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A simple CLI tool for validating and formatting JSON data.

Project description

🐍 The jsoncons Package 🐛❇️🐉

🚙🦖 COBOL-to-JSON CLI Utility in Python 🦕🐍

License: MIT Python Version PyPI version

The jsoncons package is designed to provide a basic command-line interface for handling JSON data. This can be useful for simple scripting or interoperability tasks (e.g., having a COBOL program generate a text file that this tool converts to JSON, or vice versa). COBOL-to-JSON parsing features were added in v1.0.0 and will be extended in future versions of jsoncons.

Installation:

pip install jsoncons

Basic Usage for Pretty-Print JSON:

  • Create Input File If Necessary: In your project directory, verify there is a file named input.json with the following content:

    {"key":"value", "items":[1,2]}
    
  • Validate & Pretty-print JSON: Read from stdin, write to stdout. (Linux Command)

    echo '{"key":"value", "items":[1,2]}' | jsoncons encode
    

    Windows Powershell Command: Read from stdin, write to stdout.

    echo {"\"key\"":"\"value\"", "\"items\"":[1,2]} | jsoncons encode
    
  • Validate & Pretty-print JSON from file to file: (Tested on Windows 10)

    jsoncons encode input.json output_pretty.json
    
  • (The decode command might be an alias or offer slightly different formatting if needed)

Tested Release jsonconsv1.0.4

Bug Fixed: f-string Issue in COBOL-to-JSON function

  • Jupyter Notebook Tutorial
  • COBOL-to-JSON function tested in 3.11.1,3.11.2, 3.12.1
  • Compatibility expected with Python v3.8>=

Features In Development for v1.1.0

  • Improved FP COBOL-to-JSON functionality
  • Template Python Function using jsoncons

**Roadmap to v2.0.0

  • Integration with IBM zOS

🤝 Contributing 🖥️

Contributions are welcome! If you find errors, have suggestions for improvements, or want to add more examples, please feel free to:

  1. Open an issue to discuss the change.
  2. Fork the repository.
  3. Create a new branch (git checkout -b feature/your-feature-name).
  4. Make your changes and commit them (git commit -m 'Add some feature').
  5. Push to the branch (git push origin feature/your-feature-name).
  6. Open a Pull Request.

📝 License ⚖️

This project is licensed under the MIT License - see the LICENSE file for details.


🧪 Unit Test Explanation For jsoncons Package ✅

  1. Imports: Imports necessary modules like unittest, sys (for patching argv/streams), io (for capturing streams), os, json, tempfile, shutil, and unittest.mock.patch. It also imports the cli module from the package.
  2. TestJsonConsCLI Class: Inherits from unittest.TestCase.
  3. setUp:
    • Creates a temporary directory using tempfile.mkdtemp() to isolate test files.
    • Defines paths for input, output, and invalid files within the temp directory.
    • Creates sample valid and invalid JSON strings and data structures.
    • Writes the sample valid and invalid JSON to the respective temporary files.
  4. tearDown: Cleans up by removing the temporary directory and all its contents using shutil.rmtree().
  5. run_cli Helper:
    • Takes a list of arguments (args_list) and optional stdin_data.
    • Prepends the script name ('serial-json') to the arguments list as sys.argv[0].
    • Uses unittest.mock.patch as a context manager to temporarily replace sys.argv, sys.stdout, and sys.stderr with test-controlled objects (io.StringIO for streams).
    • If stdin_data is provided, sys.stdin is also patched.
    • Calls the actual cli.main() function within the patched context.
    • Catches SystemExit (which sys.exit() raises) to get the exit code.
    • Returns the captured stdout string, stderr string, and the exit code.
  6. Test Methods (test_...):
    • Each method tests a specific scenario (stdin/stdout, file I/O, options, errors).
    • They call run_cli with appropriate arguments and/or stdin data.
    • They use self.assertEqual, self.assertNotEqual, self.assertTrue, self.assertIn, etc., to verify:
      • The exit code (0 for success, non-zero for errors).
      • The content of captured stderr (should be empty on success, contain error messages on failure).
      • The content of captured stdout (when output is expected there).
      • The existence and content of output files (when file output is expected).
  7. if __name__ == '__main__':: Allows running the tests directly using python -m unittest tests.test_cli or python tests/test_cli.py.

⛰️ Extending jsoncons to COBOL 👀

How COBOL could interact:

A COBOL program could:

  1. Write data to a temporary text file (e.g., input.txt).
  2. Use CALL 'SYSTEM' (or equivalent OS call) to execute the Python script:
    CALL 'SYSTEM' USING 'jsoncons input.txt output.json'.
    
  3. Read the resulting output.json file from COBOL.

Alternatively:

  1. COBOL generates simple key-value pairs or a structured text format.
  2. A more sophisticated jsoncons encode command could be written to parse this specific text format and produce JSON.
  3. A jsoncons decode command could parse JSON and output a simple text format readable by COBOL.

The provided CLI keeps things simple and standard, relying on JSON as the interchange format, which COBOL would interact with via file I/O and system calls.

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