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run-shell-python-file-io

Read, write, and transform workspace files by running Python through run_shell when execute_code_sandbox cannot access them. The workflow covers explicit file paths, batch processing, error handling, and checking generated outputs.

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原文查看原文说明

Use run_shell with inline Python for reliable file I/O when execute_code_sandbox cannot access working directory files

查看安装方法

适用场景

  • Reading configuration files in the workspace
  • Transforming CSV or JSON data files
  • Processing multiple text files in a batch
  • Saving generated reports to files

包含的文件(2)

  • SKILL.md3.6 KB
  • .skill_id38 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Run Shell Python File I/O

When to Use This Skill

Use this technique when execute_code_sandbox cannot access files in your working directory, but you need to perform file operations (read, write, transform) as part of your task execution.

The Pattern

Instead of using execute_code_sandbox, run Python code directly through run_shell with explicit path handling. This provides reliable file I/O capabilities within the task workspace.

How to Apply

Step 1: Identify File Access Needs

Determine which files you need to read from or write to in the working directory.

Step 2: Write Inline Python via run_shell

Construct a Python script that handles your file operations and execute it through run_shell:

python3 -c "
import os

# Get the working directory
work_dir = os.getcwd()
print(f'Working directory: {work_dir}')

# Read a file
with open('input.txt', 'r') as f:
    content = f.read()

# Process the content
processed = content.upper()

# Write to output file
with open('output.txt', 'w') as f:
    f.write(processed)

print('File operation complete')
"

Step 3: Handle Complex Logic

For more complex operations, write a temporary Python script file first:

cat > /tmp/process.py << 'EOF'
import os
import json

work_dir = os.getcwd()

# Read input
with open('data.json', 'r') as f:
    data = json.load(f)

# Transform
result = {k: v * 2 for k, v in data.items()}

# Write output
with open('result.json', 'w') as f:
    json.dump(result, f, indent=2)

print(f'Processed {len(data)} items')
EOF

python3 /tmp/process.py

Step 4: Verify File Operations

After execution, verify the files were created/modified correctly:

ls -la
cat output.txt

Best Practices

  1. Use Absolute or Relative Paths Explicitly: Always specify file paths clearly; os.getcwd() helps confirm your working directory.

  2. Handle Errors Gracefully: Add try/except blocks to catch file I/O errors:

    try:
        with open('file.txt', 'r') as f:
            content = f.read()
    except FileNotFoundError:
        print('File not found')
    
  3. Use Here-Docs for Complex Scripts: For scripts longer than a few lines, use bash here-documents to avoid escaping issues.

  4. Clean Up Temporary Files: If you create temporary scripts, consider removing them after execution.

  5. Check Working Directory First: Print os.getcwd() to confirm you're operating in the expected directory.

Common Use Cases

  • Reading configuration files from the workspace
  • Writing generated reports or outputs
  • Transforming data files (CSV, JSON, XML)
  • Batch processing multiple files
  • Generating structured documents (PDFs, spreadsheets)

Example: Processing Multiple Files

python3 -c "
import os
import glob

work_dir = os.getcwd()
files = glob.glob('*.txt')

for f in files:
    with open(f, 'r') as file:
        content = file.read()
    # Process each file
    with open(f'processed_{f}', 'w') as out:
        out.write(content.strip().upper())

print(f'Processed {len(files)} files')
"

Troubleshooting

IssueSolution
File not foundCheck os.getcwd() output; use absolute paths if needed
Permission deniedEnsure the directory is writable; avoid protected system paths
Encoding errorsSpecify encoding explicitly: open('file.txt', 'r', encoding='utf-8')
Multi-line script issuesUse here-doc (<< 'EOF') instead of -c for complex scripts

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