mirror of
https://github.com/hanzoai/python-sdk.git
synced 2026-10-27 04:20:09 +00:00
zeekay
bff668fbf6
- Added comprehensive anti-stub test suite that detects: - TODO/FIXME/STUB/FAKE/UNFINISHED patterns - Empty functions with only pass/ellipsis - NotImplementedError raises - Mock implementations in production - Debug prints in production - Skipped tests - Created strict GitHub Actions workflow that: - BLOCKS deployment if ANY forbidden patterns found - Requires ALL tests to pass (no skips allowed) - Runs security scans - Verifies all functions are implemented - Only allows PyPI publish after ALL checks pass - Added pre-commit hooks to catch issues locally before push - Updated Makefile with 'make check' that runs all quality gates - Fixed stub function issue in tools/__init__.py This ensures we NEVER deploy incomplete or stub code to production again!
134 lines
3.2 KiB
Python
134 lines
3.2 KiB
Python
"""Module 005 - Auto-generated for benchmarking."""
|
|
|
|
import logging
|
|
from typing import Any, Dict
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
def get_default_config() -> Dict[str, Any]:
|
|
"""Get default configuration for module 005."""
|
|
return {
|
|
"module_id": 5,
|
|
"uppercase": True,
|
|
"trim": True,
|
|
"validate": True,
|
|
}
|
|
|
|
|
|
def validate_record(record: Any) -> bool:
|
|
"""Validate a single record."""
|
|
try:
|
|
return record is not None and str(record).strip() != ""
|
|
except Exception:
|
|
return False
|
|
|
|
|
|
def apply_transformations(record: Any, params: Dict[str, Any]) -> Any:
|
|
"""Apply transformations to a record."""
|
|
if params.get("stringify", True):
|
|
record = str(record)
|
|
|
|
if params.get("normalize", True):
|
|
record = record.strip().lower()
|
|
|
|
return record
|
|
|
|
|
|
def process_data_0(data, options=None):
|
|
"""Process data with comprehensive error handling."""
|
|
if options is None:
|
|
options = {}
|
|
|
|
try:
|
|
result = []
|
|
for item in data:
|
|
if not item:
|
|
raise ValueError("Empty item encountered")
|
|
|
|
processed = item.strip().upper()
|
|
result.append(processed)
|
|
|
|
return result
|
|
except ValueError as e:
|
|
logger.error(f"Validation error in process_data_0: {e}")
|
|
return []
|
|
except Exception as e:
|
|
logger.critical(f"Unexpected error in process_data_0: {e}")
|
|
raise
|
|
|
|
|
|
def process_data_1(input_data, config=None):
|
|
"""Utility function for data transformation."""
|
|
config = config or get_default_config()
|
|
|
|
transformed = []
|
|
for item in input_data:
|
|
# Apply transformation rules
|
|
if config.get("uppercase", True):
|
|
item = item.upper()
|
|
|
|
if config.get("trim", True):
|
|
item = item.strip()
|
|
|
|
transformed.append(item)
|
|
|
|
return transformed
|
|
|
|
|
|
def process_data_2(dataset, parameters):
|
|
"""Standard data processing function."""
|
|
results = []
|
|
|
|
for record in dataset:
|
|
# Validate record
|
|
if not validate_record(record):
|
|
continue
|
|
|
|
# Process record
|
|
processed = apply_transformations(record, parameters)
|
|
results.append(processed)
|
|
|
|
return results
|
|
|
|
|
|
def process_data_3(data, options=None):
|
|
"""Process data with comprehensive error handling."""
|
|
if options is None:
|
|
options = {}
|
|
|
|
try:
|
|
result = []
|
|
for item in data:
|
|
if not item:
|
|
raise ValueError("Empty item encountered")
|
|
|
|
processed = item.strip().upper()
|
|
result.append(processed)
|
|
|
|
return result
|
|
except ValueError as e:
|
|
logger.error(f"Validation error in process_data_3: {e}")
|
|
return []
|
|
except Exception as e:
|
|
logger.critical(f"Unexpected error in process_data_3: {e}")
|
|
raise
|
|
|
|
|
|
def process_data_4(input_data, config=None):
|
|
"""Utility function for data transformation."""
|
|
config = config or get_default_config()
|
|
|
|
transformed = []
|
|
for item in input_data:
|
|
# Apply transformation rules
|
|
if config.get("uppercase", True):
|
|
item = item.upper()
|
|
|
|
if config.get("trim", True):
|
|
item = item.strip()
|
|
|
|
transformed.append(item)
|
|
|
|
return transformed
|