Python Resource Management

作者 wshobson46891e7e60da无许可证收录于 2026年10月8日更新于 2026年10月8日

Python resource management with context managers, cleanup patterns, and streaming. Use when managing connections, file handles, implementing cleanup logic, or building streaming responses with accumulated state.

仅含说明Software Development
AI 生成的概览

指导 Python 开发者使用上下文管理器、清理模式和流式处理来确定性管理资源。

功能
该技能提供 Python 资源管理的指导，涵盖上下文管理器、enter/exit 与异步协议、无条件清理、异常处理以及带累积状态的流式处理。它给出基于类和基于装饰器的模式，包括数据库连接、连接池、文件句柄和事务，并附代码示例。它还包含最佳实践总结，并指向参考文件以了解高级模式。
适用场景
适用于编写或审查需要可靠释放数据库连接、文件句柄、网络套接字等资源的 Python 代码时。也适用于实现自定义或异步上下文管理器、嵌套清理，或带累积状态的流式响应时。
运行要求
不包含脚本，仅为说明性内容。示例涉及 psycopg、asyncpg、structlog 和 contextlib 等 Python 库，但技能本身除供代理阅读外无需其他条件。

Python Resource Management

Manage resources deterministically using context managers. Resources like database connections, file handles, and network sockets should be released reliably, even when exceptions occur.

When to Use This Skill

  • Managing database connections and connection pools
  • Working with file handles and I/O
  • Implementing custom context managers
  • Building streaming responses with state
  • Handling nested resource cleanup
  • Creating async context managers

Core Concepts

1. Context Managers

The with statement ensures resources are released automatically, even on exceptions.

2. Protocol Methods

__enter__/__exit__ for sync, __aenter__/__aexit__ for async resource management.

3. Unconditional Cleanup

__exit__ always runs, regardless of whether an exception occurred.

4. Exception Handling

Return True from __exit__ to suppress exceptions, False to propagate them.

Quick Start

python
from contextlib import contextmanager
@contextmanagerdef managed_resource():    resource = acquire_resource()    try:        yield resource    finally:        resource.cleanup()
with managed_resource() as r:    r.do_work()

Fundamental Patterns

Pattern 1: Class-Based Context Manager

Implement the context manager protocol for complex resources.

python
class DatabaseConnection:    """Database connection with automatic cleanup."""
    def __init__(self, dsn: str) -> None:        self._dsn = dsn        self._conn: Connection | None = None
    def connect(self) -> None:        """Establish database connection."""        self._conn = psycopg.connect(self._dsn)
    def close(self) -> None:        """Close connection if open."""        if self._conn is not None:            self._conn.close()            self._conn = None
    def __enter__(self) -> "DatabaseConnection":        """Enter context: connect and return self."""        self.connect()        return self
    def __exit__(        self,        exc_type: type[BaseException] | None,        exc_val: BaseException | None,        exc_tb: TracebackType | None,    ) -> None:        """Exit context: always close connection."""        self.close()
# Usage with context manager (preferred)with DatabaseConnection(dsn) as db:    result = db.execute(query)
# Manual management when neededdb = DatabaseConnection(dsn)db.connect()try:    result = db.execute(query)finally:    db.close()

Pattern 2: Async Context Manager

For async resources, implement the async protocol.

python
class AsyncDatabasePool:    """Async database connection pool."""
    def __init__(self, dsn: str, min_size: int = 1, max_size: int = 10) -> None:        self._dsn = dsn        self._min_size = min_size        self._max_size = max_size        self._pool: asyncpg.Pool | None = None
    async def __aenter__(self) -> "AsyncDatabasePool":        """Create connection pool."""        self._pool = await asyncpg.create_pool(            self._dsn,            min_size=self._min_size,            max_size=self._max_size,        )        return self
    async def __aexit__(        self,        exc_type: type[BaseException] | None,        exc_val: BaseException | None,        exc_tb: TracebackType | None,    ) -> None:        """Close all connections in pool."""        if self._pool is not None:            await self._pool.close()
    async def execute(self, query: str, *args) -> list[dict]:        """Execute query using pooled connection."""        async with self._pool.acquire() as conn:            return await conn.fetch(query, *args)
# Usageasync with AsyncDatabasePool(dsn) as pool:    users = await pool.execute("SELECT * FROM users WHERE active = $1", True)

Pattern 3: Using @contextmanager Decorator

Simplify context managers with the decorator for straightforward cases.

python
from contextlib import contextmanager, asynccontextmanagerimport timeimport structlog
logger = structlog.get_logger()
@contextmanagerdef timed_block(name: str):    """Time a block of code."""    start = time.perf_counter()    try:        yield    finally:        elapsed = time.perf_counter() - start        logger.info(f"{name} completed", duration_seconds=round(elapsed, 3))
# Usagewith timed_block("data_processing"):    process_large_dataset()
@asynccontextmanagerasync def database_transaction(conn: AsyncConnection):    """Manage database transaction."""    await conn.execute("BEGIN")    try:        yield conn        await conn.execute("COMMIT")    except Exception:        await conn.execute("ROLLBACK")        raise
# Usageasync with database_transaction(conn) as tx:    await tx.execute("INSERT INTO users ...")    await tx.execute("INSERT INTO audit_log ...")

Pattern 4: Unconditional Resource Release

Always clean up resources in __exit__, regardless of exceptions.

python
class FileProcessor:    """Process file with guaranteed cleanup."""
    def __init__(self, path: str) -> None:        self._path = path        self._file: IO | None = None        self._temp_files: list[Path] = []
    def __enter__(self) -> "FileProcessor":        self._file = open(self._path, "r")        return self
    def __exit__(        self,        exc_type: type[BaseException] | None,        exc_val: BaseException | None,        exc_tb: TracebackType | None,    ) -> None:        """Clean up all resources unconditionally."""        # Close main file        if self._file is not None:            self._file.close()
        # Clean up any temporary files        for temp_file in self._temp_files:            try:                temp_file.unlink()            except OSError:                pass  # Best effort cleanup
        # Return None/False to propagate any exception

Detailed worked examples and patterns

Detailed sections (starting with ## Advanced Patterns) live in references/details.md. Read that file when the navigation summary above is insufficient.

Best Practices Summary

  1. Always use context managers - For any resource that needs cleanup
  2. Clean up unconditionally - __exit__ runs even on exception
  3. Don't suppress unexpectedly - Return False unless suppression is intentional
  4. Use @contextmanager - For simple resource patterns
  5. Implement both protocols - Support with and manual management
  6. Use ExitStack - For dynamic numbers of resources
  7. Accumulate efficiently - List + join, not string concatenation
  8. Track metrics - Time-to-first-byte matters for streaming
  9. Document behavior - Especially exception suppression
  10. Test cleanup paths - Verify resources are released on errors

来源与署名

来源：wshobson/agents位于plugins/python-development/skills/python-resource-management提交46891e7

许可证： 无许可证

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