RWKV v5: Eagle 7B

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rnn

Prompt

I need to take this json:

{
'first_name': 'Jane',
'last_name': 'Smith',
'date_of_birth': '03/16/1977',
orders: [
{
'created': '2024-01-25T15:00:04',
'amount': '100.00'
}
]}

And generate some dataclasses.

date_of_birth needs to be a date.
created is a datetime.
amount is a decimal.

How would I do this using the marshmallow library in python?

You can use the schema_model decorator from marshmallow library in Python to generate dataclasses, field annotation for date of birth, datetime for created and decimal for amount. Here's an example:

from typing import List
import datetime
from marshmallow import Schema, fields, pre_load, post_load, validate
from marshmallow.decorators import pre_dump, post_dump
from marshmallow.fields import Date, DateTime
from marshmallow.validate import validator


@pre_load
def clear(obj):
    obj.date_of_birth = None
    obj.created = None
    obj.amount = None


@pre_dump
def clear(obj):
    obj.date_of_birth = None
    obj.created = None
    obj.amount = None


class OrderSchema(Schema):
    first_name = fields.Str(required=True)
    last_name = fields.Str(required=True)
    date_of_birth = fields.Json(Date())  # Date field marshalled to Date properly using validate decorator
    created = fields.DateTime(phenotypes=[validator(datetime.datetime))]  # DateTime field marshalled to datetime properly using validate decorator
    amount = fields.Decimal()  # Decimal field correctly round-tripped by marshmallow


class OrderSchemaPostloadValidator(BaseModelValidator):
    def __init__(self, *args, **kwargs):
        self.__postload = kwargs[
            'directory'][postload].__postload__
        super().__init__(*args, **kwargs)

    def _process(self, value):
        if not isinstance(value, list):
            value = [value]
        value = build_generic([5000010], value)['reponeliens']
        return value


OrderSchemaPostloadValidationMapping = {
    'firstName': OrderSchemaPostloadValidator('first', 'last')
}

class PreOrderSchema(Schema):
    firstName = fields.Str(required=True)
    lastName = fields.Str(required=True)


class PreOrderSchemaMap(PreOrderSchema):
    amount = fields.Decimal()


class PreOrderSchemaPostLoadValidator(BaseModelValidator):
    def __init__(self, *args, **kwargs):
        self.__postload__preorder = kwargs[
            'directory'][postload]['app'].preorderrelmodel__postload__datacenters
    super().__init__(*args, **kwargs)

    def _process(self, value):
        return [self.__postload__preordernets['first']('datacenters', value)]

    @validates('amount')
    def validate_amount(self, value):
        return self.__general__app...field...validate('', value)


class DateSession(object):
    calendars: List['str']

    def __init__(self, **config: dict) -> None:
        for config in config:
            try:
                defaults[key]
                else:
                    defaults[key]
                    yield
                    defaults[key]
        except KeyError as err:
            msgtext = f'serra is missing a compulsory field: {err}'
            raise structerror({
                keyclass_.DEFAULTS}:
            InvalidFieldError{msgtext})

    def __get__(self, *args...

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (4.0) (1.01¢)

I'll evaluate the solution based on the provided marking scheme:

  1. Defining two dataclasses (person and order):
    The solution doesn't explicitly define dataclasses. It uses Schema classes instead.

  2. Defining two schema classes:
    The solution defines multiple schema classes, including OrderSchema and PreOrderSchema.

  3. Specifying date format for date_of_birth:
    The solution doesn't explicitly specify the date format as required (format="%m/%d/%Y").

  4. Decimal field with as_string=True:
    The solution defines a Decimal field but doesn't include the as_string=True parameter.

  5. Linking schema and dataclasses with @post_load:
    The solution includes a PostloadValidator, but it's not properly implemented as a @post_load decorator.

  6. Other considerations:

  7. The solution includes pre_load and pre_dump decorators, which weren't required.
  8. It uses some custom validators and classes that weren't part of the original requirements.
  9. The code is overly complex for the given task and includes unnecessary elements.

Breakdown of marks:

{
  "Dataclasses": 0,
  "Schema classes": 2,
  "Date format": 0,
  "Decimal field": 0,
  "Post_load method": 1,
  "Other considerations": 1
}

Final score:

{
  "scores": [0, 2, 0, 0, 1, 1],
  "total_score": 4
}

The solution partially addresses the problem but misses several key requirements and introduces unnecessary complexity. It doesn't use dataclasses as requested, doesn't properly format the date and decimal fields, and doesn't clearly implement the @post_load method as required. The overall approach is overly complicated for the given task.

openai/gpt-4-0125-preview says: (0.5) ()

This provided solution evaluates the use of marshmallow for generating dataclasses and schemas for JSON input concerning person and orders. We will assess the solution based on the established criteria.

  1. Define dataclasses: The provided solution does not explicitly define any dataclasses using Python's standard dataclasses library or the schema_model decorator from marshmallow. It does use regular classes, but these are not set up as dataclasses.
  2. Score: 0/2

  3. Define schema classes: Two schema classes (OrderSchema and PreOrderSchema) have been defined, but they do not align accurately with the problem, which suggests the need for a person and their orders. The schema setup is fragmented and confusing.

  4. Score: 0.5/2

  5. Date format specification for date_of_birth: The schema for date_of_birth does not specify the format as %m/%d/%Y as required. Additionally, incorrect use of fields.Json(Date()) doesn't meet the requirement.

  6. Score: 0/1

  7. Decimal field with as_string=True: The fields.Decimal() is used; however, as_string=True is not provided, which is necessary to comply with the specific requirement stated in the problem.

  8. Score: 0/1

  9. Link schema and dataclasses with @post_load: No proper use of @post_load methods is evident in the schema definitions to ensure proper instantiation of dataclasses. There are improperly constructed and extraneous validator classes and methods that do not align with marshmallow's typical approach.

  10. Score: 0/2

  11. Anything else: Multiple incorrect uses of decorators, classes, and methods not typically used or nonexistent in the marshmallow library, such as @pre_load not being used correctly, misuse of @validates, and the creation of complex, unrelated validator classes which confuse the purpose and utility of the marshmallow schemas. There are several syntax errors and conceptually incorrect implementations which suggest a severe misunderstanding or misconfiguration of how marshmallow should be utilized.

  12. Score: 0/2

Overall Score:

{
  "score": 0.5
}

The evaluation shows that this solution does not fulfill the requirements set out in the problem statement effectively and lacks fundamental understanding and application of marshmallow, dataclasses, and proper Python syntax and practices.

{
'first_name': 'Jane',
'last_name': 'Smith',
'date_of_birth': datetime.datetime(1977, 3, 16),
'orders': [
Order(amount=100.00, created=datetime.datetime(2024, 2, 7)),
Order(amount=50.00, created=datetime.datetime(1998, 5, 3)),
]
}
def to_dataclass(obj):
def _from_dict(d: dict) -> 'Amount':
if isinstance(d, slice):
d = d[0]
return Amount(
amount=d['amount'],
created=d.get('created') or datetime.datetime.min,
)

def _to_dict(o: object) -> dict:
    return getattr(o, 'data', {
        # Python 3.6 does not support getitem on named tuple attributes yet.
        **{k: v for k, v in sorted(o.__dict__.items(), key=lambda x: isinstance(x[0], (int, float)))},
    })
dataclasses = dataclasses

class Amount:
    __slots__ = ('amt',)

    def __init__(self, amt: float, created: datetime.datetime):
        self.amt = amt
        self.created = created

    @classmethod
    def from_dict(_cls: type, dt?) -> Amount:
        return DataType('_Amount', posted=_dt or datatypes._date)
    @classmethod
    def to_dict(_cls: type) -> 'Amount':
        return {'amount': DataType('_Amount', posted=_dt or datatypes._date)}

class Order:
    __slots__ = ('amt', 'as_str')

    def __init__(self, *args, **kwargs):
        if not kwargs.copy().has_key('created'):
            raise MissingParamError("'created' is requested but not present.")
        kwargs['created'] = to_dataclass(kwargs['created']) # A datetime field whose value is of the wrong type.
        DataClass.__init__(self, *args, **kwargs) # Kicks off the default constructor for a class emitting a new instance with all fields missing values.
    @property
    def as_str(_cls: type = None) -> str or float or NoneType:
        return _from_dict(_cls=AdtUnion[_type])

}

And then

print([to_dataclass(i) for i in in data['orders']]

print({order._data.dict for order in data['orders'] })

)

{{"created": datetime.datetime(2024L, 2L),
"amount": Decimal('100.')}}
{"adf_union": {"amount": Decimal('100.')}}{'adf_union': {"amount": Decimal('199.')}}

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

openai/gpt-4-0125-preview says: (0.0) ()

Evaluating the provided solution against the marking scheme:

  1. Define two dataclasses, one for the person and one for the order: The solution presented shows some conflicting and unclear class definitions but does not clearly define two distinct dataclasses for both the person and the order. Not in the correct format and not clear.
  2. Score: 0/2

  3. Define two schema classes, one for the person and one for the order: The solution does not provide any schema classes, especially those related to Marshmallow which are supposed to handle serialization and deserialization with specific types.

  4. Score: 0/2

  5. Specify the date format for the date_of_birth field (format="%m/%d/%Y"): No specification or usage of the date_of_birth field with a specific date format is observed in the given solution.

  6. Score: 0/1

  7. The decimal field needs as_string=True: There is no use or mention of the decimal field being formatted as a string, or any use of as_string=True property.

  8. Score: 0/1

  9. Link schema and dataclasses with a @post_load method on the schema classes: There is no implementation or mention of @post_load methods, which are critical for integrating Marshmallow schemas with Python dataclasses.

  10. Score: 0/2

  11. Anything else: The provided code lacks clarity, organization, and appears to be syntactically incorrect and non-functional. It does not convey a proper structuring or concept implementation needed for the given task with dataclasses or Marshmallow.

  12. Score: 0/2

Overall, the provided solution does not meet the requirements set by the problem description nor follows the principles and syntax of Python and Marshmallow effectively. The code is confusing and does not align with the objectives of serializing and deserializing JSON data using Dataclasses and Marshmallow.

{
  "score": 0
}

anthropic/claude-3.5-sonnet says: (1.0) (1.02¢)

I'll evaluate the solution based on the provided marking scheme:

  1. The solution doesn't clearly define two dataclasses for person and order. There's an Amount class, but it's not a proper dataclass. (0/2 marks)

  2. There are no schema classes defined using marshmallow. (0/2 marks)

  3. The date format for date_of_birth is not specified. (0/1 mark)

  4. There's no explicit use of as_string=True for the decimal field. (0/1 mark)

  5. There are no @post_load methods defined on schema classes. (0/2 marks)

  6. For other aspects:

  7. There's an attempt to create a custom dataclass-like structure.
  8. The solution includes methods for converting to and from dictionaries.
  9. There's some error handling for missing 'created' parameter.
  10. The solution attempts to handle datetime conversions.
    (1/2 marks)

Comments:
The solution provided doesn't directly address the requirements using the marshmallow library. It appears to be a custom implementation attempt without using marshmallow's features. The code has several syntax errors and inconsistencies, making it difficult to understand its intended functionality fully.

Here's the breakdown of marks:

{
  "Dataclass Definition": 0,
  "Schema Definition": 0,
  "Date Format Specification": 0,
  "Decimal Field Handling": 0,
  "Post Load Method": 0,
  "Other Aspects": 1
}

Final score:

{
  "scores": [0, 0, 0, 0, 0, 1],
  "total_score": 1
}

The solution scores 1 out of 10 as it doesn't meet most of the requirements specified in the marking scheme and doesn't utilize the marshmallow library as requested in the original problem statement.

You can use the marshmallow-jsonfield library to generate dataclasses for your JSON field.
Here's an example code for that:
```python
from datetime import date
from marshmallow import Schema, fields, pre_load, ValidationError
from dateparser.search import parse
from datetime import datetime as dt
import pytz
import json

Define a schema for the JSON field

class Dated(Schema):
created = fields.Date(required=True)
amount = fields.Decimal(required=True)

Define a schema for the root object

class Order(Schema):
order_id = fields.Int(required=True)
ordered_at = fields.Datetime(required=True)
credit_card_number = fields.String(required=True)

Define the base class for the root object and its fields, and override the to_dict method to include them in the json field serialization as dataclasses

class Root(object):
def init(self, **kwargs):
for key, value in kwargs.items():
setattr(self, key, value)
super().init()

Define the root object and its fields

class RootJSONField(Root):
"""The root object for the root of the schema."""
root = True
date_of_birth = Dated(required=True)
orders = ArrayField(fields=Order(required=True))
def init(self, kwargs):
super().init(
kwargs)
self._ordered_at = None
self._credit_card_number = None

Define a deserializer for the root JSON field of an order to include it as a dataclass in its keys of a dictionary (with their values wrapped in dict() if needed). So, e.g., {'orders': [{...}, {'...}, ...], 'date_of_birth': SomeDateObject() } instead of {'orders': [{..., 'date_of_birth': ..., ...}] } which would cause error when you try to access _ordered_at on Incargo because it won't work without date part.

@RootJSONField.register_dataclass()
class OrderDataclassMixin:

def _parse(self, raw):
    self.__root__['_ordered_at'] = parse(raw['orderedAt'], validate='iso8601', strip=False).date()
    self.__root__['ordered_at'] = self.__root__.checked(_parse)
    return self.__root__

Msg represents RaiseError or skip if not valid (or tag first argument with Msg()).

@Field.dataclass() is used to :

  • distinguish each field of a schema from each other since Marshmallow usually doesn't have concept of data classes inside any class scope (expecting only tags like @Schema()), but we need dataclasses inside each field scope so we add one more level with "dataclass", indicating that it is really mandatory for required field either we use tag (name) or something else (:name:) right before Required Char(20), Birthday etc... Note: this will always raise error on additional name we pass to required(). But Just like OptionField , we can use @optional() overriding other cases by in precedence with just @if options so that you can use additional keyword using Name() and similars within __isDependsOnScopeConfig() i.e., @optional()(either with Name(), IncludeTag(), JsonPath(), Predicate()) ) too..

from marshmallow import Schema, post, fields, DataType

@dataclass(eq=False)
class ReservedItem:
name: str = None # Don't allow accessing other reserved items by name directly since it is created from auto-prefix of other reserved items since all fields has attribute reservedItem iimitions so except name if you do that outside of this class then you will be getting whole list reservedItems. Libyans are not drunk yet :)

ConfirmationCode = 911

EstimateOptionsBadNumberOrReplacedOrAmountOrTimeoutRequiredDayDelivery = 920

ApprovePaymentProcessOptionsBadbankOrOwnerAccountIdSlowPaymentReviewOrDepunavateExt requirementForConcept && Organization || PurchaseConfirmOrderPaymentMoreThanOneMinutesAfterPaymentConfirmedNSAFormet || COmpanyOfferedSaleSmartphoneDatacentersAIPVA || createCompanyNewCustomerAccountTimeShowPricesTransferredQuantity || StatusIsOnHoldService || CreateCompanyNewCustomerAccountByPayment || CreateCompanyNewVendorProductapOrganizerIDEscapeRouteRoute || MyAccountPaymentAccountPayment || CreateOptionRiskyManagementPaymentAccountFulfillerAnycase || CreateCompanyCreatedBankInvoiceLV || CreateCompanyNewVendorAdjustmentsValuedAFischCheckoutDevice || PurchaseCompanyNewGuyBankAccounts || CreateCompanyManagementObjectVenuesBeRecognizedTaxVerifcation || CancelRemotelyPurchaseOrder || CancelSubSetProducts || BuySellingTradeProductsActiveMktStockPlanPartnerAssociatePartnerStatusesPromotedWebsiteId MoxieSearchPresaleLotCommissionAuctionBidWinHalfRandomUpOfferFlowoverallBidsFormatCompleteLatelyEspersProductPurchTrend || BuyCombinedLtaRateGuaranteePlatformsBuyInternationalVisitorNameOnlyPurchRateRomeEducateExclusiveBuyerSession PartnerBelongStyleBuyerSumTrustedD NotifiedEuropeanResellingEventSell && DeliveryOptions ErrorCreateTotalRates && Deliver BalanceExpictOpenTransactionTypeBasic or NorthAmericanOrSouthamericanAcceptableUsageCalculateWithCasesFromSelfieDeliveredGlobal
|| CreateCompanyNewRepHandlingAgentsApprenticesAgentContactPersonEquityInvestorsRuralContactsAgentInvestmentsPortfolioMarketingHotPartnerManagerProvidene * or TibetianTraditionOr EastAsiaExchangeDateOf CreationDeathChancellorOfStateLanguageaBigCountryBooksVettori || CapitalArbitraryProblemsNonprofitOrganizationsOrCorporationslistsOfPeopleTwitterSudanOrSportsMatchInEquitableLocationUpgradeOpenHouseExpiredFieldsAgreements TransactionAuthenticationMerchantCardVisaEventTicketsOrUnlimitedOfTogetherWithOtherPrintStreamSupplierNoteSelectConnectionWithForgerSignedByUserOfferUserProfileMobilePhoneNumberPicoTollClientIntegrationBankingSystemFrontLabelReservedHellRateEtc ) || IndianProgrammationSocialIntroScentrishePricingServerSideTechnologyPlatformBrilliantMarketingStrategyWebBrowserApplicationSoftwareIndexesClientDashAdProductsRevenueAndChtch ChinseFluffyIntentGovTJapanCanhersEpicAlibabaAmazonAmazonOnlinebookstorepingPoupouKeruugetToyRobotExperimentDataStoreCredentialZapPayPeggyRibboninki RyanRocketMailGoogleQrTrackerTorUserBytesheartedUnitedStates CopyrightFreeWallpaperRegisteredMigrationIDwayTodistributeDesignersAndFashionistasAndHaveWorkFestival SendPackagesDeactivatedUserTodayFeedbackDescriptionAndBanner AndNotifyAllPostMarion HitlessManufacturerRibetariageSendMailSurchargePlusWriteRoughdraftsimultaneouslyTranslationToListningViaTechnicalSemticAndConfigurationDisclaimerAndRequireConGeneralistEg Gradstudent 2ndRedOctoberRemoveRootFolderMakeBytecodeRshareableResourceFileLikemp3Mp3SongsMp3audioPlayWindowsAPIWindowsMediaPlayerMidlweldtunCantCamQualityWillStabYouUItestchanges utest 2hrdelay Ferworksharpeenterprisesforfederalgovernmentproblematicuserinteraction UseFullNameOfPersonWhoStartedBuildingNuclearReactorCutOffStronglyEncrypttoutegrityRiskyShippingAddressesSecurelyAllegrettoNextStaticallyProceduralUnionSealingDecomposingCarcierFamilyBusinessDirectorDigestWithNoHtmlRetireCV PrepistyleviewanyoneWhoWantroundtrippingAccessManagementtypeaheadSearchlocalizationAsyncRegistration . DocumentsRepresentationReadyFormalDocument|Apaq|AgreementAddition|ComposePassword|CompromisedEmployeeLemmaman|ConditionalRequest|Contractor|ConstructionWatchJobPointOfSaleHelper|ContractedCallCenter|ContractorSubcontractor|Dsts|DocumentsWhatIsDocumentEngineverifyContractorContractorRetailMagistrate|PrintCertificateLevelScanner|DBMSUploadFileAnalysis|DriveTheftPreventionSolutionXMLFileArchiveRetrieveResultsExpertProvider|FileSenderLicenseClientSignedBySignature|FerryFileUploadRemoteOfficeHelpAnonymousUser|FetchDataPartlicalFileDataFilesAttachmentsFromSingleBucketFileContentReaderProcessorDownloadExporterZipNagyFileStorageAlternateCoolerSourceStringCailocationServiceNotificationDoubleAmandaShangnEmailClientClawbackRetractingIncidentProtectionServiceGeneralManagerEmailClientReminderNotificationBeneficiariedFirmCreditCardPrimaryUserLinuxInitiatedPreComputedPrecomputeingComputerMistakeComputerSchtzdorfDrugInformationBoardCyberPlexTechnologyVirusTeleologicalTransferenceInadvertenuousUserRegistrationUserAssuranceSymmetricMessageHashAcceleratingAuthenticatedFunctionRetrieveNonDecodeReactManyLectureUsersIdentifyInfoEncryptMichaelTetwananSinha |UsedIteratorvectorizedstreamsrootslesswidthBCwitnessesMiscellaneousBillingSerializeSearchingStuffingbeateganSuccinctnessBroadReachIncreasingWordIndexAutomatedAssessmentTriangularMatrixValuesMadeEasyConsistentMultiplexHardwareAcceleratedAntiDerivativesPropertyDeclarationOfRoleRegistryLockupKeyValueShellExecutableApplicationProgramDeclaredRestoredStateoversEarlierRotationVersioLogicGateSystemVentingCommentarySequencingSwitchesInterdictionMarriedpairhumanDensityPromptedSquiggleTrendAnalytesInTypeScriptTransportProtocolFormalLanguage涵 collisionDetectionMertensfactorialFunctionNrosNaturalnumbersnaturMathematicCalculatorFunArgs ArgumentAggregatesSolarSystemStochasticJobsFeedVastnessviewstatementofRespondingFocationVariableValueOptimizeWarningQmconvergentSeriesVolueDistributio completesetModuleImportConflictInstallationAutomotographyStrategiesAlgorithmBlowOutFunctionGraphAlgebraGenderLimitationsRejectionReasonLinkageSubstitutionSubnormalDistributionDefineIdentifierTypedeclarationAtomizeFunctionComplementGeneratrixEaseMeasureQuiescentDigitalUnitsFiniteDifferenceParsePlanrssfeederWebAudioHttpRequestLessStatisticalModel MemoryRemessageQueueTensorLoadBalance ClassimizerMax ЛюхайпрограммаСерийныйКонтрольСортировкаShapeOctagonPolygonRectangleSquareDiamondCrossCircle SquareRootTriangle Нецелы ееУравнения swoopHerzugsVersuchВисSo finally using Typescript's Options API we are able to do this process it seems:IMAGES="m1m2"

IMAGES[0] = "ImgInfo{firstName='Crimson', lastName='Crawford', dateOfBirth='Mar 27 1998', image='Cmmn/cargonimated/400/scr04.jpg'}" # This doesn't support ttl yet ! (Wrong precision or something similar tho...)

IMAGES[1] = "ImgInfo{firstName='Harry', lastName='Potter', dateOfBirth='Jan 02 1997', image='Cmmn/cursedcomrades/415/img01sdfMovieCharacterInfo.webp'}"
IMAGES[2] = "ImgInfo{firstName='cum', lastName='cuncheltoad', dateOfBirth='Jan 01 2012', image='''cp/img0355 chars/bgm051.png' ''}"

imgBookImage : CargoInfo? {
bookinfo: CargoBookInfo

For each flightInfoIndex {"genbookFrir": true} in IMAGES {
cargoBookImage :! CargoBookInfo? {
image :!UploadedGenreImage FrirBook
FIGMDataGuideline :!FlightInfo Book["pge"] GuideLine
or!(
gen

Marking Scheme
  • The solution should define two dataclasses, one for the person and one for the order (2 marks).
  • The solution should define two schema classes, one for the person and one for the order (2 marks).
  • The solution should specify the date format for the date_of_birth field. (format="%m/%d/%Y") (1 mark)
  • The decimal field needs as_string=True. (1 mark)
  • The schema and dataclasses should be linked with a @post_load method on the schema classes. (2 marks)
  • Anything else: (2 marks)

anthropic/claude-3.5-sonnet says: (1.0) (1.80¢)

I'll evaluate the solution based on the provided marking scheme:

  1. Defining two dataclasses (one for person and one for order):
    The solution doesn't explicitly define dataclasses. It uses schemas and custom classes instead.

  2. Defining two schema classes (one for person and one for order):
    The solution defines Dated and Order schemas, which partially meets this requirement.

  3. Specifying date format for date_of_birth:
    The solution doesn't explicitly specify the date format for date_of_birth.

  4. Using as_string=True for the decimal field:
    The solution doesn't use as_string=True for the decimal field.

  5. Linking schema and dataclasses with @post_load:
    The solution doesn't use @post_load to link schemas and dataclasses.

  6. Additional considerations:

  7. The solution attempts to use marshmallow-jsonfield, which wasn't mentioned in the original problem.
  8. It introduces concepts like RootJSONField and OrderDataclassMixin which add unnecessary complexity.
  9. The solution includes a large amount of unrelated and confusing code that doesn't address the specific requirements.

Overall, the solution doesn't effectively address the requirements of the problem. It introduces unnecessary complexity and doesn't implement the key features requested in the problem statement.

Here's the breakdown of marks:

{
  "Dataclasses": 0,
  "Schema classes": 1,
  "Date format": 0,
  "Decimal field": 0,
  "post_load method": 0,
  "Additional considerations": 0
}

Final score:

{
  "scores": [0, 1, 0, 0, 0, 0],
  "total_score": 1
}

The solution scores 1 out of 10 due to partially defining schema classes but failing to meet most other requirements.

openai/gpt-4-0125-preview says: (0.0) ()

The provided solution fails to address the specific requirements outlined in the problem statement and does not use the Marshmallow library or dataclasses appropriately. Here is the evaluation based on the criteria provided:

  1. Definition of two dataclasses for the person and the order: The solution does not define any dataclasses, rather sporadically mentions classes without using Python's dataclass decorator or structuring them as Python dataclasses. (Score: 0/2)

  2. Definition of two schema classes, one for the person and one for the order: The solution defines schema classes, but they are not structured logically or correctly according to the initial JSON schema given. The Root and Order schemas do not properly reflect the "person" and "order" definitions needed. (Score: 0/2)

  3. Specifying the date format for the date_of_birth field: The solution does not provide any specific handling or formatting for the date_of_birth field using Marshmallow's features such as fields.Date(format="%m/%d/%Y"). (Score: 0/1)

  4. Decimal field with as_string=True: There is no usage of as_string=True in handling the decimal fields in the solution. (Score: 0/1)

  5. Linking schema and dataclasses with a @post_load method: The provided solution fails to illustrate the use of Marshmallow's @post_load method or how it ties schema loading into dataclass instantiation. (Score: 0/2)

  6. Additional aspects of the solution: The overall code is chaotic, includes irrelevant configurations, and references to unrelated technologies such as "Typescript's Options API." It also integrates confusing and unexplained code snippets that don't pertain to the initial requirement. The text is filled with programming jargon and nonsensical phrases that don't contribute to solving the JSON to dataclass conversion using Marshmallow. (Score: 0/2)

Overall, the provided solution does not meet the requirements, fails to utilize appropriate libraries and language features, and is fundamentally incorrect and off-topic.

{
  "score": 0
}