738d9d543e
python-redmine exposes as a context manager, while the
actual requests.Session lives in . Mounting the
retry adapter on the wrong object caused:
'function' object has no attribute 'mount'
on startup. Update the related test to mock the real session.
111 lines
4.0 KiB
Python
111 lines
4.0 KiB
Python
from typing import Any, Dict, List, Optional, Tuple
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import requests
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from redminelib import Redmine
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from redminelib.resources import Issue
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from urllib3.util.retry import Retry
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from .config import Config
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# Таймаут на один HTTP-запрос к Redmine (секунды).
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REQUEST_TIMEOUT = 30
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# Размер чанка для запроса задач по issue_id, чтобы не превышать лимит длины URL (#21).
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ISSUE_ID_CHUNK_SIZE = 100
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def _get_redmine_auth_kwargs() -> Dict[str, Any]:
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"""Return Redmine auth kwargs. API key has priority over legacy password auth."""
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api_key = Config.get_redmine_api_key()
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if api_key:
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return {"key": api_key}
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return {
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"username": Config.get_redmine_user(),
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"password": Config.get_redmine_password(),
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}
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def _make_retry_adapter() -> requests.adapters.HTTPAdapter:
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"""Создаёт HTTPAdapter с retry для временных ошибок (#24)."""
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retry = Retry(
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total=3,
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backoff_factor=0.5,
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status_forcelist=[429, 500, 502, 503, 504],
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allowed_methods=["GET", "HEAD", "OPTIONS"],
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)
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return requests.adapters.HTTPAdapter(max_retries=retry)
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def _create_redmine() -> Redmine:
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"""Создаёт Redmine-клиент с таймаутом и retry-адаптером (#24)."""
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redmine = Redmine(
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Config.get_redmine_url(),
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**_get_redmine_auth_kwargs(),
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requests={
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"verify": Config.get_redmine_verify(),
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"timeout": REQUEST_TIMEOUT,
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},
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)
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# Монтируем retry-адаптер на сессию для автоматических повторов.
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# В python-redmine сессия живёт в engine, а redmine.session — контекстный менеджер.
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retry_adapter = _make_retry_adapter()
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redmine.engine.session.mount("https://", retry_adapter)
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redmine.engine.session.mount("http://", retry_adapter)
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return redmine
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def _fetch_issues_chunked(redmine: Redmine, issue_ids: List[int]) -> List[Issue]:
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"""Загружает задачи чанками, чтобы не превышать лимит длины URL (#21)."""
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all_issues: List[Issue] = []
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for i in range(0, len(issue_ids), ISSUE_ID_CHUNK_SIZE):
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chunk = issue_ids[i : i + ISSUE_ID_CHUNK_SIZE]
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issue_list_str = ",".join(str(x) for x in chunk)
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issues = redmine.issue.filter(issue_id=issue_list_str, status_id="*", sort="project:asc")
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all_issues.extend(issues)
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return all_issues
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def fetch_issues_with_spent_time(
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from_date: str, to_date: str
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) -> Optional[List[Tuple[Issue, float]]]:
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"""
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Fetch unique issues linked to time entries of the current user in given date range,
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along with total spent hours per issue.
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Returns list of (issue, total_hours) tuples.
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"""
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redmine = _create_redmine()
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current_user = redmine.user.get("current")
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time_entries = redmine.time_entry.filter(
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user_id=current_user.id, from_date=from_date, to_date=to_date
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)
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# Агрегируем часы по issue.id
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spent_time: Dict[int, float] = {}
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issue_ids = set()
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for entry in time_entries:
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if hasattr(entry, "issue") and entry.issue and hasattr(entry, "hours"):
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iid = entry.issue.id
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issue_ids.add(iid)
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spent_time[iid] = spent_time.get(iid, 0.0) + float(entry.hours)
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if not issue_ids:
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return None
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# Загружаем полные объекты задач чанками (#21)
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sorted_ids = sorted(issue_ids)
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issues = _fetch_issues_chunked(redmine, sorted_ids)
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# Сопоставляем задачи с суммарным временем.
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# Сортировка выполняется в report_builder.build_grouped_report,
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# здесь оставляем порядок API как есть.
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result = []
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for issue in issues:
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total_hours = spent_time.get(issue.id, 0.0)
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result.append((issue, total_hours))
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return result
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