I have specific format of list containing complex dictionary & containing again list of dictionaries (Nested Format), e.g.
And Requirement is to remove question_id from all associate dictionaries.
options = [
{
"value": 1,
"label": "Paints",
"question_id": "207",
"question": "Which Paint Brand?",
"question_type_id": 2,
"options": [
{
"value": 2,
"label": "Glidden",
"question": "Is it Glidden Paint?",
"question_id": 1,
"options": [{"question_id": 1,"value": 10000, "label": "No"}, {"question_id": 1,"value": 10001, "label": "Yes"}],
},
{
"value": 1,
"label": "Valspar",
"question": "Is it Valspar Paint?",
"question_id": 1,
"options": [{"question_id": 1,"value": 10000, "label": "No"}, {"question_id": 1,"value": 10001, "label": "Yes"}],
},
{
"value": 3,
"label": "DuPont",
"question": "Is it DuPont Paint?",
"question_id": 1,
"options": [{"question_id": 1,"value": 10000, "label": "No"}, {"question_id": 1,"value": 10001, "label": "Yes"}],
},
],
},
{
"value": 4,
"label": "Rods",
"question": "Which Rods Brand?",
"question_id": 2,
"options": [
{"value": 3, "label": "Trabucco"},
{"value": 5, "label": "Yuki"},
{"value": 1, "label": "Shimano"},
{"value": 4, "label": "Daiwa"},
{"value": 2, "label": "Temple Reef"},
],
},
{
"value": 3,
"label": "Metal Sheets",
"question": "Which Metal Sheets Brand?",
"question_id": 2,
"options": [
{"value": 2, "label": "Nippon Steel Sumitomo Metal Corporation"},
{"value": 3, "label": "Hebei Iron and Steel Group"},
{"value": 1, "label": "ArcelorMittal"},
],
},
{
"value": 2,
"label": "Door Knobs Locks",
"question": "Which Door Knobs Locks Brand?",
"question_id": 2,
"options": [
{
"value": 1,
"label": "ASSA-Abloy",
"question": "Is it ASSA-Abloy Door Knobs Locks?",
"question_type_id": 1,
"options": [{"value": 10000, "label": "No"}, {"value": 10001, "label": "Yes"}],
},
{
"value": 4,
"label": "RR Brink",
"question": "Is it RR Brink Door Knobs Locks?",
"question_type_id": 1,
"options": [{"value": 10000, "label": "No"}, {"value": 10001, "label": "Yes"}],
},
{
"value": 3,
"label": "Medeco",
"question": "Is it Medeco Door Knobs Locks?",
"question_type_id": 1,
"options": [{"value": 10000, "label": "No"}, {"value": 10001, "label": "Yes"}],
},
{
"value": 2,
"label": "Evva",
"question": "Is it Evva Door Knobs Locks?",
"question_type_id": 1,
"options": [{"value": 10000, "label": "No"}, {"value": 10001, "label": "Yes"}],
},
],
},
]
For this I have written a code & trying to run it recursively.
from collections import MutableMapping
def delete_keys_from_dict(dictionary_list, keys):
keys_set = set(keys) # Just an optimization for the "if key in keys" lookup.
# modified_list=[]
for index, dictionary in enumerate(dictionary_list):
modified_dict = {}
for key, value in dictionary.items():
if key not in keys_set:
if isinstance(value, list):
modified_dict[key] = delete_keys_from_dict(value, keys_set)
else:
if isinstance(value, MutableMapping):
modified_dict[key] = delete_keys_from_dict(value, keys_set)
else:
modified_dict[key] = value
# or copy.deepcopy(value) if a copy is desired for non-dicts.
dictionary_list[index] = modified_dict
return dictionary_list
It's returning incorrect list & which is not preserving the existing list data.
May i know, Where am i going wrong or missing something somewhere?
I think something like this should do what you want.
obj may be any object, and this recurses into lists and dicts.
def delete_keys(obj, keys):
if isinstance(obj, list):
return [
delete_keys(item, keys)
for item in obj
]
if isinstance(obj, dict):
return {
key: delete_keys(value, keys)
for (key, value) in obj.items()
if key not in keys
}
return obj # Nothing to do for this value
e.g.
from pprint import pprint
options = [
{
"value": 1,
"label": "Paints",
"question_id": "207",
"question": "Which Paint Brand?",
"question_type_id": 2,
"options": [
{
"value": 2,
"label": "Glidden",
"question": "Is it Glidden Paint?",
"question_id": 1,
"options": [{"question_id": 1,"value": 10000, "label": "No"}, {"question_id": 1,"value": 10001, "label": "Yes"}],
}
],
},
{
"value": 4,
"label": "Rods",
"question": "Which Rods Brand?",
"question_id": 2,
"options": [
{"value": 3, "label": "Trabucco"},
{"value": 5, "label": "Yuki"},
{"value": 1, "label": "Shimano"},
{"value": 4, "label": "Daiwa"},
{"value": 2, "label": "Temple Reef"},
],
},
]
pprint(delete_keys(options, {"question_id"}))
outputs
[{'label': 'Paints',
'options': [{'label': 'Glidden',
'options': [{'label': 'No', 'value': 10000},
{'label': 'Yes', 'value': 10001}],
'question': 'Is it Glidden Paint?',
'value': 2}],
'question': 'Which Paint Brand?',
'question_type_id': 2,
'value': 1},
{'label': 'Rods',
'options': [{'label': 'Trabucco', 'value': 3},
{'label': 'Yuki', 'value': 5},
{'label': 'Shimano', 'value': 1},
{'label': 'Daiwa', 'value': 4},
{'label': 'Temple Reef', 'value': 2}],
'question': 'Which Rods Brand?',
'value': 4}]
Related
I have a list of dictionary. I want to convert this list into dictionary using parent and child relation. I have try many time. But its difficult for me.
Thanks in advance for solving the problem.
Input =
data = [
{
"_id": 1,
"label": "Property",
"index": 1
},
{
"_id": 2,
"label": "Find Property",
"index": 1,
"parent_id": 1
},
{
"_id": 3,
"label": "Add Property",
"index": 2,
"parent_id": 1
},
{
"_id": 4,
"label": "Offer",
"index": 2
},
{
"_id": 5,
"label": "My Offer",
"index": 1,
"parent_id": 4
},
{
"_id": 6,
"label": "Accept",
"index": 1,
"parent_id": 5
}
]
I have a list of dictionary. I want to convert this list into dictionary using parent and child relation. I have try many time. But its difficult for me.
Thanks in advance for solving the problem.
Expected Output:
[
{
"_id": 1,
"label": "Property",
"index": 1,
"children" : [
{
"_id": 2,
"label": "Find Property",
"index": 1
},
{
"_id": 3,
"label": "Add Property",
"index": 2
}
]
},
{
"_id": 4,
"label": "Offer",
"index": 2,
"children" : [
{
"_id": 5,
"label": "My Offer",
"index": 1,
"children" : [
{
"_id": 6,
"label": "Accept",
"index": 1
}
]
}
]
},
]
I would do it like this. Keep in mind that this solution also affects the original data list.
parents = list()
# First, create a new dict where the key is property id and the value
# is the property itself.
indexed = {d["_id"]:d for d in data}
for id_, item in indexed.items():
# If a property doesn't have "parent_id" key it means that
# this is the root property, appending it to the result list.
if "parent_id" not in item:
parents.append(item)
continue
# Saving parent id for convenience.
p_id = item["parent_id"]
# Adding a children list if a parent doesn't have it yet.
if "children" not in indexed[p_id]:
indexed[p_id]["children"] = list()
indexed[p_id]["children"].append(item)
And the result is:
import pprint
pprint.pprint(parents)
[{'_id': 1,
'children': [{'_id': 2, 'index': 1, 'label': 'Find Property', 'parent_id': 1},
{'_id': 3, 'index': 2, 'label': 'Add Property', 'parent_id': 1}],
'index': 1,
'label': 'Property'},
{'_id': 4,
'children': [{'_id': 5,
'children': [{'_id': 6,
'index': 1,
'label': 'Accept',
'parent_id': 5}],
'index': 1,
'label': 'My Offer',
'parent_id': 4}],
'index': 2,
'label': 'Offer'}]
movies={
'actors':{'prabhas':{'knownAs':'Darling', 'awards':{'nandi':1, 'cinemaa':1, 'siima':1},'remuneration':100, 'hits':{'industry':2, 'super':3,'flops':8}, 'age':41, 'height':6.1, 'mStatus':'single','sRate':'35%'},
'pavan':{'knownAs':'Power Star', 'awards':{'nandi':2, 'cinemaa':2, 'siima':5}, 'hits':{'industry':2, 'super':7,'flops':16}, 'age':48, 'height':5.9, 'mStatus':'married','sRate':'37%','remuneration':50},
},
'actress':{
'tamanna':{'knownAs':'Milky Beauty', 'awards':{'nandi':0, 'cinemaa':1, 'siima':1}, 'remuneration':10, 'hits':{'industry':1, 'super':7,'flops':11}, 'age':28, 'height':5.9, 'mStatus':'single', 'sRate':'40%'},
'rashmika':{'knownAs':'Butter Milky Beauty', 'awards':{'nandi':0, 'cinemaa':0, 'siima':2}, 'remuneration':12,'hits':{'industry':0, 'super':4,'flops':2}, 'age':36, 'height':5.9, 'mStatus':'single', 'sRate':'30%'},
1.What are the total number of Nandi Awards won by actors?
2. What is the success rate of Prince?
3.What is the name of Prince?
you can answer the first question with this:
import jmespath
movies={
"actors": {
"prabhas": {
"knownAs": "Darling",
"awards": {
"nandi": 1,
"cinemaa": 1,
"siima": 1
},
"remuneration": 100,
"hits": {
"industry": 2,
"super": 3,
"flops": 8
},
"age": 41,
"height": 6.1,
"mStatus": "single",
"sRate": "35%"
},
"pavan": {
"knownAs": "Power Star",
"awards": {
"nandi": 2,
"cinemaa": 2,
"siima": 5
},
"hits": {
"industry": 2,
"super": 7,
"flops": 16
},
"age": 48,
"height": 5.9,
"mStatus": "married",
"sRate": "37%",
"remuneration": 50
}
},
"actress": {
"tamanna": {
"knownAs": "Milky Beauty",
"awards": {
"nandi": 0,
"cinemaa": 1,
"siima": 1
},
"remuneration": 10,
"hits": {
"industry": 1,
"super": 7,
"flops": 11
},
"age": 28,
"height": 5.9,
"mStatus": "single",
"sRate": "40%"
},
"rashmika": {
"knownAs": "Butter Milky Beauty",
"awards": {
"nandi": 0,
"cinemaa": 0,
"siima": 2
},
"remuneration": 12,
"hits": {
"industry": 0,
"super": 4,
"flops": 2
},
"age": 36,
"height": 5.9,
"mStatus": "single",
"sRate": "30%"
}
}
}
total_nandies_by_actors = sum(jmespath.search('[]',jmespath.search('actors.*.*.nandi',movies)))
but there is no Prince in the data you've provided
I have this list of dictionaries:
"ingredients": [
{
"unit_of_measurement": {"name": "Pound (Lb)", "id": 13},
"quantity": "1/2",
"ingredient": {"name": "Balsamic Vinegar", "id": 12},
},
{
"unit_of_measurement": {"name": "Pound (Lb)", "id": 13},
"quantity": "1/2",
"ingredient": {"name": "Balsamic Vinegar", "id": 12},
},
{
"unit_of_measurement": {"name": "Tablespoon", "id": 15},
"ingredient": {"name": "Basil Leaves", "id": 14},
"quantity": "3",
},
]
I want to be able to find the duplicates of ingredients (by either name or id). If there are duplicates and have the same unit_of_measurement, combine them into one dictionary and add the quantity accordingly. So the above data should return:
[
{
"unit_of_measurement": {"name": "Pound (Lb)", "id": 13},
"quantity": "1",
"ingredient": {"name": "Balsamic Vinegar", "id": 12},
},
{
"unit_of_measurement": {"name": "Tablespoon", "id": 15},
"ingredient": {"name": "Basil Leaves", "id": 14},
"quantity": "3",
},
]
How do I go about it?
Assuming you have a dictionary represented like this:
data = {
"ingredients": [
{
"unit_of_measurement": {"name": "Pound (Lb)", "id": 13},
"quantity": "1/2",
"ingredient": {"name": "Balsamic Vinegar", "id": 12},
},
{
"unit_of_measurement": {"name": "Pound (Lb)", "id": 13},
"quantity": "1/2",
"ingredient": {"name": "Balsamic Vinegar", "id": 12},
},
{
"unit_of_measurement": {"name": "Tablespoon", "id": 15},
"ingredient": {"name": "Basil Leaves", "id": 14},
"quantity": "3",
},
]
}
What you could do is use a collections.defaultdict of lists to group the ingredients by a (name, id) grouping key:
from collections import defaultdict
ingredient_groups = defaultdict(list)
for ingredient in data["ingredients"]:
key = tuple(ingredient["ingredient"].items())
ingredient_groups[key].append(ingredient)
Then you could go through the grouped values of this defaultdict, and calculate the sum of the fraction quantities using fractions.Fractions. For unit_of_measurement and ingredient, we could probably just use the first grouped values.
from fractions import Fraction
result = [
{
"unit_of_measurement": value[0]["unit_of_measurement"],
"quantity": str(sum(Fraction(ingredient["quantity"]) for ingredient in value)),
"ingredient": value[0]["ingredient"],
}
for value in ingredient_groups.values()
]
Which will then give you this result:
[{'ingredient': {'id': 12, 'name': 'Balsamic Vinegar'},
'quantity': '1',
'unit_of_measurement': {'id': 13, 'name': 'Pound (Lb)'}},
{'ingredient': {'id': 14, 'name': 'Basil Leaves'},
'quantity': '3',
'unit_of_measurement': {'id': 15, 'name': 'Tablespoon'}}]
You'll probably need to amend the above to account for ingredients with different units or measurements, but this should get you started.
{
"took": 0,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": 3,
"max_score": 0.2876821,
"hits": [
{
"_index": "product_index",
"_type": "product",
"_id": "1115",
"_score": 0.2876821,
"_source": {
"isactive": true,
"in_use": false,
"brand_name": "Adidas",
"sku_id": "56456487987987",
"long_description": "this is long description",
"key_feature": [
{
"id": 1148,
"key_feature": "sport wear"
},
{
"id": 1147,
"key_feature": "Cotton shirt"
},
{
"id": 1146,
"key_feature": "White and blue"
}
],
"isdeleted": false,
"created_by": null,
"brand_id": 5,
"search_terms": [
{
"label": "white shirt",
"value": 9
}
]
"color_id": 2,
"specific_keywords": "",
"item_list": [
{
"item_id": 1114,
"product_id": 1115,
"isactive": true,
"id": 9,
"isdeleted": false
},
{
"item_id": 1113,
"product_id": 1115,
"isactive": true,
"id": 10,
"isdeleted": false
}
],
"upc_code": "",
"display_size": "L",
"name": "New White shirt",
"updated_by": null,
"id": 1115,
"updated_date": "2020-03-25T08:24:37.644571+00:00",
"color_name": "blue",
"created_date": "2020-03-25T08:11:14.966673+00:00",
"category": [
{
"parent_category_id": 78,
"sub_sub_category": null,
"sub_category": null,
"sub_category_id": null,
"sub_sub_category_id": null,
"parent_category": "new Shirt Cate",
"id": 1151
}
]
}
},
{
"_index": "product_index",
"_type": "product",
"_id": "1113",
"_score": 0.2876821,
"_source": {
"isactive": true,
"in_use": false,
"sku_id": "1456456488",
"brand_name": "Adidas",
"long_description": "",
"key_feature": [
{
"id": 1142,
"key_feature": "Cotton"
},
{
"id": 1141,
"key_feature": "Office Use"
},
{
"id": 1140,
"key_feature": "Black formal"
}
],
"isdeleted": false,
"created_by": null,
"brand_id": 5,
"search_terms": [
]
"color_id": 1,
"specific_keywords": "",
"item_list": [
],
"display_size": "L",
"upc_code": "",
"name": "New Cotton formal shirt black",
"updated_by": null,
"id": 1113,
"updated_date": "2020-03-25T06:48:30.903041+00:00",
"created_date": "2020-03-25T06:48:29.943043+00:00",
"color_name": "black",
"category": [
{
"sub_sub_category": null,
"parent_category_id": 54,
"sub_category": null,
"sub_category_id": null,
"sub_sub_category_id": null,
"parent_category": "MEN'S CLOTHING",
"id": 1149
}
]
}
},
{
"_index": "product_index",
"_type": "product",
"_id": "1114",
"_score": 0.2876821,
"_source": {
"isactive": true,
"in_use": false,
"sku_id": "145645648811",
"brand_name": "Adidas",
"long_description": "",
"key_feature": [
{
"id": 1145,
"key_feature": "Cotton"
},
{
"id": 1144,
"key_feature": "Office Use"
},
{
"id": 1143,
"key_feature": "Black formal"
}
],
"isdeleted": false,
"created_by": null,
"brand_id": 5,
"search_terms": [
],
"color_id": 1,
"specific_keywords": "",
"item_list": [
],
"display_size": "L",
"upc_code": "",
"updated_by": null,
"name": "New Cotton Casual shirt black",
"id": 1114,
"created_date": "2020-03-25T07:13:26.233675+00:00",
"color_name": "black",
"updated_date": "2020-03-25T07:13:27.229363+00:00",
"category": [
{
"sub_sub_category": null,
"parent_category_id": 54,
"sub_category": null,
"sub_category_id": null,
"sub_sub_category_id": null,
"parent_category": "MEN'S CLOTHING",
"id": 1150
}
]
}
}
]
}
}
my requirement is to attach all related documents with specific key value fields which is specify in item_list based on item_id. In above result doc id 1115 has item_list which contains item_id 1114 and 1113. so the particular fields attach in the doc 1115.
what should be the search query for that in elastic search?
You can't do join in Elasticsearch, to achieve your goal, you can do two things:
duplicate the information of item_id 1114 and 1113 in the item_id
1115 (and for sure in all others documents).
Do join at application level, so after this query you can extract the item_id 1114 and 1113 and run two others query to get the information about this items. Then join all the json at application level.
I have a json file I need to add pairs to, I convert it into a dict, but now I need to put my new values in a specific place.
This is some of the json file I convert:
"rootObject": {
"id": "6ff0010c-00fe-485b-b695-4ddd6aca4dcd",
"type": "IDO_GEAR",
"children": [
{
"id": "1dd94d1a-e52d-40b3-a82b-6db02a8fbbab",
"type": "IDO_SYSTEM_LOADCASE",
"children": [],
"childList": "SYSTEMLOADCASE",
"properties": [
{
"name": "IDCO_IDENTIFICATION",
"value": "1dd94d1a-e52d-40b3-a82b-6db02a8fbbab"
},
{
"name": "IDCO_DESIGNATION",
"value": "Lastfall 1"
},
{
"name": "IDSLC_TIME_PORTION",
"value": 100
},
{
"name": "IDSLC_DISTANCE_PORTION",
"value": 100
},
{
"name": "IDSLC_OPERATING_TIME_IN_HOURS",
"value": 1
},
{
"name": "IDSLC_OPERATING_TIME_IN_SECONDS",
"value": 3600
},
{
"name": "IDSLC_OPERATING_REVOLUTIONS",
"value": 1
},
{
"name": "IDSLC_OPERATING_DISTANCE",
"value": 1
},
{
"name": "IDSLC_ACCELERATION",
"value": 9.81
},
{
"name": "IDSLC_EPSILON_X",
"value": 0
},
{
"name": "IDSLC_EPSILON_Y",
"value": 0
},
{
"name": "IDSLC_EPSILON_Z",
"value": 0
},
{
"name": "IDSLC_CALCULATION_WITH_OWN_WEIGHT",
"value": "CO_CALCULATION_WITHOUT_OWN_WEIGHT"
},
{
"name": "IDSLC_CALCULATION_WITH_TEMPERATURE",
"value": "CO_CALCULATION_WITH_TEMPERATURE"
},
{
"name": "IDSLC_FLAG_FOR_LOADCASE_CALCULATION",
"value": "LB_CALCULATE_LOADCASE"
},
{
"name": "IDSLC_STATUS_OF_LOADCASE_CALCULATION",
"value": false
}
I want to add somthing like ENTRY_ONE and ENTRY_TWO like this:
"rootObject": {
"id": "6ff0010c-00fe-485b-b695-4ddd6aca4dcd",
"type": "IDO_GEAR",
"children": [
{
"id": "1dd94d1a-e52d-40b3-a82b-6db02a8fbbab",
"type": "IDO_SYSTEM_LOADCASE",
"children": [],
"childList": "SYSTEMLOADCASE",
"properties": [
{
"name": "IDCO_IDENTIFICATION",
"value": "1dd94d1a-e52d-40b3-a82b-6db02a8fbbab"
},
{
"name": "IDCO_DESIGNATION",
"value": "Lastfall 1"
},
{
"name": "IDSLC_TIME_PORTION",
"value": 100
},
{
"name": "IDSLC_DISTANCE_PORTION",
"value": 100
},
{
"name": "ENTRY_ONE",
"value": 100
},
{
"name": "ENTRY_TWO",
"value": 55
},
{
"name": "IDSLC_OPERATING_TIME_IN_HOURS",
"value": 1
},
{
"name": "IDSLC_OPERATING_TIME_IN_SECONDS",
"value": 3600
},
{
"name": "IDSLC_OPERATING_REVOLUTIONS",
"value": 1
},
{
"name": "IDSLC_OPERATING_DISTANCE",
"value": 1
},
{
"name": "IDSLC_ACCELERATION",
"value": 9.81
},
{
"name": "IDSLC_EPSILON_X",
"value": 0
},
{
"name": "IDSLC_EPSILON_Y",
"value": 0
},
{
"name": "IDSLC_EPSILON_Z",
"value": 0
},
{
"name": "IDSLC_CALCULATION_WITH_OWN_WEIGHT",
"value": "CO_CALCULATION_WITHOUT_OWN_WEIGHT"
},
{
"name": "IDSLC_CALCULATION_WITH_TEMPERATURE",
"value": "CO_CALCULATION_WITH_TEMPERATURE"
},
{
"name": "IDSLC_FLAG_FOR_LOADCASE_CALCULATION",
"value": "LB_CALCULATE_LOADCASE"
},
{
"name": "IDSLC_STATUS_OF_LOADCASE_CALCULATION",
"value": false
}
How can I add the entries so that they are under the IDCO_IDENTIFICATION tag, and not under the rootObject?
The way I see your json file, it WOULD be under rootObject as EVERYTHING is under that key. There's quite a few closing brackets and braces missing.
So I can only assume you are meaning you want it directly under IDCO_IDENTIFICATION (which is nested under rootObject). But that doesn't match what you have as your example output either. You have the new ENTRY_ONE and ENTRY_TWO within the properties, within the children, within the rootObject, not "under" IDCO_IDENTIFICATION. So I'm going to follow what you are asking for from your example output.
import json
with open('C:/test.json') as f:
data = json.load(f)
new_elements = [{"name":"ENTRY_ONE", "value":100},
{"name":"ENTRY_TWO", "value":55}]
for each in new_elements:
data['rootObject']['children'][0]['properties'].append(each)
with open('C:/test.json', 'w') as f:
json.dump(data, f)
Output:
import pprint
pprint.pprint(data)
{'rootObject': {'children': [{'childList': 'SYSTEMLOADCASE',
'children': [],
'id': '1dd94d1a-e52d-40b3-a82b-6db02a8fbbab',
'properties': [{'name': 'IDCO_IDENTIFICATION',
'value': '1dd94d1a-e52d-40b3-a82b-6db02a8fbbab'},
{'name': 'IDCO_DESIGNATION',
'value': 'Lastfall 1'},
{'name': 'IDSLC_TIME_PORTION',
'value': 100},
{'name': 'IDSLC_DISTANCE_PORTION',
'value': 100},
{'name': 'IDSLC_OPERATING_TIME_IN_HOURS',
'value': 1},
{'name': 'IDSLC_OPERATING_TIME_IN_SECONDS',
'value': 3600},
{'name': 'IDSLC_OPERATING_REVOLUTIONS',
'value': 1},
{'name': 'IDSLC_OPERATING_DISTANCE',
'value': 1},
{'name': 'IDSLC_ACCELERATION',
'value': 9.81},
{'name': 'IDSLC_EPSILON_X',
'value': 0},
{'name': 'IDSLC_EPSILON_Y',
'value': 0},
{'name': 'IDSLC_EPSILON_Z',
'value': 0},
{'name': 'IDSLC_CALCULATION_WITH_OWN_WEIGHT',
'value': 'CO_CALCULATION_WITHOUT_OWN_WEIGHT'},
{'name': 'IDSLC_CALCULATION_WITH_TEMPERATURE',
'value': 'CO_CALCULATION_WITH_TEMPERATURE'},
{'name': 'IDSLC_FLAG_FOR_LOADCASE_CALCULATION',
'value': 'LB_CALCULATE_LOADCASE'},
{'name': 'IDSLC_STATUS_OF_LOADCASE_CALCULATION',
'value': False},
{'name': 'ENTRY_ONE',
'value': 100},
{'name': 'ENTRY_TWO',
'value': 55}],
'type': 'IDO_SYSTEM_LOADCASE'}],
'id': '6ff0010c-00fe-485b-b695-4ddd6aca4dcd',
'type': 'IDO_GEAR'}}