Back to Collection Items
import sys
import chilkat2
# This example assumes the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.
http = chilkat2.Http()
queryParams = chilkat2.JsonObject()
queryParams.UpdateString("query","tempor Ut sed velit")
queryParams.UpdateInt("page[size]",-62147425)
queryParams.UpdateInt("page[number]",-62147425)
queryParams.UpdateString("include_facets","true")
http.SetRequestHeader("Accept","application/json")
# resp is a CkHttpResponse
resp = http.QuickRequestParams("GET","https://api.app.ddog-gov.com/api/v1/slo/search",queryParams)
if (http.LastMethodSuccess == False):
print(http.LastErrorText)
sys.exit()
sbResponseBody = chilkat2.StringBuilder()
resp.GetBodySb(sbResponseBody)
jResp = chilkat2.JsonObject()
jResp.LoadSb(sbResponseBody)
jResp.EmitCompact = False
print("Response Body:")
print(jResp.Emit())
respStatusCode = resp.StatusCode
print("Response Status Code = " + str(respStatusCode))
if (respStatusCode >= 400):
print("Response Header:")
print(resp.Header)
print("Failed.")
sys.exit()
# Sample JSON response:
# (Sample code for parsing the JSON response is shown below)
# {
# "data": {
# "attributes": {
# "facets": {
# "all_tags": [
# {
# "count": -8530751,
# "name": "est cillum id ex"
# },
# {
# "count": 20390494,
# "name": "adipisicing minim quis velit dolore"
# }
# ],
# "creator_name": [
# {
# "count": 77247452,
# "name": "cupidatat elit eu id aute"
# },
# {
# "count": -77371710,
# "name": "dolore"
# }
# ],
# "env_tags": [
# {
# "count": -42199690,
# "name": "dolor eiusmod"
# },
# {
# "count": -60615528,
# "name": "commodo mollit"
# }
# ],
# "service_tags": [
# {
# "count": 49217615,
# "name": "aute cupidatat"
# },
# {
# "count": 77659232,
# "name": "est Ut aute"
# }
# ],
# "slo_type": [
# {
# "count": 55153641,
# "name": 41482978.922150195
# },
# {
# "count": 11427450,
# "name": 85748817.01266047
# }
# ],
# "target": [
# {
# "count": 96778717,
# "name": -37511597.68983867
# },
# {
# "count": 15549994,
# "name": 30406993.57594505
# }
# ],
# "team_tags": [
# {
# "count": -61109884,
# "name": "laborum ex esse proident"
# },
# {
# "count": 68412080,
# "name": "nisi qui cillum exercitation"
# }
# ],
# "timeframe": [
# {
# "count": -21958451,
# "name": "fugiat"
# },
# {
# "count": 12824105,
# "name": "tempor adipisi"
# }
# ]
# },
# "slos": [
# {
# "data": {
# "attributes": {
# "all_tags": [
# "env:prod",
# "app:core"
# ],
# "created_at": 2857983,
# "creator": {
# "email": "non Lorem",
# "id": 39288042,
# "name": "voluptate"
# },
# "description": "fugiat sit in quis",
# "env_tags": [
# "irure tempor",
# "laborum reprehenderi"
# ],
# "groups": [
# "env:prod",
# "role:mysql"
# ],
# "modified_at": -85796945,
# "monitor_ids": [
# 99205206,
# 23793820
# ],
# "name": "Custom Metric SLO",
# "overall_status": [
# {
# "error": "occaecat dolore",
# "error_budget_remaining": 100,
# "indexed_at": 1662496260,
# "raw_error_budget_remaining": {
# "unit": "requests",
# "value": 60
# },
# "span_precision": 2,
# "state": "ok",
# "status": 100,
# "target": 99,
# "timeframe": "30d"
# },
# {
# "error": "in officia",
# "error_budget_remaining": 100,
# "indexed_at": 1662496260,
# "raw_error_budget_remaining": {
# "unit": "requests",
# "value": 60
# },
# "span_precision": 2,
# "state": "ok",
# "status": 100,
# "target": 99,
# "timeframe": "30d"
# }
# ],
# "query": {
# "denominator": "sum:my.custom.metric{*}.as_count()",
# "metrics": [
# "my.custom.metric",
# "my.other.custom.metric"
# ],
# "numerator": "sum:my.custom.metric{type:good}.as_count()"
# },
# "service_tags": [
# "aute amet dolor pariatur mollit",
# "officia"
# ],
# "slo_type": "metric",
# "status": {
# "calculation_error": "qui",
# "error_budget_remaining": 100,
# "indexed_at": 1662496260,
# "raw_error_budget_remaining": {
# "unit": "requests",
# "value": 60
# },
# "sli": 100,
# "span_precision": 2,
# "state": "ok"
# },
# "team_tags": [
# "quis veniam magna",
# "ad"
# ],
# "thresholds": [
# {
# "target": 95,
# "target_display": "95",
# "timeframe": "7d"
# },
# {
# "target": 95,
# "target_display": "95",
# "timeframe": "30d",
# "warning": 97,
# "warning_display": "97"
# }
# ]
# },
# "id": "sed fugiat est cillum",
# "type": "mollit dolore"
# }
# },
# {
# "data": {
# "attributes": {
# "all_tags": [
# "env:prod",
# "app:core"
# ],
# "created_at": -97407922,
# "creator": {
# "email": "in nulla",
# "id": -4202515,
# "name": "elit et consequat"
# },
# "description": "dolor sed cupidatat pariatur sint",
# "env_tags": [
# "magna ex pariatur dolore sed",
# "velit dolor aute in nostrud"
# ],
# "groups": [
# "env:prod",
# "role:mysql"
# ],
# "modified_at": -32142227,
# "monitor_ids": [
# 83809238,
# -63596037
# ],
# "name": "Custom Metric SLO",
# "overall_status": [
# {
# "error": "reprehenderit cupidat",
# "error_budget_remaining": 100,
# "indexed_at": 1662496260,
# "raw_error_budget_remaining": {
# "unit": "requests",
# "value": 60
# },
# "span_precision": 2,
# "state": "ok",
# "status": 100,
# "target": 99,
# "timeframe": "30d"
# },
# {
# "error": "consequat",
# "error_budget_remaining": 100,
# "indexed_at": 1662496260,
# "raw_error_budget_remaining": {
# "unit": "requests",
# "value": 60
# },
# "span_precision": 2,
# "state": "ok",
# "status": 100,
# "target": 99,
# "timeframe": "30d"
# }
# ],
# "query": {
# "denominator": "sum:my.custom.metric{*}.as_count()",
# "metrics": [
# "my.custom.metric",
# "my.other.custom.metric"
# ],
# "numerator": "sum:my.custom.metric{type:good}.as_count()"
# },
# "service_tags": [
# "magna velit",
# "occaecat tempor proident ex ea"
# ],
# "slo_type": "metric",
# "status": {
# "calculation_error": "in occaecat e",
# "error_budget_remaining": 100,
# "indexed_at": 1662496260,
# "raw_error_budget_remaining": {
# "unit": "requests",
# "value": 60
# },
# "sli": 100,
# "span_precision": 2,
# "state": "ok"
# },
# "team_tags": [
# "Ut nisi ipsum fugiat",
# "exercitation proident consequat aute"
# ],
# "thresholds": [
# {
# "target": 95,
# "target_display": "95",
# "timeframe": "7d"
# },
# {
# "target": 95,
# "target_display": "95",
# "timeframe": "30d",
# "warning": 97,
# "warning_display": "97"
# }
# ]
# },
# "id": "et sit commodo",
# "type": "Lorem ut quis"
# }
# }
# ]
# },
# "type": ""
# },
# "links": {
# "first": "voluptate veniam aliqua ea enim",
# "last": "non cupidatat amet dolore et",
# "next": "reprehenderit ex anim Lorem",
# "prev": "aute ex",
# "self": "deserunt"
# },
# "meta": {
# "pagination": {
# "first_number": 71439942,
# "last_number": -13516974,
# "next_number": -42474877,
# "number": 60934593,
# "prev_number": -25990176,
# "size": -54076764,
# "total": 58951452,
# "type": "deserunt et voluptate"
# }
# }
# }
# Sample code for parsing the JSON response...
# Use this online tool to generate parsing code from sample JSON: Generate JSON Parsing Code
v_Type = jResp.StringOf("data.type")
First = jResp.StringOf("links.first")
Last = jResp.StringOf("links.last")
v_Next = jResp.StringOf("links.next")
Prev = jResp.StringOf("links.prev")
v_Self = jResp.StringOf("links.self")
First_number = jResp.IntOf("meta.pagination.first_number")
Last_number = jResp.IntOf("meta.pagination.last_number")
Next_number = jResp.IntOf("meta.pagination.next_number")
v_Number = jResp.IntOf("meta.pagination.number")
Prev_number = jResp.IntOf("meta.pagination.prev_number")
Size = jResp.IntOf("meta.pagination.size")
Total = jResp.IntOf("meta.pagination.total")
PaginationType = jResp.StringOf("meta.pagination.type")
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.all_tags")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.all_tags[i].count")
name = jResp.StringOf("data.attributes.facets.all_tags[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.creator_name")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.creator_name[i].count")
name = jResp.StringOf("data.attributes.facets.creator_name[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.env_tags")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.env_tags[i].count")
name = jResp.StringOf("data.attributes.facets.env_tags[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.service_tags")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.service_tags[i].count")
name = jResp.StringOf("data.attributes.facets.service_tags[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.slo_type")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.slo_type[i].count")
name = jResp.StringOf("data.attributes.facets.slo_type[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.target")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.target[i].count")
name = jResp.StringOf("data.attributes.facets.target[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.team_tags")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.team_tags[i].count")
name = jResp.StringOf("data.attributes.facets.team_tags[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.facets.timeframe")
while i < count_i :
jResp.I = i
count = jResp.IntOf("data.attributes.facets.timeframe[i].count")
name = jResp.StringOf("data.attributes.facets.timeframe[i].name")
i = i + 1
i = 0
count_i = jResp.SizeOfArray("data.attributes.slos")
while i < count_i :
jResp.I = i
Created_at = jResp.IntOf("data.attributes.slos[i].data.attributes.created_at")
v_Email = jResp.StringOf("data.attributes.slos[i].data.attributes.creator.email")
Id = jResp.IntOf("data.attributes.slos[i].data.attributes.creator.id")
Name = jResp.StringOf("data.attributes.slos[i].data.attributes.creator.name")
Description = jResp.StringOf("data.attributes.slos[i].data.attributes.description")
Modified_at = jResp.IntOf("data.attributes.slos[i].data.attributes.modified_at")
AttributesName = jResp.StringOf("data.attributes.slos[i].data.attributes.name")
Denominator = jResp.StringOf("data.attributes.slos[i].data.attributes.query.denominator")
Numerator = jResp.StringOf("data.attributes.slos[i].data.attributes.query.numerator")
Slo_type = jResp.StringOf("data.attributes.slos[i].data.attributes.slo_type")
Calculation_error = jResp.StringOf("data.attributes.slos[i].data.attributes.status.calculation_error")
Error_budget_remaining = jResp.IntOf("data.attributes.slos[i].data.attributes.status.error_budget_remaining")
Indexed_at = jResp.IntOf("data.attributes.slos[i].data.attributes.status.indexed_at")
Unit = jResp.StringOf("data.attributes.slos[i].data.attributes.status.raw_error_budget_remaining.unit")
Value = jResp.IntOf("data.attributes.slos[i].data.attributes.status.raw_error_budget_remaining.value")
Sli = jResp.IntOf("data.attributes.slos[i].data.attributes.status.sli")
Span_precision = jResp.IntOf("data.attributes.slos[i].data.attributes.status.span_precision")
State = jResp.StringOf("data.attributes.slos[i].data.attributes.status.state")
dataId = jResp.StringOf("data.attributes.slos[i].data.id")
dataType = jResp.StringOf("data.attributes.slos[i].data.type")
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.all_tags")
while j < count_j :
jResp.J = j
strVal = jResp.StringOf("data.attributes.slos[i].data.attributes.all_tags[j]")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.env_tags")
while j < count_j :
jResp.J = j
strVal = jResp.StringOf("data.attributes.slos[i].data.attributes.env_tags[j]")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.groups")
while j < count_j :
jResp.J = j
strVal = jResp.StringOf("data.attributes.slos[i].data.attributes.groups[j]")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.monitor_ids")
while j < count_j :
jResp.J = j
intVal = jResp.IntOf("data.attributes.slos[i].data.attributes.monitor_ids[j]")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.overall_status")
while j < count_j :
jResp.J = j
error = jResp.StringOf("data.attributes.slos[i].data.attributes.overall_status[j].error")
error_budget_remaining = jResp.IntOf("data.attributes.slos[i].data.attributes.overall_status[j].error_budget_remaining")
indexed_at = jResp.IntOf("data.attributes.slos[i].data.attributes.overall_status[j].indexed_at")
raw_error_budget_remainingUnit = jResp.StringOf("data.attributes.slos[i].data.attributes.overall_status[j].raw_error_budget_remaining.unit")
raw_error_budget_remainingValue = jResp.IntOf("data.attributes.slos[i].data.attributes.overall_status[j].raw_error_budget_remaining.value")
span_precision = jResp.IntOf("data.attributes.slos[i].data.attributes.overall_status[j].span_precision")
state = jResp.StringOf("data.attributes.slos[i].data.attributes.overall_status[j].state")
status = jResp.IntOf("data.attributes.slos[i].data.attributes.overall_status[j].status")
target = jResp.IntOf("data.attributes.slos[i].data.attributes.overall_status[j].target")
timeframe = jResp.StringOf("data.attributes.slos[i].data.attributes.overall_status[j].timeframe")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.query.metrics")
while j < count_j :
jResp.J = j
strVal = jResp.StringOf("data.attributes.slos[i].data.attributes.query.metrics[j]")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.service_tags")
while j < count_j :
jResp.J = j
strVal = jResp.StringOf("data.attributes.slos[i].data.attributes.service_tags[j]")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.team_tags")
while j < count_j :
jResp.J = j
strVal = jResp.StringOf("data.attributes.slos[i].data.attributes.team_tags[j]")
j = j + 1
j = 0
count_j = jResp.SizeOfArray("data.attributes.slos[i].data.attributes.thresholds")
while j < count_j :
jResp.J = j
target = jResp.IntOf("data.attributes.slos[i].data.attributes.thresholds[j].target")
target_display = jResp.StringOf("data.attributes.slos[i].data.attributes.thresholds[j].target_display")
timeframe = jResp.StringOf("data.attributes.slos[i].data.attributes.thresholds[j].timeframe")
warning = jResp.IntOf("data.attributes.slos[i].data.attributes.thresholds[j].warning")
warning_display = jResp.StringOf("data.attributes.slos[i].data.attributes.thresholds[j].warning_display")
j = j + 1
i = i + 1
Curl Command
curl -G -d "query=tempor%20Ut%20sed%20velit"
-d "page[size]=-62147425"
-d "page[number]=-62147425"
-d "include_facets=true"
-H "Accept: application/json"
https://api.app.ddog-gov.com/api/v1/slo/search
Postman Collection Item JSON
{
"name": "Search for SLOs",
"request": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
}
],
"url": {
"raw": "{{baseUrl}}/api/v1/slo/search?query=tempor Ut sed velit&page[size]=-62147425&page[number]=-62147425&include_facets=true",
"host": [
"{{baseUrl}}"
],
"path": [
"api",
"v1",
"slo",
"search"
],
"query": [
{
"key": "query",
"value": "tempor Ut sed velit",
"description": "The query string to filter results based on SLO names.\nSome examples of queries include `service:<service-name>`\nand `<slo-name>`."
},
{
"key": "page[size]",
"value": "-62147425",
"description": "The number of files to return in the response `[default=10]`."
},
{
"key": "page[number]",
"value": "-62147425",
"description": "The identifier of the first page to return. This parameter is used for the pagination feature `[default=0]`."
},
{
"key": "include_facets",
"value": "true",
"description": "Whether or not to return facet information in the response `[default=false]`."
}
]
},
"description": "Get a list of service level objective objects for your organization."
},
"response": [
{
"name": "OK",
"originalRequest": {
"method": "GET",
"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"description": "Added as a part of security scheme: apikey",
"key": "DD-API-KEY",
"value": "<API Key>"
}
],
"url": {
"raw": "{{baseUrl}}/api/v1/slo/search?query=tempor Ut sed velit&page[size]=-62147425&page[number]=-62147425&include_facets=true",
"host": [
"{{baseUrl}}"
],
"path": [
"api",
"v1",
"slo",
"search"
],
"query": [
{
"key": "query",
"value": "tempor Ut sed velit",
"description": "The query string to filter results based on SLO names.\nSome examples of queries include `service:<service-name>`\nand `<slo-name>`."
},
{
"key": "page[size]",
"value": "-62147425",
"description": "The number of files to return in the response `[default=10]`."
},
{
"key": "page[number]",
"value": "-62147425",
"description": "The identifier of the first page to return. This parameter is used for the pagination feature `[default=0]`."
},
{
"key": "include_facets",
"value": "true",
"description": "Whether or not to return facet information in the response `[default=false]`."
}
]
}
},
"status": "OK",
"code": 200,
"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
"value": "application/json"
}
],
"cookie": [
],
"body": "{\n \"data\": {\n \"attributes\": {\n \"facets\": {\n \"all_tags\": [\n {\n \"count\": -8530751,\n \"name\": \"est cillum id ex\"\n },\n {\n \"count\": 20390494,\n \"name\": \"adipisicing minim quis velit dolore\"\n }\n ],\n \"creator_name\": [\n {\n \"count\": 77247452,\n \"name\": \"cupidatat elit eu id aute\"\n },\n {\n \"count\": -77371710,\n \"name\": \"dolore\"\n }\n ],\n \"env_tags\": [\n {\n \"count\": -42199690,\n \"name\": \"dolor eiusmod\"\n },\n {\n \"count\": -60615528,\n \"name\": \"commodo mollit\"\n }\n ],\n \"service_tags\": [\n {\n \"count\": 49217615,\n \"name\": \"aute cupidatat\"\n },\n {\n \"count\": 77659232,\n \"name\": \"est Ut aute\"\n }\n ],\n \"slo_type\": [\n {\n \"count\": 55153641,\n \"name\": 41482978.922150195\n },\n {\n \"count\": 11427450,\n \"name\": 85748817.01266047\n }\n ],\n \"target\": [\n {\n \"count\": 96778717,\n \"name\": -37511597.68983867\n },\n {\n \"count\": 15549994,\n \"name\": 30406993.57594505\n }\n ],\n \"team_tags\": [\n {\n \"count\": -61109884,\n \"name\": \"laborum ex esse proident\"\n },\n {\n \"count\": 68412080,\n \"name\": \"nisi qui cillum exercitation\"\n }\n ],\n \"timeframe\": [\n {\n \"count\": -21958451,\n \"name\": \"fugiat\"\n },\n {\n \"count\": 12824105,\n \"name\": \"tempor adipisi\"\n }\n ]\n },\n \"slos\": [\n {\n \"data\": {\n \"attributes\": {\n \"all_tags\": [\n \"env:prod\",\n \"app:core\"\n ],\n \"created_at\": 2857983,\n \"creator\": {\n \"email\": \"non Lorem\",\n \"id\": 39288042,\n \"name\": \"voluptate\"\n },\n \"description\": \"fugiat sit in quis\",\n \"env_tags\": [\n \"irure tempor\",\n \"laborum reprehenderi\"\n ],\n \"groups\": [\n \"env:prod\",\n \"role:mysql\"\n ],\n \"modified_at\": -85796945,\n \"monitor_ids\": [\n 99205206,\n 23793820\n ],\n \"name\": \"Custom Metric SLO\",\n \"overall_status\": [\n {\n \"error\": \"occaecat dolore\",\n \"error_budget_remaining\": 100,\n \"indexed_at\": 1662496260,\n \"raw_error_budget_remaining\": {\n \"unit\": \"requests\",\n 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{
"name": "Bad Request",
"originalRequest": {
"method": "GET",
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{
"key": "Accept",
"value": "application/json"
},
{
"description": "Added as a part of security scheme: apikey",
"key": "DD-API-KEY",
"value": "<API Key>"
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"host": [
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},
{
"key": "page[size]",
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"description": "The number of files to return in the response `[default=10]`."
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{
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},
{
"key": "include_facets",
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}
},
"status": "Bad Request",
"code": 400,
"_postman_previewlanguage": "json",
"header": [
{
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"cookie": [
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"body": "{\n \"errors\": [\n \"Bad Request\",\n \"Bad Request\"\n ]\n}"
},
{
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"originalRequest": {
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{
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},
{
"description": "Added as a part of security scheme: apikey",
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"value": "<API Key>"
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"url": {
"raw": "{{baseUrl}}/api/v1/slo/search?query=tempor Ut sed velit&page[size]=-62147425&page[number]=-62147425&include_facets=true",
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},
{
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},
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}
},
"status": "Forbidden",
"code": 403,
"_postman_previewlanguage": "json",
"header": [
{
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"cookie": [
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"body": "{\n \"errors\": [\n \"Bad Request\",\n \"Bad Request\"\n ]\n}"
},
{
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"originalRequest": {
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"header": [
{
"key": "Accept",
"value": "application/json"
},
{
"description": "Added as a part of security scheme: apikey",
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{
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"_postman_previewlanguage": "json",
"header": [
{
"key": "Content-Type",
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}
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"cookie": [
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"body": "{\n \"errors\": [\n \"Bad Request\",\n \"Bad Request\"\n ]\n}"
}
]
}
