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fix/457-ss
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dawn/375-1
| Author | SHA1 | Date | |
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| c4582188c8 |
270
deploy-crons.py
270
deploy-crons.py
@@ -1,154 +1,174 @@
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#!/usr/bin/env python3
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"""
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deploy-crons — normalize cron job schemas for consistent model field types.
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deploy-crons -- deploy cron jobs from YAML config and normalize jobs.json.
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This script ensures that the model field in jobs.json is always a dict when
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either model or provider is specified, preventing schema inconsistency.
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Two modes:
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--deploy Sync jobs from cron-jobs.yaml into jobs.json (create / update).
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--normalize Normalize model field types in existing jobs.json.
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The --deploy comparison checks prompt, schedule, model, and provider so
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that model/provider-only changes are never silently dropped.
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Usage:
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python deploy-crons.py [--dry-run] [--jobs-file PATH]
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python deploy-crons.py --deploy [--config PATH] [--jobs-file PATH] [--dry-run]
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python deploy-crons.py --normalize [--jobs-file PATH] [--dry-run]
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"""
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import argparse
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import json
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import sys
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import uuid
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from pathlib import Path
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from typing import Any, Dict, Optional
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from typing import Any, Dict, List, Optional
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try:
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import yaml
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HAS_YAML = True
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except ImportError:
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HAS_YAML = False
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def _flat_model(job: Dict[str, Any]) -> Optional[str]:
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m = job.get("model")
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if isinstance(m, dict):
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return m.get("model")
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return m
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def _flat_provider(job: Dict[str, Any]) -> Optional[str]:
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m = job.get("model")
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if isinstance(m, dict):
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return m.get("provider")
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return job.get("provider")
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def normalize_job(job: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Normalize a job dict to ensure consistent model field types.
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Before normalization:
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- If model AND provider: model = raw string, provider = raw string (inconsistent)
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- If only model: model = raw string
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- If only provider: provider = raw string at top level
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After normalization:
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- If model exists: model = {"model": "xxx"}
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- If provider exists: model = {"provider": "yyy"}
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- If both exist: model = {"model": "xxx", "provider": "yyy"}
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- If neither: model = None
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"""
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job = dict(job) # Create a copy to avoid modifying the original
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model = job.get("model")
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provider = job.get("provider")
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# Skip if already normalized (model is a dict)
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job = dict(job)
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model, provider = job.get("model"), job.get("provider")
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if isinstance(model, dict):
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return job
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# Build normalized model dict
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model_dict = {}
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if model is not None and isinstance(model, str):
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model_dict["model"] = model.strip()
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if provider is not None and isinstance(provider, str):
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model_dict["provider"] = provider.strip()
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# Set model field
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if model_dict:
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job["model"] = model_dict
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else:
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job["model"] = None
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# Remove top-level provider field if it was moved into model dict
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if provider is not None and "provider" in model_dict:
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# Keep provider field for backward compatibility but mark it as deprecated
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# This allows existing code that reads job["provider"] to continue working
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pass
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d = {}
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if isinstance(model, str): d["model"] = model.strip()
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if isinstance(provider, str): d["provider"] = provider.strip()
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job["model"] = d if d else None
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return job
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def normalize_jobs_file(jobs_file: Path, dry_run: bool = False) -> int:
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"""
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Normalize all jobs in a jobs.json file.
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Returns the number of jobs that were modified.
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"""
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if not jobs_file.exists():
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print(f"Error: Jobs file not found: {jobs_file}", file=sys.stderr)
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return 1
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def _jobs_changed(cur: Dict[str, Any], desired: Dict[str, Any]) -> bool:
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if cur.get("prompt") != desired.get("prompt"): return True
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if cur.get("schedule") != desired.get("schedule"): return True
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if _flat_model(cur) != _flat_model(desired): return True
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if _flat_provider(cur) != _flat_provider(desired): return True
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return False
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def _parse_schedule(schedule: str) -> Dict[str, Any]:
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try:
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with open(jobs_file, 'r', encoding='utf-8') as f:
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from cron.jobs import parse_schedule
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return parse_schedule(schedule)
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except ImportError:
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pass
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schedule = schedule.strip()
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if schedule.startswith("every "):
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dur = schedule[6:].strip()
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minutes = int(dur[:-1]) * {"m": 1, "h": 60, "d": 1440}.get(dur[-1], 1)
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return {"kind": "interval", "minutes": minutes, "display": f"every {minutes}m"}
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return {"kind": "cron", "expr": schedule, "display": schedule}
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def deploy_from_yaml(config_path: Path, jobs_file: Path, dry_run: bool = False) -> int:
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if not HAS_YAML:
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print("Error: PyYAML required. pip install pyyaml", file=sys.stderr); return 1
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if not config_path.exists():
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print(f"Error: {config_path}", file=sys.stderr); return 1
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with open(config_path, "r", encoding="utf-8") as f:
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yaml_jobs = (yaml.safe_load(f) or {}).get("jobs", [])
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if jobs_file.exists():
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with open(jobs_file, "r", encoding="utf-8") as f:
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data = json.load(f)
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except json.JSONDecodeError as e:
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print(f"Error: Invalid JSON in {jobs_file}: {e}", file=sys.stderr)
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return 1
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jobs = data.get("jobs", [])
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if not jobs:
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print("No jobs found in file.")
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return 0
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modified_count = 0
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for i, job in enumerate(jobs):
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original_model = job.get("model")
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original_provider = job.get("provider")
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normalized_job = normalize_job(job)
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# Check if anything changed
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if (normalized_job.get("model") != original_model or
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normalized_job.get("provider") != original_provider):
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jobs[i] = normalized_job
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modified_count += 1
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job_id = job.get("id", "?")
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job_name = job.get("name", "(unnamed)")
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print(f"Normalized job {job_id} ({job_name}):")
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print(f" model: {original_model!r} -> {normalized_job.get('model')!r}")
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print(f" provider: {original_provider!r} -> {normalized_job.get('provider')!r}")
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if modified_count == 0:
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print("All jobs already have consistent model field types.")
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return 0
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else:
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data = {"jobs": [], "updated_at": None}
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existing = data.get("jobs", [])
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index = {}
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for i, j in enumerate(existing):
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key = f"{j.get('prompt','')}||{json.dumps(j.get('schedule',{}),sort_keys=True)}"
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index[key] = i
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created = updated = skipped = 0
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for spec in yaml_jobs:
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prompt, schedule_str = spec.get("prompt",""), spec.get("schedule","")
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name, model, provider = spec.get("name",""), spec.get("model"), spec.get("provider")
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skills = spec.get("skills", [])
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parsed = _parse_schedule(schedule_str)
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key = f"{prompt}||{json.dumps(parsed,sort_keys=True)}"
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desired = {"prompt":prompt,"schedule":parsed,
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"schedule_display":parsed.get("display",schedule_str),
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"model":model,"provider":provider,
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"skills":skills if isinstance(skills,list) else [skills] if skills else [],
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"name":name or prompt[:50].strip()}
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if key in index:
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idx = index[key]
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if _jobs_changed(existing[idx], desired):
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if dry_run:
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print(f" WOULD UPDATE: {existing[idx].get('id','?')} model: {_flat_model(existing[idx])!r} -> {model!r} provider: {_flat_provider(existing[idx])!r} -> {provider!r}")
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else:
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existing[idx].update(desired)
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updated += 1
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else:
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skipped += 1
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else:
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if dry_run:
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print(f" WOULD CREATE: ({name or prompt[:50]})")
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else:
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jid = uuid.uuid4().hex[:12]
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existing.append({"id":jid,"enabled":True,"state":"scheduled",
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"paused_at":None,"paused_reason":None,"created_at":None,
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"next_run_at":None,"last_run_at":None,"last_status":None,
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"last_error":None,"repeat":{"times":None,"completed":0},
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"deliver":"local","origin":None,"base_url":None,"script":None,**desired})
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created += 1
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if dry_run:
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print(f"DRY RUN: Would normalize {modified_count} jobs.")
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return 0
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# Write back to file
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print(f"DRY RUN: {created} create, {updated} update, {skipped} unchanged."); return 0
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data["jobs"] = existing
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jobs_file.parent.mkdir(parents=True, exist_ok=True)
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with open(jobs_file, "w", encoding="utf-8") as f:
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json.dump(data, f, indent=2, ensure_ascii=False)
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print(f"Deployed: {created} created, {updated} updated, {skipped} unchanged."); return 0
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def normalize_jobs_file(jobs_file: Path, dry_run: bool = False) -> int:
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if not jobs_file.exists():
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print(f"Error: {jobs_file}", file=sys.stderr); return 1
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with open(jobs_file, "r", encoding="utf-8") as f:
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data = json.load(f)
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jobs = data.get("jobs", [])
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if not jobs: print("No jobs."); return 0
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modified = 0
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for i, job in enumerate(jobs):
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om, op = job.get("model"), job.get("provider")
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n = normalize_job(job)
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if n.get("model") != om or n.get("provider") != op:
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jobs[i] = n; modified += 1
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print(f"Normalized {job.get('id','?')}: model {om!r} -> {n['model']!r} provider {op!r} -> {n['provider']!r}")
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if modified == 0: print("All consistent."); return 0
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if dry_run: print(f"DRY RUN: {modified}"); return 0
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data["jobs"] = jobs
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try:
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with open(jobs_file, 'w', encoding='utf-8') as f:
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json.dump(data, f, indent=2, ensure_ascii=False)
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print(f"Normalized {modified_count} jobs in {jobs_file}")
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return 0
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except Exception as e:
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print(f"Error writing to {jobs_file}: {e}", file=sys.stderr)
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return 1
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with open(jobs_file, "w", encoding="utf-8") as f:
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json.dump(data, f, indent=2, ensure_ascii=False)
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print(f"Normalized {modified} jobs."); return 0
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def main():
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parser = argparse.ArgumentParser(
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description="Normalize cron job schemas for consistent model field types."
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)
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parser.add_argument(
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"--dry-run",
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action="store_true",
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help="Show what would be changed without modifying the file."
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)
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parser.add_argument(
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"--jobs-file",
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type=Path,
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default=Path.home() / ".hermes" / "cron" / "jobs.json",
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help="Path to jobs.json file (default: ~/.hermes/cron/jobs.json)"
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)
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args = parser.parse_args()
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if args.dry_run:
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print("DRY RUN MODE — no changes will be made.")
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print()
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return normalize_jobs_file(args.jobs_file, args.dry_run)
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p = argparse.ArgumentParser(description="Deploy and normalize cron jobs.")
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g = p.add_mutually_exclusive_group(required=True)
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g.add_argument("--deploy", action="store_true")
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g.add_argument("--normalize", action="store_true")
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p.add_argument("--config", type=Path, default=Path.home()/".hermes"/"cron-jobs.yaml")
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p.add_argument("--jobs-file", type=Path, default=Path.home()/".hermes"/"cron"/"jobs.json")
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p.add_argument("--dry-run", action="store_true")
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a = p.parse_args()
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if a.dry_run: print("DRY RUN."); print()
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if a.deploy: return deploy_from_yaml(a.config, a.jobs_file, a.dry_run)
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else: return normalize_jobs_file(a.jobs_file, a.dry_run)
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if __name__ == "__main__":
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sys.exit(main())
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