Best way to build denormilazed dataframe with pandas from spotify API - python

I just downloaded some json from spotify and took a look into the pd.normalize_json().
But if I normalise the data i still have dictionaries within my dataframe. Also setting the level doesnt help.
DATA I want to have in my dataframe:
{
"collaborative": false,
"description": "",
"external_urls": {
"spotify": "https://open.spotify.com/playlist/5"
},
"followers": {
"href": null,
"total": 0
},
"href": "https://api.spotify.com/v1/playlists/5?additional_types=track",
"id": "5",
"images": [
{
"height": 640,
"url": "https://i.scdn.co/image/a",
"width": 640
}
],
"name": "Another",
"owner": {
"display_name": "user",
"external_urls": {
"spotify": "https://open.spotify.com/user/user"
},
"href": "https://api.spotify.com/v1/users/user",
"id": "user",
"type": "user",
"uri": "spotify:user:user"
},
"primary_color": null,
"public": true,
"snapshot_id": "M2QxNTcyYTkMDc2",
"tracks": {
"href": "https://api.spotify.com/v1/playlists/100&additional_types=track",
"items": [
{
"added_at": "2020-12-13T18:34:09Z",
"added_by": {
"external_urls": {
"spotify": "https://open.spotify.com/user/user"
},
"href": "https://api.spotify.com/v1/users/user",
"id": "user",
"type": "user",
"uri": "spotify:user:user"
},
"is_local": false,
"primary_color": null,
"track": {
"album": {
"album_type": "album",
"artists": [
{
"external_urls": {
"spotify": "https://open.spotify.com/artist/1dfeR4Had"
},
"href": "https://api.spotify.com/v1/artists/1dfDbWqFHLkxsg1d",
"id": "1dfeR4HaWDbWqFHLkxsg1d",
"name": "Q",
"type": "artist",
"uri": "spotify:artist:1dfeRqFHLkxsg1d"
}
],
"available_markets": [
"CA",
"US"
],
"external_urls": {
"spotify": "https://open.spotify.com/album/6wPXmlLzZ5cCa"
},
"href": "https://api.spotify.com/v1/albums/6wPXUJ9LzZ5cCa",
"id": "6wPXUmYJ9zZ5cCa",
"images": [
{
"height": 640,
"url": "https://i.scdn.co/image/ab676620a47",
"width": 640
},
{
"height": 300,
"url": "https://i.scdn.co/image/ab67616d0620a47",
"width": 300
},
{
"height": 64,
"url": "https://i.scdn.co/image/ab603e6620a47",
"width": 64
}
],
"name": "The (Deluxe ",
"release_date": "1920-07-17",
"release_date_precision": "day",
"total_tracks": 15,
"type": "album",
"uri": "spotify:album:6m5cCa"
},
"artists": [
{
"external_urls": {
"spotify": "https://open.spotify.com/artist/1dg1d"
},
"href": "https://api.spotify.com/v1/artists/1dsg1d",
"id": "1dfeR4HaWDbWqFHLkxsg1d",
"name": "Q",
"type": "artist",
"uri": "spotify:artist:1dxsg1d"
}
],
"available_markets": [
"CA",
"US"
],
"disc_number": 1,
"duration_ms": 21453,
"episode": false,
"explicit": false,
"external_ids": {
"isrc": "GBU6015"
},
"external_urls": {
"spotify": "https://open.spotify.com/track/5716J"
},
"href": "https://api.spotify.com/v1/tracks/5716J",
"id": "5716J",
"is_local": false,
"name": "Another",
"popularity": 73,
"preview_url": null,
"track": true,
"track_number": 3,
"type": "track",
"uri": "spotify:track:516J"
},
"video_thumbnail": {
"url": null
}
}
],
"limit": 100,
"next": null,
"offset": 0,
"previous": null,
"total": 1
},
"type": "playlist",
"uri": "spotify:playlist:fek"
}
So what are best practices to read nested data like this into one dataframe in pandas?
I'm glad for any advice.
EDIT:
so basically I want all keys as columns in my dataframe. But with normalise it stops at "tracks.items" and if I normalise this again i have the recursive problem again.

It depends on the information you are looking for. Take a look at pandas.read_json() to see if that can work. Also you can select data as such
json_output = {"collaborative": 'false',"description": "", "external_urls": {"spotify": "https://open.spotify.com/playlist/5"}}
df['collaborative'] = json_output['collaborative'] #set value of your df to value of returned json values

Related

Modify the value of a field of a specific nested object (its index) depending on a condition

I would like to modify the value of a field on a specific index of a nested type depending on another value of the same nested object or a field outside of the nested object.
As example, I have the current mapping of my index feed:
{
"feed": {
"mappings": {
"properties": {
"attacks_ids": {
"type": "keyword"
},
"created_by": {
"type": "keyword"
},
"date": {
"type": "date"
},
"groups_related": {
"type": "keyword"
},
"indicators": {
"type": "nested",
"properties": {
"date": {
"type": "date"
},
"description": {
"type": "text"
},
"role": {
"type": "keyword"
},
"type": {
"type": "keyword"
},
"value": {
"type": "keyword"
}
}
},
"malware_families": {
"type": "keyword"
},
"published": {
"type": "boolean"
},
"references": {
"type": "keyword"
},
"tags": {
"type": "keyword"
},
"targeted_countries": {
"type": "keyword"
},
"title": {
"type": "text"
},
"tlp": {
"type": "keyword"
}
}
}
}
}
Take the following document as example:
{
"took": 194,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 1,
"hits": [
{
"_index": "feed",
"_type": "_doc",
"_id": "W3CS7IABovFpcGfZjfyu",
"_score": 1,
"_source": {
"title": "Test",
"date": "2022-05-22T16:21:09.159711",
"created_by": "finch",
"tlp": "white",
"published": true,
"references": [
"test",
"test"
],
"tags": [
"tag1",
"tag2"
],
"targeted_countries": [
"Italy",
"Germany"
],
"malware_families": [
"family1",
"family2"
],
"groups_related": [
"group1",
"griup2"
],
"attacks_ids": [
""
],
"indicators": [
{
"value": "testest",
"description": "This is a test",
"type": "sha256",
"role": "file",
"date": "2022-05-22T16:21:09.159560"
},
{
"value": "testest2",
"description": "This is a test 2",
"type": "ipv4",
"role": "c2",
"date": "2022-05-22T16:21:09.159699"
}
]
}
}
]
}
}
I would like to make this update: indicators[0].value = 'changed'
if _id == 'W3CS7IABovFpcGfZjfyu'
or if title == 'some_title'
or if indicators[0].role == 'c2'
I already tried with a script, but it seems I can't manage to get it work, I hope the explanation is clear, ask any question if not, thank you.
Edit 1:
I managed to make it work, however it needs the _id, still looking for a way to do that without it.
My partial solution:
update = Pulse.get(id="XHCz7IABovFpcGfZWfz9") #Pulse is my document
update.update(script="for (indicator in ctx._source.indicators) {if (indicator.value=='changed2') {indicator.value='changed3'}}")
# Modify depending on the value of a field inside the same nested object

Loading variables into json string using python for MS teams

The 3rd party system I am using (vendor product) still uses Python 2.7 and doesn't support Python 3+ so bear with me, I'm fully aware Python 3 is out and this is a limitation of the system I have to use rather than a choice.
I am trying to do an integration between this third party product and MS teams - basically, the third party system provides data, I read this into my Python script and output a message to Teams using a webhook. It mostly works, but I'm struggling to load in some of the variables from the systems data.
For example, in my code, I use the following:
messageID='"{}"'.format(item["messageId"])
recipient='"{}"'.format(item["recipient"]["email"])
subject='"{}"'.format(item["subject"])
sender='"{}"'.format(item["sender"]["email"])
which has output like this:
messageId="34239482030783472#test.net"
recipient="testuser#domain.com"
subject="Email subject here"
sender="sender#domain2.com"
This is all fine, the trouble comes when I need to format my string to post to the Teams webhook.
It currently looks like:
teams_card='{"#type": "MessageCard","#context": "http://schema.org/extensions","themeColor": "0076D7","summary": “PTR”,”sections": [{"activityTitle": "PTR Incident Created","activitySubtitle": “End “User Exposed to Phishing Threat,”facts": [{"name": “Message” ID,”value": %s}, {"name": "Subject”,”value": %s},{“name": "End User","value": %s},{“name": “sender”,”value": %s}],”markdown": true}],"potentialAction": [{"#type": "OpenUri","name": "View Related Emails","targets": [{"os": "default","uri": "https://maskedurlhere.com”}]}]}’ % (messageId,subject,recipient,sender)
which throws an error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: not enough arguments for format string
I tried to use .format option also, but this fails with a different error:
teams_card='{"#type": "MessageCard","#context": "http://schema.org/extensions","themeColor": "0076D7","summary": “PTR”,”sections": [{"activityTitle": "PTR Incident Created","activitySubtitle": “End “User Exposed to Phishing Threat,”facts": [{"name": “Message” ID,”value": %s}, {"name": "Subject”,”value": %s},{“name": "End User","value": %s},{“name": “sender”,”value": %s}],”markdown": true}],"potentialAction": [{"#type": "OpenUri","name": "View Related Emails","targets": [{"os": "default","uri": "https://maskedurlhere.com”}]}]}’.format(messageId,subject,recipient,sender)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
KeyError: '"#type"'
The teams card variable is fine and posts to Teams successfully when it's just text, but trying to load in these variables doesn't seem to work at all.
Any ideas?
To pass dynamic values in Json you need to use format like ${value}
Please follow below example json format
Template JSON
{
"type": "AdaptiveCard",
"body": [
{
"type": "Container",
"style": "emphasis",
"items": [
{
"type": "ColumnSet",
"columns": [
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"size": "Large",
"weight": "Bolder",
"text": "**EXPENSE APPROVAL**",
"wrap": true
}
],
"width": "stretch"
},
{
"type": "Column",
"items": [
{
"type": "Image",
"url": "${status_url}",
"altText": "${status}",
"height": "30px"
}
],
"width": "auto"
}
]
}
],
"bleed": true
},
{
"type": "Container",
"items": [
{
"type": "ColumnSet",
"columns": [
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"size": "ExtraLarge",
"text": "${purpose}",
"wrap": true
}
],
"width": "stretch"
},
{
"type": "Column",
"items": [
{
"type": "ActionSet",
"actions": [
{
"type": "Action.OpenUrl",
"title": "EXPORT AS PDF",
"url": "https://adaptivecards.io"
}
]
}
],
"width": "auto"
}
]
},
{
"type": "TextBlock",
"spacing": "Small",
"size": "Small",
"weight": "Bolder",
"color": "Accent",
"text": "[${code}](https://adaptivecards.io)",
"wrap": true
},
{
"type": "FactSet",
"spacing": "Large",
"facts": [
{
"title": "Submitted By",
"value": "**${created_by_name}** ${creater_email}"
},
{
"title": "Duration",
"value": "${formatTicks(min(select(expenses, x, int(x.created_by))), 'yyyy-MM-dd')} - ${formatTicks(max(select(expenses, x, int(x.created_by))), 'yyyy-MM-dd')}"
},
{
"title": "Submitted On",
"value": "${formatDateTime(submitted_date, 'yyyy-MM-dd')}"
},
{
"title": "Reimbursable Amount",
"value": "$${formatNumber(sum(select(expenses, x, if(x.is_reimbursable, x.total, 0))), 2)}"
},
{
"title": "Awaiting approval from",
"value": "**${approver}** ${approver_email}"
},
{
"title": "Submitted to",
"value": "**${other_submitter}** ${other_submitter_email}"
}
]
}
]
},
{
"type": "Container",
"spacing": "Large",
"style": "emphasis",
"items": [
{
"type": "ColumnSet",
"columns": [
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"weight": "Bolder",
"text": "DATE",
"wrap": true
}
],
"width": "auto"
},
{
"type": "Column",
"spacing": "Large",
"items": [
{
"type": "TextBlock",
"weight": "Bolder",
"text": "CATEGORY",
"wrap": true
}
],
"width": "stretch"
},
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"weight": "Bolder",
"text": "AMOUNT",
"wrap": true
}
],
"width": "auto"
}
]
}
],
"bleed": true
},
{
"$data": "${expenses}",
"type": "Container",
"items": [
{
"type": "ColumnSet",
"columns": [
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"text": "${formatDateTime(created_time, 'MM-dd')}",
"wrap": true
}
],
"width": "auto"
},
{
"type": "Column",
"spacing": "Medium",
"items": [
{
"type": "TextBlock",
"text": "${description}",
"wrap": true
}
],
"width": "stretch"
},
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"text": "$${formatNumber(total, 2)}",
"wrap": true
}
],
"width": "auto"
},
{
"type": "Column",
"spacing": "Small",
"selectAction": {
"type": "Action.ToggleVisibility",
"targetElements": [
"cardContent${$index}",
"chevronDown${$index}",
"chevronUp${$index}"
]
},
"verticalContentAlignment": "Center",
"items": [
{
"type": "Image",
"id": "chevronDown${$index}",
"url": "https://adaptivecards.io/content/down.png",
"width": "20px",
"altText": "${description} $${total} collapsed"
},
{
"type": "Image",
"id": "chevronUp${$index}",
"url": "https://adaptivecards.io/content/up.png",
"width": "20px",
"altText": "${description} $${total} expanded",
"isVisible": false
}
],
"width": "auto"
}
]
},
{
"type": "Container",
"id": "cardContent${$index}",
"isVisible": false,
"items": [
{
"type": "Container",
"items": [
{
"$data": "${custom_fields}",
"type": "TextBlock",
"text": "* ${value}",
"isSubtle": true,
"wrap": true
},
{
"type": "Container",
"items": [
{
"type": "Input.Text",
"id": "comment${$index}",
"placeholder": "Add your comment here."
}
]
}
]
},
{
"type": "Container",
"items": [
{
"type": "ColumnSet",
"columns": [
{
"type": "Column",
"items": [
{
"type": "ActionSet",
"actions": [
{
"type": "Action.Submit",
"title": "Send",
"data": {
"id": "_qkQW8dJlUeLVi7ZMEzYVw",
"action": "comment",
"lineItem": 1
}
}
]
}
],
"width": "auto"
}
]
}
]
}
]
}
]
},
{
"type": "ColumnSet",
"spacing": "Large",
"separator": true,
"columns": [
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"horizontalAlignment": "Right",
"text": "Total Expense Amount \t",
"wrap": true
},
{
"type": "TextBlock",
"horizontalAlignment": "Right",
"text": "Non-reimbursable Amount",
"wrap": true
},
{
"type": "TextBlock",
"horizontalAlignment": "Right",
"text": "Advance Amount",
"wrap": true
}
],
"width": "stretch"
},
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"text": "$${formatNumber(sum(select(expenses, x, x.total)), 2)}",
"wrap": true
},
{
"type": "TextBlock",
"text": "(-) $${formatNumber(sum(select(expenses, x, if(x.is_reimbursable, 0, x.total))), 2)} \t",
"wrap": true
},
{
"type": "TextBlock",
"text": "(-) 0.00 \t",
"wrap": true
}
],
"width": "auto"
},
{
"type": "Column",
"width": "auto"
}
]
},
{
"type": "Container",
"style": "emphasis",
"items": [
{
"type": "ColumnSet",
"columns": [
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"horizontalAlignment": "Right",
"text": "Amount to be Reimbursed",
"wrap": true
}
],
"width": "stretch"
},
{
"type": "Column",
"items": [
{
"type": "TextBlock",
"weight": "Bolder",
"text": "$${formatNumber(sum(select(expenses, x, if(x.is_reimbursable, x.total, 0))), 2)}",
"wrap": true
}
],
"width": "auto"
},
{
"type": "Column",
"width": "auto"
}
]
}
],
"bleed": true
},
{
"type": "ColumnSet",
"columns": [
{
"type": "Column",
"selectAction": {
"type": "Action.ToggleVisibility",
"targetElements": [
"cardContent4",
"showHistory",
"hideHistory"
]
},
"verticalContentAlignment": "Center",
"items": [
{
"type": "TextBlock",
"id": "showHistory",
"horizontalAlignment": "Right",
"color": "Accent",
"text": "Show history",
"wrap": true
},
{
"type": "TextBlock",
"id": "hideHistory",
"horizontalAlignment": "Right",
"color": "Accent",
"text": "Hide history",
"wrap": true,
"isVisible": false
}
],
"width": 1
}
]
},
{
"type": "Container",
"id": "cardContent4",
"isVisible": false,
"items": [
{
"type": "Container",
"items": [
{
"type": "TextBlock",
"text": "* Expense submitted by **${created_by_name}** on {{DATE(${formatDateTime(created_date, 'yyyy-MM-ddTHH:mm:ssZ')}, SHORT)}}",
"isSubtle": true,
"wrap": true
},
{
"type": "TextBlock",
"text": "* Expense ${expenses[0].status} by **${expenses[0].approver}** on {{DATE(${formatDateTime(approval_date, 'yyyy-MM-ddTHH:mm:ssZ')}, SHORT)}}",
"isSubtle": true,
"wrap": true
}
]
}
]
},
{
"type": "Container",
"items": [
{
"type": "ActionSet",
"actions": [
{
"type": "Action.Submit",
"title": "Approve",
"style": "positive",
"data": {
"id": "_qkQW8dJlUeLVi7ZMEzYVw",
"action": "approve"
}
},
{
"type": "Action.ShowCard",
"title": "Reject",
"style": "destructive",
"card": {
"type": "AdaptiveCard",
"body": [
{
"type": "Input.Text",
"id": "RejectCommentID",
"placeholder": "Please specify an appropriate reason for rejection.",
"isMultiline": true
}
],
"actions": [
{
"type": "Action.Submit",
"title": "Send",
"data": {
"id": "_qkQW8dJlUeLVi7ZMEzYVw",
"action": "reject"
}
}
],
"$schema": "http://adaptivecards.io/schemas/adaptive-card.json"
}
}
]
}
]
}
],
"$schema": "http://adaptivecards.io/schemas/adaptive-card.json",
"version": "1.2",
"fallbackText": "This card requires Adaptive Cards v1.2 support to be rendered properly."
}
Data Json
{
"code": "ER-13052",
"message": "success",
"created_by_name" : "Matt Hidinger",
"created_date" : "2019-07-15T18:33:12+0800",
"submitted_date": "2019-04-14T18:33:12+0800",
"creater_email" : "matt#contoso.com",
"status" : "Pending",
"status_url" : "https://adaptivecards.io/content/pending.png",
"approver": "Thomas",
"purpose" : "Trip to UAE",
"approval_date" : "2019-07-15T22:33:12+0800",
"approver" : "Thomas",
"approver_email" : "thomas#contoso.com",
"other_submitter" : "David",
"other_submitter_email" : "david#contoso.com",
"expenses": [
{
"expense_id": "16367000000083065",
"approver" : "Thomas",
"date": "2017-02-21",
"description": "Air Travel Expense",
"created_by": "636965431200000000",
"created_by_name": "PATRICIA",
"employee_number": "E001",
"currency_id": "16367000000000097",
"currency_code": "USD",
"paid_through_account_id": "16367000000036003",
"paid_through_account_name": "Employee Reimbursements",
"bcy_total": 13900.79,
"bcy_subtotal": 13900.79,
"total": 300,
"total_without_tax": 300,
"is_billable": true,
"is_reimbursable": true,
"reference_number": "DD145",
"due_days": "Due in 15 days",
"merchant_id": "16367000000074027",
"merchant_name": "ABS Solutions",
"status": "approved",
"created_time": "2019-06-19T18:33:12+0800",
"last_modified_time": "2017-02-21T18:42:46+0530",
"receipt_name": "receipt1.jpg",
"report_id": "16367000000083075",
"mileage_type": "non_mileage",
"report_name": "Purchase",
"is_receipt_only": false,
"distance": 0,
"per_diem_rate": 0,
"per_diem_days": 0,
"per_diem_id": "",
"per_diem_name": "",
"expense_type": "non_mileage",
"location": "Washington",
"receipt_type": "jpg",
"policy_violated": false,
"comments_count": 0,
"report_status": "submitted",
"price_precision": 2,
"mileage_rate": 0,
"mileage_unit": "km",
"receipt_status": "processed",
"is_uncategorized": false,
"is_expired": false,
"gl_code": "LG001",
"exchange_rate": 66.943366,
"start_reading": "",
"end_reading": "",
"payment_mode": "Check",
"customer_id": "27927000000075081",
"customer_name": "ACME Corp.",
"custom_fields": [
{
"customfield_id": "16367000000277001",
"label": "Other Name",
"value": "Leg 1 on Tue, Jun 19th, 2019 at 6:00 AM."
},
{
"customfield_id": "16367000000277001",
"label": "Other Name",
"value": "Leg 2 on Tue, Jun 19th, 2019 at 7:15 PM."
}
],
"project_id": "27927000001243001",
"project_name": "Coffee Research",
"transaction_description": "",
"tax_id": "16367000000086001",
"tax_name": "Sales Tax",
"tax_percentage": 2,
"amount": 207.65,
"is_inclusive_tax": false,
"vehicle_type": "Bike",
"vehicle_id": "17456000000078029",
"fuel_type": "lpg",
"engine_capacity_range": "between_1401cc_and_1600cc",
"is_personal": false,
"policy_id": "16367000000092011",
"policy_name": "LIC",
"documents": [
{
"file_name": "receipt1.jpg",
"file_size_formatted": "71.8 KB",
"attachment_order": 1,
"document_id": "16367000000083071"
}
],
"reimbursement_reference": "",
"reimbursement_date": "",
"reimbursement_paid_through_account_id": "",
"reimbursement_paid_through_account_name": "",
"reimbursement_currency_id": "",
"reimbursement_currency_code": ""
},
{
"expense_id": "16367000000083065",
"date": "2019-06-19",
"description": "Auto Mobile Expense",
"created_by": "636965431200000000",
"created_by_name": "PATRICIA",
"employee_number": "E001",
"currency_id": "16367000000000097",
"currency_code": "USD",
"paid_through_account_id": "16367000000036003",
"paid_through_account_name": "Employee Reimbursements",
"bcy_total": 13900.79,
"bcy_subtotal": 13900.79,
"total": 100,
"total_without_tax": 100,
"is_billable": true,
"is_reimbursable": true,
"reference_number": "DD145",
"due_days": "Due in 15 days",
"merchant_id": "16367000000074027",
"merchant_name": "ABS Solutions",
"status": "submitted",
"created_time": "2019-06-19T18:33:12+0800",
"last_modified_time": "2017-02-21T18:42:46+0530",
"receipt_name": "receipt1.jpg",
"report_id": "16367000000083075",
"mileage_type": "non_mileage",
"report_name": "Purchase",
"is_receipt_only": false,
"distance": 0,
"per_diem_rate": 0,
"per_diem_days": 0,
"per_diem_id": "",
"per_diem_name": "",
"expense_type": "non_mileage",
"location": "Washington",
"receipt_type": "jpg",
"policy_violated": false,
"comments_count": 0,
"report_status": "submitted",
"price_precision": 2,
"mileage_rate": 0,
"mileage_unit": "km",
"receipt_status": "processed",
"is_uncategorized": false,
"is_expired": false,
"gl_code": "LG001",
"exchange_rate": 66.943366,
"start_reading": "",
"end_reading": "",
"payment_mode": "Check",
"customer_id": "27927000000075081",
"customer_name": "ACME Corp.",
"custom_fields": [
{
"customfield_id": "16367000000277001",
"label": "Other Name",
"value": " Contoso Car Rentrals, Tues 6/19 at 7:00 AM"
}
],
"project_id": "27927000001243001",
"project_name": "Coffee Research",
"transaction_description": "",
"tax_id": "16367000000086001",
"tax_name": "Sales Tax",
"tax_percentage": 2,
"amount": 207.65,
"is_inclusive_tax": false,
"vehicle_type": "Bike",
"vehicle_id": "17456000000078029",
"fuel_type": "lpg",
"engine_capacity_range": "between_1401cc_and_1600cc",
"is_personal": false,
"policy_id": "16367000000092011",
"policy_name": "LIC",
"documents": [
{
"file_name": "receipt1.jpg",
"file_size_formatted": "71.8 KB",
"attachment_order": 1,
"document_id": "16367000000083071"
}
],
"reimbursement_reference": "",
"reimbursement_date": "",
"reimbursement_paid_through_account_id": "",
"reimbursement_paid_through_account_name": "",
"reimbursement_currency_id": "",
"reimbursement_currency_code": ""
},
{
"expense_id": "16367000000083065",
"date": "2019-06-21",
"description": "Excess Baggage Cost",
"created_by": "636967159200000000",
"created_by_name": "PATRICIA",
"employee_number": "E001",
"currency_id": "16367000000000097",
"currency_code": "USD",
"paid_through_account_id": "16367000000036003",
"paid_through_account_name": "Employee Reimbursements",
"bcy_total": 13900.79,
"bcy_subtotal": 13900.79,
"total": 50.38,
"total_without_tax": 4.3,
"is_billable": true,
"is_reimbursable": false,
"reference_number": "DD145",
"due_days": "Due in 15 days",
"merchant_id": "16367000000074027",
"merchant_name": "ABS Solutions",
"status": "submitted",
"created_time": "2019-06-21T18:33:12+0800",
"last_modified_time": "2017-02-21T18:42:46+0530",
"receipt_name": "receipt1.jpg",
"report_id": "16367000000083075",
"mileage_type": "non_mileage",
"report_name": "Purchase",
"is_receipt_only": false,
"distance": 0,
"per_diem_rate": 0,
"per_diem_days": 0,
"per_diem_id": "",
"per_diem_name": "",
"expense_type": "non_mileage",
"location": "Washington",
"receipt_type": "jpg",
"policy_violated": false,
"comments_count": 0,
"report_status": "submitted",
"price_precision": 2,
"mileage_rate": 0,
"mileage_unit": "km",
"receipt_status": "processed",
"is_uncategorized": false,
"is_expired": false,
"gl_code": "LG001",
"exchange_rate": 66.943366,
"start_reading": "",
"end_reading": "",
"payment_mode": "Check",
"customer_id": "27927000000075081",
"customer_name": "ACME Corp.",
"custom_fields": [
],
"project_id": "27927000001243001",
"project_name": "Coffee Research",
"transaction_description": "",
"tax_id": "16367000000086001",
"tax_name": "Sales Tax",
"tax_percentage": 2,
"amount": 207.65,
"is_inclusive_tax": false,
"vehicle_type": "Bike",
"vehicle_id": "17456000000078029",
"fuel_type": "lpg",
"engine_capacity_range": "between_1401cc_and_1600cc",
"is_personal": false,
"policy_id": "16367000000092011",
"policy_name": "LIC",
"documents": [
{
"file_name": "receipt1.jpg",
"file_size_formatted": "71.8 KB",
"attachment_order": 1,
"document_id": "16367000000083071"
}
],
"reimbursement_reference": "",
"reimbursement_date": "",
"reimbursement_paid_through_account_id": "",
"reimbursement_paid_through_account_name": "",
"reimbursement_currency_id": "",
"reimbursement_currency_code": ""
}
]
}
Please go through this for more info.

Extract IF cases from AST tree which is stored as Dictionary in Python

I have an AST tree of javascript in the form of json (Dictionary).
I need to extract only the information about the ifstatement (entire if condition block) in the AST tree using python, so that I can tokenize the extracted data and use for some deep learning tasks.
{
"type": "Program",
"body": [
{
"type": "ExpressionStatement",
"expression": {
"type": "AssignmentExpression",
"operator": "=",
"left": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "MemberExpression",
"computed": true,
"object": {
"type": "Identifier",
"name": "Template"
},
"property": {
"type": "CallExpression",
"callee": {
"type": "Identifier",
"name": "getTemplate"
},
"arguments": [
{
"type": "Literal",
"value": "layout",
"raw": "'layout'"
}
]
}
},
"property": {
"type": "Identifier",
"name": "rendered"
}
},
"right": {
"type": "FunctionExpression",
"id": null,
"params": [],
"body": {
"type": "BlockStatement",
"body": [
{
"type": "IfStatement",
"test": {
"type": "AssignmentExpression",
"operator": "=",
"left": {
"type": "Identifier",
"name": "currentScroll"
},
"right": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "Session"
},
"property": {
"type": "Identifier",
"name": "get"
}
},
"arguments": [
{
"type": "Literal",
"value": "currentScroll",
"raw": "'currentScroll'"
}
]
}
},
"consequent": {
"type": "BlockStatement",
"body": [
{
"type": "ExpressionStatement",
"expression": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "CallExpression",
"callee": {
"type": "Identifier",
"name": "$"
},
"arguments": [
{
"type": "Literal",
"value": "body",
"raw": "'body'"
}
]
},
"property": {
"type": "Identifier",
"name": "scrollTop"
}
},
"arguments": [
{
"type": "Identifier",
"name": "currentScroll"
}
]
}
},
{
"type": "ExpressionStatement",
"expression": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "Session"
},
"property": {
"type": "Identifier",
"name": "set"
}
},
"arguments": [
{
"type": "Literal",
"value": "currentScroll",
"raw": "'currentScroll'"
},
{
"type": "Literal",
"value": null,
"raw": "null"
}
]
}
}
]
},
"alternate": null
},
{
"type": "VariableDeclaration",
"declarations": [
{
"type": "VariableDeclarator",
"id": {
"type": "Identifier",
"name": "link"
},
"init": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "document"
},
"property": {
"type": "Identifier",
"name": "createElement"
}
},
"arguments": [
{
"type": "Literal",
"value": "link",
"raw": "'link'"
}
]
}
}
],
"kind": "var"
},
{
"type": "ExpressionStatement",
"expression": {
"type": "AssignmentExpression",
"operator": "=",
"left": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "link"
},
"property": {
"type": "Identifier",
"name": "type"
}
},
"right": {
"type": "Literal",
"value": "image/x-icon",
"raw": "'image/x-icon'"
}
}
},
{
"type": "ExpressionStatement",
"expression": {
"type": "AssignmentExpression",
"operator": "=",
"left": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "link"
},
"property": {
"type": "Identifier",
"name": "rel"
}
},
"right": {
"type": "Literal",
"value": "shortcut icon",
"raw": "'shortcut icon'"
}
}
},
{
"type": "ExpressionStatement",
"expression": {
"type": "AssignmentExpression",
"operator": "=",
"left": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "link"
},
"property": {
"type": "Identifier",
"name": "href"
}
},
"right": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "Settings"
},
"property": {
"type": "Identifier",
"name": "get"
}
},
"arguments": [
{
"type": "Literal",
"value": "faviconUrl",
"raw": "'faviconUrl'"
},
{
"type": "Literal",
"value": "/img/favicon.ico",
"raw": "'/img/favicon.ico'"
}
]
}
}
},
{
"type": "ExpressionStatement",
"expression": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "MemberExpression",
"computed": true,
"object": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "document"
},
"property": {
"type": "Identifier",
"name": "getElementsByTagName"
}
},
"arguments": [
{
"type": "Literal",
"value": "head",
"raw": "'head'"
}
]
},
"property": {
"type": "Literal",
"value": 0,
"raw": "0"
}
},
"property": {
"type": "Identifier",
"name": "appendChild"
}
},
"arguments": [
{
"type": "Identifier",
"name": "link"
}
]
}
},
{
"type": "ExpressionStatement",
"expression": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "CallExpression",
"callee": {
"type": "Identifier",
"name": "$"
},
"arguments": [
{
"type": "Literal",
"value": "a.category-silent-hangout",
"raw": "'a.category-silent-hangout'"
}
]
},
"property": {
"type": "Identifier",
"name": "after"
}
},
"arguments": [
{
"type": "Literal",
"value": "<span class=\"silent-icons\"> <img src=\"http://codebuddies.org/images/icon-video-off.png\" alt=\"turn off video\" width=\"25\" height=\"25\"> <img src=\"http://codebuddies.org/images/icon-mute.png\" alt=\"turn off microphone\" width=\"25\" height=\"25\"></span>",
"raw": "'<span class=\"silent-icons\"> <img src=\"http://codebuddies.org/images/icon-video-off.png\" alt=\"turn off video\" width=\"25\" height=\"25\"> <img src=\"http://codebuddies.org/images/icon-mute.png\" alt=\"turn off microphone\" width=\"25\" height=\"25\"></span>'"
}
]
}
}
]
},
"generator": false,
"expression": false,
"async": false
}
}
},
{
"type": "ExpressionStatement",
"expression": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "MemberExpression",
"computed": true,
"object": {
"type": "Identifier",
"name": "Template"
},
"property": {
"type": "CallExpression",
"callee": {
"type": "Identifier",
"name": "getTemplate"
},
"arguments": [
{
"type": "Literal",
"value": "layout",
"raw": "'layout'"
}
]
}
},
"property": {
"type": "Identifier",
"name": "events"
}
},
"arguments": [
{
"type": "ObjectExpression",
"properties": [
{
"type": "Property",
"key": {
"type": "Literal",
"value": "click .inner-wrapper",
"raw": "'click .inner-wrapper'"
},
"computed": false,
"value": {
"type": "FunctionExpression",
"id": null,
"params": [
{
"type": "Identifier",
"name": "e"
}
],
"body": {
"type": "BlockStatement",
"body": [
{
"type": "IfStatement",
"test": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "CallExpression",
"callee": {
"type": "Identifier",
"name": "$"
},
"arguments": [
{
"type": "Literal",
"value": "body",
"raw": "'body'"
}
]
},
"property": {
"type": "Identifier",
"name": "hasClass"
}
},
"arguments": [
{
"type": "Literal",
"value": "mobile-nav-open",
"raw": "'mobile-nav-open'"
}
]
},
"consequent": {
"type": "BlockStatement",
"body": [
{
"type": "ExpressionStatement",
"expression": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "Identifier",
"name": "e"
},
"property": {
"type": "Identifier",
"name": "preventDefault"
}
},
"arguments": []
}
},
{
"type": "ExpressionStatement",
"expression": {
"type": "CallExpression",
"callee": {
"type": "MemberExpression",
"computed": false,
"object": {
"type": "CallExpression",
"callee": {
"type": "Identifier",
"name": "$"
},
"arguments": [
{
"type": "Literal",
"value": "body",
"raw": "'body'"
}
]
},
"property": {
"type": "Identifier",
"name": "removeClass"
}
},
"arguments": [
{
"type": "Literal",
"value": "mobile-nav-open",
"raw": "'mobile-nav-open'"
}
]
}
}
]
},
"alternate": null
}
]
},
"generator": false,
"expression": false,
"async": false
},
"kind": "init",
"method": false,
"shorthand": false
}
]
}
]
}
}
],
"sourceType": "script"
}
I want the subtree of below mentioned IF cases.
if(currentScroll=Session.get('currentScroll'))
if ($('body').hasClass('mobile-nav-open'))
Is there an easy way to extract this information in Python?
I am looking for some methods or packages in python to solve this problem, instead of completely traversing entire dictionary.
You can use the tree-sitter library for this purpose.
Check out the Usage section in the README file to setup the package.
This is what you need to do at a high-level:
from tree_sitter import Language, Parser
JS_LANGUAGE = Language('build/my-languages.so', 'javascript')
parser = Parser()
parser.set_language(JS_LANGUAGE)
parser.parse(bytes(<code string>, 'utf-8'))

Cannot import grafana dashboard via Grafana API

I am trying to import the Grafana dashboard using HTTP API by following Grafana
Grafana Version: 5.1.3
OS -Windows 10
This is what i tried
curl --user admin:admin "http://localhost:3000/api/dashboards/db" -X POST -H "Content-Type:application/json;charset=UTF-8" --data-binary #c:/Users/Mahadev/Desktop/Dashboard.json
and
Here is my python code
import requests
headers = {
'Content-Type': 'application/json;charset=UTF-8',
}
data = open('C:/Users/Mahadev/Desktop/Dashboard.json', 'rb').read()
response = requests.post('http://admin:admin#localhost:3000/api/dashboards/db', headers=headers, data=data)
print (response.text)
And output of both is:
[{"fieldNames":["Dashboard"],"classification":"RequiredError","message":"Required"}]
It is asking for root property called dashboard in my json payload. Can anybody suggest me how to use that porperty and what data should i provide.
If any one want to dig more here are some links.
https://github.com/grafana/grafana/issues/8193
https://github.com/grafana/grafana/issues/2816
https://github.com/grafana/grafana/issues/8193
https://community.grafana.com/t/how-can-i-import-a-dashboard-from-a-json-file/669
https://github.com/grafana/grafana/issues/273
https://github.com/grafana/grafana/issues/5811
https://stackoverflow.com/questions/39968111/unable-to-post-to-grafana-using-python3-module-requests
https://stackoverflow.com/questions/39954475/post-request-works-in-postman-but-not-in-python/39954514#39954514
https://www.bountysource.com/issues/44431991-use-api-to-import-json-file-error
https://github.com/grafana/grafana/issues/7029
Maybe you should try to download your dashboard from the API so you will a "proper" json model to push after?
You can download it with the following command :
curl -H "Authorization: Bearer $TOKEN" https://grafana.domain.tld/api/dashboards/uid/$DASHBOARD_UID
An other way to do it , you can download a dashboard JSON on grafana website => grafana.com/dashboards and try to upload it with your current code? ;)
The dashboard field contain everything that will be display, alerts, graph etc....
Here is an example of dashboard.json :
{
"meta": {
"type": "db",
"canSave": true,
"canEdit": true,
"canAdmin": false,
"canStar": true,
"slug": "status-app",
"url": "/d/lOy3lIImz/status-app",
"expires": "0001-01-01T00:00:00Z",
"created": "2018-06-04T11:40:20+02:00",
"updated": "2018-06-14T17:51:23+02:00",
"updatedBy": "jean",
"createdBy": "jean",
"version": 89,
"hasAcl": false,
"isFolder": false,
"folderId": 0,
"folderTitle": "General",
"folderUrl": "",
"provisioned": false
},
"dashboard": {
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": "-- Grafana --",
"enable": true,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"name": "Annotations & Alerts",
"type": "dashboard"
}
]
},
"editable": true,
"gnetId": null,
"graphTooltip": 0,
"id": 182,
"links": [],
"panels": [
{
"alert": {
"conditions": [
{
"evaluator": {
"params": [
1
],
"type": "lt"
},
"operator": {
"type": "and"
},
"query": {
"params": [
"A",
"5m",
"now"
]
},
"reducer": {
"params": [],
"type": "avg"
},
"type": "query"
}
],
"executionErrorState": "alerting",
"frequency": "60s",
"handler": 1,
"name": "Status of alert",
"noDataState": "alerting",
"notifications": [
{
"id": 7
}
]
},
"aliasColors": {},
"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": "Collectd",
"fill": 1,
"gridPos": {
"h": 7,
"w": 8,
"x": 0,
"y": 0
},
"id": 4,
"legend": {
"alignAsTable": true,
"avg": true,
"current": true,
"max": false,
"min": false,
"rightSide": false,
"show": true,
"total": false,
"values": true
},
"lines": true,
"linewidth": 1,
"links": [],
"nullPointMode": "connected",
"percentage": false,
"pointradius": 5,
"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{
"alias": "Status",
"groupBy": [
{
"params": [
"$__interval"
],
"type": "time"
},
{
"params": [
"null"
],
"type": "fill"
}
],
"measurement": "processes_processes",
"orderByTime": "ASC",
"policy": "default",
"query": "SELECT mean(value) FROM \"processes_processes\" WHERE (\"instance\" = '' AND \"host\" = 'Webp01') AND $timeFilter GROUP BY time($interval) fill(null)",
"rawQuery": true,
"refId": "A",
"resultFormat": "time_series",
"select": [
[
{
"params": [
"value"
],
"type": "field"
},
{
"params": [],
"type": "mean"
}
]
],
"tags": [
{
"key": "instance",
"operator": "=",
"value": ""
},
{
"condition": "AND",
"key": "host",
"operator": "=",
"value": "Webp01"
}
]
}
],
"thresholds": [
{
"colorMode": "critical",
"fill": true,
"line": true,
"op": "lt",
"value": 1
}
],
"timeFrom": null,
"timeShift": null,
"title": "Status of ",
"tooltip": {
"shared": true,
"sort": 0,
"value_type": "individual"
},
"type": "graph",
"xaxis": {
"buckets": null,
"mode": "time",
"name": null,
"show": true,
"values": []
},
"yaxes": [
{
"format": "short",
"label": null,
"logBase": 1,
"max": null,
"min": null,
"show": true
},
{
"format": "short",
"label": null,
"logBase": 1,
"max": null,
"min": null,
"show": true
}
],
"yaxis": {
"align": false,
"alignLevel": null
}
}
],
"refresh": "5m",
"schemaVersion": 16,
"style": "dark",
"tags": [
"web",
"nodejs"
],
"templating": {
"list": []
},
"time": {
"from": "now/d",
"to": "now"
},
"timepicker": {
"hidden": false,
"refresh_intervals": [
"5s",
"10s",
"30s",
"1m",
"5m",
"15m",
"30m",
"1h",
"2h",
"1d"
],
"time_options": [
"5m",
"15m",
"1h",
"6h",
"12h",
"24h",
"2d",
"7d",
"30d"
]
},
"timezone": "",
"title": "Status APP",
"uid": "lOy3lIImz",
"version": 89
},
}
Edit:
Here is a JSON snipper for templating your dashboard :
"templating": {
"list": [
{
"allValue": null,
"current": {
"text": "PRD_Web01",
"value": "PRD_Web01"
},
"datasource": "Collectd",
"hide": 0,
"includeAll": false,
"label": null,
"multi": false,
"name": "host",
"options": [],
"query": "SHOW TAG VALUES WITH KEY=host",
"refresh": 1,
"regex": "",
"sort": 0,
"tagValuesQuery": "",
"tags": [],
"tagsQuery": "",
"type": "query",
"useTags": false
},
{
"allValue": null,
"current": {
"text": "sda",
"value": "sda"
},
"datasource": "Collectd",
"hide": 0,
"includeAll": false,
"label": null,
"multi": false,
"name": "device",
"options": [],
"query": "SHOW TAG VALUES FROM \"disk_read\" WITH KEY = \"instance\"",
"refresh": 1,
"regex": "",
"sort": 0,
"tagValuesQuery": "",
"tags": [],
"tagsQuery": "",
"type": "query",
"useTags": false
}
]
},
As I read your answer, I guess you will be OK with this ;). I will try to keep a better eye on this thread
Can you show how your dashboard json looks like ? The json MUST contain a key dashboard in it with all the details inside its value like the following:
{
"dashboard": {
"id": null,
"uid": null,
"title": "Production Overview",
"tags": [ "templated" ],
"timezone": "browser",
"schemaVersion": 16,
"version": 0
},
"folderId": 0,
"overwrite": false
}

How to Remove Outer Layer of JSON in Python

I am trying to remove the outer (parent) layer of a JSON file so that I can process it, however I have no idea how.
As you will see by the code below, the outer 2 most layers are 2 dictionaries, however, python says the 2nd dictionary ("item") is just a string when I call its type. Am I incorrect in how I interpret the structure?
sample_object6 = {
"items":
{
"item":
[
{
"id": "0001",
"type": "donut",
"name": "Cake",
"ppu": 0.55,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" },
{ "id": "1002", "type": "Chocolate" },
{ "id": "1003", "type": "Blueberry" },
{ "id": "1004", "type": "Devil's Food" }
]
},
"topping":
[
{ "id": "5001", "type": "None" },
{ "id": "5002", "type": "Glazed" },
{ "id": "5005", "type": "Sugar" },
{ "id": "5007", "type": "Powdered Sugar" },
{ "id": "5006", "type": "Chocolate with Sprinkles" },
{ "id": "5003", "type": "Chocolate" },
{ "id": "5004", "type": "Maple" }
]
},
{
"id": "0002",
"type": "donut",
"name": "Raised",
"ppu": 0.55,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" }
]
},
"topping":
[
{ "id": "5001", "type": "None" },
{ "id": "5002", "type": "Glazed" },
{ "id": "5005", "type": "Sugar" },
{ "id": "5003", "type": "Chocolate" },
{ "id": "5004", "type": "Maple" }
]
},
{
"id": "0003",
"type": "donut",
"name": "Old Fashioned",
"ppu": 0.55,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" },
{ "id": "1002", "type": "Chocolate" }
]
},
"topping":
[
{ "id": "5001", "type": "None" },
{ "id": "5002", "type": "Glazed" },
{ "id": "5003", "type": "Chocolate" },
{ "id": "5004", "type": "Maple" }
]
},
{
"id": "0004",
"type": "bar",
"name": "Bar",
"ppu": 0.75,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" },
]
},
"topping":
[
{ "id": "5003", "type": "Chocolate" },
{ "id": "5004", "type": "Maple" }
],
"fillings":
{
"filling":
[
{ "id": "7001", "name": "None", "addcost": 0 },
{ "id": "7002", "name": "Custard", "addcost": 0.25 },
{ "id": "7003", "name": "Whipped Cream", "addcost": 0.25 }
]
}
},
{
"id": "0005",
"type": "twist",
"name": "Twist",
"ppu": 0.65,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" },
]
},
"topping":
[
{ "id": "5002", "type": "Glazed" },
{ "id": "5005", "type": "Sugar" },
]
},
{
"id": "0006",
"type": "filled",
"name": "Filled",
"ppu": 0.75,
"batters":
{
"batter":
[
{ "id": "1001", "type": "Regular" },
]
},
"topping":
[
{ "id": "5002", "type": "Glazed" },
{ "id": "5007", "type": "Powdered Sugar" },
{ "id": "5003", "type": "Chocolate" },
{ "id": "5004", "type": "Maple" }
],
"fillings":
{
"filling":
[
{ "id": "7002", "name": "Custard", "addcost": 0 },
{ "id": "7003", "name": "Whipped Cream", "addcost": 0 },
{ "id": "7004", "name": "Strawberry Jelly", "addcost": 0 },
{ "id": "7005", "name": "Rasberry Jelly", "addcost": 0 }
]
}
}
]
}
}
I thought that it might be possible to store the nested portion starting at the first list (right after 'item') in a variable and then work with this but if I can't get python to see that item is a dictionary inside the items dictionary, then I fear I am at a loss with how to proceed.
Does anyone know what I am doing wrong?
Thank you in advance!
As far as the processing goes, there has been none because I could not even get the string to read as a dictionary appropriately.
This is what I tried to test if it was a dictionary:
for i in sample_object6:
print(i + str(type(i)))
for n in i["item"]:
print(n + str(type(n)))
After submitting the same code that I thought I had already submitted, I noticed that python is interpreting the object correctly. I have some obvious fundamental gaps in how to work in python and I'm sorry I took it to the forum.
For the record (and for future python newbies out there like me), I used the following code which returned the proper class types:
#this returned a class type of dictionary
print(type(sample_object6["items"]))
#this returned a class type of list
print(type(sample_object6["items"]["item"]))
Thank you SungJin Steve Yoo & Pm2Ring for your help.

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