Open tawada opened 2 months ago
Please be specific, showing the code before the change and the code after the proposed change
To enhance the error handling mechanisms in the services/github/github_utils.py
module for improved robustness and localization support, the following changes are proposed. These changes aim to mitigate the brittleness associated with error message changes and the limited localization support by incorporating exit code analysis and structured error output parsing.
exec_command
Function:def exec_command(repo: str,
command: list[str],
capture_output: bool = False) -> subprocess.CompletedProcess:
"""
Execute a shell command within the specified git repository path.
"""
repo_path = os.path.join(DEFAULT_PATH, repo)
try:
complete_process = subprocess.run(
command,
stdout=subprocess.PIPE if capture_output else None,
stderr=subprocess.PIPE if capture_output else None,
cwd=repo_path,
check=True,
)
return complete_process
except subprocess.CalledProcessError as err:
log(
f"Command {command} failed with error ({err.returncode}): {err}",
level="error",
)
exception, error_message = exceptions.parse_exception(err)
raise exception(error_message) from err
Exit Code Analysis: Analyze the exit codes and map them to predefined exceptions. This reduces the reliance on error message content.
Structured Output Parsing: This example assumes git commands have a structure that can be parsed more reliably than plain text errors (as an illustrative example; actual implementation will vary based on the output provided by the tools in use).
Forcing Locale for Subprocess: Force the locale of the subprocess to ensure error messages are in English, enabling reliable parsing.
import json
def exec_command(repo: str,
command: list[str],
capture_output: bool = False,
expected_exit_codes: list[int] = [0]) -> subprocess.CompletedProcess:
"""
Execute a shell command within the specified git repository path.
Force the locale to English for consistent error message parsing.
"""
command_with_locale = ['env', 'LC_ALL=en_US.UTF-8'] + command # Force English error messages
repo_path = os.path.join(DEFAULT_PATH, repo)
try:
complete_process = subprocess.run(
command_with_locale,
stdout=subprocess.PIPE if capture_output else None,
stderr=subprocess.PIPE if capture_output else None,
cwd=repo_path,
check=False, # Don't raise error immediately on non-zero exit
)
if complete_process.returncode in expected_exit_codes:
return complete_process
else:
# Attempt to parse structured error message if available
try:
err_data = json.loads(complete_process.stderr)
error_code = err_data.get('error_code', 'UNKNOWN_ERROR')
raise exceptions.ErrorFromCode(error_code) # Custom function to map error codes to exceptions
except json.JSONDecodeError:
# Fallback if output is not JSON-parsable
raise exceptions.CommandExecutionException(f"Command {command} failed with exit code {complete_process.returncode}")
except subprocess.CalledProcessError as err:
log(f"Command {command} failed: {err}", level="error")
raise # Re-raise enhanced exception
expected_exit_codes
parameter allows the caller to specify which exit codes are considered successful, enhancing the flexibility of command execution handling.env LC_ALL=en_US.UTF-8
in the command ensures that the subprocess's output will be in English, which eases the parsing of error messages.stderr
as JSON allows for robust and structured error handling when commands offer JSON formatted errors. It falls back to a generic command execution exception if the parsing fails, indicating non-JSON structured errors. Implementing these changes would enhance maintainability and robustness, especially concerning internationalization and evolving tool error messages.
The provided codebase for automating issue handling on GitHub is well-structured and covers a wide range of functionalities, including interaction with GitHub issues, automated code generation, logging, and robust argument parsing. However, upon a detailed review, one area that stands out for improvement concerns error handling, specifically in the context of the
services/github/github_utils.py
module.In the
exec_command
function within thegithub_utils.py
module, exceptions are caught, and specific exception classes are raised based on the error message contained within the subprocess'sCalledProcessError
. This mechanism relies heavily on the presence of certain keywords in the error message to map to predefined exceptions. This approach, while functional, has a couple of drawbacks:Brittleness to Error Message Changes: The current design assumes that certain keywords will always be present in error messages for specific types of failures. However, error messages could change over time due to updates in the tools being invoked (git, the shell, etc.). This could lead to the incorrect mapping of errors or potentially missing the detection of some errors entirely.
Limited Localization Support: Relying on the content of error messages makes this tool less effective in environments where tools might not output error messages in English. This limits the internationalization potential of the tool.
To address these concerns, a more robust error handling mechanism could be implemented. Instead of relying solely on the content of error messages, consider augmenting the system with the following strategies:
Exit Code Analysis: In addition to message analysis, consider the exit codes of subprocesses. Many tools provide different exit codes for different types of errors, which can offer a more stable basis for error categorization.
Structured Logging or Output Parsing: Where possible, configure tools to output errors in a more structured format (such as JSON) that includes error codes or other programmatically assessable indicators of the error type. This approach could provide a more reliable way to determine the nature of an error.
Enhanced Localization Support: For tools that support it, force the locale to a known state (such as English) for the execution environment of subprocesses when parsing output or error messages. Alternatively, rely more on error codes or structured outputs that are less susceptible to changes across locales.
Implementing these suggestions will lead to more resilient and maintainable error handling, ultimately enhancing the robustness of the tool in handling a wider variety of error conditions and operational environments.