Atlas / Skills / wshobson / Python Resource Management

Python Resource ManagementSAFE

skills/wshobson/python-resource-management

Multi-harness agentic plugin marketplace for Claude Code, Codex, Cursor, OpenCode, GitHub Copilot, Google Antigravity, and Pi

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
—
License
MIT
Stars
40,124
01

Overview

Multi-harness agentic plugin marketplace for Claude Code, Codex, Cursor, OpenCode, GitHub Copilot, Google Antigravity, and Pi

Read from source at commit adb71e0b2512OBSERVED · 2026-10-01
02

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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 OSE
03

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (1)

LOWInventory / provenance · inv.symlink · CWE-1104
CLAUDE.md
CLAUDE.md
Why it matters. link not followed

Gates applied: no_behavioural_pass.

Audited 2026-10-01 · audit v0.4.1 · source sha adb71e0b2512full audit observations/trust-audit/skill/wshobson__python-resource-management.json · Report an issue / request a re-scan
04

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-01adb71e0b2512SAFEB89first audit
05

Questions

What does the Python Resource Management skill do?

Multi-harness agentic plugin marketplace for Claude Code, Codex, Cursor, OpenCode, GitHub Copilot, Google Antigravity, and Pi

Is Python Resource Management safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Python Resource Management access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

How current is this page?

The grade is for one exact copy of the source (adb71e0b2512), read on 2026-10-01. The repository is watched, and a new audit runs when it changes — this is the first audit.

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