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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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

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

설치 방법 보기

이럴 때 유용합니다

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

포함된 파일(2)

  • SKILL.md3.6 KB
  • .skill_id38 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

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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