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How to use run_scenario method in robotframework-pageobjects
Best Python code snippet using robotframework-pageobjects_python
test_highlevel_open_tcp_stream.py
Source:test_highlevel_open_tcp_stream.py 
...217 assert ip in self.ip_dict218 if socket is not succeeded:219 assert socket.closed220 assert socket.port == self.port221async def run_scenario(222 # The port to connect to223 port,224 # A list of225 # (ip, delay, result)226 # tuples, where delay is in seconds and result is "success" or "error"227 # The ip's will be returned from getaddrinfo in this order, and then228 # connect() calls to them will have the given result.229 ip_list,230 *,231 # If False, AF_INET4/6 sockets error out on creation, before connect is232 # even called.233 ipv4_supported=True,234 ipv6_supported=True,235 # Normally, we return (winning_sock, scenario object)236 # If this is True, we require there to be an exception, and return237 # (exception, scenario object)238 expect_error=(),239 **kwargs,240):241 supported_families = set()242 if ipv4_supported:243 supported_families.add(trio.socket.AF_INET)244 if ipv6_supported:245 supported_families.add(trio.socket.AF_INET6)246 scenario = Scenario(port, ip_list, supported_families)247 trio.socket.set_custom_hostname_resolver(scenario)248 trio.socket.set_custom_socket_factory(scenario)249 try:250 stream = await open_tcp_stream("test.example.com", port, **kwargs)251 assert expect_error == ()252 scenario.check(stream.socket)253 return (stream.socket, scenario)254 except AssertionError: # pragma: no cover255 raise256 except expect_error as exc:257 scenario.check(None)258 return (exc, scenario)259async def test_one_host_quick_success(autojump_clock):260 sock, scenario = await run_scenario(80, [("1.2.3.4", 0.123, "success")])261 assert sock.ip == "1.2.3.4"262 assert trio.current_time() == 0.123263async def test_one_host_slow_success(autojump_clock):264 sock, scenario = await run_scenario(81, [("1.2.3.4", 100, "success")])265 assert sock.ip == "1.2.3.4"266 assert trio.current_time() == 100267async def test_one_host_quick_fail(autojump_clock):268 exc, scenario = await run_scenario(269 82, [("1.2.3.4", 0.123, "error")], expect_error=OSError270 )271 assert isinstance(exc, OSError)272 assert trio.current_time() == 0.123273async def test_one_host_slow_fail(autojump_clock):274 exc, scenario = await run_scenario(275 83, [("1.2.3.4", 100, "error")], expect_error=OSError276 )277 assert isinstance(exc, OSError)278 assert trio.current_time() == 100279async def test_one_host_failed_after_connect(autojump_clock):280 exc, scenario = await run_scenario(281 83, [("1.2.3.4", 1, "postconnect_fail")], expect_error=KeyboardInterrupt282 )283 assert isinstance(exc, KeyboardInterrupt)284# With the default 0.250 second delay, the third attempt will win285async def test_basic_fallthrough(autojump_clock):286 sock, scenario = await run_scenario(287 80,288 [289 ("1.1.1.1", 1, "success"),290 ("2.2.2.2", 1, "success"),291 ("3.3.3.3", 0.2, "success"),292 ],293 )294 assert sock.ip == "3.3.3.3"295 # current time is default time + default time + connection time296 assert trio.current_time() == (0.250 + 0.250 + 0.2)297 assert scenario.connect_times == {298 "1.1.1.1": 0,299 "2.2.2.2": 0.250,300 "3.3.3.3": 0.500,301 }302async def test_early_success(autojump_clock):303 sock, scenario = await run_scenario(304 80,305 [306 ("1.1.1.1", 1, "success"),307 ("2.2.2.2", 0.1, "success"),308 ("3.3.3.3", 0.2, "success"),309 ],310 )311 assert sock.ip == "2.2.2.2"312 assert trio.current_time() == (0.250 + 0.1)313 assert scenario.connect_times == {314 "1.1.1.1": 0,315 "2.2.2.2": 0.250,316 # 3.3.3.3 was never even started317 }318# With a 0.450 second delay, the first attempt will win319async def test_custom_delay(autojump_clock):320 sock, scenario = await run_scenario(321 80,322 [323 ("1.1.1.1", 1, "success"),324 ("2.2.2.2", 1, "success"),325 ("3.3.3.3", 0.2, "success"),326 ],327 happy_eyeballs_delay=0.450,328 )329 assert sock.ip == "1.1.1.1"330 assert trio.current_time() == 1331 assert scenario.connect_times == {332 "1.1.1.1": 0,333 "2.2.2.2": 0.450,334 "3.3.3.3": 0.900,335 }336async def test_custom_errors_expedite(autojump_clock):337 sock, scenario = await run_scenario(338 80,339 [340 ("1.1.1.1", 0.1, "error"),341 ("2.2.2.2", 0.2, "error"),342 ("3.3.3.3", 10, "success"),343 # .25 is the default timeout344 ("4.4.4.4", 0.25, "success"),345 ],346 )347 assert sock.ip == "4.4.4.4"348 assert trio.current_time() == (0.1 + 0.2 + 0.25 + 0.25)349 assert scenario.connect_times == {350 "1.1.1.1": 0,351 "2.2.2.2": 0.1,352 "3.3.3.3": 0.1 + 0.2,353 "4.4.4.4": 0.1 + 0.2 + 0.25,354 }355async def test_all_fail(autojump_clock):356 exc, scenario = await run_scenario(357 80,358 [359 ("1.1.1.1", 0.1, "error"),360 ("2.2.2.2", 0.2, "error"),361 ("3.3.3.3", 10, "error"),362 ("4.4.4.4", 0.250, "error"),363 ],364 expect_error=OSError,365 )366 assert isinstance(exc, OSError)367 assert isinstance(exc.__cause__, trio.MultiError)368 assert len(exc.__cause__.exceptions) == 4369 assert trio.current_time() == (0.1 + 0.2 + 10)370 assert scenario.connect_times == {371 "1.1.1.1": 0,372 "2.2.2.2": 0.1,373 "3.3.3.3": 0.1 + 0.2,374 "4.4.4.4": 0.1 + 0.2 + 0.25,375 }376async def test_multi_success(autojump_clock):377 sock, scenario = await run_scenario(378 80,379 [380 ("1.1.1.1", 0.5, "error"),381 ("2.2.2.2", 10, "success"),382 ("3.3.3.3", 10 - 1, "success"),383 ("4.4.4.4", 10 - 2, "success"),384 ("5.5.5.5", 0.5, "error"),385 ],386 happy_eyeballs_delay=1,387 )388 assert not scenario.sockets["1.1.1.1"].succeeded389 assert (390 scenario.sockets["2.2.2.2"].succeeded391 or scenario.sockets["3.3.3.3"].succeeded392 or scenario.sockets["4.4.4.4"].succeeded393 )394 assert not scenario.sockets["5.5.5.5"].succeeded395 assert sock.ip in ["2.2.2.2", "3.3.3.3", "4.4.4.4"]396 assert trio.current_time() == (0.5 + 10)397 assert scenario.connect_times == {398 "1.1.1.1": 0,399 "2.2.2.2": 0.5,400 "3.3.3.3": 1.5,401 "4.4.4.4": 2.5,402 "5.5.5.5": 3.5,403 }404async def test_does_reorder(autojump_clock):405 sock, scenario = await run_scenario(406 80,407 [408 ("1.1.1.1", 10, "error"),409 # This would win if we tried it first...410 ("2.2.2.2", 1, "success"),411 # But in fact we try this first, because of section 5.4412 ("::3", 0.5, "success"),413 ],414 happy_eyeballs_delay=1,415 )416 assert sock.ip == "::3"417 assert trio.current_time() == 1 + 0.5418 assert scenario.connect_times == {419 "1.1.1.1": 0,420 "::3": 1,421 }422async def test_handles_no_ipv4(autojump_clock):423 sock, scenario = await run_scenario(424 80,425 # Here the ipv6 addresses fail at socket creation time, so the connect426 # configuration doesn't matter427 [428 ("::1", 10, "success"),429 ("2.2.2.2", 0, "success"),430 ("::3", 0.1, "success"),431 ("4.4.4.4", 0, "success"),432 ],433 happy_eyeballs_delay=1,434 ipv4_supported=False,435 )436 assert sock.ip == "::3"437 assert trio.current_time() == 1 + 0.1438 assert scenario.connect_times == {439 "::1": 0,440 "::3": 1.0,441 }442async def test_handles_no_ipv6(autojump_clock):443 sock, scenario = await run_scenario(444 80,445 # Here the ipv6 addresses fail at socket creation time, so the connect446 # configuration doesn't matter447 [448 ("::1", 0, "success"),449 ("2.2.2.2", 10, "success"),450 ("::3", 0, "success"),451 ("4.4.4.4", 0.1, "success"),452 ],453 happy_eyeballs_delay=1,454 ipv6_supported=False,455 )456 assert sock.ip == "4.4.4.4"457 assert trio.current_time() == 1 + 0.1458 assert scenario.connect_times == {459 "2.2.2.2": 0,460 "4.4.4.4": 1.0,461 }462async def test_no_hosts(autojump_clock):463 exc, scenario = await run_scenario(80, [], expect_error=OSError)464 assert "no results found" in str(exc)465async def test_cancel(autojump_clock):466 with trio.move_on_after(5) as cancel_scope:467 exc, scenario = await run_scenario(468 80,469 [470 ("1.1.1.1", 10, "success"),471 ("2.2.2.2", 10, "success"),472 ("3.3.3.3", 10, "success"),473 ("4.4.4.4", 10, "success"),474 ],475 expect_error=trio.MultiError,476 )477 # What comes out should be 1 or more Cancelled errors that all belong478 # to this cancel_scope; this is the easiest way to check that479 raise exc480 assert cancel_scope.cancelled_caught481 assert trio.current_time() == 5...
transforms_test.py
Source:transforms_test.py
...56Nested = typing.NamedTuple(57 'Nested', [('id', int), ('animal_speed', AnimalSpeed)])58coders.registry.register_coder(Nested, coders.RowCoder)59class TransformTest(unittest.TestCase):60 def run_scenario(self, input, func):61 expected = func(input)62 empty = input.iloc[0:0]63 input_placeholder = expressions.PlaceholderExpression(empty)64 input_deferred = frame_base.DeferredFrame.wrap(input_placeholder)65 actual_deferred = func(input_deferred)._expr.evaluate_at(66 expressions.Session({input_placeholder: input}))67 check_correct(expected, actual_deferred)68 with beam.Pipeline() as p:69 input_pcoll = p | beam.Create([input.iloc[::2], input.iloc[1::2]])70 input_df = convert.to_dataframe(input_pcoll, proxy=empty)71 output_df = func(input_df)72 output_proxy = output_df._expr.proxy()73 if isinstance(output_proxy, pd.core.generic.NDFrame):74 self.assertTrue(75 output_proxy.iloc[:0].equals(expected.iloc[:0]),76 (77 'Output proxy is incorrect:\n'78 f'Expected:\n{expected.iloc[:0]}\n\n'79 f'Actual:\n{output_proxy.iloc[:0]}'))80 else:81 self.assertEqual(type(output_proxy), type(expected))82 output_pcoll = convert.to_pcollection(output_df, yield_elements='pandas')83 assert_that(84 output_pcoll, lambda actual: check_correct(expected, concat(actual)))85 def test_identity(self):86 df = pd.DataFrame({87 'Animal': ['Falcon', 'Falcon', 'Parrot', 'Parrot'],88 'Speed': [380., 370., 24., 26.]89 })90 self.run_scenario(df, lambda x: x)91 def test_groupby_sum_mean(self):92 df = pd.DataFrame({93 'Animal': ['Falcon', 'Falcon', 'Parrot', 'Parrot'],94 'Speed': [380., 370., 24., 26.]95 })96 self.run_scenario(df, lambda df: df.groupby('Animal').sum())97 with expressions.allow_non_parallel_operations():98 self.run_scenario(df, lambda df: df.groupby('Animal').mean())99 self.run_scenario(100 df, lambda df: df.loc[df.Speed > 25].groupby('Animal').sum())101 def test_groupby_apply(self):102 df = pd.DataFrame({103 'group': ['a' if i % 5 == 0 or i % 3 == 0 else 'b' for i in range(100)],104 'foo': [None if i % 11 == 0 else i for i in range(100)],105 'bar': [None if i % 7 == 0 else 99 - i for i in range(100)],106 'baz': [None if i % 13 == 0 else i * 2 for i in range(100)],107 })108 def median_sum_fn(x):109 return (x.foo + x.bar).median()110 describe = lambda df: df.describe()111 self.run_scenario(df, lambda df: df.groupby('group').foo.apply(describe))112 self.run_scenario(113 df, lambda df: df.groupby('group')[['foo', 'bar']].apply(describe))114 self.run_scenario(df, lambda df: df.groupby('group').apply(median_sum_fn))115 self.run_scenario(116 df,117 lambda df: df.set_index('group').foo.groupby(level=0).apply(describe))118 self.run_scenario(df, lambda df: df.groupby(level=0).apply(median_sum_fn))119 self.run_scenario(120 df, lambda df: df.groupby(lambda x: x % 3).apply(describe))121 def test_filter(self):122 df = pd.DataFrame({123 'Animal': ['Aardvark', 'Ant', 'Elephant', 'Zebra'],124 'Speed': [5, 2, 35, 40]125 })126 self.run_scenario(df, lambda df: df.filter(items=['Animal']))127 self.run_scenario(df, lambda df: df.filter(regex='Anim.*'))128 self.run_scenario(129 df, lambda df: df.set_index('Animal').filter(regex='F.*', axis='index'))130 with expressions.allow_non_parallel_operations():131 a = pd.DataFrame({'col': [1, 2, 3]})132 self.run_scenario(a, lambda a: a.agg(sum))133 self.run_scenario(a, lambda a: a.agg(['mean', 'min', 'max']))134 def test_scalar(self):135 with expressions.allow_non_parallel_operations():136 a = pd.Series([1, 2, 6])137 self.run_scenario(a, lambda a: a.agg(sum))138 self.run_scenario(a, lambda a: a / a.agg(sum))139 # Tests scalar being used as an input to a downstream stage.140 df = pd.DataFrame({'key': ['a', 'a', 'b'], 'val': [1, 2, 6]})141 self.run_scenario(142 df, lambda df: df.groupby('key').sum().val / df.val.agg(sum))143 def test_getitem_projection(self):144 df = pd.DataFrame({145 'Animal': ['Aardvark', 'Ant', 'Elephant', 'Zebra'],146 'Speed': [5, 2, 35, 40],147 'Size': ['Small', 'Extra Small', 'Large', 'Medium']148 })149 self.run_scenario(df, lambda df: df[['Speed', 'Size']])150 def test_offset_elementwise(self):151 s = pd.Series(range(10)).astype(float)152 df = pd.DataFrame({'value': s, 'square': s * s, 'cube': s * s * s})153 # Only those values that are both squares and cubes will intersect.154 self.run_scenario(155 df,156 lambda df: df.set_index('square').value + df.set_index('cube').value)157 def test_batching_named_tuple_input(self):158 with beam.Pipeline() as p:159 result = (160 p | beam.Create([161 AnimalSpeed('Aardvark', 5),162 AnimalSpeed('Ant', 2),163 AnimalSpeed('Elephant', 35),164 AnimalSpeed('Zebra', 40)165 ]).with_output_types(AnimalSpeed)166 | transforms.DataframeTransform(lambda df: df.filter(regex='Anim.*')))167 assert_that(168 result,169 equal_to([('Aardvark', ), ('Ant', ), ('Elephant', ), ('Zebra', )]))170 def test_batching_beam_row_input(self):171 with beam.Pipeline() as p:172 result = (173 p174 | beam.Create([(u'Falcon', 380.), (u'Falcon', 370.), (u'Parrot', 24.),175 (u'Parrot', 26.)])176 | beam.Map(lambda tpl: beam.Row(Animal=tpl[0], Speed=tpl[1]))177 | transforms.DataframeTransform(178 lambda df: df.groupby('Animal').mean(), include_indexes=True))179 assert_that(result, equal_to([('Falcon', 375.), ('Parrot', 25.)]))180 def test_batching_beam_row_to_dataframe(self):181 with beam.Pipeline() as p:182 df = convert.to_dataframe(183 p184 | beam.Create([(u'Falcon', 380.), (u'Falcon', 370.), (185 u'Parrot', 24.), (u'Parrot', 26.)])186 | beam.Map(lambda tpl: beam.Row(Animal=tpl[0], Speed=tpl[1])))187 result = convert.to_pcollection(188 df.groupby('Animal').mean(), include_indexes=True)189 assert_that(result, equal_to([('Falcon', 375.), ('Parrot', 25.)]))190 def test_batching_passthrough_nested_schema(self):191 with beam.Pipeline() as p:192 nested_schema_pc = (193 p | beam.Create([Nested(1, AnimalSpeed('Aardvark', 5))194 ]).with_output_types(Nested))195 result = nested_schema_pc | transforms.DataframeTransform( # pylint: disable=expression-not-assigned196 lambda df: df.filter(items=['animal_speed']))197 assert_that(result, equal_to([(('Aardvark', 5), )]))198 def test_batching_passthrough_nested_array(self):199 Array = typing.NamedTuple(200 'Array', [('id', int), ('business_numbers', typing.Sequence[int])])201 coders.registry.register_coder(Array, coders.RowCoder)202 with beam.Pipeline() as p:203 array_schema_pc = (p | beam.Create([Array(1, [7, 8, 9])]))204 result = array_schema_pc | transforms.DataframeTransform( # pylint: disable=expression-not-assigned205 lambda df: df.filter(items=['business_numbers']))206 assert_that(result, equal_to([([7, 8, 9], )]))207 def test_unbatching_series(self):208 with beam.Pipeline() as p:209 result = (210 p211 | beam.Create([(u'Falcon', 380.), (u'Falcon', 370.), (u'Parrot', 24.),212 (u'Parrot', 26.)])213 | beam.Map(lambda tpl: beam.Row(Animal=tpl[0], Speed=tpl[1]))214 | transforms.DataframeTransform(lambda df: df.Animal))215 assert_that(result, equal_to(['Falcon', 'Falcon', 'Parrot', 'Parrot']))216 def test_input_output_polymorphism(self):217 one_series = pd.Series([1])218 two_series = pd.Series([2])219 three_series = pd.Series([3])220 proxy = one_series[:0]221 def equal_to_series(expected):222 def check(actual):223 actual = pd.concat(actual)224 if not expected.equals(actual):225 raise AssertionError(226 'Series not equal: \n%s\n%s\n' % (expected, actual))227 return check228 with beam.Pipeline() as p:229 one = p | 'One' >> beam.Create([one_series])230 two = p | 'Two' >> beam.Create([two_series])231 assert_that(232 one | 'PcollInPcollOut' >> transforms.DataframeTransform(233 lambda x: 3 * x, proxy=proxy, yield_elements='pandas'),234 equal_to_series(three_series),235 label='CheckPcollInPcollOut')236 assert_that(237 (one, two)238 | 'TupleIn' >> transforms.DataframeTransform(239 lambda x, y: (x + y), (proxy, proxy), yield_elements='pandas'),240 equal_to_series(three_series),241 label='CheckTupleIn')242 assert_that(243 dict(x=one, y=two)244 | 'DictIn' >> transforms.DataframeTransform(245 lambda x,246 y: (x + y),247 proxy=dict(x=proxy, y=proxy),248 yield_elements='pandas'),249 equal_to_series(three_series),250 label='CheckDictIn')251 double, triple = one | 'TupleOut' >> transforms.DataframeTransform(252 lambda x: (2*x, 3*x), proxy, yield_elements='pandas')253 assert_that(double, equal_to_series(two_series), 'CheckTupleOut0')254 assert_that(triple, equal_to_series(three_series), 'CheckTupleOut1')255 res = one | 'DictOut' >> transforms.DataframeTransform(256 lambda x: {'res': 3 * x}, proxy, yield_elements='pandas')257 assert_that(res['res'], equal_to_series(three_series), 'CheckDictOut')258 def test_cat(self):259 # verify that cat works with a List[Series] since this is260 # missing from doctests261 df = pd.DataFrame({262 'one': ['A', 'B', 'C'],263 'two': ['BB', 'CC', 'A'],264 'three': ['CCC', 'AA', 'B'],265 })266 self.run_scenario(df, lambda df: df.two.str.cat([df.three], join='outer'))267 self.run_scenario(268 df, lambda df: df.one.str.cat([df.two, df.three], join='outer'))269 def test_repeat(self):270 # verify that repeat works with a Series since this is271 # missing from doctests272 df = pd.DataFrame({273 'strings': ['A', 'B', 'C', 'D', 'E'],274 'repeats': [3, 1, 4, 5, 2],275 })276 self.run_scenario(df, lambda df: df.strings.str.repeat(df.repeats))277 def test_rename(self):278 df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})279 self.run_scenario(280 df, lambda df: df.rename(columns={'B': 'C'}, index={281 0: 2, 2: 0282 }))283 with expressions.allow_non_parallel_operations():284 self.run_scenario(285 df,286 lambda df: df.rename(287 columns={'B': 'C'}, index={288 0: 2, 2: 0289 }, errors='raise'))290class TransformPartsTest(unittest.TestCase):291 def test_rebatch(self):292 with beam.Pipeline() as p:293 sA = pd.Series(range(1000))294 sB = sA * sA295 pcA = p | 'CreatePCollA' >> beam.Create([('k0', sA[::3]),296 ('k1', sA[1::3]),297 ('k2', sA[2::3])])298 pcB = p | 'CreatePCollB' >> beam.Create([('k0', sB[::3]),...
test_unitconv.py
Source:test_unitconv.py
...71 self.assertDictEqual(72 unitconv.parse_unitname(''),73 {'multiplier': 1, 'unit_class': None, 'primary_unit': '',74 'base_unit': ''})75def run_scenario(user_asked_for, data_exists_as, allow_derivation=True,76 allow_integration=False, allow_prefixes_in_denominator=False,77 round_result=6):78 userunit = unitconv.parse_unitname(user_asked_for, fold_scale_prefix=False)79 prefixclass = unitconv.prefix_class_for(userunit['scale_multiplier'])80 use_unit = userunit['base_unit']81 compatibles = unitconv.determine_compatible_units(82 allow_derivation=allow_derivation,83 allow_integration=allow_integration,84 allow_prefixes_in_denominator=allow_prefixes_in_denominator,85 **userunit)86 try:87 scale, extra_op = compatibles[data_exists_as]88 except KeyError:89 return90 if round_result is not None:91 scale = round(scale, round_result)92 return (data_exists_as, use_unit, scale, extra_op, prefixclass)93class TestDetermineCompatible(unittest.TestCase):94 def test_compatible_to_simple_primary_type(self):95 all_time_units = [pair[0] for pair in unitconv.unit_classes_by_name['time']]96 u = unitconv.determine_compatible_units('s', 'time', allow_integration=False)97 compatunits = u.keys()98 for timeunit in all_time_units:99 self.assertIn(timeunit, compatunits)100 self.assertEqual(u['MM'], (60000000.0, None))101 self.assertEqual(u['h'], (3600.0, None))102 self.assertEqual([extra_op for (_multiplier, extra_op) in u.values()],103 [None] * len(u))104 def test_allow_derivation(self):105 u = unitconv.determine_compatible_units('b', 'datasize', 1, 's', 'time', allow_integration=False)106 self.assertEqual(u['b'], (1.0, 'derive'))107 self.assertEqual(u['B'], (8.0, 'derive'))108 self.assertEqual(u['b/s'], (1.0, None))109 self.assertAlmostEqual(u['B/d'][0], 9.26e-05)110 self.assertIsNone(u['B/d'][1])111 self.assertNotIn('h', u)112 def test_allow_integration(self):113 u = unitconv.determine_compatible_units('Eggnog', None, 0.125, allow_integration=True)114 self.assertEqual(u['Eggnog'], (8.0, None))115 self.assertAlmostEqual(u['Eggnog/h'][0], 0.0022222)116 self.assertEqual(u['Eggnog/h'][1], 'integrate')117 self.assertNotIn('derive', [extra_op for (_multiplier, extra_op) in u.values()])118class TestUnitconv(unittest.TestCase):119 # in the comments explaining results, X(t) represents a data series in120 # graphite with the "data_exists_as" unit, and Y(t) represents the data121 # series we want to graph, in the "user_asked_for" unit. the results of122 # run_scenario should give the necessary steps to convert X(t) to Y(t).123 def test_straightforward_conversion(self):124 self.assertEqual(run_scenario(user_asked_for='B', data_exists_as='b'),125 ('b', 'B', 0.125, None, 'si'))126 # 0.125 * X(t) b = Y(t) B127 def test_esoteric_conversion_with_derive(self):128 self.assertEqual(run_scenario(user_asked_for='MiB/d', data_exists_as='kb'),129 ('kb', 'B/d', 10800000, 'derive', 'binary'))130 # d(X(t) kb)/dt kb/s * 86400 s/d * 1B/8b * 1000 B/kB = Y(t) B/d131 # 86400 * 1000 / 8 = 10800000132 def test_unrecognized_unit_derive(self):133 self.assertEqual(run_scenario(user_asked_for='Cheese/w', data_exists_as='Cheese'),134 ('Cheese', 'Cheese/w', 604800.0, 'derive', 'si'))135 # d(604800.0 * X(t) Cheese)/dt = Y(t) Cheese/w136 def test_integration(self):137 self.assertEqual(run_scenario(user_asked_for='b', data_exists_as='MB/s',138 allow_integration=True),139 ('MB/s', 'b', 8000000.0, 'integrate', 'si'))140 # Integral(8000000.0 * X(t) MB/s, dt) = Y(t) b141 def test_conversion_between_unrecognized_units(self):142 self.assertIsNone(run_scenario(user_asked_for='pony', data_exists_as='coal'))143 # can't convert144 def test_conversion_between_units_of_different_class(self):145 self.assertIsNone(run_scenario(user_asked_for='d', data_exists_as='Mb'))146 # we know what they are but we can't convert days to megabits147 def test_straightforward_conversion_with_compound_units(self):148 self.assertEqual(run_scenario(user_asked_for='kb/s', data_exists_as='TiB/w'),149 ('TiB/w', 'b/s', 14543804.600212, None, 'si'))150 # X(t) TiB/w * (1024**4 B/TiB) * (8 b/B) * (1 w/604800 s) = Y(t) kb/s151 # 1024**4 * 8 / 604800 =~ 14543804.600212152 def test_straightforward_conversion_between_iec_data_rates(self):153 self.assertEqual(run_scenario(user_asked_for='KiB', data_exists_as='TiB/w',154 allow_integration=True),155 ('TiB/w', 'B', 1817975.575026, 'integrate', 'binary'))156 # X(t) TiB/w * (1024**4 B/TiB) * (1 w/604800 s) = Z(t) B/s...
test_combine.py
Source:test_combine.py
...31 # block 6 Includes back-dated activity to last item of block 132 add_block(test_scope, entity_code, bs,'2020-01-05','2020-01-15','2020-02-02')33 # block 7 Includes back-dated activity to exclude block 1 entirely34 add_block(test_scope, entity_code, bs,'2012-12-31','2020-01-15','2020-02-03')35 def run_scenario(entity_scope, entity_code, to_date,asat_date,expected_open_tmv,expected_locked_tmv):36 blocks = bs.find_blocks(entity_scope, entity_code, '2020-01-03',to_date,asat_date)37 df = pd.DataFrame.from_records(38 [(o.date,o.tmv) 39 for o in 40 combine(blocks,locked,'2020-01-03',to_date,asat_date)],41 columns=['date','tmv']42 )43 total = df['tmv'].sum()44 expected = expected_locked_tmv if locked else expected_open_tmv45 if debug:46 print(nicer(df))47 print(f"Expected: {expected}, Actual: {total}")48 assert (total == pytest.approx(expected,0.001))49 # View on 01/10 for 01/0950 run_scenario(test_scope, entity_code, '2020-01-09','2020-01-10',6061.34,6061.34)51 # View on 01/10 for 01/1052 run_scenario(test_scope, entity_code, '2020-01-10','2020-01-10',7082.17,7082.17)53 # View on 01/1154 run_scenario(test_scope, entity_code, '2020-01-11','2020-01-11',7963.82,7963.82)55 # View on 01/15 for 01/1156 run_scenario(test_scope, entity_code, '2020-01-11','2020-01-15',8295.58,7963.82)57 # View on 01/15 for 01/1558 run_scenario(test_scope, entity_code, '2020-01-15','2020-01-15',12158.41,11826.65)59 # View on 02/0160 run_scenario(test_scope, entity_code, '2020-01-15','2020-02-01',2425.39,11826.65)61 # View on 02/0262 run_scenario(test_scope, entity_code, '2020-01-15','2020-02-02',1606.25,11826.65)63 # View on 02/03...
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