {sample_count} samples:")
+    for i in range(min(sample_count, len(dataset))):
+        print(f"\nSample {i}:")
+        for key, value in dataset[i].items():
+            print(f"  {key}: {type(value).__name__} ({len(str(value))} chars)")
+
+def analyze_serialization(dataset, sample_count=3):
+    """Analyze the deserialization results of fields"""
+    print("\nDeserialization result analysis: " + "-" * 50)
+    for i in range(min(sample_count, len(dataset))):
+        print(f"\nSample {i}:")
+        item = dataset[i]
+        for key in SERIALIZATION_FIELDS:
+            safe_key = key.replace(' ', '_')
+            raw_value = item.get(safe_key)
+            deserialized = safe_deserialize(raw_value)
+            
+            print(f"Field [{key}]:")
+            print(f"  Original type: {type(raw_value).__name__}")
+            print(f"  Deserialized type: {type(deserialized).__name__ if deserialized else 'None'}")
+            
+            if isinstance(deserialized, dict):
+                sample = dict(list(deserialized.items())[:2])
+                print(f"  Sample content: {str(sample)[:200]}...")
+            elif deserialized:
+                print(f"  Content preview: {str(deserialized)[:200]}...")
+            else:
+                print("  Empty/Invalid data")
+
+def main():
+    """Main function entry"""
+    dataset = load_hf_dataset()
+    # analyze_dataset_structure(dataset)
+    # print_data_types(dataset)
+    analyze_serialization(dataset)
+
+if __name__ == "__main__":
+    main()
+
+```
+