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How to use from_raw method in lisa
Best Python code snippet using lisa_python
test_factories.py
Source:test_factories.py 
...44 ]45 }46 }47 }48 schema = Object.from_raw(Schema, spec)49 prop = PropertyFactory.generate(schema)50 cat_payload = {51 'pet': {52 'name': 'Misty'53 }54 }55 cat = prop.unmarshal(Cursor.from_raw(cat_payload))56 self.assertEqual(cat['pet']['name'], 'Misty')57 dog_payload = {58 'pet': {59 'nickname': 'Max'60 }61 }62 dog = prop.unmarshal(Cursor.from_raw(dog_payload))63 self.assertEqual(dog['pet']['nickname'], 'Max')64 # Implicit discriminator65 spec = {66 'schemas': {67 'Cat': {68 'type': 'object',69 'required': [70 'pet_type'71 ],72 'properties': {73 'pet_type': {74 'type': 'string'75 },76 'name': {77 'type': 'string'78 }79 }80 },81 'Dog': {82 'type': 'object',83 'additionalProperties': False,84 'required': [85 'pet_type'86 ],87 'properties': {88 'pet_type': {89 'type': 'string'90 },91 'nickname': {92 'type': 'string'93 }94 }95 },96 'Pet': {97 'type': 'object',98 'properties': {99 'pet': {100 'oneOf': [101 {102 '$ref': '#/schemas/Cat'103 },104 {105 '$ref': '#/schemas/Dog'106 }107 ],108 'discriminator': {109 'propertyName': 'pet_type'110 }111 }112 }113 }114 }115 }116 schema = Object.from_raw(Components, spec)117 prop = PropertyFactory.generate(schema['schemas']['Pet'])118 cat_payload = {119 'pet': {120 'pet_type': 'Cat',121 'name': 'Misty'122 }123 }124 cat = prop.unmarshal(Cursor.from_raw(cat_payload))125 self.assertEqual(cat['pet']['name'], 'Misty')126 self.assertEqual(cat['pet']['pet_type'], 'Cat')127 ambiguous_cat_payload = {128 'pet': {129 'pet_type': '',130 'name': 'Misty'131 }132 }133 try:134 prop.unmarshal(Cursor.from_raw(ambiguous_cat_payload))135 except SchemaError as e:136 self.assertTrue("No one of property types are not matched to discriminator value" in str(e))137 else:138 self.fail("MUST failed because pet type not specified")139 dog_with_cat_properties = {140 'pet': {141 'pet_type': 'Dog',142 'name': 'Misty'143 }144 }145 try:146 prop.unmarshal(Cursor.from_raw(dog_with_cat_properties))147 except SchemaError as e:148 self.assertTrue("Unexpected additional property" in str(e))149 else:150 self.fail("MUST failed because Dog not accept additional properties")151 # Semi explicit discriminator152 spec = {153 'schemas': {154 'Cat': {155 'type': 'object',156 'additionalProperties': False,157 'required': [158 'pet_type'159 ],160 'properties': {161 'pet_type': {162 'type': 'string'163 },164 'name': {165 'type': 'string'166 }167 }168 },169 'Dog': {170 'type': 'object',171 'additionalProperties': False,172 'required': [173 'pet_type'174 ],175 'properties': {176 'pet_type': {177 'type': 'string'178 },179 'nickname': {180 'type': 'string'181 }182 }183 },184 'Pet': {185 'type': 'object',186 'properties': {187 'pet': {188 'oneOf': [189 {190 '$ref': '#/schemas/Cat'191 },192 {193 '$ref': '#/schemas/Dog'194 }195 ],196 'discriminator': {197 'propertyName': 'pet_type',198 'mapping': {199 '1': '#/schemas/Cat',200 }201 }202 }203 }204 }205 }206 }207 schema = Object.from_raw(Components, spec)208 prop = PropertyFactory.generate(schema['schemas']['Pet'])209 cat_payload = {210 'pet': {211 'pet_type': '1',212 'name': 'Misty'213 }214 }215 cat = prop.unmarshal(Cursor.from_raw(cat_payload))216 self.assertEqual(cat['pet']['name'], 'Misty')217 dog_payload = {218 'pet': {219 'pet_type': 'Dog',220 'nickname': 'Max'221 }222 }223 dog = prop.unmarshal(Cursor.from_raw(dog_payload))224 self.assertEqual(dog['pet']['nickname'], 'Max')225 unknown_payload = {226 'pet': {227 'pet_type': '2',228 'nickname': 'Max'229 }230 }231 try:232 prop.unmarshal(Cursor.from_raw(unknown_payload))233 except SchemaError as e:234 self.assertTrue("No one of property types are not matched to discriminator value" in str(e))235 else:236 self.fail("MUST failed because object has unknown pet type")237 # Discriminator with inline schemas238 spec = {239 'x-schemas': {240 'Cat': {241 'type': 'object',242 'additionalProperties': False,243 'required': [244 'pet_type'245 ],246 'properties': {247 'pet_type': {248 'type': 'string'249 },250 'name': {251 'type': 'string'252 }253 }254 },255 'Dog': {256 'type': 'object',257 'additionalProperties': False,258 'required': [259 'pet_type'260 ],261 'properties': {262 'pet_type': {263 'type': 'string'264 },265 'nickname': {266 'type': 'string'267 }268 }269 }270 },271 'type': 'object',272 'properties': {273 'pet': {274 'oneOf': [275 {276 '$ref': '#/x-schemas/Cat'277 },278 {279 '$ref': '#/x-schemas/Dog'280 },281 {282 'type': 'object',283 'additionalProperties': False,284 'required': [285 'pet_type'286 ],287 'properties': {288 'pet_type': {289 'type': 'string'290 },291 'last_name': {292 'type': 'string'293 }294 }295 }296 ],297 'discriminator': {298 'propertyName': 'pet_type'299 }300 }301 }302 }303 schema = Object.from_raw(Schema, spec)304 prop = PropertyFactory.generate(schema)305 inline_payload = {306 'pet': {307 'pet_type': 'Inline',308 'last_name': 'Misty'309 }310 }311 try:312 prop.unmarshal(Cursor.from_raw(inline_payload))313 except SchemaError as e:314 self.assertTrue("No one of property types are not matched to discriminator value" in str(e))315 else:316 self.fail("MUST failed because inline schema in oneOf not considered")317 def test_generate_anyOf(self):318 spec = {319 'x-schemas': {320 'Cat': {321 'type': 'object',322 'additionalProperties': False,323 'properties': {324 'name': {325 'type': 'string'326 }327 }328 },329 'Dog': {330 'type': 'object',331 'additionalProperties': False,332 'properties': {333 'nickname': {334 'type': 'string'335 }336 }337 }338 },339 'type': 'object',340 'properties': {341 'pet': {342 'anyOf': [343 {344 '$ref': '#/x-schemas/Cat'345 },346 {347 '$ref': '#/x-schemas/Dog'348 }349 ]350 }351 }352 }353 schema = Object.from_raw(Schema, spec)354 prop = PropertyFactory.generate(schema)355 cat_payload = {356 'pet': {357 'name': 'Misty'358 }359 }360 cat = prop.unmarshal(Cursor.from_raw(cat_payload))361 self.assertEqual(cat['pet']['name'], 'Misty')362 dog_payload = {363 'pet': {364 'nickname': 'Max'365 }366 }367 dog = prop.unmarshal(Cursor.from_raw(dog_payload))368 self.assertEqual(dog['pet']['nickname'], 'Max')369 not_any_payload = {370 'pet': {371 'weight': '10kg'372 }373 }374 try:375 prop.unmarshal(Cursor.from_raw(not_any_payload))376 except SchemaError as e:377 self.assertEqual(378 e.errors,379 {380 "pet": {381 "__any__": [382 {"weight": "Unexpected additional property"},383 {"weight": "Unexpected additional property"}384 ]385 }386 }387 )388 else:389 self.fail("MUST failed because payload not match for all of schemas")390 spec = {391 'x-schemas': {392 'Cat': {393 'type': 'object',394 'properties': {395 'name': {396 'type': 'string'397 }398 }399 },400 'Dog': {401 'type': 'object',402 'properties': {403 'nickname': {404 'type': 'string'405 }406 }407 }408 },409 'type': 'object',410 'properties': {411 'pet': {412 'anyOf': [413 {414 '$ref': '#/x-schemas/Cat'415 },416 {417 '$ref': '#/x-schemas/Dog'418 }419 ]420 }421 }422 }423 schema = Object.from_raw(Schema, spec)424 prop = PropertyFactory.generate(schema)425 cat_dog_payload = {426 'pet': {427 'name': 'Misty',428 'nickname': 'Max'429 }430 }431 cat_dog = prop.unmarshal(Cursor.from_raw(cat_dog_payload))432 self.assertEqual(cat_dog['pet']['name'], 'Misty')433 self.assertEqual(cat_dog['pet']['nickname'], 'Max')434 def test_generate_allOf(self):435 spec = {436 'x-schemas': {437 'Cat': {438 'type': 'object',439 'properties': {440 'name': {441 'type': 'string'442 },443 's': {444 'type': 'integer'445 }446 }447 },448 'Dog': {449 'type': 'object',450 'properties': {451 'nickname': {452 'type': 'string'453 }454 }455 }456 },457 'type': 'object',458 'properties': {459 'pet': {460 'allOf': [461 {462 '$ref': '#/x-schemas/Cat'463 },464 {465 '$ref': '#/x-schemas/Dog'466 }467 ]468 }469 }470 }471 schema = Object.from_raw(Schema, spec)472 prop = PropertyFactory.generate(schema)473 cat_dog_payload = {474 'pet': {475 'name': 'Misty',476 'nickname': 'Max',477 's': '45'478 }479 }480 cat_dog = prop.unmarshal(Cursor.from_raw(cat_dog_payload), context=Context(strict=False))481 self.assertEqual(cat_dog['pet']['name'], 'Misty')482 self.assertEqual(cat_dog['pet']['nickname'], 'Max')483 self.assertTrue(isinstance(cat_dog['pet']['s'], int))484 def test_generate_recursive_property(self):485 spec = {486 'properties': {487 'payload': {},488 'nested_nodes': {489 'type': 'array',490 'items': {491 '$ref': '#/'492 }493 }494 }495 }496 schema = Object.from_raw(Schema, spec)497 prop = PropertyFactory.generate(schema)498 payload = {499 'adsad': 'sdsd',500 'payload': {501 'ddd': 34502 },503 'nested_nodes': [504 {505 'payload': {},506 'nested_nodes': [507 {508 'payload': {509 'fdf': 54510 }511 }512 ]513 },514 {515 'payload': {516 'ff': 'dd'517 }518 }519 ]520 }521 root = prop.unmarshal(Cursor.from_raw(payload))522 self.assertEqual(root['adsad'], 'sdsd')523 def test_defaults(self):524 spec = {525 'properties': {526 'with_default': {527 'type': 'integer',528 'default': 5529 }530 }531 }532 schema = Object.from_raw(Schema, spec)533 prop = PropertyFactory.generate(schema)534 payload = {}535 obj = prop.unmarshal(Cursor.from_raw(payload))536 self.assertEqual(obj['with_default'], 5)537 spec = {538 'properties': {539 'with_default': {540 'type': 'string',541 'pattern': '^\+?\d{7,20}$',542 'default': 'sdfdf'543 }544 }545 }546 schema = Object.from_raw(Schema, spec)547 prop = PropertyFactory.generate(schema)548 payload = {}549 try:550 prop.unmarshal(Cursor.from_raw(payload))551 except SchemaError as e:552 self.assertEqual(e.errors, {"with_default": ["Value did not match to pattern"]})553 else:554 self.fail("MUST failed because default value doesn't match to pattern")555 def test_enum_primitive(self):556 spec = {557 'properties': {558 'prop': {559 'type': 'integer',560 'enum': [5, 'ret', '56']561 }562 }563 }564 schema = Object.from_raw(Schema, spec)565 prop = PropertyFactory.generate(schema)566 payload = {567 'prop': 5568 }569 obj = prop.unmarshal(Cursor.from_raw(payload))570 self.assertEqual(obj['prop'], 5)571 payload = {572 'prop': 45573 }574 try:575 prop.unmarshal(Cursor.from_raw(payload))576 except SchemaError as e:577 self.assertEqual(e.errors, {"prop": ["Value is invalid. Expected one of: 5, ret, 56"]})578 else:579 self.fail("MUST failed because property value doesn't match to enumerated values")580 spec = {581 'properties': {582 'prop': {583 'type': 'string',584 'enum': ['5', 'ret', '56']585 }586 }587 }588 schema = Object.from_raw(Schema, spec)589 prop = PropertyFactory.generate(schema)590 payload = {591 'prop': '5'592 }593 obj = prop.unmarshal(Cursor.from_raw(payload))594 self.assertEqual(obj['prop'], '5')595 spec = {596 'properties': {597 'prop': {598 'type': 'boolean',599 'enum': [True]600 }601 }602 }603 schema = Object.from_raw(Schema, spec)604 prop = PropertyFactory.generate(schema)605 payload = {606 'prop': True607 }608 obj = prop.unmarshal(Cursor.from_raw(payload))609 self.assertEqual(obj['prop'], True)610 def test_enum_list(self):611 spec = {612 'properties': {613 'prop': {614 'type': 'array',615 'items': {616 'type': 'integer'617 },618 'enum': [[3], [1, 4]]619 }620 }621 }622 schema = Object.from_raw(Schema, spec)623 prop = PropertyFactory.generate(schema)624 payload = {625 'prop': [3]626 }627 obj = prop.unmarshal(Cursor.from_raw(payload))628 self.assertEqual(obj['prop'], [3])629 payload = {630 'prop': [1, 4]631 }632 obj = prop.unmarshal(Cursor.from_raw(payload))633 self.assertEqual(obj['prop'], [1, 4])634 payload = {635 'prop': [1, 45]636 }637 try:638 prop.unmarshal(Cursor.from_raw(payload))639 except SchemaError as e:640 self.assertEqual(e.errors, {"prop": ["Value is invalid. Expected one of: [3], [1, 4]"]})641 else:642 self.fail("MUST failed because property value doesn't match to enumerated values")643 def test_enum_object(self):644 spec = {645 'properties': {646 'prop': {647 'type': 'object',648 'additionalProperties': False,649 'properties': {650 'type': {651 'type': 'integer',652 'nullable': True653 }654 },655 'enum': [{'type': 0}, {'type': None}]656 }657 }658 }659 schema = Object.from_raw(Schema, spec)660 prop = PropertyFactory.generate(schema)661 payload = {662 'prop': {663 'type': 0664 }665 }666 obj = prop.unmarshal(Cursor.from_raw(payload))667 self.assertEqual(obj['prop']['type'], 0)668 payload = {669 'prop': {670 'type': None671 }672 }673 obj = prop.unmarshal(Cursor.from_raw(payload))674 self.assertEqual(obj['prop']['type'], None)675 payload = {676 'prop': {677 'type': 1678 }679 }680 try:681 prop.unmarshal(Cursor.from_raw(payload))682 except SchemaError as e:683 self.assertTrue('Expected one of' in str(e))684 else:685 self.fail("MUST failed because property value doesn't match to enumerated values")686 def test_required(self):687 spec = {688 'required': ['prop'],689 'properties': {690 'prop': {691 'type': 'object',692 'required': ['subprop'],693 'properties': {694 'subprop': {695 'type': 'integer'696 }697 }698 }699 }700 }701 schema = Object.from_raw(Schema, spec)702 prop = PropertyFactory.generate(schema)703 payload = {704 'prop': {705 'subprop': 314706 }707 }708 obj = prop.unmarshal(Cursor.from_raw(payload))709 self.assertEqual(obj['prop']['subprop'], 314)710 payload = {711 }712 try:713 prop.unmarshal(Cursor.from_raw(payload))714 except SchemaError as e:715 self.assertEqual(e.errors, {"prop": ["Missing value of required property"]})716 else:717 self.fail("MUST failed because property is required")718 payload = {719 'prop': {}720 }721 try:722 prop.unmarshal(Cursor.from_raw(payload))723 except SchemaError as e:724 self.assertEqual(e.errors, {"prop": {"subprop": ["Missing value of required property"]}})725 else:726 self.fail("MUST failed because sub property is required")727 def test_nullable(self):728 spec = {729 'properties': {730 'prop': {731 'type': 'integer',732 'nullable': True733 }734 }735 }736 schema = Object.from_raw(Schema, spec)737 prop = PropertyFactory.generate(schema)738 payload = {739 'prop': None740 }741 obj = prop.unmarshal(Cursor.from_raw(payload))742 self.assertEqual(obj['prop'], None)743 spec = {744 'properties': {745 'prop': {746 'type': 'integer',747 'nullable': False748 }749 }750 }751 schema = Object.from_raw(Schema, spec)752 prop = PropertyFactory.generate(schema)753 payload = {754 'prop': None755 }756 try:757 prop.unmarshal(Cursor.from_raw(payload))758 except SchemaError as e:759 self.assertTrue("Property not allow null values" in str(e))760 else:761 self.fail("MUST failed because null values not allowed")762 def test_strict(self):763 spec = {764 'allOf': [765 {'type': 'integer'},766 {'type': 'string'}767 ]768 }769 schema = Object.from_raw(Schema, spec)770 prop = PropertyFactory.generate(schema)771 payload = 5772 try:773 prop.unmarshal(Cursor.from_raw(payload))774 except SchemaError as e:775 self.assertEqual(776 e.errors,777 {"__all__": [["Couldn't interpret value as string"]]}778 )779 else:780 self.fail("MUST failed because payload is not string")781 payload = 5782 obj = prop.unmarshal(Cursor.from_raw(payload), context=Context(strict=False))783 self.assertEqual(obj, '5')784 def test_date(self):785 today = datetime.datetime.now().date()786 spec = {787 'properties': {788 'date': {789 'type': 'string',790 'format': 'date',791 }792 }793 }794 schema = Object.from_raw(Schema, spec)795 prop = PropertyFactory.generate(schema)796 payload = {797 'date': today.isoformat()798 }799 obj = prop.unmarshal(Cursor.from_raw(payload))800 self.assertEqual(obj['date'], today)801 def test_datetime(self):802 now = datetime.datetime.now().replace(microsecond=0)803 spec = {804 'properties': {805 'datetime': {806 'type': 'string',807 'format': 'date-time',808 }809 }810 }811 schema = Object.from_raw(Schema, spec)812 prop = PropertyFactory.generate(schema)813 payload = {814 'datetime': rfc3339.rfc3339(now)815 }816 obj = prop.unmarshal(Cursor.from_raw(payload))817 self.assertEqual(obj['datetime'], now)818 def test_min_max_properties(self):819 spec = {820 'additionalProperties': True,821 'minProperties': 2,822 'maxProperties': 4,823 'properties': {824 'prop1': {'type': 'string'}825 }826 }827 schema = Object.from_raw(Schema, spec)828 prop = PropertyFactory.generate(schema)829 payload = {830 'prop1': 'abracadabra',831 'prop2': 2832 }833 obj = prop.unmarshal(Cursor.from_raw(payload))834 self.assertEqual(obj['prop1'], 'abracadabra')835 self.assertEqual(obj['prop2'], 2)836 payload = {837 'prop1': 'abracadabra'838 }839 try:840 prop.unmarshal(Cursor.from_raw(payload))841 except SchemaError as e:842 self.assertEqual(e.errors, ["Object does not have enough properties"])843 else:844 self.fail("MUST failed because properties count less than specified in `minProperties`")845 payload = {846 'prop1': 'abracadabra',847 'prop2': 2,848 'prop3': 3,849 'prop4': 4,850 'prop5': 5851 }852 try:853 prop.unmarshal(Cursor.from_raw(payload))854 except SchemaError as e:855 self.assertEqual(e.errors, ["Object has too many properties"])856 else:857 self.fail("MUST failed because properties count more than specified in `maxProperties`")858 def test_styles(self):859 primitive = '5'860 lst = ['3', '4', '5']861 obj = {'role': 'admin', 'firstName': 'Alex'}862 self.assertEqual(factories.style_simple_primitive('5', True), primitive)863 self.assertEqual(factories.style_simple_primitive('5', False), primitive)864 self.assertEqual(factories.style_simple_array('3,4,5', True), lst)865 self.assertEqual(factories.style_simple_array('3,4,5', False), lst)866 self.assertEqual(factories.style_simple_objects('role,admin,firstName,Alex', False), obj)867 self.assertEqual(factories.style_simple_objects('role=admin,firstName=Alex', True), obj)868 self.assertEqual(factories.style_label_primitive('.5', True), primitive)869 self.assertEqual(factories.style_label_primitive('.5', False), primitive)870 self.assertEqual(factories.style_label_array('.3.4.5', True), lst)871 self.assertEqual(factories.style_label_array('.3,4,5', False), lst)872 self.assertEqual(factories.style_label_object('.role=admin.firstName=Alex', True), obj)873 self.assertEqual(factories.style_label_object('.role,admin,firstName,Alex', False), obj)874 self.assertEqual(factories.style_matrix_primitive(';id=5', True), primitive)875 self.assertEqual(factories.style_matrix_primitive(';id=5', False), primitive)876 self.assertEqual(factories.style_matrix_array(';id=3;id=4;id=5', True), lst)877 self.assertEqual(factories.style_matrix_array(';id=3,4,5', False), lst)878 self.assertEqual(factories.style_matrix_object(';role=admin;firstName=Alex', True), obj)879 self.assertEqual(factories.style_matrix_object(';id=role,admin,firstName,Alex', False), obj)880 self.assertEqual(factories.style_form_primitive('5', True), primitive)881 self.assertEqual(factories.style_form_primitive('5', False), primitive)882 self.assertEqual(factories.style_form_array(lst, True), lst)883 self.assertEqual(factories.style_form_array('3,4,5', False), lst)884 self.assertEqual(factories.style_form_object('role,admin,firstName,Alex', False), obj)885 self.assertEqual(factories.style_space_delimited_array('3 4 5', False), lst)886 self.assertEqual(factories.style_pipe_delimited_array('3|4|5', False), lst)887 def test_polymorphic(self):888 spec = {889 "schemas": {890 "Pet": {891 "type": "object",892 "discriminator": {893 "propertyName": "petType"894 },895 "properties": {896 "name": {897 "type": "string"898 },899 "petType": {900 "type": "string"901 }902 },903 "required": [904 "name",905 "petType"906 ]907 },908 "Cat": {909 "description": (910 "A representation of a cat. Note that `Cat` will be used as the discriminator value."),911 "allOf": [912 {913 "$ref": "#/schemas/Pet"914 },915 {916 "type": "object",917 "properties": {918 "huntingSkill": {919 "type": "string",920 "description": "The measured skill for hunting",921 "default": "lazy",922 "enum": [923 "clueless",924 "lazy",925 "adventurous",926 "aggressive"927 ]928 }929 },930 "required": [931 "huntingSkill"932 ]933 }934 ]935 },936 "Dog": {937 "description": (938 "A representation of a dog. Note that `Dog` will be used as the discriminator value."),939 "allOf": [940 {941 "$ref": "#/schemas/Pet"942 },943 {944 "type": "object",945 "properties": {946 "packSize": {947 "type": "integer",948 "format": "int32",949 "description": "the size of the pack the dog is from",950 "default": 0,951 "minimum": 0952 }953 },954 "required": [955 "packSize"956 ]957 }958 ]959 }960 }961 }962 schema = Object.from_raw(Components, spec)963 prop = PropertyFactory.generate(schema['schemas']['Pet'])964 payload = {965 "petType": "Cat",966 "name": "Misty",967 "huntingSkill": "adventurous",968 "age": 3969 }970 cat = prop.unmarshal(Cursor.from_raw(payload))971 self.assertEqual(cat['age'], 3)972 self.assertEqual(cat['name'], "Misty")973 self.assertEqual(cat['huntingSkill'], "adventurous")974 payload = {975 "petType": "Dog",976 "name": "Max",977 "packSize": 314,978 "age": 2979 }980 dog = prop.unmarshal(Cursor.from_raw(payload))981 self.assertEqual(dog['age'], 2)982 self.assertEqual(dog['name'], "Max")983 self.assertEqual(dog['packSize'], 314)984 payload = {985 "age": 3986 }987 try:988 prop.unmarshal(Cursor.from_raw(payload))989 except SchemaError as e:990 self.assertEqual(e.errors, ["Could't discriminate type. Property with name `petType` not found"])991 else:992 self.fail("MUST failed because `petType` not specified")993 payload = {994 "petType": "Cat",995 "name": "Misty"996 }997 try:998 prop.unmarshal(Cursor.from_raw(payload))999 except SchemaError as e:1000 self.assertEqual(1001 e.errors,1002 {"__all__": [{"huntingSkill": ["Missing value of required property"]}]}1003 )1004 else:1005 self.fail("MUST failed because `huntingSkill` property of `Cat` schema is not specified")1006if __name__ == '__main__':...
test_field.py
Source:test_field.py
...4from jumpscale.core.base import fields, ValidationError5class TestFields(unittest.TestCase):6 def test_bool(self):7 field = fields.Boolean()8 self.assertEqual(field.from_raw("yes"), True)9 self.assertEqual(field.from_raw("off"), False)10 self.assertEqual(field.from_raw(complex(1, 2)), True)11 self.assertEqual(field.from_raw(0), False)12 with self.assertRaises(ValidationError):13 field.validate("habd kteer")14 def test_int(self):15 field = fields.Integer()16 self.assertEqual(field.from_raw("1212"), 1212)17 self.assertEqual(field.from_raw(" 12"), 12)18 with self.assertRaises(ValidationError):19 field.validate(1.4)20 with self.assertRaises(ValidationError):21 field.validate("hbd akter")22 def test_int(self):23 field = fields.Float()24 self.assertEqual(field.from_raw("1212.2"), 1212.2)25 self.assertEqual(field.from_raw(" 12.2"), 12.2)26 with self.assertRaises(ValidationError):27 field.validate(1)28 with self.assertRaises(ValidationError):29 field.validate("more hbd here")30 # Email tests31 def test_email(self):32 email = fields.Email(default="test@gmail.com")33 self.assertEqual(email.default, "test@gmail.com")34 email.validate("test@gmail.com")35 with self.assertRaises(ValidationError):36 email.validate("test")37 # Path tests38 def test_url(self):39 """Success scenario for path validation"""40 path = fields.Path("/home")41 self.assertEqual(path.default, "/home")42 self.assertIsNone(path.validate("/home"))43 path = fields.Path("/home")44 self.assertEqual(path.default, "/home")45 with self.assertRaises(ValidationError):46 path.validate("test")47 # URL tests48 def test_url(self):49 """Success scenario for URL validation"""50 url = fields.URL("https://www.test.com")51 self.assertEqual(url.default, "https://www.test.com")52 self.assertIsNone(url.validate("https://www.test.com"))53 """Failure scenario for URL validation"""54 url = fields.URL("https://www.test.com")55 self.assertEqual(url.default, "https://www.test.com")56 with self.assertRaises(ValidationError):57 url.validate("test")58 # Tel tests59 def test_tel(self):60 """Success scenario for tel validation"""61 tel = fields.Tel(default="01222222222")62 self.assertEqual(tel.default, "01222222222")63 """Failure scenario for tel validation"""64 tel = fields.Tel(default="012-222-22222")65 self.assertEqual(tel.from_raw(tel.default), "01222222222")66 with self.assertRaises(ValidationError):67 tel.validate("test")68 # IPaddress tests69 def test_ipaddress_v4(self):70 """Success scenario for ipaddress ipv4 validation"""71 ipaddress = fields.IPAddress("192.168.0.1")72 self.assertEqual(ipaddress.default, "192.168.0.1")73 self.assertIsNone(ipaddress.validate("192.168.0.1"))74 """Failure scenario for ipaddress validation"""75 ipaddress = fields.IPAddress("192.168.0.1")76 self.assertEqual(ipaddress.default, "192.168.0.1")77 with self.assertRaises(ValidationError):78 ipaddress.validate("test")79 def test_ipaddress_v6(self):80 """Success scenario for ipaddress ipv6 validation"""81 ipaddress = fields.IPAddress("2001:db8::")82 self.assertEqual(ipaddress.default, "2001:db8::")83 self.assertIsNone(ipaddress.validate("2001:db8::"))84 def test_ipaddress_network(self):85 """Success scenario for ipaddress network validation"""86 ipaddress = fields.IPRange("192.168.0.0/28")87 self.assertEqual(ipaddress.default, "192.168.0.0/28")88 self.assertIsNone(ipaddress.validate("192.168.0.0/28"))89 # Datetime tests90 def test_datetime(self):91 """Success scenario for datetime validation"""92 value = "2020-12-03 12:30"93 dt_field = fields.DateTime(default=value)94 from_raw = dt_field.from_raw(dt_field.default)95 dt_obj = datetime.datetime.strptime(value, dt_field.format).replace(tzinfo=datetime.timezone.utc)96 self.assertEqual(from_raw, dt_obj)97 # check conversion (utc)98 self.assertEqual(dt_field.to_raw(dt_obj), 1606998600.0)99 self.assertEqual(dt_field.from_raw(1606998600.0), dt_obj)100 """Failure scenario for DateTime validation"""101 with self.assertRaises(ValidationError):102 dt_field.validate("1992/2/22")103 # Date tests104 def testest_date(self):105 """Success scenario for date validation"""106 value = "2020-12-03"107 timestamp = 1606953600108 dt_field = fields.Date(default=value)109 from_raw = dt_field.from_raw(dt_field.default)110 dt_obj = datetime.datetime.strptime(value, dt_field.format).replace(tzinfo=datetime.timezone.utc)111 dt_obj = dt_obj.date()112 self.assertEqual(from_raw, dt_obj)113 # check conversion114 self.assertEqual(dt_field.to_raw(dt_obj), timestamp)115 self.assertEqual(dt_field.from_raw(timestamp), dt_obj)116 """Failure scenario for Date validation"""117 date = fields.Date("2020-12-03")118 with self.assertRaises(ValidationError):119 date.validate("12:30")120 # Time tests121 def test_time(self):122 """Success scenario for time validation"""123 value = "12:30"124 t_field = fields.Time(default=value)125 from_raw = t_field.from_raw(t_field.default)126 t_obj = datetime.datetime.strptime(value, t_field.format).replace(tzinfo=datetime.timezone.utc).time()127 self.assertEqual(from_raw, t_obj)128 # check conversion129 # -2208943800 => 1/1/1 12:30:00130 # arrow does this to deal with time only, sets 1/1/1 as a date if time only us given)131 self.assertEqual(t_field.to_raw(t_obj), -2208943800)132 self.assertEqual(t_field.from_raw(-2208943800), t_obj)133 """Failure scenario for time validation"""134 time = fields.Time("12:30")135 self.assertEqual(time.default, "12:30")136 with self.assertRaises(ValidationError):137 time.validate("2020-12-03")138 def test_required_and_empty(self):139 field1 = fields.Json(required=True)140 field2 = fields.Json(required=True, allow_empty=True)141 field3 = fields.Json(required=True, allow_empty=False)142 field4 = fields.Json(required=False, allow_empty=False)143 with self.assertRaises(ValidationError):144 field1.validate(None)145 field2.validate("")146 field3.validate("null")...
commons.py
Source:commons.py
1import torch2import torch.nn as nn3class GlobalAverage(nn.Module):4 def __init__(self, rank=2, keepdims=False):5 """6 :param rank: dimension of image7 :param keepdims: whether to preserve shape after averaging8 """9 super().__init__()10 self.axes = list(range(2, 2 + rank))11 self.keepdims = keepdims12 def forward(self, x):13 return torch.mean(x, dim=self.axes, keepdim=self.keepdims)14 def extra_repr(self):15 return f"axes={self.axes}, keepdims={self.keepdims}"16class Reshape(nn.Module):17 def __init__(self, *shape):18 """19 final tensor forward result (B, *shape)20 :param shape: shape to resize to except batch dimension21 """22 super().__init__()23 self.shape = shape24 def forward(self, x):25 return x.reshape([x.shape[0], *self.shape])26 def extra_repr(self):27 return f"shape={self.shape}"28class Identity(nn.Module):29 def forward(self, x):30 return x31class ImagenetNorm(nn.Module):32 def __init__(self, from_raw=True):33 """34 :param from_raw: whether the input image lies in the range of [0, 255]35 """36 super().__init__()37 self.from_raw = from_raw38 self.mean = nn.Parameter(torch.tensor([0.485, 0.456, 0.406]), requires_grad=False)39 self.std = nn.Parameter(torch.tensor([0.229, 0.224, 0.225]), requires_grad=False)40 def forward(self, x: torch.Tensor):41 if x.dtype != torch.float:42 x = x.float()43 x = x / 255 if self.from_raw else x44 mean = self.mean.view(1, 3, 1, 1)45 std = self.std.view(1, 3, 1, 1)46 return (x - mean) / std47 def extra_repr(self):48 return f"from_raw={self.from_raw}"49class Normalization(nn.Module):50 def __init__(self, from_raw=True):51 """52 :param from_raw: whether the input image lies in the range of [0, 255]53 """54 super().__init__()55 self.from_raw = from_raw56 def forward(self, x):57 if x.dtype != torch.float:58 x = x.float()59 if self.from_raw:60 return x / 127.5 - 161 else:62 return x * 2 - 163 def extra_repr(self):...
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