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1"""Base TestBed Class""" 

2 

3import typing as t 

4import logging 

5from importlib import import_module 

6from datetime import datetime, timezone 

7from shutil import rmtree 

8from es_testbed.exceptions import ResultNotExpected 

9from es_testbed.defaults import NAMEMAPPER 

10from es_testbed.helpers.es_api import delete, get 

11from es_testbed.helpers.utils import prettystr, process_preset 

12from es_testbed._plan import PlanBuilder 

13from es_testbed.mgrs import ( 

14 ComponentMgr, 

15 DataStreamMgr, 

16 IlmMgr, 

17 IndexMgr, 

18 SnapshotMgr, 

19 TemplateMgr, 

20) 

21 

22if t.TYPE_CHECKING: 

23 from elasticsearch8 import Elasticsearch 

24 

25logger = logging.getLogger('es_testbed.TestBed') 

26 

27# pylint: disable=R0902,R0913,R0917 

28 

29# Preset Import 

30# This imports the preset directory which must include the following files: 

31# - A plan YAML file. 

32# - A buildlist YAML file. 

33# - A functions.py file (the actual python code), which must contain a 

34# function named doc_generator(). This function must accept all kwargs from 

35# the buildlist's options 

36# - A definitions.py file, which is a Python variable file that helps find 

37# the path to the module, etc., as well as import the plan, the buildlist, 

38# the mappings and settings, etc. This must at least include a get_plan() 

39# function that returns a dictionary of a plan. 

40# - A mappings.json file (contains the index mappings your docs need) 

41# - A settings.json file (contains the index settings) 

42# 

43# Any other files can be included to help your doc_generator function, e.g. 

44# Faker definitions and classes, etc. Once the preset module is imported, 

45# relative imports should work. 

46 

47 

48class TestBed: 

49 """TestBed Class""" 

50 

51 __test__ = False # Without this, this appears to be test class because of the name 

52 

53 def __init__( 

54 self, 

55 client: t.Optional['Elasticsearch'] = None, 

56 builtin: t.Optional[str] = None, 

57 path: t.Optional[str] = None, 

58 ref: t.Optional[str] = None, 

59 url: t.Optional[str] = None, 

60 scenario: t.Optional[str] = None, 

61 ): 

62 #: The plan settings 

63 self.settings = None 

64 

65 modpath, tmpdir = process_preset(builtin, path, ref, url) 

66 if modpath is None: 

67 msg = 'Must define a preset' 

68 logger.critical(msg) 

69 raise ValueError(msg) 

70 

71 try: 

72 preset = import_module(f'{modpath}.definitions') 

73 self.settings = preset.get_plan(scenario) 

74 except ImportError as err: 

75 logger.critical('Preset settings incomplete or incorrect') 

76 raise err 

77 

78 self.settings['modpath'] = modpath 

79 if scenario: 

80 self.settings['scenario'] = scenario 

81 if tmpdir: 

82 self.settings['tmpdir'] = tmpdir 

83 

84 #: The Elasticsearch client object 

85 self.client = client 

86 #: The test plan 

87 self.plan = None 

88 

89 # Set up for tracking 

90 #: The ILM entity manager 

91 self.ilmmgr = None 

92 #: The Component Template entity manager 

93 self.componentmgr = None 

94 #: The (index) Template entity manager 

95 self.templatemgr = None 

96 #: The Snapshot entity manager 

97 self.snapshotmgr = None 

98 #: The Index entity manager 

99 self.indexmgr = None 

100 #: The data_stream entity manager 

101 self.data_streammgr = None 

102 

103 def _erase(self, kind: str, lst: t.Sequence[str]) -> None: 

104 overall_success = True 

105 if not lst: 

106 logger.debug(f'{kind}: nothing to delete.') 

107 return True 

108 if kind == 'ilm': # ILM policies can't be batch deleted 

109 ilm = [self._while(kind, x) for x in lst] 

110 overall_success = False not in ilm # No False values == True 

111 else: 

112 overall_success = self._while(kind, ','.join(lst)) 

113 return overall_success 

114 

115 def _fodder_generator( 

116 self, 

117 ) -> t.Generator[str, t.Sequence[str], None]: 

118 """Method to delete everything matching our pattern(s)""" 

119 items = ['index', 'data_stream', 'snapshot', 'template', 'component', 'ilm'] 

120 for i in items: 

121 if i == 'snapshot' and self.plan.repository is None: 

122 logger.debug('No repository, no snapshots.') 

123 continue 

124 pattern = f'*{self.plan.prefix}-{NAMEMAPPER[i]}-{self.plan.uniq}*' 

125 entities = get(self.client, i, pattern, repository=self.plan.repository) 

126 yield (i, entities) 

127 

128 def _while(self, kind: str, item: str) -> bool: 

129 count = 1 

130 success = False 

131 exc = None 

132 while count < 4 and not success: 

133 try: 

134 success = delete( 

135 self.client, kind, item, repository=self.plan.repository 

136 ) 

137 break 

138 except ResultNotExpected as err: 

139 logger.debug(f'Tried deleting "{item}" {count} time(s)') 

140 exc = err 

141 count += 1 

142 if not success: 

143 logger.warning( 

144 f'Failed to delete "{item}" after {count - 1} tries. ' 

145 f'Final error: {exc}' 

146 ) 

147 return success 

148 

149 def get_ilm_polling(self) -> None: 

150 """ 

151 Get current ILM polling settings and store them in self.plan.polling_interval 

152 """ 

153 logger.info('Storing current ILM polling settings, if any...') 

154 try: 

155 res = dict(self.client.cluster.get_settings()) 

156 logger.debug(f'Cluster settings: {prettystr(res)}') 

157 except Exception as err: 

158 logger.critical('Unable to get persistent cluster settings') 

159 logger.critical('This could be permissions, or something larger.') 

160 logger.critical(f'Exception: {prettystr(err)}') 

161 logger.critical('Exiting.') 

162 raise err 

163 try: 

164 retval = res['persistent']['indices']['lifecycle']['poll_interval'] 

165 except KeyError: 

166 logger.debug( 

167 'No setting for indices.lifecycle.poll_interval. Must be default' 

168 ) 

169 retval = None # Must be an actual value to go into a DotMap 

170 if retval == '1s': 

171 msg = ( 

172 'ILM polling already set at 1s. A previous run most likely did not ' 

173 'tear down properly. Resetting to null after this run' 

174 ) 

175 logger.warning(msg) 

176 retval = None # Must be an actual value to go into a DotMap 

177 self.plan.ilm_polling_interval = retval 

178 logger.info(f'Stored ILM Polling Interval: {retval}') 

179 

180 def ilm_polling(self, interval: t.Union[str, None] = None) -> t.Dict: 

181 """Return persistent cluster settings to speed up ILM polling during testing""" 

182 return {'indices.lifecycle.poll_interval': interval} 

183 

184 def setup(self) -> None: 

185 """Setup the instance""" 

186 start = datetime.now(timezone.utc) 

187 # If we build self.plan here, then we can modify settings before setup() 

188 self.plan = PlanBuilder(settings=self.settings).plan 

189 self.get_ilm_polling() 

190 logger.info(f'Setting: {self.ilm_polling(interval="1s")}') 

191 self.client.cluster.put_settings(persistent=self.ilm_polling(interval='1s')) 

192 self.setup_entitymgrs() 

193 end = datetime.now(timezone.utc) 

194 logger.info(f'Testbed setup elapsed time: {(end - start).total_seconds()}') 

195 

196 def setup_entitymgrs(self) -> None: 

197 """ 

198 Setup each EntityMgr child class 

199 """ 

200 kw = {'client': self.client, 'plan': self.plan} 

201 

202 self.ilmmgr = IlmMgr(**kw) 

203 self.ilmmgr.setup() 

204 self.componentmgr = ComponentMgr(**kw) 

205 self.componentmgr.setup() 

206 self.templatemgr = TemplateMgr(**kw) 

207 self.templatemgr.setup() 

208 self.snapshotmgr = SnapshotMgr(**kw) 

209 self.snapshotmgr.setup() 

210 if self.plan.type == 'indices': 

211 self.indexmgr = IndexMgr(**kw, snapmgr=self.snapshotmgr) 

212 self.indexmgr.setup() 

213 if self.plan.type == 'data_stream': 

214 self.data_streammgr = DataStreamMgr(**kw, snapmgr=self.snapshotmgr) 

215 self.data_streammgr.setup() 

216 

217 def teardown(self) -> None: 

218 """Tear down anything we created""" 

219 start = datetime.now(timezone.utc) 

220 successful = True 

221 if self.plan.tmpdir: 

222 logger.debug(f'Removing tmpdir: {self.plan.tmpdir}') 

223 rmtree(self.plan.tmpdir) # Remove the tmpdir stored here 

224 for kind, list_of_kind in self._fodder_generator(): 

225 if not self._erase(kind, list_of_kind): 

226 successful = False 

227 persist = self.ilm_polling(interval=self.plan.ilm_polling_interval) 

228 logger.info( 

229 f'Restoring ILM polling to previous value: ' 

230 f'{self.plan.ilm_polling_interval}' 

231 ) 

232 self.client.cluster.put_settings(persistent=persist) 

233 end = datetime.now(timezone.utc) 

234 logger.info(f'Testbed teardown elapsed time: {(end - start).total_seconds()}') 

235 if successful: 

236 logger.info('Cleanup successful') 

237 else: 

238 logger.error('Cleanup was unsuccessful/incomplete') 

239 self.plan.cleanup = successful