Coverage for melissa/scheduler/dummy.py: 90%

1#!/usr/bin/python3 

2 

3# Copyright (c) 2021-2022, Institut National de Recherche en Informatique et en Automatique (Inria) 

4# All rights reserved. 

5# 

6# Redistribution and use in source and binary forms, with or without 

7# modification, are permitted provided that the following conditions are met: 

8# 

9# * Redistributions of source code must retain the above copyright notice, this 

10# list of conditions and the following disclaimer. 

11# 

12# * Redistributions in binary form must reproduce the above copyright notice, 

13# this list of conditions and the following disclaimer in the documentation 

14# and/or other materials provided with the distribution. 

15# 

16# * Neither the name of the copyright holder nor the names of its 

17# contributors may be used to endorse or promote products derived from 

18# this software without specific prior written permission. 

19# 

20# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 

21# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 

22# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 

23# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE 

24# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL 

25# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR 

26# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 

27# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, 

28# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 

29# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 

30 

31from typing import List, Tuple, Union 

32 

33from melissa.utility.process import ArgumentList, Environment, Process 

34 

35from .job import Job, State 

36from .scheduler import DirectScheduler, Options 

37 

38 

39class DummyJob(Job): 

40 def __init__(self, jid: Union[str, int]) -> None: 

41 super().__init__() 

42 self._id = jid 

43 self._state = State.WAITING 

44 

45 def id(self) -> Union[str, int]: 

46 return self._id 

47 

48 def unique_id(self) -> Union[str, int]: 

49 return self._id 

50 

51 def state(self) -> State: 

52 return self._state 

53 

54 def __repr__(self) -> str: 

55 r = f"DummyJob(id={self.id()},state={str(self.state())})" 

56 return r 

57 

58 def set_state(self, new_state: State) -> None: 

59 self._state = new_state 

60 

61 

62class DummyScheduler(DirectScheduler[DummyJob]): 

63 """ 

64 This class implements a scheduler that never runs the submitted jobs. 

65 """ 

66 

67 @classmethod 

68 def _name_impl(cls) -> str: 

69 return "dummy" 

70 

71 @classmethod 

72 def _is_available_impl(cls) -> Tuple[bool, Union[str, Tuple[str, str]]]: 

73 return True, ("\0", "1.0") 

74 

75 def _submit_job_impl( 

76 self, 

77 commands: List[ArgumentList], 

78 env: Environment, 

79 options: Options, 

80 name: str, 

81 unique_id: int, 

82 ) -> Tuple[ArgumentList, Environment]: 

83 return ["/bin/true"], {} 

84 

85 def _make_job_impl(self, proc: "Process[str]", unique_id: int) -> DummyJob: 

86 proc.wait() 

87 return DummyJob(unique_id) 

88 

89 @classmethod 

90 def _update_jobs_impl(cls, jobs: List[DummyJob]) -> None: 

91 for j in jobs: 

92 if j.state() == State.WAITING: 

93 j.set_state(State.RUNNING) 

94 

95 @classmethod 

96 def _cancel_jobs_impl(cls, jobs: List[DummyJob]) -> None: 

97 for j in jobs: 

98 j.set_state(State.FAILED)