code-execution

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Chinese

Code Execution

代码执行

Execute Python locally with API access. 90-99% token savings for bulk operations.

通过API访问在本地执行Python代码。批量操作可节省90-99%的token。

When to Use

使用场景

Bulk operations (10+ files)
Complex multi-step workflows
Iterative processing across many files
User mentions efficiency/performance

批量操作（10个及以上文件）
复杂多步骤工作流
跨多个文件的迭代处理
用户提及效率/性能

How to Use

使用方法

Use direct Python imports in Claude Code:

python

from execution_runtime import fs, code, transform, git

在Claude Code中直接使用Python导入：

python

from execution_runtime import fs, code, transform, git

Code analysis (metadata only!)

functions = code.find_functions('app.py', pattern='handle_.*')

File operations

code_block = fs.copy_lines('source.py', 10, 20) fs.paste_code('target.py', 50, code_block)

Bulk transformations

result = transform.rename_identifier('.', 'oldName', 'newName', '**/*.py')

Git operations

git.git_add(['.']) git.git_commit('feat: refactor code')


**If not installed:** Run `~/.claude/plugins/marketplaces/mhattingpete-claude-skills/execution-runtime/setup.sh`

git.git_add(['.']) git.git_commit('feat: refactor code')


**若未安装：** 运行 `~/.claude/plugins/marketplaces/mhattingpete-claude-skills/execution-runtime/setup.sh`

Available APIs

可用API

Filesystem (
```
fs
```
): copy_lines, paste_code, search_replace, batch_copy
Code Analysis (
```
code
```
): find_functions, find_classes, analyze_dependencies - returns METADATA only!
Transformations (
```
transform
```
): rename_identifier, remove_debug_statements, batch_refactor
Git (
```
git
```
): git_status, git_add, git_commit, git_push

文件系统 (
```
fs
```
)：copy_lines、paste_code、search_replace、batch_copy
代码分析 (
```
code
```
)：find_functions、find_classes、analyze_dependencies - 仅返回元数据！
代码转换 (
```
transform
```
)：rename_identifier、remove_debug_statements、batch_refactor
Git (
```
git
```
)：git_status、git_add、git_commit、git_push

Pattern

执行模式

Analyze locally (metadata only, not source)
Process locally (all operations in execution)
Return summary (not data!)

本地分析（仅元数据，不包含源代码）
本地处理（所有操作在执行环境中完成）
返回摘要（不返回数据！）

Examples

示例

Bulk refactor (50 files):

python

from execution_runtime import transform
result = transform.rename_identifier('.', 'oldName', 'newName', '**/*.py')

批量重构（50个文件）：

python

from execution_runtime import transform
result = transform.rename_identifier('.', 'oldName', 'newName', '**/*.py')

Returns: {'files_modified': 50, 'total_replacements': 247}


**Extract functions:**
```python
from execution_runtime import code, fs

functions = code.find_functions('app.py', pattern='.*_util$')  # Metadata only!
for func in functions:
    code_block = fs.copy_lines('app.py', func['start_line'], func['end_line'])
    fs.paste_code('utils.py', -1, code_block)

result = {'functions_moved': len(functions)}

Code audit (100 files):

python

from execution_runtime import code
from pathlib import Path

files = list(Path('.').glob('**/*.py'))
issues = []

for file in files:
    deps = code.analyze_dependencies(str(file))  # Metadata only!
    if deps.get('complexity', 0) > 15:
        issues.append({'file': str(file), 'complexity': deps['complexity']})

result = {'files_audited': len(files), 'high_complexity': len(issues)}


**提取函数：**
```python
from execution_runtime import code, fs

functions = code.find_functions('app.py', pattern='.*_util$')  # Metadata only!
for func in functions:
    code_block = fs.copy_lines('app.py', func['start_line'], func['end_line'])
    fs.paste_code('utils.py', -1, code_block)

result = {'functions_moved': len(functions)}

代码审计（100个文件）：

python

from execution_runtime import code
from pathlib import Path

files = list(Path('.').glob('**/*.py'))
issues = []

for file in files:
    deps = code.analyze_dependencies(str(file))  # Metadata only!
    if deps.get('complexity', 0) > 15:
        issues.append({'file': str(file), 'complexity': deps['complexity']})

result = {'files_audited': len(files), 'high_complexity': len(issues)}

Best Practices

最佳实践

✅ Return summaries, not data ✅ Use code_analysis (returns metadata, not source) ✅ Batch operations ✅ Handle errors, return error count

❌ Don't return all code to context ❌ Don't read full source when you need metadata ❌ Don't process files one by one

✅ 返回摘要，而非数据 ✅ 使用code_analysis（返回元数据，而非源代码） ✅ 批量操作 ✅ 处理错误，返回错误数量

❌ 不要将所有代码返回到上下文 ❌ 当仅需元数据时不要读取完整源代码 ❌ 不要逐个处理文件

Token Savings

Token节省情况

Files	Traditional	Execution	Savings
10	5K tokens	500	90%
50	25K tokens	600	97.6%
100	150K tokens	1K	99.3%

文件数量	传统方式	本地执行方式	节省比例
10	5K tokens	500	90%
50	25K tokens	600	97.6%
100	150K tokens	1K	99.3%