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.
/plugin marketplace add wshobson/agents
/plugin install python-development@claude-code-workflowsWhat 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-workflowsThis installs the whole python-development plugin with all its skills
2Skills CLI (Vercel)
npx skills add wshobson/agents --skill python-resource-management -a claude-code3Manually: put the files in place
~/.claude/skills/python-resource-management/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/python-resource-management/
1Skills CLI (Vercel)
npx skills add wshobson/agents --skill python-resource-management -a codex2Manually: put the files in place
.agents/skills/python-resource-management/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add wshobson/agents --skill python-resource-management -a cursor2Manually: put the files in place
.cursor/skills/python-resource-management/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install wshobson/agents python-resource-management2Manually: put the files in place
.github/skills/python-resource-management/SKILL.mdPlatform CLI
gemini skills install https://github.com/wshobson/agents --path plugins/python-development/skills/python-resource-managementManually: put the files in place
.devin/skills/python-resource-management/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set213
The whole set →Similar
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