我正在尝试使用 JOLT v0.1.1 转换从 JSON 输入填充 JSON 数组。但我遇到的问题是，数组在我想要包含的元素之前填充了空元素。
这是输入：
{
"data": {
"type": "applications",
"id": "664caa6588bf5100sdfsdf078bb060",
"attributes": {
"appliedAt": 1716300389,
"completedAt": 1716300607,
"status": "new",
"progress": {
"all": 12,
"completed": 12
},
"matchingScore": 48,
"language": "en-GB",
"matchingProfile": {
"bracketId": "poor",
"label": "Poor Fit"
}
},
"relationships": {
"candidate": {
"data": {
"type": "candidates",
"id": "664caa6588bf5100078bb060",
"email": "[email protected]",
"attributes": {
"firstName": "test",
"lastName": "test",
"email": "[email protected]"
}
}
},
"vacancy": {
"data": {
"type": "vacancies",
"id": "65bd009dde98c00007e0e7b4"
}
},
"report": {
"data": {
"type": "reports",
"id": "1716300609586aco_REPORT.pdf"
}
},
"fact-sheets": {
"data": {
"type": "fact-sheeto_FACT_SHEET.pdf"
}
},
"candidate-detail-page": {
"data": {
"type": "candidate-detail-page",
"id": "664caa6588bf5100078bb060"
}
},
"matching-results": {
"data": [
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bcfffd74158f00070d5a96"
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bd0023de98c00007e0e6a8"
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bd006cde98c00007e0e6fa"
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bd007f74158f00070d5b0f"
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65c6263974b26da67537703d"
}
]
},
"matching-indicators": {
"data": [
{
"type": "matching-indicators",
"id": "65bd128774158f00070d67bd"
},
{
"type": "matching-indicators",
"id": "65bd129c74158f00070d67d4"
},
{
"type": "matching-indicators",
"id": "65bd133fde98c00007e0fa12"
},
{
"type": "matching-indicators",
"id": "65bd1463de98c00007e0fa9d"
}
]
},
"personal-information": {
"data": {
"type": "personal-information",
"id": "65bcfff5de98c00007e0e64b"
}
}
}
},
"included": [
{
"type": "reports",
"id": "1716300609586agustin_braco_REPORT.pdf",
"attributes": {
"expiresAt": 1716390988,
"url": "https:ludGVncmF0aW9uLnRyYW5zY29tZW1lYQ=="
}
},
{
"type": "fact-sheets",
"id": "1716300609489agustin_braco_FACT_SHEET.pdf",
"attributes": {
"expiresAt": 1716390988,
"url": "https://edHeaders=host"
}
},
{
"type": "candidate-detail-page",
"id": "664caa6588bf5100078bb060",
"attributes": {
"url": "https://100078bb060"
}
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bcfffd74158f00070d5a96",
"attributes": {
"moduleType": "PersonalityPrintModule",
"calculatedAt": 1716300607,
"moduleScore": 0,
"moduleWeight": 0
},
"relationships": {
"module": {
"data": {
"type": "modules",
"id": "65bcfffd74158f00070d5a96"
}
}
},
"meta": {
"dimensionScores": {
"agreeableness": {
"percentile": 5.7,
"rawScore": 3.5
},
"assertiveness": {
"percentile": 91.14,
"rawScore": 4.333333333333333
},
"empathy": {
"percentile": 23.9,
"rawScore": 4.125
},
"followThrough": {
"percentile": 61.3,
"rawScore": 5
},
"learningFocused": {
"percentile": 81.05,
"rawScore": 5
},
"multitasking": {
"percentile": 18,
"rawScore": 3
},
"organization": {
"percentile": 0.01,
"rawScore": 2.25
},
"preferenceForDirection": {
"percentile": 0.01,
"rawScore": 2.25
},
"resilience": {
"percentile": 77.82,
"rawScore": 5.166666666666667
},
"sociability": {
"percentile": 84.81,
"rawScore": 5
},
"workIntensity": {
"percentile": 4.3,
"rawScore": 3.142857142857143
}
},
"normGroup": "europe",
"variant": "short"
}
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bd0023de98c00007e0e6a8",
"attributes": {
"moduleType": "NOAModule",
"calculatedAt": 1716300607,
"moduleScore": 0,
"moduleWeight": 0
},
"relationships": {
"module": {
"data": {
"type": "modules",
"id": "65bd0023de98c00007e0e6a8"
}
}
},
"meta": {
"components": [
{
"normGroup": "medium",
"score": 0,
"type": "NOA Exclusion"
}
]
}
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bd006cde98c00007e0e6fa",
"attributes": {
"moduleType": "LanguageTestModule",
"calculatedAt": 1716300607,
"moduleScore": 16.333333333333332,
"moduleWeight": 0
},
"relationships": {
"module": {
"data": {
"type": "modules",
"id": "65bd006cde98c00007e0e6fa"
}
}
},
"meta": {
"grading": "<B2",
"sectionScores": [
{
"name": "vocabulary",
"score": 13
},
{
"name": "grammar",
"score": 20
},
{
"name": "comprehension",
"score": 16
}
]
}
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65bd007f74158f00070d5b0f",
"attributes": {
"moduleType": "JobKnowledgeTestModule",
"calculatedAt": 1716300607,
"moduleScore": 0,
"moduleWeight": 0
},
"relationships": {
"module": {
"data": {
"type": "modules",
"id": "65bd007f74158f00070d5b0f"
}
}
},
"meta": {
"scoresByQuestionId": {
"0daeeeb4-eabd-4b64-9f0f-7d01fb09bf08": 0,
"2dba74a2-d527-4c65-a734-2d6017355ac3": 0,
"3bbe3045-6a74-463a-8242-8f8b1ae778c7": 0,
"3db7a0c7-0027-4836-8208-475e41009d56": 0,
"613592b8-6b95-4e55-ac87-2dc3d08f92c7": 0,
"68a710b6-ac2b-4986-90e2-5d14695d3405": 0,
"6c331725-12f0-4ebd-8282-37a1361771d8": 0,
"8156b45b-6c4f-469d-8698-902e6cc12400": 0,
"8a1c0138-3f57-42d0-bbf7-4c6f577ab5a9": 0,
"bee5f06f-7353-4de7-b078-4ce17fa58542": 0
}
}
},
{
"type": "matching-results",
"id": "664caa6588bf5100078bb060-65c6263974b26da67537703d",
"attributes": {
"moduleType": "SituationalJudgmentTestModule",
"calculatedAt": 1716300607,
"moduleScore": 41.66666666666667,
"moduleWeight": 0
},
"relationships": {
"module": {
"data": {
"type": "modules",
"id": "65c6263974b26da67537703d"
}
}
},
"meta": {
"pointsPerQuestion": {
"026c7707-7f0e-43ef-bfc0-c165f6a1e5e2": {
"points": -1,
"score": 25
},
"5a4922e4-b15d-4e5f-9fb7-566ee88b7a9c": {
"points": 1,
"score": 75
},
"a0052eaa-fc4f-4235-b5d4-77209c79e0db": {
"points": -1,
"score": 25
}
}
}
},
{
"type": "ats-parameters",
"attributes": {
"candidateId": "395303",
"jobId": "893",
"createdBy": "api"
}
},
{
"type": "matching-indicators",
"id": "65bd128774158f00070d67bd",
"attributes": {
"name": "Logical Reasoning",
"score": 0,
"bracketId": "poor",
"externalId": "",
"fail": false,
"label": "Poor Fit",
"brackets": [
{
"bracketId": "good",
"cutoff": false,
"name": "Good Fit",
"treshold": 40
},
{
"bracketId": "great",
"cutoff": false,
"name": "Great Fit",
"treshold": 66
}
]
}
},
{
"type": "matching-indicators",
"id": "65bd129c74158f00070d67d4",
"attributes": {
"name": "English Proficiency",
"score": 16,
"bracketId": "poor",
"externalId": "",
"fail": false,
"label": "Below B2",
"brackets": [
{
"bracketId": "good",
"cutoff": false,
"name": "B2 and above",
"treshold": 66
}
]
}
},
{
"type": "matching-indicators",
"id": "65bd133fde98c00007e0fa12",
"attributes": {
"name": "Customer Support Personality V2TEST",
"score": 57,
"bracketId": "poor",
"externalId": "",
"fail": false,
"label": "Poor Fit",
"brackets": [
{
"bracketId": "good",
"cutoff": false,
"name": "Good Fit",
"treshold": 65
},
{
"bracketId": "great",
"cutoff": false,
"name": "Great Fit",
"treshold": 80
}
]
}
},
{
"type": "matching-indicators",
"id": "65bd1463de98c00007e0fa9d",
"attributes": {
"name": "Situational Judgement Test",
"score": 42,
"bracketId": "good",
"externalId": "",
"fail": false,
"label": "Good Fit",
"brackets": [
{
"bracketId": "good",
"cutoff": false,
"name": "Good Fit",
"treshold": 40
},
{
"bracketId": "great",
"cutoff": false,
"name": "Great Fit",
"treshold": 80
}
]
}
}
]
}
我只需要一个元素数组，其中包含“包含”数组中每个元素的名称、标签和分数，其中“type”：“matching-indicators”。
震动：
[
{
"operation": "shift",
"spec": {
"included": {
"*": {
"type": {
"matching-indicators": {
"@2,attributes": {
"name|score|label": "[&4].&"
}
}
}
}
}
}
}
]
我也用过这个：
[
{
"operation": "shift",
"spec": {
"included": {
"*": {
"attributes": {
"name": "[&2].name",
"label": "[&2].label",
"score": "[&2].score"
}
}
}
}
}
]
预期输出：
[
{
"name": "Logical Reasoning",
"score": 0,
"label": "Poor Fit"
},
{
"name": "English Proficiency",
"score": 16,
"label": "Below B2"
},
{
"name": "Customer Support Personality V2TEST",
"score": 57,
"label": "Poor Fit"
},
{
"name": "Situational Judgement Test",
"score": 42,
"label": "Good Fit"
}
]
获得的输出：
[
null,
null,
null,
null,
null,
null,
null,
null,
null,
{
"name": "Logical Reasoning",
"score": 0,
"label": "Poor Fit"
},
{
"name": "English Proficiency",
"score": 16,
"label": "Below B2"
},
{
"name": "Customer Support Personality V2TEST",
"score": 57,
"label": "Poor Fit"
},
{
"name": "Situational Judgement Test",
"score": 42,
"label": "Good Fit"
}
]
简而言之，我需要正在获取的数组，但没有出现在其开头的空元素。
null的生成是由于一些 type
matching-indicators 和 [&<int>] 类型标识符期望索引从零开始并且没有像 0 这样的间隙， 1,2,3 ...能够防止 null 生成，因此，更喜欢 &<int> 类型标识符
在一个规范中，然后将整个内容用方括号嵌套在即将到来的规范中，并获取没有键值的对象数组，例如
[
{
"operation": "shift",
"spec": {
"included": {
"*": {
"type": {
"matching-indicators": {
"@2,attributes": {
"name|score|label": "&4.&"
}
}
}
}
}
}
},
{
"operation": "shift",
"spec": {
"*": "[]"
}
}
]