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How to use _findFirst method in pyatom
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tensor_format_test.py
Source:tensor_format_test.py 
...93 self.assertEqual(match.start(), start_col)94 self.assertEqual(match.end(), end_col)95 element_index += 196 self.assertEqual(element_index, np.size(a))97 def _findFirst(self, lines, string):98 """Find first occurrence of a string in a list of strings."""99 for i, line in enumerate(lines):100 find_index = line.find(string)101 if find_index >= 0:102 return i, find_index103 def _extractBoldNumbers(self, out, start_line):104 """Extract all numbers that have the bold font attribute.105 Args:106 out: An instance of RichTextLines.107 start_line: 0-based index to start from.108 Returns:109 A list of floats.110 """111 floats = []112 for i in range(start_line, len(out.lines)):113 if i not in out.font_attr_segs:114 continue115 line_attrs = out.font_attr_segs[i]116 for begin, end, attr_value in line_attrs:117 if attr_value == "bold":118 floats.append(float(out.lines[i][begin:end]))119 return floats120 def testFormatZeroDimensionTensor(self):121 a = np.array(42, dtype=np.int32)122 out = tensor_format.format_tensor(a, "a")123 cli_test_utils.assert_lines_equal_ignoring_whitespace(124 self, ["Tensor \"a\":", ""], out.lines[:2])125 self.assertTrue(out.lines[2].startswith("array(42"))126 self._checkTensorMetadata(a, out.annotations)127 def testFormatTensorHighlightsTensorNameWithoutDebugOp(self):128 tensor_name = "a_tensor:0"129 a = np.zeros(2)130 out = tensor_format.format_tensor(131 a, tensor_name, np_printoptions={"linewidth": 40})132 self.assertEqual([(8, 8 + len(tensor_name), "bold")], out.font_attr_segs[0])133 def testFormatTensorHighlightsTensorNameWithDebugOp(self):134 tensor_name = "a_tensor:0"135 debug_op = "DebugIdentity"136 a = np.zeros(2)137 out = tensor_format.format_tensor(138 a, "%s:%s" % (tensor_name, debug_op), np_printoptions={"linewidth": 40})139 self.assertEqual([(8, 8 + len(tensor_name), "bold"),140 (8 + len(tensor_name) + 1,141 8 + len(tensor_name) + 1 + len(debug_op), "yellow")],142 out.font_attr_segs[0])143 def testFormatTensor1DNoEllipsis(self):144 a = np.zeros(20)145 out = tensor_format.format_tensor(146 a, "a", np_printoptions={"linewidth": 40})147 cli_test_utils.assert_lines_equal_ignoring_whitespace(148 self, ["Tensor \"a\":", ""], out.lines[:2])149 self.assertEqual(repr(a).split("\n"), out.lines[2:])150 self._checkTensorMetadata(a, out.annotations)151 # Check annotations for beginning indices of the lines.152 self._checkBeginIndicesAnnotations(out, a)153 def testFormatTensor2DNoEllipsisNoRowBreak(self):154 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])155 out = tensor_format.format_tensor(a, "a")156 cli_test_utils.assert_lines_equal_ignoring_whitespace(157 self, ["Tensor \"a\":", ""], out.lines[:2])158 self.assertEqual(repr(a).split("\n"), out.lines[2:])159 self._checkTensorMetadata(a, out.annotations)160 self._checkBeginIndicesAnnotations(out, a)161 def testFormatTensorSuppressingTensorName(self):162 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])163 out = tensor_format.format_tensor(a, None)164 self.assertEqual(repr(a).split("\n"), out.lines)165 self._checkTensorMetadata(a, out.annotations)166 self._checkBeginIndicesAnnotations(out, a)167 def testFormatTensorWithMetadata(self):168 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])169 out = tensor_format.format_tensor(a, "a", include_metadata=True)170 cli_test_utils.assert_lines_equal_ignoring_whitespace(171 self,172 ["Tensor \"a\":",173 " dtype: float64",174 " shape: (4, 4)",175 ""], out.lines[:4])176 self.assertEqual(repr(a).split("\n"), out.lines[4:])177 self._checkTensorMetadata(a, out.annotations)178 self._checkBeginIndicesAnnotations(out, a)179 def testFormatTensor2DNoEllipsisWithRowBreak(self):180 a = np.linspace(0.0, 1.0 - 1.0 / 40.0, 40).reshape([2, 20])181 out = tensor_format.format_tensor(182 a, "a", np_printoptions={"linewidth": 50})183 self.assertEqual(184 {"dtype": a.dtype, "shape": a.shape},185 out.annotations["tensor_metadata"])186 cli_test_utils.assert_lines_equal_ignoring_whitespace(187 self, ["Tensor \"a\":", ""], out.lines[:2])188 self.assertEqual(repr(a).split("\n"), out.lines[2:])189 self._checkTensorMetadata(a, out.annotations)190 # Check annotations for the beginning indices of the lines.191 self._checkBeginIndicesAnnotations(out, a)192 def testFormatTensor3DNoEllipsis(self):193 a = np.linspace(0.0, 1.0 - 1.0 / 24.0, 24).reshape([2, 3, 4])194 out = tensor_format.format_tensor(a, "a")195 cli_test_utils.assert_lines_equal_ignoring_whitespace(196 self, ["Tensor \"a\":", ""], out.lines[:2])197 self.assertEqual(repr(a).split("\n"), out.lines[2:])198 self._checkTensorMetadata(a, out.annotations)199 self._checkBeginIndicesAnnotations(out, a)200 def testFormatTensor3DNoEllipsisWithArgwhereHighlightWithMatches(self):201 a = np.linspace(0.0, 1.0 - 1.0 / 24.0, 24).reshape([2, 3, 4])202 lower_bound = 0.26203 upper_bound = 0.5204 def highlight_filter(x):205 return np.logical_and(x > lower_bound, x < upper_bound)206 highlight_options = tensor_format.HighlightOptions(207 highlight_filter, description="between 0.26 and 0.5")208 out = tensor_format.format_tensor(209 a, "a", highlight_options=highlight_options)210 cli_test_utils.assert_lines_equal_ignoring_whitespace(211 self,212 ["Tensor \"a\": "213 "Highlighted(between 0.26 and 0.5): 5 of 24 element(s) (20.83%)",214 ""],215 out.lines[:2])216 self.assertEqual(repr(a).split("\n"), out.lines[2:])217 self._checkTensorMetadata(a, out.annotations)218 # Check annotations for beginning indices of the lines.219 self._checkBeginIndicesAnnotations(out, a)220 self.assertAllClose(221 [0.29166667, 0.33333333, 0.375, 0.41666667, 0.45833333],222 self._extractBoldNumbers(out, 2))223 def testFormatTensor3DNoEllipsisWithArgwhereHighlightWithNoMatches(self):224 a = np.linspace(0.0, 1.0 - 1.0 / 24.0, 24).reshape([2, 3, 4])225 def highlight_filter(x):226 return x > 10.0227 highlight_options = tensor_format.HighlightOptions(highlight_filter)228 out = tensor_format.format_tensor(229 a, "a", highlight_options=highlight_options)230 cli_test_utils.assert_lines_equal_ignoring_whitespace(231 self,232 ["Tensor \"a\": Highlighted: 0 of 24 element(s) (0.00%)", ""],233 out.lines[:2])234 self.assertEqual(repr(a).split("\n"), out.lines[2:])235 self._checkTensorMetadata(a, out.annotations)236 self._checkBeginIndicesAnnotations(out, a)237 # Check font attribute segments for highlighted elements.238 for i in range(2, len(out.lines)):239 self.assertNotIn(i, out.font_attr_segs)240 def testFormatTensorWithEllipses(self):241 a = (np.arange(11 * 11 * 11) + 1000).reshape([11, 11, 11]).astype(np.int32)242 out = tensor_format.format_tensor(243 a, "a", False, np_printoptions={"threshold": 100, "edgeitems": 2})244 cli_test_utils.assert_lines_equal_ignoring_whitespace(245 self, ["Tensor \"a\":", ""], out.lines[:2])246 self.assertEqual(repr(a).split("\n"), out.lines[2:])247 self._checkTensorMetadata(a, out.annotations)248 # Check annotations for beginning indices of the lines.249 actual_row_0_0_0, _ = self._findFirst(out.lines, "1000")250 self.assertEqual({tensor_format.BEGIN_INDICES_KEY: [0, 0, 0]},251 out.annotations[actual_row_0_0_0])252 actual_row_0_1_0, _ = self._findFirst(out.lines, "1011")253 self.assertEqual({tensor_format.BEGIN_INDICES_KEY: [0, 1, 0]},254 out.annotations[actual_row_0_1_0])255 # Find the first line that is completely omitted.256 omitted_line = 2257 while not out.lines[omitted_line].strip().startswith("..."):258 omitted_line += 1259 self.assertEqual({tensor_format.OMITTED_INDICES_KEY: [0, 2, 0]},260 out.annotations[omitted_line])261 actual_row_10_10_0, _ = self._findFirst(out.lines, "2320")262 self.assertEqual({tensor_format.BEGIN_INDICES_KEY: [10, 10, 0]},263 out.annotations[actual_row_10_10_0])264 # Find the last line that is completely omitted.265 omitted_line = len(out.lines) - 1266 while not out.lines[omitted_line].strip().startswith("..."):267 omitted_line -= 1268 self.assertEqual({tensor_format.OMITTED_INDICES_KEY: [10, 2, 0]},269 out.annotations[omitted_line])270 def testFormatUninitializedTensor(self):271 tensor_proto = tensor_pb2.TensorProto(272 dtype=types_pb2.DataType.Value("DT_FLOAT"),273 tensor_shape=tensor_shape_pb2.TensorShapeProto(274 dim=[tensor_shape_pb2.TensorShapeProto.Dim(size=1)]))275 out = tensor_format.format_tensor(276 debug_data.InconvertibleTensorProto(tensor_proto, False), "a")277 self.assertEqual(["Tensor \"a\":", "", "Uninitialized tensor:"],278 out.lines[:3])279 self.assertEqual(str(tensor_proto).split("\n"), out.lines[3:])280 def testFormatResourceTypeTensor(self):281 tensor_proto = tensor_pb2.TensorProto(282 dtype=types_pb2.DataType.Value("DT_RESOURCE"),283 tensor_shape=tensor_shape_pb2.TensorShapeProto(284 dim=[tensor_shape_pb2.TensorShapeProto.Dim(size=1)]))285 out = tensor_format.format_tensor(286 debug_data.InconvertibleTensorProto(tensor_proto), "a")287 self.assertEqual(["Tensor \"a\":", ""], out.lines[:2])288 self.assertEqual(str(tensor_proto).split("\n"), out.lines[2:])289 def testLocateTensorElement1DNoEllipsis(self):290 a = np.zeros(20)291 out = tensor_format.format_tensor(292 a, "a", np_printoptions={"linewidth": 40})293 cli_test_utils.assert_lines_equal_ignoring_whitespace(294 self, ["Tensor \"a\":", ""], out.lines[:2])295 self.assertEqual(repr(a).split("\n"), out.lines[2:])296 self._checkTensorElementLocations(out, a)297 with self.assertRaisesRegexp(298 ValueError, "Indices exceed tensor dimensions"):299 tensor_format.locate_tensor_element(out, [20])300 with self.assertRaisesRegexp(301 ValueError, "Indices contain negative"):302 tensor_format.locate_tensor_element(out, [-1])303 with self.assertRaisesRegexp(304 ValueError, "Dimensions mismatch"):305 tensor_format.locate_tensor_element(out, [0, 0])306 def testLocateTensorElement1DNoEllipsisBatchMode(self):307 a = np.zeros(20)308 out = tensor_format.format_tensor(309 a, "a", np_printoptions={"linewidth": 40})310 cli_test_utils.assert_lines_equal_ignoring_whitespace(311 self, ["Tensor \"a\":", ""], out.lines[:2])312 self.assertEqual(repr(a).split("\n"), out.lines[2:])313 self._checkTensorElementLocations(out, a)314 def testBatchModeWithErrors(self):315 a = np.zeros(20)316 out = tensor_format.format_tensor(317 a, "a", np_printoptions={"linewidth": 40})318 cli_test_utils.assert_lines_equal_ignoring_whitespace(319 self, ["Tensor \"a\":", ""], out.lines[:2])320 self.assertEqual(repr(a).split("\n"), out.lines[2:])321 with self.assertRaisesRegexp(ValueError, "Dimensions mismatch"):322 tensor_format.locate_tensor_element(out, [[0, 0], [0]])323 with self.assertRaisesRegexp(ValueError,324 "Indices exceed tensor dimensions"):325 tensor_format.locate_tensor_element(out, [[0], [20]])326 with self.assertRaisesRegexp(ValueError,327 r"Indices contain negative value\(s\)"):328 tensor_format.locate_tensor_element(out, [[0], [-1]])329 with self.assertRaisesRegexp(330 ValueError, "Input indices sets are not in ascending order"):331 tensor_format.locate_tensor_element(out, [[5], [0]])332 def testLocateTensorElement1DTinyAndNanValues(self):333 a = np.ones([3, 3]) * 1e-8334 a[1, 0] = np.nan335 a[1, 2] = np.inf336 out = tensor_format.format_tensor(337 a, "a", np_printoptions={"linewidth": 100})338 cli_test_utils.assert_lines_equal_ignoring_whitespace(339 self, ["Tensor \"a\":", ""], out.lines[:2])340 self.assertEqual(repr(a).split("\n"), out.lines[2:])341 self._checkTensorElementLocations(out, a)342 def testLocateTensorElement2DNoEllipsis(self):343 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])344 out = tensor_format.format_tensor(a, "a")345 cli_test_utils.assert_lines_equal_ignoring_whitespace(346 self, ["Tensor \"a\":", ""], out.lines[:2])347 self.assertEqual(repr(a).split("\n"), out.lines[2:])348 self._checkTensorElementLocations(out, a)349 with self.assertRaisesRegexp(350 ValueError, "Indices exceed tensor dimensions"):351 tensor_format.locate_tensor_element(out, [1, 4])352 with self.assertRaisesRegexp(353 ValueError, "Indices contain negative"):354 tensor_format.locate_tensor_element(out, [-1, 2])355 with self.assertRaisesRegexp(356 ValueError, "Dimensions mismatch"):357 tensor_format.locate_tensor_element(out, [0])358 def testLocateTensorElement2DNoEllipsisWithNumericSummary(self):359 a = np.linspace(0.0, 1.0 - 1.0 / 16.0, 16).reshape([4, 4])360 out = tensor_format.format_tensor(a, "a", include_numeric_summary=True)361 cli_test_utils.assert_lines_equal_ignoring_whitespace(362 self,363 ["Tensor \"a\":",364 "",365 "Numeric summary:",366 "| 0 + | total |",367 "| 1 15 | 16 |",368 "| min max mean std |"],369 out.lines[:6])370 cli_test_utils.assert_array_lines_close(371 self, [0.0, 0.9375, 0.46875, 0.28811076429], out.lines[6:7])372 cli_test_utils.assert_array_lines_close(self, a, out.lines[8:])373 self._checkTensorElementLocations(out, a)374 with self.assertRaisesRegexp(375 ValueError, "Indices exceed tensor dimensions"):376 tensor_format.locate_tensor_element(out, [1, 4])377 with self.assertRaisesRegexp(378 ValueError, "Indices contain negative"):379 tensor_format.locate_tensor_element(out, [-1, 2])380 with self.assertRaisesRegexp(381 ValueError, "Dimensions mismatch"):382 tensor_format.locate_tensor_element(out, [0])383 def testLocateTensorElement3DWithEllipses(self):384 a = (np.arange(11 * 11 * 11) + 1000).reshape([11, 11, 11]).astype(np.int32)385 out = tensor_format.format_tensor(386 a, "a", False, np_printoptions={"threshold": 100, "edgeitems": 2})387 cli_test_utils.assert_lines_equal_ignoring_whitespace(388 self, ["Tensor \"a\":", ""], out.lines[:2])389 actual_row_0_0_0, actual_col_0_0_0 = self._findFirst(out.lines, "1000")390 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(391 out, [0, 0, 0])392 self.assertFalse(is_omitted)393 self.assertEqual(actual_row_0_0_0, row)394 self.assertEqual(actual_col_0_0_0, start_col)395 self.assertEqual(actual_col_0_0_0 + 4, end_col)396 actual_row_0_0_10, _ = self._findFirst(out.lines, "1010")397 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(398 out, [0, 0, 10])399 self.assertFalse(is_omitted)400 self.assertEqual(actual_row_0_0_10, row)401 self.assertIsNone(start_col) # Passes ellipsis.402 self.assertIsNone(end_col)403 actual_row_0_1_0, actual_col_0_1_0 = self._findFirst(out.lines, "1011")404 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(405 out, [0, 1, 0])406 self.assertFalse(is_omitted)407 self.assertEqual(actual_row_0_1_0, row)408 self.assertEqual(actual_col_0_1_0, start_col)409 self.assertEqual(actual_col_0_1_0 + 4, end_col)410 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(411 out, [0, 2, 0])412 self.assertTrue(is_omitted) # In omitted line.413 self.assertIsNone(start_col)414 self.assertIsNone(end_col)415 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(416 out, [0, 2, 10])417 self.assertTrue(is_omitted) # In omitted line.418 self.assertIsNone(start_col)419 self.assertIsNone(end_col)420 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(421 out, [0, 8, 10])422 self.assertTrue(is_omitted) # In omitted line.423 self.assertIsNone(start_col)424 self.assertIsNone(end_col)425 actual_row_0_10_1, actual_col_0_10_1 = self._findFirst(out.lines, "1111")426 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(427 out, [0, 10, 1])428 self.assertFalse(is_omitted)429 self.assertEqual(actual_row_0_10_1, row)430 self.assertEqual(actual_col_0_10_1, start_col)431 self.assertEqual(actual_col_0_10_1 + 4, end_col)432 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(433 out, [5, 1, 1])434 self.assertTrue(is_omitted) # In omitted line.435 self.assertIsNone(start_col)436 self.assertIsNone(end_col)437 actual_row_10_10_10, _ = self._findFirst(out.lines, "2330")438 is_omitted, row, start_col, end_col = tensor_format.locate_tensor_element(439 out, [10, 10, 10])440 self.assertFalse(is_omitted)441 self.assertEqual(actual_row_10_10_10, row)442 self.assertIsNone(start_col) # Past ellipsis.443 self.assertIsNone(end_col)444 with self.assertRaisesRegexp(445 ValueError, "Indices exceed tensor dimensions"):446 tensor_format.locate_tensor_element(out, [11, 5, 5])447 with self.assertRaisesRegexp(448 ValueError, "Indices contain negative"):449 tensor_format.locate_tensor_element(out, [-1, 5, 5])450 with self.assertRaisesRegexp(451 ValueError, "Dimensions mismatch"):452 tensor_format.locate_tensor_element(out, [5, 5])453 def testLocateTensorElement3DWithEllipsesBatchMode(self):454 a = (np.arange(11 * 11 * 11) + 1000).reshape([11, 11, 11]).astype(np.int32)455 out = tensor_format.format_tensor(456 a, "a", False, np_printoptions={"threshold": 100,457 "edgeitems": 2})458 cli_test_utils.assert_lines_equal_ignoring_whitespace(459 self, ["Tensor \"a\":", ""], out.lines[:2])460 self.assertEqual(repr(a).split("\n"), out.lines[2:])461 actual_row_0_0_0, actual_col_0_0_0 = self._findFirst(out.lines, "1000")462 actual_row_0_0_10, _ = self._findFirst(out.lines, "1010")463 actual_row_10_10_10, _ = self._findFirst(out.lines, "2330")464 (are_omitted, rows, start_cols,465 end_cols) = tensor_format.locate_tensor_element(out, [[0, 0, 0]])466 self.assertEqual([False], are_omitted)467 self.assertEqual([actual_row_0_0_0], rows)468 self.assertEqual([actual_col_0_0_0], start_cols)469 self.assertEqual([actual_col_0_0_0 + 4], end_cols)470 (are_omitted, rows, start_cols,471 end_cols) = tensor_format.locate_tensor_element(out,472 [[0, 0, 0], [0, 0, 10]])473 self.assertEqual([False, False], are_omitted)474 self.assertEqual([actual_row_0_0_0, actual_row_0_0_10], rows)475 self.assertEqual([actual_col_0_0_0, None], start_cols)476 self.assertEqual([actual_col_0_0_0 + 4, None], end_cols)477 (are_omitted, rows, start_cols,...
dao.py
Source:dao.py
1import random2from typing import List3from sqlalchemy import create_engine, select4from sqlalchemy.orm import sessionmaker, subqueryload5from datetime import datetime6from leetcode_service.leetcode_util import ParseSlugFromUrl7from db.models import Problem, Solve, Base, Member8from db.db_constants import Constants9class DAO:10 _instance = None11 def MakeMember(self, member: Member):12 self._session.add(member)13 self._session.commit()14 return member15 def MakeProblem(self, problem: Problem):16 self._session.add(problem)17 self._session.commit()18 return problem19 def Solved(self, solvee: Member, problem: Problem):20 solution = Solve()21 solution.date = datetime.now()22 solution.problem = problem23 solution.solvee = solvee24 solution.takeaway = ''25 26 solvee.num_solutions += 127 self._session.add(solvee)28 self._session.add(solution)29 self._session.commit()30 return solution31 def UpdateTakeaway(self, solution: Solve, takeaway: str):32 solution.takeaway = takeaway33 self._session.add(solution)34 self._session.commit()35 return solution36 def DeleteSolution(self, solution):37 solvee = solution.solvee38 solvee.num_solutions -= 139 self._session.add(solvee)40 self.DeleteRow(solution)41 def DeleteRow(self, obj):42 klass = obj.__class__43 if klass in Constants.MODELS:44 self._session.delete(obj)45 self._session.commit()46 47 else:48 raise Exception(49 f"""50 Given row is not a member of the models: {51 [klass.__name__ for klass in Constants.MODELS]52 } 53 """54 )55 def GetMember(self, discordID: str) -> Member:56 query = select(Member).where(Member.discordID == discordID)57 return self._FindFirst(query)58 def GetMemberCount(self) -> int:59 return self._session.query(Member).count()60 def GetMemberStats(self, member: Member):61 joins = self._session.query(Solve).join(Solve.problem).where(Solve.solvee == member)62 retVal = [0, 0, 0]63 for k in Constants.DIFFICULTY_MAPPING.keys():64 retVal[k] = joins.where(Problem.difficulty == k).count()65 return retVal66 def GetTopUsers(self, limit: int = 10):67 return self._session.query(Member).order_by(Member.num_solutions.desc()).limit(limit).all()68 69 def GetSolution(self, id: int) -> Solve:70 query = select(Solve).where(Solve.id == id)71 return self._FindFirst(query)72 73 def GetProblem(self, search: str, n_args: int) -> Problem:74 if search.isnumeric():75 # Query based on problem number76 problem_number = int(search)77 return self._GetProblemByNumber(problem_number)78 elif search.startswith('https'):79 # Query based on slug80 slug = ParseSlugFromUrl(search)81 return self._GetProblemBySlug(slug)82 elif n_args == 1:83 # Query based on slug84 return self._GetProblemBySlug(search)85 else:86 # Query based on title87 return self._GetProblemByTitle(search)88 def RecentProblemSolutions(self, problem: Problem = None, limit: int = 5) -> List[Solve]:89 query = select(Solve)90 if problem:91 query = query.where(Solve.problem == problem)92 query = query.order_by(Solve.date.desc()).limit(limit).options(subqueryload(Solve.solvee))93 return self._session.execute(query).scalars().all()94 def RecentUserSolutions(self, solvee: Member = None, limit: int = 5) -> List[Solve]:95 query = select(Solve)96 if solvee:97 query = query.where(Solve.solvee == solvee)98 query = query.order_by(Solve.date.desc()).limit(limit).options(subqueryload(Solve.problem))99 return self._session.execute(query).scalars().all()100 def GetRandomProblem(self, difficulty_filter = None, premium_filter = None) -> Problem:101 query = self._session.query(Problem)102 if premium_filter is False:103 query = query.where(Problem.premium == premium_filter)104 105 if difficulty_filter is not None:106 query = query.where(Problem.difficulty == difficulty_filter)107 108 row_count = query.count()109 return query.order_by(Problem.id).limit(1).offset(random.randint(0, row_count-1)).first()110 def _GetProblemByNumber(self, number: int):111 query = select(Problem).where(Problem.problem_number == number)112 return self._FindFirst(query)113 114 def _GetProblemBySlug(self, slug: str):115 query = select(Problem).where(Problem.slug == slug)116 return self._FindFirst(query)117 118 def _GetProblemByTitle(self, title: str):119 query = select(Problem).where(Problem.problem_name == title)120 return self._FindFirst(query)121 def _FindFirst(self, query):122 return self._session.execute(query.limit(1)).scalars().first()123 def __new__(cls):124 if cls._instance is None:125 cls._instance = super(DAO, cls).__new__(cls)126 127 engine = create_engine(Constants.CONNECTION_URL, pool_size=300, pool_pre_ping=True) 128 Base.metadata.create_all(bind=engine)129 Session = sessionmaker(bind=engine)130 cls._session = Session()131 return cls._instance132 def __del__(cls):...
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