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python-resource-management — Claude Code skill: setup

This skill guides Python resource handling with context managers, cleanup, and streaming state. Use it when code opens files, database connections, or other resources.

Install into Claude Code · Plugin marketplace All methods and platforms ↓
/plugin marketplace add wshobson/agents
/plugin install python-development@claude-code-workflows
Open on GitHub

What python-resource-management does

The skill covers deterministic cleanup with with, __enter__, and __exit__. Its examples include psycopg database connections, file handles, temporary files, and cleanup paths that still run after an exception. Exception suppression is treated as an explicit choice.

Async code uses __aenter__ and __aexit__, an asyncpg pool, and transactions with COMMIT and ROLLBACK. The material also shows @contextmanager, @asynccontextmanager, and streaming responses with accumulated state. Lists plus join are used for accumulation, while time-to-first-byte is tracked as a metric.

Install it when an agent works on Python code with files, databases, sockets, or streaming output. It is unnecessary for a small script that owns no long-lived resources.

What it helps with

  • close a database connection after an exception
  • build a sync or async context manager
  • remove temporary files after processing
  • roll back a transaction when a query fails
  • assemble a streaming response with accumulated state

Example prompts for the agent

  • Review `DatabaseConnection` and guarantee cleanup when the managed block raises.
  • Create an async context manager for an `asyncpg` pool and roll back the transaction on failure.
  • Refactor the streaming response to accumulate items in a list, use `join`, and track time-to-first-byte.

How to install python-resource-management

1Plugin marketplace

/plugin marketplace add wshobson/agents
/plugin install python-development@claude-code-workflows

This installs the whole python-development plugin with all its skills

2Skills CLI (Vercel)

npx skills add wshobson/agents --skill python-resource-management -a claude-code

3Manually: put the files in place

~/.claude/skills/python-resource-management/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/python-resource-management/

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Questions about python-resource-management

How do I install python-resource-management in Claude Code?

Run npx skills add wshobson/agents --skill python-resource-management -a claude-code. The skill is placed at ~/.claude/skills/python-resource-management/SKILL.md.

What does python-resource-management do?

It guides the agent through Python context managers, unconditional cleanup, exception handling, async resources, and streaming state.

Which libraries appear in the examples?

The examples use psycopg for database connections, asyncpg for an async pool, and structlog for logging.

Source text

SKILL.md · MIT
---
name: python-resource-management
description: 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.
---

# 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

@contextmanager
def 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 needed
db = 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)

# Usage
async 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, asynccontextmanager
import time
import structlog

logger = structlog.get_logger()

@contextmanager
def 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))

# Usage
with timed_block("data_processing"):
    process_large_dataset()

@asynccontextmanager
async 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

# Usage
async 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

© Seth Hobson · MIT · wshobson/agents

See also

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