Get names of keys in objectpath - python

How would I get the names of the keys, for example [800, 801] (the key names are unknown) with objectpath.
It is easy in jmespath: keys(#).
"groups": {
"800": {
"short_name": "22",
"oname": "11",
"group": 8,
"title": "SS",
"name": "33",
"onames": [""],
"alt_name": False,
"waytype": 1,
"multiple": 1,
"primary": 1
},
"801": {
"short_name": "ss",
"oname": "zz",
"group": 8,
"title": "ss",
"name": "bbb",
"onames": [""],
"alt_name": False,
"waytype": 1,
"multiple": 1,
"primary": 0
},


let your object is assigned to name variable
const name = { "groups": {
"800": {
"short_name": "22",
"oname": "11",
"group": 8,
"title": "SS",
"name": "33",
"onames": [""],
"alt_name": false,
"waytype": 1,
"multiple": 1,
"primary": 1
},
"801": {
"short_name": "ss",
"oname": "zz",
"group": 8,
"title": "ss",
"name": "bbb",
"onames": [""],
"alt_name": false,
"waytype": 1,
"multiple": 1,
"primary": 0
} } }
Use for loop to get the key name as
for(var num in name.groups) {
console.log(num);
}
and to get the values of key
for(var num in name.groups) {
console.log(name.groups[num]);
}

Related

Get fields from a JSON file with Python

I have this json file loaded in Python with json.loads('myfile.json'):
[
{
"cart": {
"items": {
"3154ba405e5c5a22bbdf9bf1": {
"item": {
"_id": "3154ba405e5c5a22bbdf9bf1",
"title": "Drink alla cannella",
"price": 5.65,
"__v": 0
},
"qty": 1,
"price": 5.65
}
},
"totalQty": 1,
"totalPrice": 5.65
}
},
{
"cart": {
"items": {
"6214ba405e4c5a31bbdf9ad7": {
"item": {
"_id": "6214ba405e4c5a31bbdf9ad7",
"title": "Drink alla menta",
"price": 5.65,
"__v": 0
},
"qty": 2,
"price": 11.3
}
},
"totalQty": 2,
"totalPrice": 11.3
}
}
]
How I can access to both totalQty and totalPrice fields at same time and sum them?
How I can access to both Title fields to print it?

Let's assume that you have the JSON data available as a string then:
jdata = '''
[
{
"cart": {
"items": {
"3154ba405e5c5a22bbdf9bf1": {
"item": {
"_id": "3154ba405e5c5a22bbdf9bf1",
"title": "Drink alla cannella",
"price": 5.65,
"__v": 0
},
"qty": 1,
"price": 5.65
}
},
"totalQty": 1,
"totalPrice": 5.65
}
},
{
"cart": {
"items": {
"6214ba405e4c5a31bbdf9ad7": {
"item": {
"_id": "6214ba405e4c5a31bbdf9ad7",
"title": "Drink alla menta",
"price": 5.65,
"__v": 0
},
"qty": 2,
"price": 11.3
}
},
"totalQty": 2,
"totalPrice": 11.3
}
}
]
'''
totalQty = 0
totalPrice = 0
for d in json.loads(jdata):
c = d['cart']
totalQty += c['totalQty']
totalPrice += c['totalPrice']
for sd in c['items'].values():
print(sd['item']['title'])
print(f'{totalQty:d}', f'{totalPrice:.2f}')
Output:
3 16.95
Note:
I suspect that what you really want to do is multiply those two values

Split Json Data by certain string values (Python)

I want to split incidents by "incidentType" values for python. It always have 5 of these values: period, injuryTime, goal, card and substitution.
Json File
{
"incidents": [
{
"text": "FT",
"homeScore": 2,
"awayScore": 1,
"isLive": false,
"time": 90,
"addedTime": 999,
"incidentType": "period"
},
{
"length": 4,
"time": 90,
"addedTime": 0,
"incidentType": "injuryTime"
},
{
"homeScore": 2,
"awayScore": 1,
"player": {
"name": "Mostafa Mohamed",
"firstName": "",
"lastName": "",
"slug": "mostafa-mohamed",
"shortName": "M. Mohamed",
"position": "F",
"userCount": 3949,
"id": 873551
},
"id": 141786584,
"time": 89,
"isHome": true,
"incidentClass": "penalty",
"incidentType": "goal"
},
{
"player": {
"name": "Duško Tošić",
"slug": "dusko-tosic",
"shortName": "D. Tošić",
"position": "D",
"userCount": 215,
"id": 14557
},
"playerName": "Duško Tošić",
"reason": "Foul",
"id": 119728583,
"time": 85,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "Younès Belhanda",
"slug": "younes-belhanda",
"shortName": "Y. Belhanda",
"position": "M",
"userCount": 2165,
"id": 72999
},
"playerOut": {
"name": "Martin Linnes",
"slug": "martin-linnes",
"shortName": "M. Linnes",
"position": "D",
"userCount": 339,
"id": 109569
},
"id": 120059400,
"time": 82,
"isHome": true,
"incidentType": "substitution"
},
{
"player": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerName": "Kevin Varga",
"reason": "Foul",
"id": 119728582,
"time": 82,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "DeAndre Yedlin",
"slug": "deandre-yedlin",
"shortName": "D. Yedlin",
"position": "D",
"userCount": 702,
"id": 314040
},
"playerOut": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 120059399,
"time": 77,
"isHome": true,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Ryan Donk",
"slug": "ryan-donk",
"shortName": "R. Donk",
"position": "D",
"userCount": 489,
"id": 14900
},
"playerOut": {
"name": "Ryan Babel",
"slug": "ryan-babel",
"shortName": "R. Babel",
"position": "F",
"userCount": 1577,
"id": 1876
},
"id": 120059397,
"time": 72,
"isHome": true,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Emre Akbaba",
"slug": "emre-akbaba",
"shortName": "E. Akbaba",
"position": "M",
"userCount": 604,
"id": 343527
},
"playerOut": {
"name": "Gedson Fernandes",
"slug": "fernandes-gedson",
"shortName": "G. Fernandes",
"position": "M",
"userCount": 3030,
"id": 862055
},
"id": 120059396,
"time": 71,
"isHome": true,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Henry Onyekuru",
"slug": "henry-onyekuru",
"shortName": "H. Onyekuru",
"position": "M",
"userCount": 1474,
"id": 809220
},
"playerOut": {
"name": "Emre Kılınç",
"slug": "emre-kilinc",
"shortName": "E. Kılınç",
"position": "M",
"userCount": 526,
"id": 202032
},
"id": 120059398,
"time": 71,
"isHome": true,
"incidentType": "substitution"
},
{
"player": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"playerName": "Haris Hajradinović",
"reason": "Foul",
"id": 119728581,
"time": 71,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 1,
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"assist1": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"id": 141786585,
"time": 51,
"isHome": false,
"incidentClass": "regular",
"incidentType": "goal"
},
{
"playerIn": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerOut": {
"name": "Gilbert Koomson",
"slug": "gilbert-koomson",
"shortName": "G. Koomson",
"position": "F",
"userCount": 76,
"id": 341107
},
"id": 120059401,
"time": 46,
"isHome": false,
"incidentType": "substitution"
},
{
"text": "HT",
"homeScore": 1,
"awayScore": 0,
"isLive": false,
"time": 45,
"addedTime": 999,
"incidentType": "period"
},
{
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"playerName": "Isaac Kiese Thelin",
"reason": "Foul",
"id": 119728580,
"time": 15,
"isHome": false,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 0,
"player": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 141786583,
"time": 9,
"isHome": true,
"incidentClass": "regular",
"incidentType": "goal"
}
]
}

ABC = {
"incidents": [
{
"text": "FT",
"homeScore": 2,
"awayScore": 1,
"isLive": False,
"time": 90,
"addedTime": 999,
"incidentType": "period"
},
{
"length": 4,
"time": 90,
"addedTime": 0,
"incidentType": "injuryTime"
},
{
"homeScore": 2,
"awayScore": 1,
"player": {
"name": "Mostafa Mohamed",
"firstName": "",
"lastName": "",
"slug": "mostafa-mohamed",
"shortName": "M. Mohamed",
"position": "F",
"userCount": 3949,
"id": 873551
},
"id": 141786584,
"time": 89,
"isHome": True,
"incidentClass": "penalty",
"incidentType": "goal"
},
{
"player": {
"name": "Duško Tošić",
"slug": "dusko-tosic",
"shortName": "D. Tošić",
"position": "D",
"userCount": 215,
"id": 14557
},
"playerName": "Duško Tošić",
"reason": "Foul",
"id": 119728583,
"time": 85,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "Younès Belhanda",
"slug": "younes-belhanda",
"shortName": "Y. Belhanda",
"position": "M",
"userCount": 2165,
"id": 72999
},
"playerOut": {
"name": "Martin Linnes",
"slug": "martin-linnes",
"shortName": "M. Linnes",
"position": "D",
"userCount": 339,
"id": 109569
},
"id": 120059400,
"time": 82,
"isHome": True,
"incidentType": "substitution"
},
{
"player": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerName": "Kevin Varga",
"reason": "Foul",
"id": 119728582,
"time": 82,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"playerIn": {
"name": "DeAndre Yedlin",
"slug": "deandre-yedlin",
"shortName": "D. Yedlin",
"position": "D",
"userCount": 702,
"id": 314040
},
"playerOut": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 120059399,
"time": 77,
"isHome": True,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Ryan Donk",
"slug": "ryan-donk",
"shortName": "R. Donk",
"position": "D",
"userCount": 489,
"id": 14900
},
"playerOut": {
"name": "Ryan Babel",
"slug": "ryan-babel",
"shortName": "R. Babel",
"position": "F",
"userCount": 1577,
"id": 1876
},
"id": 120059397,
"time": 72,
"isHome": True,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Emre Akbaba",
"slug": "emre-akbaba",
"shortName": "E. Akbaba",
"position": "M",
"userCount": 604,
"id": 343527
},
"playerOut": {
"name": "Gedson Fernandes",
"slug": "fernandes-gedson",
"shortName": "G. Fernandes",
"position": "M",
"userCount": 3030,
"id": 862055
},
"id": 120059396,
"time": 71,
"isHome": True,
"incidentType": "substitution"
},
{
"playerIn": {
"name": "Henry Onyekuru",
"slug": "henry-onyekuru",
"shortName": "H. Onyekuru",
"position": "M",
"userCount": 1474,
"id": 809220
},
"playerOut": {
"name": "Emre Kılınç",
"slug": "emre-kilinc",
"shortName": "E. Kılınç",
"position": "M",
"userCount": 526,
"id": 202032
},
"id": 120059398,
"time": 71,
"isHome": True,
"incidentType": "substitution"
},
{
"player": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"playerName": "Haris Hajradinović",
"reason": "Foul",
"id": 119728581,
"time": 71,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 1,
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"assist1": {
"name": "Haris Hajradinović",
"slug": "haris-hajradinovic",
"shortName": "H. Hajradinović",
"position": "M",
"userCount": 357,
"id": 254979
},
"id": 141786585,
"time": 51,
"isHome": False,
"incidentClass": "regular",
"incidentType": "goal"
},
{
"playerIn": {
"name": "Kevin Varga",
"slug": "kevin-varga",
"shortName": "K. Varga",
"position": "M",
"userCount": 274,
"id": 602730
},
"playerOut": {
"name": "Gilbert Koomson",
"slug": "gilbert-koomson",
"shortName": "G. Koomson",
"position": "F",
"userCount": 76,
"id": 341107
},
"id": 120059401,
"time": 46,
"isHome": False,
"incidentType": "substitution"
},
{
"text": "HT",
"homeScore": 1,
"awayScore": 0,
"isLive": False,
"time": 45,
"addedTime": 999,
"incidentType": "period"
},
{
"player": {
"name": "Isaac Kiese Thelin",
"slug": "isaac-kiese-thelin",
"shortName": "I. K. Thelin",
"position": "F",
"userCount": 386,
"id": 178743
},
"playerName": "Isaac Kiese Thelin",
"reason": "Foul",
"id": 119728580,
"time": 15,
"isHome": False,
"incidentClass": "yellow",
"incidentType": "card"
},
{
"homeScore": 1,
"awayScore": 0,
"player": {
"name": "Muhammed Kerem Aktürkoğlu",
"firstName": "",
"lastName": "",
"slug": "muhammed-kerem-akturkoglu",
"shortName": "M. K. Aktürkoğlu",
"position": "F",
"userCount": 281,
"id": 903324
},
"id": 141786583,
"time": 9,
"isHome": True,
"incidentClass": "regular",
"incidentType": "goal"
}
]
}
First, create a dictionary to hold all distinct incidentType. Then iterate through incidents and check if whether incidentType exists in the dictionary or not. If it exists? Append. if not, create a new key : value pair
result = {}
for js in ABC["incidents"]:
icdType = js["incidentType"]
if icdType in result:
result[icdType].append(js)
else:
result[icdType] = [js]
for key,val in result.items():
print(key, ":", val, "\n")

How to map the dictionary values to another dictionary

I have dictionary which is below
{
"aggregations": {
"A": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{ "key": "ADL", "doc_count": 1 },
{ "key": "SDD", "doc_count": 1 },
{ "key": "JJD", "doc_count": 1 }
]
},
"B": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{ "key": "ABC", "doc_count": 1 },
{ "key": "CDE", "doc_count": 1 },
{ "key": "FGH", "doc_count": 1 }
]
},
"C": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{ "key": "XYX", "doc_count": 1 },
{ "key": "NXS", "doc_count": 1 }
]
}
}
}
aggregations.keys will be aggregationfilters.fieldName
aggregations.buckets.key will be aggregationfilters.values.title
aggregationfilters.values.paragraph is null everytime
aggregations.buckets.doc_count will be aggregationfilters.values.count
Basically I need to extract aggregations.keys and aggregations.bucket values and put into different dictionary.
Need to write a general code structure to do that.
I cannot do with .pop(rename) the dictioanry
My expected out
{
"aggregationfilters": [
{
"name": "ABC",
"fieldName": "A",
"values": [
{ "title": "ADL", "paragraph": null, "count": 1 },
{ "title": "SDD", "paragraph": null, "count": 1 },
{ "title": "JJD", "paragraph": null, "count": 1 }
]
}, {
"name": "CDE",
"fieldName": "B",
"values": [
{ "title": "ABC", "paragraph": null, "count": 1 },
{ "title": "CDE", "paragraph": null, "count": 1 },
{ "title": "FGH", "paragraph": null, "count": 1 }
]
}, {
"name": "FGH",
"fieldName": "C",
"values": [
{ "title": "XYX", "paragraph": null, "count": 1 },
{ "title": "NXS", "paragraph": null, "count": 1 }
]
}
]
}

Well, this works, but even with my best effort this still doesn't look that clean.
import json
source = {
"aggregations": {
"A": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{"key": "ADL", "doc_count": 1},
{"key": "SDD", "doc_count": 1},
{"key": "JJD", "doc_count": 1},
],
},
"B": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{"key": "ABC", "doc_count": 1},
{"key": "CDE", "doc_count": 1},
{"key": "FGH", "doc_count": 1},
],
},
"C": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [{"key": "XYX", "doc_count": 1}, {"key": "NXS", "doc_count": 1}],
},
}
}
convert_map = {
"buckets": "values",
"doc_count": "count",
"key": "title",
}
remove_map = {"sum_other_doc_count", "doc_count_error_upper_bound"}
add_map = {"name": "Changed VAL_", "fieldName": "VAL_"}
def converting_generator(
source_: dict, convert_map_: dict, remove_map_: set, add_map_: dict
):
working_dict = {k: v for k, v in source_.items()}
variable_identifier = "VAL_"
for key, inner_dic in working_dict.items():
inner_dic: dict
for rm_key in remove_map_:
try:
inner_dic.pop(rm_key)
except KeyError:
pass
for add_key, add_val in add_map_.items():
inner_dic[add_key] = add_val.replace(variable_identifier, key)
dumped = json.dumps(inner_dic, indent=2)
for original, target in convert_map_.items():
dumped = dumped.replace(original, target)
yield json.loads(dumped)
converted = {
"aggregation_filters": list(
converting_generator(source["aggregations"], convert_map, remove_map, add_map)
)
}
for inner_dict in converted["aggregation_filters"]:
for even_inner_dict in inner_dict["values"]:
even_inner_dict["paragraph"] = None
print(json.dumps(converted, indent=2))
Output:
{
"aggregation_filters": [
{
"values": [
{
"title": "ADL",
"count": 1,
"paragraph": null
},
{
"title": "SDD",
"count": 1,
"paragraph": null
},
{
"title": "JJD",
"count": 1,
"paragraph": null
}
],
"name": "Changed A",
"fieldName": "A"
},
{
"values": [
{
"title": "ABC",
"count": 1,
"paragraph": null
},
{
"title": "CDE",
"count": 1,
"paragraph": null
},
{
"title": "FGH",
"count": 1,
"paragraph": null
}
],
"name": "Changed B",
"fieldName": "B"
},
{
"values": [
{
"title": "XYX",
"count": 1,
"paragraph": null
},
{
"title": "NXS",
"count": 1,
"paragraph": null
}
],
"name": "Changed C",
"fieldName": "C"
}
]
}
Always show your code, would be nice if that's a working one - to show that you've put at least that worth of the effort on your problem.
I don't bother it as this feels like puzzle solving, but others may not.

Parsing and creating nested dictionaries

I would like to create a dictionary containing a nested structure of dictionaries, like bellow :
{
"Jaque": {
"ES": {
"Madrid": [
{
"experience": 9
}
]
},
"FR": {
"Lyon": [
{
"experience": 11.4
}
],
"Paris": [
{
"experience": 20
}
]
}
},
"James": {
"UK": {
"London": [
{
"experience": 10.9
}
]
}
},
"Henry": {
"UK": {
"London": [
{
"experience": 15
}
]
}
},
"Joe": {
"US": {
"Boston": [
{
"experience": 100
}
]
}
}
}
}
My input is a list of dictionaries of this format:
c = [{
"country": "US",
"city": "Boston",
"name": "Joe",
"experience": 100
},
{
"country": "FR",
"city": "Paris",
"name": "Jaque",
"experience": 20
},
{
"country": "FR",
"city": "Lyon",
"name": "Jaque",
"experience": 11.4
},
{
"country": "ES",
"city": "Madrid",
"name": "Jaque",
"experience": 9
},
{
"country": "UK",
"city": "London",
"name": "Henry",
"experience": 15
},
{
"country": "UK",
"city": "London",
"name": "James",
"experience": 10.9
}
]
My first approach was to create the nested dict, step by step:
dd = dict.fromkeys([i.get("name") for i in c],defaultdict(dict))
#will create
# dd = {'Joe': defaultdict(<class 'dict'>, {}), 'Jaque': defaultdict(<class 'dict'>, {}), 'James': defaultdict(<class 'dict'>, {}), 'Henry': defaultdict(<class 'dict'>, {})}
for i in dd:
for j in c:
#verify if name from d is in dict j
if i in j.values():
dd[i]=dict(zip([a.get("country") for a in c if i in a.values() ],[b.get("city") for b in c if i in b.values() ]))
# dd will become
#{'Joe': {'US': 'Boston'}, 'Jaque': {'FR': 'Lyon', 'ES': 'Madrid'}, 'Henry': {'UK': 'London'}, 'James': {'UK': 'London'}}
Now I can't figure a way to create/update the nested structure of dict dd. Is there a more dynamic way to create dict? Thx

You could use itertools.groupby to organize the list similarly to your expected output and then loop to convert to a dict.
from itertools import groupby
from operator import itemgetter
data = [{"country": "US", "city": "Boston", "name": "Joe", "experience": 100 }, {"country": "FR", "city": "Paris", "name": "Jaque", "experience": 20 }, {"country": "FR", "city": "Lyon", "name": "Jaque", "experience": 11.4 }, {"country": "ES", "city": "Madrid", "name": "Jaque", "experience": 9 }, {"country": "UK", "city": "London", "name": "Henry", "experience": 15 }, {"country": "UK", "city": "London", "name": "James", "experience": 10.9 } ]
result = {}
for key, values in groupby(sorted(data, key=itemgetter('name')), key=itemgetter('name')):
result[key] = {
v['country']: {v['city']: [{'experience': v['experience']}]} for v in values
}
print(result)
# {'Henry': {'UK': {'London': [{'experience': 15}]}}, 'James': {'UK': {'London': [{'experience': 10.9}]}}, 'Jaque': {'FR': {'Lyon': [{'experience': 11.4}]}, 'ES': {'Madrid': [{'experience': 9}]}}, 'Joe': {'US': {'Boston': [{'experience': 100}]}}}

You can use recursion with itertools.groupby:
from itertools import groupby
def group(d, keys = None):
key, *keys = keys
new_d = {a:list(b) for a, b in groupby(sorted(d, key=lambda x:x[key]), key=lambda x:x[key])}
t = {a:[{c:d for c, d in k.items() if c != key} for k in b] for a, b in new_d.items()}
return {a:group(b, keys) if not all(len(i) == 1 for i in b) else b for a, b in t.items()}
result = group(data, keys = ['name', 'country', 'city', 'experience'])
import json
print(json.dumps(result, indent=4)))
Output:
{
"Henry": {
"UK": {
"London": [
{
"experience": 15
}
]
}
},
"James": {
"UK": {
"London": [
{
"experience": 10.9
}
]
}
},
"Jaque": {
"ES": {
"Madrid": [
{
"experience": 9
}
]
},
"FR": {
"Lyon": [
{
"experience": 11.4
}
],
"Paris": [
{
"experience": 20
}
]
}
},
"Joe": {
"US": {
"Boston": [
{
"experience": 100
}
]
}
}
}

How to Convert a list of dicts into nested JSON in python without using pandas DataFrame

I have a list of dicts like this
[
{
"subject_id": 1,
"subject_name": "HR Sector 0",
"id": 1,
"name": "parent2",
"value": 10.6
},
{
"subject_id": 18,
"subject_name": "Test11",
"id": 1,
"name": "parent2",
"value": 12
},
{
"subject_id": 2,
"subject_name": "AG1",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 17
},
{
"subject_id": 3,
"subject_name": "Finance Group 2",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 1.5
},
{
"subject_id": 10,
"subject_name": "test",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 10
},
{
"subject_id": null,
"subject_name": null,
"id": 3,
"name": "Technology Team 2",
"value": null
},
{
"subject_id": 8,
"subject_name": "Group 4",
"id": 5,
"name": "Accounting Group 4",
"value": 10
},
{
"subject_id": null,
"subject_name": null,
"id": 9,
"name": "PG2",
"value": null
}
]
I want to convert it into nested JSON and ignore null values to get below result set
[
{
"id": 1,
"name": "parent2",
"subjects”: [
{”subject_id": 1,
"subject_name": "HR Sector 0",
"value": 10.6
},
{”subject_id": 18,
"subject_name": "Test11",
"value": 12
}
]
},
{
"id": 2,
"name": "Customer Delivery Dpt. 1",
"subjects”: [
{“subject_id": 2,
"subject_name": "AG1",
"value": 17
},
{“subject_id": 3,
"subject_name": "Finance Group 2",
"value": 1.5
},
{“subject_id": 10,
"subject_name": “test”,
"value": 10
}
]
},
{
"id": 3,
"name": "Technology Team 2",
"subjects”: []
},
{
"id": 5,
"name": "Accounting Group 4",
"subjects” : [
{ "subject_id": 8,
"subject_name": "Group 4",
"value": 10
}
]
},
{
"id": 9,
"name": "PG2",
"subjects”: []
}
]

import json
arr = [
{
"subject_id": 1,
"subject_name": "HR Sector 0",
"id": 1,
"name": "parent2",
"value": 10.6
},
{
"subject_id": 18,
"subject_name": "Test11",
"id": 1,
"name": "parent2",
"value": 12
},
{
"subject_id": 2,
"subject_name": "AG1",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 17
},
{
"subject_id": 3,
"subject_name": "Finance Group 2",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 1.5
},
{
"subject_id": 10,
"subject_name": "test",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 3,
"name": "Technology Team 2",
"value": None
},
{
"subject_id": 8,
"subject_name": "Group 4",
"id": 5,
"name": "Accounting Group 4",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 9,
"name": "PG2",
"value": None
}
]
def process_arr_to_json(arr):
newArr = []
addedIds = {}
for item in arr:
if(addedIds.get(item["id"]) is None):
formatted_item = {"subjects":[]}
newArr.append(formatted_item)
addedIds[item["id"]] = {"idx": 0, "pos": len(newArr)-1} #index in the dictionary for the subject item
else:
formatted_item = newArr[addedIds[item["id"]]["pos"]]
addedIds[item["id"]]["idx"] += 1
for k,v in item.items():
if(v is not None):
if(k == "id" or k == "name"):
formatted_item[k] = v
else:
if(len(formatted_item["subjects"]) <= addedIds[item["id"]]["idx"]):
formatted_item["subjects"].append({k:v})
else:
formatted_item["subjects"][addedIds[item["id"]]["idx"]][k] = v
print(newArr)
return json.dumps(newArr)
if __name__ == "__main__":
process_arr_to_json(arr)
my solution

Please see code below to form the merged results
import json
def process_items(items):
results = {}
for item in items:
results[item['id']] = {
'id': item['id'],
'name': item['name'],
}
to_append = {}
for k in ['subject_id', 'value', 'subject_name']:
if item.get(k):
to_append[k] = item[k]
results[item['id']].setdefault('subjects', [])
if to_append:
results[item['id']]['subjects'].append(to_append)
return results
items = [
{
"subject_id": 1,
"subject_name": "HR Sector 0",
"id": 1,
"name": "parent2",
"value": 10.6
},
{
"subject_id": 18,
"subject_name": "Test11",
"id": 1,
"name": "parent2",
"value": 12
},
{
"subject_id": 2,
"subject_name": "AG1",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 17
},
{
"subject_id": 3,
"subject_name": "Finance Group 2",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 1.5
},
{
"subject_id": 10,
"subject_name": "test",
"id": 2,
"name": "Customer Delivery Dpt. 1",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 3,
"name": "Technology Team 2",
"value": None
},
{
"subject_id": 8,
"subject_name": "Group 4",
"id": 5,
"name": "Accounting Group 4",
"value": 10
},
{
"subject_id": None,
"subject_name": None,
"id": 9,
"name": "PG2",
"value": None
}
]
result = process_items(items)
json.dumps(result.values()) # For python 3: json.dumps(list(results.values()))

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