I'm facing an issue while working with a filtered array of delivery objects. My goal is to extract the pods.pictures from each delivery's trackingData and generate a CSV table.
Here’s a brief overview of my flow:
1) filter array given below output
===========
[
{
"type": "delivery",
"orderId": "a75dfbe8-fde9-452c-a9dc-92fcded9cdb4",
"idleTimeSec": "0",
"perStopTimeSec": "0",
"arrivalSec": "40523",
"startSec": "40523",
"endSec": "41947",
"driveToNextSec": "-1",
"distanceToNextMt": "-1",
"stopIdx": "1",
"displayLabel": "1.1",
"trackingLink": "https://l-nk.io/WdJEWYN",
"trackingData": {
"driverId": "d1731329-2420-4de2-b5f0-0abcd1778b82",
"vehicleId": "71538fd8-47c5-4b5b-b0af-494b1e4ea1d3",
"timeInSec": "40620",
"timeInLatLng": [
"39927583",
"-105042349"
],
"timeOutSec": "41880",
"timeOutLatLng": [
"39927617",
"-105041746"
],
"status": "done",
"statusSec": "41890",
"statusLatLng": [
"39927632",
"-105041850"
],
"statusReason": null,
"timeInDetectedSec": "40523",
"timeInDetectedLatLng": [
"39927713",
"-105042102"
],
"timeOutDetectedSec": "41947",
"timeOutDetectedLatLng": [
"39927701",
"-105040564"
],
"trackedLoadMap": null,
"trackedCustomFieldMap": null,
"pods": {
"pictures": {
"4a40069f-e1bb-4909-9da9-cc10ece39fa6": {
"sec": "41973",
"latLng": [
"39927907",
"-105040668"
],
"text": "",
"token": "20250710-60d610de-00604b6e.jpg"
},
"ab1b0911-bf60-418d-b552-b53b56357966": {
"sec": "41973",
"latLng": [
"39927907",
"-105040668"
],
"text": "",
"token": "20250710-60d610de-c08ffae2.jpg"
},
"c3f3b4ad-a7ba-4315-8865-322917821eda": {
"sec": "41973",
"latLng": [
"39927907",
"-105040668"
],
"text": "",
"token": "20250710-60d610de-434d835c.jpg"
},
"c03c4cf1-cc7b-4876-8677-bd0be3e3893d": {
"sec": "41973",
"latLng": [
"39927907",
"-105040668"
],
"text": "",
"token": "20250710-60d610de-6fb4d598.jpg"
}
}
}
}
},
{
"type": "delivery",
"orderId": "2576e493-80b4-4984-804f-a85273d2ed6b",
"idleTimeSec": "0",
"perStopTimeSec": "0",
"arrivalSec": "43353",
"startSec": "43353",
"endSec": "43810",
"driveToNextSec": "-1",
"distanceToNextMt": "-1",
"stopIdx": "2",
"displayLabel": "1.2",
"trackingLink": "https://l-nk.io/7lbJb3P",
"trackingData": {
"driverId": "d1731329-2420-4de2-b5f0-0abcd1778b82",
"vehicleId": "71538fd8-47c5-4b5b-b0af-494b1e4ea1d3",
"timeInSec": "43443",
"timeInLatLng": [
"40018027",
"-105087557"
],
"timeOutSec": "43758",
"timeOutLatLng": [
"40017975",
"-105087578"
],
"status": "done",
"statusSec": "43757",
"statusLatLng": [
"40017975",
"-105087578"
],
"statusReason": null,
"timeInDetectedSec": "43353",
"timeInDetectedLatLng": [
"40018202",
"-105087489"
],
"timeOutDetectedSec": "43810",
"timeOutDetectedLatLng": [
"40017527",
"-105088630"
],
"trackedLoadMap": null,
"trackedCustomFieldMap": null,
"pods": {
"pictures": {
"f550fbec-abac-4865-862b-b06e226ff714": {
"sec": "43820",
"latLng": [
"40017250",
"-105089119"
],
"text": "",
"token": "20250710-60d610de-367be765.jpg"
},
"66e79dcd-e3ee-41f0-baf1-266fc78eb8e7": {
"sec": "43820",
"latLng": [
"40017250",
"-105089119"
],
"text": "",
"token": "20250710-60d610de-a6d5fd47.jpg"
},
"8fea88c4-5a8f-4045-87f2-636428afea1e": {
"sec": "43820",
"latLng": [
"40017250",
"-105089119"
],
"text": "",
"token": "20250710-60d610de-5e13afe6.jpg"
},
"a5334a58-09c7-4a68-98c3-f9492e9d7e25": {
"sec": "43820",
"latLng": [
"40017250",
"-105089119"
],
"text": "",
"token": "20250710-60d610de-bdac9f83.jpg"
}
}
}
}
},
{
"type": "delivery",
"orderId": "91d3bf2a-204f-4ca3-9e4d-969d4451079b",
"idleTimeSec": "0",
"perStopTimeSec": "0",
"arrivalSec": "44204",
"startSec": "44204",
"endSec": "46904",
"driveToNextSec": "1782",
"distanceToNextMt": "33620",
"stopIdx": "3",
"displayLabel": "1.3",
"trackingLink": null,
"trackingData": {
"driverId": "d1731329-2420-4de2-b5f0-0abcd1778b82",
"vehicleId": "71538fd8-47c5-4b5b-b0af-494b1e4ea1d3",
"timeInSec": "44244",
"timeInLatLng": [
"40035438",
"-105082236"
],
"timeOutSec": "-1",
"timeOutLatLng": null,
"status": null,
"statusSec": "-1",
"statusLatLng": null,
"statusReason": null,
"timeInDetectedSec": "44204",
"timeInDetectedLatLng": [
"40035300",
"-105082205"
],
"timeOutDetectedSec": "-1",
"timeOutDetectedLatLng": null,
"trackedLoadMap": null,
"trackedCustomFieldMap": null,
"pods": null
}
},
{
"type": "delivery",
"orderId": "212fac46-b212-469c-998a-e30e9fc2729c",
"idleTimeSec": "0",
"perStopTimeSec": "0",
"arrivalSec": "48686",
"startSec": "48686",
"endSec": "49886",
"driveToNextSec": "2020",
"distanceToNextMt": "45098",
"stopIdx": "4",
"displayLabel": "1.4",
"trackingLink": "https://l-nk.io/1yQV4yf"
},
{
"type": "delivery",
"orderId": "8d6a734d-063c-4260-9d24-eecdaa098bfe",
"idleTimeSec": "0",
"perStopTimeSec": "0",
"arrivalSec": "51906",
"startSec": "51906",
"endSec": "53106",
"driveToNextSec": "540",
"distanceToNextMt": "4298",
"stopIdx": "5",
"displayLabel": "1.5",
"trackingLink": "https://l-nk.io/Y7KHPHV"
},
{
"type": "delivery",
"orderId": "79d82db0-f127-4bdf-aab2-2ea3f279e0b6",
"idleTimeSec": "0",
"perStopTimeSec": "0",
"arrivalSec": "53646",
"startSec": "53646",
"endSec": "54846",
"driveToNextSec": "1623",
"distanceToNextMt": "36677",
"stopIdx": "6",
"displayLabel": "1.6",
"trackingLink": "https://l-nk.io/vHybSHh"
},
{
"type": "delivery",
"orderId": "b6d2a695-309b-4bec-b35e-616859add95a",
"idleTimeSec": "4731",
"perStopTimeSec": "0",
"arrivalSec": "56469",
"startSec": "61200",
"endSec": "62400",
"driveToNextSec": "2132",
"distanceToNextMt": "51539",
"stopIdx": "7",
"displayLabel": "1.7",
"trackingLink": "https://l-nk.io/hNbbc9N"
},
{
"type": "delivery",
"orderId": "db784a86-e97d-443c-8141-4f2663c47f73",
"idleTimeSec": "0",
"perStopTimeSec": "0",
"arrivalSec": "64532",
"startSec": "64532",
"endSec": "66632",
"driveToNextSec": "392",
"distanceToNextMt": "3235",
"stopIdx": "8",
"displayLabel": "1.8",
"trackingLink": "https://l-nk.io/ofEibXw"
}
]
my flow strcture is
2) apply to each 4 - trackingData
@{body('Filter_array')}
3) Compose 3 - POD
@{items('Apply_to_each_4_-_trackingData')?['trackingData']?['pods']}
4) Create CSV table
@{createArray(outputs('Compose_3_-_POD').pictures)}
5) Select 3
From
------------
@{split(
first(
split(
body('Create_CSV_table'),
decodeUriComponent('%0D%0A')
)
),
','
)}
Map:
---------
@outputs('Compose_3_-_POD').pictures[item()]
in apply to each loop this error
ActionFailed. An action failed. No dependent actions succeeded.
but in 3 to 8 number object
in csv table step
--------------
InvalidTemplate. Unable to process template language expressions in action 'Create_CSV_table' inputs at line '0' and column '0': 'The template language expression 'createArray(outputs('Compose_3_-_POD').pictures)' cannot be evaluated because property 'pictures' cannot be selected. Please see https://aka.ms/logicexpressions for usage details.'.
in select 3 step
--------------------
ActionConditionFailed. The execution of template action 'Select_3' is skipped: the 'runAfter' condition for action 'Create_CSV_table' is not satisfied. Expected status values 'Succeeded' and actual value 'Failed'.
-
Filter Array – Filtering delivery objects from a JSON array.
-
Apply to Each (Apply_to_each_4 - trackingData) – Iterates over the filtered array:
@{body('Filter_array')}
-
Compose 3 - POD – Extracts the pods object:
@{items('Apply_to_each_4_-_trackingData')?['trackingData']?['pods']}
-
Create CSV Table – Trying to access pictures:
@{createArray(outputs('Compose_3_-_POD').pictures)}
-
Select 3 – Attempts to map data from pictures using split logic.
Issue:
-
The flow fails at Create CSV Table with the error:
InvalidTemplate. Unable to process template language expressions in action 'Create_CSV_table' inputs... because property 'pictures' cannot be selected.
-
In Apply to Each, it shows: yaml
ActionFailed. An action failed. No dependent actions succeeded.
-
And Select 3 is skipped due to the previous failure.
My observations:
-
Items 3 to 8 in the original array don't have pods or pictures — they are either null or missing.
-
I suspect the flow breaks when trackingData.pods or pictures is not available in some items.
​​​​​​​
Question:
How can I safely extract only those pods.pictures that exist and avoid breaking the flow when they are missing?
Any guidance, workaround, or sample expression to skip null or missing fields would be highly appreciated.
Thanks in advance!
