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9148e02679
* fix: coerce pipeline config types at load time using metadata definitions Pipeline configs stored in SQLAlchemy JSON columns can have values turned into strings after UI edits (e.g. "120" instead of 120), causing runtime arithmetic/logic errors. Add centralized type coercion in load_pipeline() that leverages existing metadata YAML type definitions (integer, number, float, boolean) to convert values before they reach downstream stages. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: address review - defensive getattr + add unit tests for config_coercion - Use getattr with defaults for pipeline_config_meta_* attributes to avoid AttributeError when MockApplication lacks these fields - Add 18 unit tests for config_coercion module covering all code paths Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add dynamic form stage tracking and snapshot management * fix: standardize string formatting in config coercion and improve logging messages --------- Co-authored-by: KPC <kpc@kpc.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: Junyan Qin <rockchinq@gmail.com>
106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
from __future__ import annotations
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import logging
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logger = logging.getLogger(__name__)
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# metadata type -> coercion function
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_COERCE_MAP = {
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'integer': lambda v: int(v),
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'number': lambda v: float(v),
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'float': lambda v: float(v),
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}
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def _coerce_bool(v):
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if isinstance(v, bool):
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return v
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if isinstance(v, str):
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if v.lower() == 'true':
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return True
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if v.lower() == 'false':
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return False
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raise ValueError(f'Cannot convert string {v!r} to bool')
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return bool(v)
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def _coerce_value(value, expected_type: str):
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"""Convert a single value to the expected type.
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Returns the converted value, or the original value if no conversion needed.
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"""
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if value is None:
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return value
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if expected_type == 'boolean':
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if isinstance(value, bool):
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return value
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return _coerce_bool(value)
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coerce_fn = _COERCE_MAP.get(expected_type)
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if coerce_fn is None:
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return value
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# Already the correct type
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if expected_type == 'integer' and isinstance(value, int) and not isinstance(value, bool):
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return value
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if expected_type in ('number', 'float') and isinstance(value, (int, float)) and not isinstance(value, bool):
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return float(value)
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return coerce_fn(value)
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def coerce_pipeline_config(
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config: dict,
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*metadata_list: dict,
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) -> None:
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"""Coerce pipeline config values according to metadata type definitions.
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Walks each metadata dict (trigger, safety, ai, output) and converts
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config values in-place so that strings coming from the JSON column are
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cast to their declared types (integer, number/float, boolean).
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Args:
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config: The pipeline config dict to modify in-place.
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*metadata_list: Metadata dicts loaded from the YAML templates.
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"""
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for meta in metadata_list:
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section_name = meta.get('name')
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if not section_name or section_name not in config:
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continue
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section = config[section_name]
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if not isinstance(section, dict):
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continue
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for stage_def in meta.get('stages', []):
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stage_name = stage_def.get('name')
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if not stage_name or stage_name not in section:
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continue
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stage_config = section[stage_name]
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if not isinstance(stage_config, dict):
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continue
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for field_def in stage_def.get('config', []):
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field_name = field_def.get('name')
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field_type = field_def.get('type')
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if not field_name or not field_type or field_name not in stage_config:
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continue
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old_value = stage_config[field_name]
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try:
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new_value = _coerce_value(old_value, field_type)
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if new_value is not old_value:
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stage_config[field_name] = new_value
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except (ValueError, TypeError) as e:
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logger.warning(
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'Failed to coerce config %s.%s.%s (%r) to %s: %s',
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section_name,
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stage_name,
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field_name,
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old_value,
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field_type,
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e,
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)
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