MachineLearning2025/2311020116_CreditCardFraudDetection
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删除 check_environment.py

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骆华华 2026-01-15 22:31:42 +08:00
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check_environment.py
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"""
环境检查脚本
用于验证项目依赖和环境配置是否正确
"""
import sys
import importlib
from pathlib import Path
def check_python_version():
"""检查Python版本"""
print("=" * 60)
print("检查 Python 版本...")
print("=" * 60)
version = sys.version_info
print(f"当前 Python 版本: {version.major}.{version.minor}.{version.micro}")
if version.major == 3 and version.minor >= 10:
print("✓ Python 版本符合要求 (>= 3.10)")
return True
else:
print("✗ Python 版本不符合要求，需要 3.10 或更高版本")
return False
def check_dependencies():
"""检查必要的依赖包"""
print("\n" + "=" * 60)
print("检查依赖包...")
print("=" * 60)
required_packages = {
'numpy': 'numpy',
'polars': 'polars',
'sklearn': 'scikit-learn',
'imblearn': 'imbalanced-learn',
'matplotlib': 'matplotlib',
'seaborn': 'seaborn',
'joblib': 'joblib',
'pydantic': 'pydantic',
'streamlit': 'streamlit',
}
missing_packages = []
for module_name, package_name in required_packages.items():
try:
module = importlib.import_module(module_name)
version = getattr(module, '__version__', 'unknown')
print(f"✓ {package_name:20s} - 版本: {version}")
except ImportError:
print(f"✗ {package_name:20s} - 未安装")
missing_packages.append(package_name)
if missing_packages:
print(f"\n缺少 {len(missing_packages)} 个依赖包")
print(f"请运行: pip install {' '.join(missing_packages)}")
return False
else:
print("\n✓ 所有依赖包已正确安装")
return True
def check_data_files():
"""检查数据文件"""
print("\n" + "=" * 60)
print("检查数据文件...")
print("=" * 60)
data_dir = Path("data")
creditcard_csv = data_dir / "creditcard.csv"
if creditcard_csv.exists():
file_size = creditcard_csv.stat().st_size / (1024 * 1024) # MB
print(f"✓ data/creditcard.csv 存在 (大小: {file_size:.2f} MB)")
return True
else:
print("✗ data/creditcard.csv 不存在")
print("请从以下地址下载数据集:")
print("https://www.kaggle.com/mlg-ulb/creditcardfraud")
print("并将 creditcard.csv 文件放入 data/ 目录")
return False
def check_model_files():
"""检查模型文件"""
print("\n" + "=" * 60)
print("检查模型文件...")
print("=" * 60)
models_dir = Path("models")
required_models = [
"random_forest_model.joblib",
"logistic_regression_model.joblib",
"scaler.joblib"
]
missing_models = []
for model_file in required_models:
model_path = models_dir / model_file
if model_path.exists():
file_size = model_path.stat().st_size / 1024 # KB
print(f"✓ {model_file:35s} (大小: {file_size:.2f} KB)")
else:
print(f"✗ {model_file:35s} - 不存在")
missing_models.append(model_file)
if missing_models:
print(f"\n缺少 {len(missing_models)} 个模型文件")
print("请运行: python src/train.py 来训练模型")
return False
else:
print("\n✓ 所有模型文件已存在")
return True
def check_source_files():
"""检查源代码文件"""
print("\n" + "=" * 60)
print("检查源代码文件...")
print("=" * 60)
src_dir = Path("src")
required_files = [
"__init__.py",
"data.py",
"features.py",
"train.py",
"infer.py",
"agent_app.py",
"streamlit_app.py"
]
missing_files = []
for file_name in required_files:
file_path = src_dir / file_name
if file_path.exists():
print(f"✓ src/{file_name}")
else:
print(f"✗ src/{file_name} - 不存在")
missing_files.append(file_name)
if missing_files:
print(f"\n缺少 {len(missing_files)} 个源代码文件")
return False
else:
print("\n✓ 所有源代码文件完整")
return True
def run_all_checks():
"""运行所有检查"""
print("\n" + "=" * 60)
print("信用卡欺诈检测系统 - 环境检查")
print("=" * 60)
results = {
"Python 版本": check_python_version(),
"依赖包": check_dependencies(),
"数据文件": check_data_files(),
"模型文件": check_model_files(),
"源代码文件": check_source_files(),
}
print("\n" + "=" * 60)
print("检查结果汇总")
print("=" * 60)
for check_name, result in results.items():
status = "✓ 通过" if result else "✗ 失败"
print(f"{check_name:15s}: {status}")
all_passed = all(results.values())
print("\n" + "=" * 60)
if all_passed:
print("✓ 所有检查通过！您可以运行系统了")
print("\n运行命令:")
print(" python src/agent_app.py")
else:
print("✗ 部分检查未通过，请根据上述提示解决问题")
print("\n快速修复:")
if not results["依赖包"]:
print(" 1. 安装依赖: pip install -r requirements.txt")
if not results["数据文件"]:
print(" 2. 下载数据: 从 Kaggle 下载 creditcard.csv 到 data/ 目录")
if not results["模型文件"]:
print(" 3. 训练模型: python src/train.py")
print("=" * 60)
return all_passed
if __name__ == "__main__":
success = run_all_checks()
sys.exit(0 if success else 1)