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Python : How to loop through data to access similar keys present inside nested dict

I have an API, after calling which I'm getting a very big json in response.
I want to access similar keys which are present inside the nested dict.
I'm using following lines to make a get request and storing the json data : -
p25_st_devices = r'https://url_from_where_im_getting_data.com'
header_events = {
'Authorization': 'Basic random_keys'}
r2 = requests.get(p25_st_devices, headers= header_events)
r2_json = json.loads(r2.content)
The sample of the json is as follows : -
{
"next": "value",
"self": "value",
"managedObjects": [
{
"creationTime": "2021-08-02T10:48:15.120Z",
"type": " c8y_MQTTdevice",
"lastUpdated": "2022-03-24T17:09:01.240+03:00",
"childAdditions": {
"self": "value",
"references": []
},
"name": "PS_MQTT1",
"assetParents": {
"self": "value",
"references": []
},
"self": "value",
"id": "338",
"Building": "value"
},
{
"creationTime": "2021-08-02T13:06:09.834Z",
"type": " c8y_MQTTdevice",
"lastUpdated": "2021-12-27T12:08:20.186+03:00",
"childAdditions": {
"self": "value",
"references": []
},
"name": "FS_MQTT2",
"assetParents": {
"self": "value",
"references": []
},
"self": "value",
"id": "339",
"c8y_IsDevice": {}
},
{
"creationTime": "2021-08-02T13:06:39.602Z",
"type": " c8y_MQTTdevice",
"lastUpdated": "2021-12-27T12:08:20.433+03:00",
"childAdditions": {
"self": "value",
"references": []
},
"name": "PS_MQTT3",
"assetParents": {
"self": "value",
"references": []
},
"self": "value",
"id": "340",
"c8y_IsDevice": {}
}
],
"statistics": {
"totalPages": 423,
"currentPage": 1,
"pageSize": 3
}
}
As per my understanding I can access name key using r2_json['managedObjects'][0]['name']
But how do I iterate over this json and store all values of name inside an array?
EDIT 1 :
Another thing which I'm trying to achieve is get all id from the JSON data and store in an array where the nested dict managedObjects contains name starting with PS_ only.
Therefore, the expected output would be device_id = ['338','340']

You should not just call the [0] index of the list, but loop over it:
all_names = []
for object in r2_json['managedObjects']:
all_names.append(object['name'])
print(all_names)
edit: Updated answer after OP updated theirs.
For your second question you can use startswith(). The code is almost the same.
PS_names = []
for object in r2_json['managedObjects']:
if object['name'].startswith("PS_"):
PS_names.append(object['id']) # we append with the id, if startswith("PS_") returns True.
print(PS_names)

Ignore specific JSON keys when extracting data in Python

I'm extracting certain keys in several JSON files and then converting it to a CSV in Python. I'm able to define a key list when I run my code and get the information I need.
However, there are certain sub-keys that I want to ignore from the JSON file. For example, if we look at the following snippet:
JSON Sample
[
{
"callId": "abc123",
"errorCode": 0,
"apiVersion": 2,
"statusCode": 200,
"statusReason": "OK",
"time": "2020-12-14T12:00:32.744Z",
"registeredTimestamp": 1417731582000,
"UID": "_guid_abc123==",
"created": "2014-12-04T22:19:42.894Z",
"createdTimestamp": 1417731582000,
"data": {},
"preferences": {},
"emails": {
"verified": [],
"unverified": []
},
"identities": [
{
"provider": "facebook",
"providerUID": "123",
"allowsLogin": true,
"isLoginIdentity": true,
"isExpiredSession": true,
"lastUpdated": "2014-12-04T22:26:37.002Z",
"lastUpdatedTimestamp": 1417731997002,
"oldestDataUpdated": "2014-12-04T22:26:37.002Z",
"oldestDataUpdatedTimestamp": 1417731997002,
"firstName": "John",
"lastName": "Doe",
"nickname": "John Doe",
"profileURL": "https://www.facebook.com/John.Doe",
"age": 50,
"birthDay": 31,
"birthMonth": 12,
"birthYear": 1969,
"city": "City, State",
"education": [
{
"school": "High School Name",
"schoolType": "High School",
"degree": null,
"startYear": 0,
"fieldOfStudy": null,
"endYear": 0
}
],
"educationLevel": "High School",
"favorites": {
"music": [
{
"name": "Music 1",
"id": "123",
"category": "Musician/band"
},
{
"name": "Music 2",
"id": "123",
"category": "Musician/band"
}
],
"movies": [
{
"name": "Movie 1",
"id": "123",
"category": "Movie"
},
{
"name": "Movie 2",
"id": "123",
"category": "Movie"
}
],
"television": [
{
"name": "TV 1",
"id": "123",
"category": "Tv show"
}
]
},
"followersCount": 0,
"gender": "m",
"hometown": "City, State",
"languages": "English",
"likes": [
{
"name": "Like 1",
"id": "123",
"time": "2014-10-31T23:52:53.0000000Z",
"category": "TV",
"timestamp": "1414799573"
},
{
"name": "Like 2",
"id": "123",
"time": "2014-09-16T08:11:35.0000000Z",
"category": "Music",
"timestamp": "1410855095"
}
],
"locale": "en_US",
"name": "John Doe",
"photoURL": "https://graph.facebook.com/123/picture?type=large",
"timezone": "-8",
"thumbnailURL": "https://graph.facebook.com/123/picture?type=square",
"username": "john.doe",
"verified": "true",
"work": [
{
"companyID": null,
"isCurrent": null,
"endDate": null,
"company": "Company Name",
"industry": null,
"title": "Company Title",
"companySize": null,
"startDate": "2010-12-31T00:00:00"
}
]
}
],
"isActive": true,
"isLockedOut": false,
"isRegistered": true,
"isVerified": false,
"lastLogin": "2014-12-04T22:26:33.002Z",
"lastLoginTimestamp": 1417731993000,
"lastUpdated": "2014-12-04T22:19:42.769Z",
"lastUpdatedTimestamp": 1417731582769,
"loginProvider": "facebook",
"loginIDs": {
"emails": [],
"unverifiedEmails": []
},
"rbaPolicy": {
"riskPolicyLocked": false
},
"oldestDataUpdated": "2014-12-04T22:19:42.894Z",
"oldestDataUpdatedTimestamp": 1417731582894,
"registered": "2014-12-04T22:19:42.956Z",
"regSource": "",
"socialProviders": "facebook"
}
]
I want to extract data from created and identities but ignore identities.favorites and identities.likes as well as their data underneath it.
This is what I have so far, below. I defined the JSON keys that I want to extract in the key_list variable:
Current Code
import json, pandas
from flatten_json import flatten
# Enter the path to the JSON and the filename without appending '.json'
file_path = r'C:\Path\To\file_name'
# Open and load the JSON file
json_list = json.load(open(file_path + '.json', 'r', encoding='utf-8', errors='ignore'))
# Extract data from the defined key names
key_list = ['created', 'identities']
json_list = [{k:d[k] for k in key_list} for d in json_list]
# Flatten and convert to a data frame
json_list_flattened = (flatten(d, '.') for d in json_list)
df = pandas.DataFrame(json_list_flattened)
# Export to CSV in the same directory with the original file name
export_csv = df.to_csv (file_path + r'.csv', sep=',', encoding='utf-8', index=None, header=True)
Similar to the key_list, I suspect that I would make an ignore list and factor that in the json_list for loop that I have? Something like:
key_ignore = ['identities.favorites', 'identities.likes']`
Then utilize the dict.pop() which looks like it will remove the unwanted sub-keys if it matches? Just not sure how to implement that correctly.
Expected Output
As a result, the code should extract data from the defined keys in key_list and ignore the sub keys defined in key_ignore, which is identities.favorites and identities.likes. Then the rest of the code will continue to convert it into a CSV:
created
identities.0.provider
identities.0.providerUID
identities...
2014-12-04T19:23:05.191Z
site
cb8168b0cf734b70ad541f0132763761
...

If the keys are always there, you can use
del d[0]['identities'][0]['likes']
del d[0]['identities'][0]['favorites']
or if you want to remove the columns from the dataframe after reading all the json data in you can use
df.drop(df.filter(regex='identities.0.favorites|identities.0.likes').columns, axis=1, inplace=True)

Parse specific data from JSON

I have a JSON file with lots of data, and I want to keep only specific data.
I thought reading the file, get all the data I want and save as a new JSON.
The JSON is like this:
{
"event": [
{
"date": "2019-01-01",
"location": "world",
"url": "www.com",
"comments": "null",
"country": "china",
"genre": "blues"
},
{
"date": "2000-01-01",
"location": "street x",
"url": "www.cn",
"comments": "null",
"country":"turkey",
"genre": "reds"
},
{...
and I want it to be like this (with just date and url from each event.
{
"event": [
{
"date": "2019-01-01",
"url": "www.com"
},
{
"date": "2000-01-01",
"url": "www.cn"
},
{...
I can open the JSON and read from it using
with open('xx.json') as f:
data = json.load(f)
data2=data["events"]["date"]
But I still need to understand how to save the data I want in a new JSON keeping it's structure

You can use loop comprehension to loop over the events in and return a dictionary containing only the keys that you want.
data = { "event": [
{
"date": "2019-01-01",
"location": "world",
"url": "www.com",
"comments": None,
"country": "china",
"genre": "blues",
},
{
"date": "2000-01-01",
"location": "street x",
"url": "www.cn",
"comments": None,
"country" :"turkey",
"genre":"reds",
}
]}
# List comprehension
data["event"] = [{"date": x["date"], "url": x["url"]} for x in data["event"]]
Alternatively, you can map a function over the events list
keys_to_keep = ["date", "url"]
def subset_dict(d):
return {x: d[x] for x in keys_to_keep}
data["event"] = list(map(subset_dict, data["event"]))

Convert json data to dictionary

I am trying to convert my json data into a dictionary with key the id of the json data. for example lets say i have the following json:
{
"id": "1",
"name": "John",
"surname": "Smith"
},
{
"id": "2",
"name": "Steve",
"surname": "Ger"
}
And i want to construct a new dictionary which includes the id as a key and save it into a file so i wrote the following code:
json_dict = []
request = requests.get('http://example.com/...')
with open("data.json", "w") as out:
loaded_data = json.loads(request.text)
for list_item in loaded_data:
json_dict.append({"id": list_item["id"], "data": list_item })
out.write(json.dumps(json_dict))
In the file i get the following output:
[{"data": {"id":"1",
"name":"John",
"Surname":"Smith"
}
},
{"data": {"id":"2",
"name":"Steve",
"Surname":"Ger"
}
},
]
Why the id is not included in my dict before data ?

I'm pretty sure you're looking at a ghost here. You probably tested wrong. It will go away when you try to create a minimal, complete, and verifiable example for us (i. e. with a fixed string as input instead of a request call, with a print instead of an out.write, etc).
This is my test in which I could not reproduce the problem:
entries = [
{
"id": "1",
"name": "John",
"surname": "Smith"
},
{
"id": "2",
"name": "Steve",
"surname": "Ger"
}
]
json_dict = []
for i in entries:
json_dict.append({"id":i["id"], "data": i})
json.dumps(json_dict, indent=2)
This prints as expected:
[
{
"id": "1",
"data": {
"id": "1",
"surname": "Smith",
"name": "John"
}
},
{
"id": "2",
"data": {
"id": "2",
"surname": "Ger",
"name": "Steve"
}
}
]

You could try this instead:
json_dict = []
with open('data.json', 'w) as f:
loaded_data = json.loads(request.text)
for list_item in loaded_data:
json_dict.append({list_item['id'] : list_item})

Nested JSON not loading as Keys in dict

I have the below JSON currently in a dict called returned_data- I would like to get the account ID out, but it looks like it is not recognizing any keys deeper than the 2nd level. eg:
returned_data["command1"]["customers"]
works
returned_data["command1"]["customers"]["acctid"]
does not work.
returned_data["command1"]["customers"].keys()
does not display any keys.
What do I need to do to be able to reference the acctid?
{
"command1": {
"customers": [{
"city": "none",
"cust_id": 204567,
"name_first": "John",
"name_last": "Smith",
"zip": "39199",
"street_addr_1": "1 Bat St",
"phones": [
{"phone_number": "(01) 5555555",
"phone_type": "Mobile",
"phone_code": "C"
},
{"phone_number": "(01) 5555555",
"phone_type": "Home",
"phone_code": "E"
}
],
"email_addr": "test#test.com",
"acctid": 123456,
"state": "WA",
"add_user": "JR",
"country": "AUS",
"acct_type": "P",
}
],
"ref": "123456",
"result": 0
},
"header": {"src_sys_type": 2,
"ver": 1,
"result": 0}
}

This is what you'll need.
['command1']['customers'][0]['acctid']
You're probably getting an index error. The [0] is needed because of the bracket after 'customers'. As the comment said, it's a list, not a json.