Access dictionary with elements from array softcoded
I have a dictionary created from JSON. I would like to access items in the dictionairy through arrays containing their keys. Visualised JSON:
{
"name": "Chiel",
"industry": {
"IndustryName": "Computer Science",
"company": {
"companyName": "Apple",
"address": {
"streetName": "Apple Park Way",
"streetNumber": "1"
}
}
},
"hobby": {
"hobbyName": "Music production",
"genre": {
"genreName": "Deep house",
"genreYearOrigin": "1980"
}
}
}
See the following code example:
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
print(dictionary[companyElements[0]][companyElements[1]][companyElements[2]][companyElements[3]])
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
print(dictionary[hobbyElements[0]][hobbyElements[1]][hobbyElements[2]])
The problem is that accessing the dictionaries is being done hardcoded. In other words, there are numbers being used (0, 1, 2, 3).
Is it possible to access the dictionairy through an array, but soft coded? So passing in an array (or another data structure) to the dict without making use of numbers? If so, how can one achieve this?
python arrays dictionary data-structures hardcode
add a comment |
I have a dictionary created from JSON. I would like to access items in the dictionairy through arrays containing their keys. Visualised JSON:
{
"name": "Chiel",
"industry": {
"IndustryName": "Computer Science",
"company": {
"companyName": "Apple",
"address": {
"streetName": "Apple Park Way",
"streetNumber": "1"
}
}
},
"hobby": {
"hobbyName": "Music production",
"genre": {
"genreName": "Deep house",
"genreYearOrigin": "1980"
}
}
}
See the following code example:
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
print(dictionary[companyElements[0]][companyElements[1]][companyElements[2]][companyElements[3]])
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
print(dictionary[hobbyElements[0]][hobbyElements[1]][hobbyElements[2]])
The problem is that accessing the dictionaries is being done hardcoded. In other words, there are numbers being used (0, 1, 2, 3).
Is it possible to access the dictionairy through an array, but soft coded? So passing in an array (or another data structure) to the dict without making use of numbers? If so, how can one achieve this?
python arrays dictionary data-structures hardcode
1
Don't post images of textual data, especially when they make it even less readable than a pure text version.
– Jim Stewart
Nov 23 '18 at 13:31
I changed it to beatified plain text.
– Chiel
Nov 23 '18 at 13:40
add a comment |
I have a dictionary created from JSON. I would like to access items in the dictionairy through arrays containing their keys. Visualised JSON:
{
"name": "Chiel",
"industry": {
"IndustryName": "Computer Science",
"company": {
"companyName": "Apple",
"address": {
"streetName": "Apple Park Way",
"streetNumber": "1"
}
}
},
"hobby": {
"hobbyName": "Music production",
"genre": {
"genreName": "Deep house",
"genreYearOrigin": "1980"
}
}
}
See the following code example:
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
print(dictionary[companyElements[0]][companyElements[1]][companyElements[2]][companyElements[3]])
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
print(dictionary[hobbyElements[0]][hobbyElements[1]][hobbyElements[2]])
The problem is that accessing the dictionaries is being done hardcoded. In other words, there are numbers being used (0, 1, 2, 3).
Is it possible to access the dictionairy through an array, but soft coded? So passing in an array (or another data structure) to the dict without making use of numbers? If so, how can one achieve this?
python arrays dictionary data-structures hardcode
I have a dictionary created from JSON. I would like to access items in the dictionairy through arrays containing their keys. Visualised JSON:
{
"name": "Chiel",
"industry": {
"IndustryName": "Computer Science",
"company": {
"companyName": "Apple",
"address": {
"streetName": "Apple Park Way",
"streetNumber": "1"
}
}
},
"hobby": {
"hobbyName": "Music production",
"genre": {
"genreName": "Deep house",
"genreYearOrigin": "1980"
}
}
}
See the following code example:
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
print(dictionary[companyElements[0]][companyElements[1]][companyElements[2]][companyElements[3]])
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
print(dictionary[hobbyElements[0]][hobbyElements[1]][hobbyElements[2]])
The problem is that accessing the dictionaries is being done hardcoded. In other words, there are numbers being used (0, 1, 2, 3).
Is it possible to access the dictionairy through an array, but soft coded? So passing in an array (or another data structure) to the dict without making use of numbers? If so, how can one achieve this?
python arrays dictionary data-structures hardcode
python arrays dictionary data-structures hardcode
edited Nov 23 '18 at 13:40
Chiel
asked Nov 23 '18 at 13:27
ChielChiel
134114
134114
1
Don't post images of textual data, especially when they make it even less readable than a pure text version.
– Jim Stewart
Nov 23 '18 at 13:31
I changed it to beatified plain text.
– Chiel
Nov 23 '18 at 13:40
add a comment |
1
Don't post images of textual data, especially when they make it even less readable than a pure text version.
– Jim Stewart
Nov 23 '18 at 13:31
I changed it to beatified plain text.
– Chiel
Nov 23 '18 at 13:40
1
1
Don't post images of textual data, especially when they make it even less readable than a pure text version.
– Jim Stewart
Nov 23 '18 at 13:31
Don't post images of textual data, especially when they make it even less readable than a pure text version.
– Jim Stewart
Nov 23 '18 at 13:31
I changed it to beatified plain text.
– Chiel
Nov 23 '18 at 13:40
I changed it to beatified plain text.
– Chiel
Nov 23 '18 at 13:40
add a comment |
3 Answers
3
active
oldest
votes
A possible solution is (from the example you provided):
def get_element(dictionary, array):
x = dictionary.copy()
for i in array:
x = x[i]
return x
companyElements = ["industry", "company", "address", "streetName"]
hobbyElements = ["hobby", "genre", "genreName"]
print(get_element(dictionary, companyElements))
print(get_element(dictionary, hobbyElements))
add a comment |
You could write a function that iterates the given keys.
Beware that the following implementation will not catch exceptions if one or more keys are missing in your JSON:
import json
import copy
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
def get_dict_value(data, keys):
result = copy.deepcopy(data)
for key in keys:
result = result[key]
return result
print( get_dict_value(dictionary, companyElements) )
print( get_dict_value(dictionary, hobbyElements) )
Result:
Apple Park Way
Deep house
add a comment |
You can use pandas library . It handles file operations very efficiently in Python because it's written in C.
You could use json_normalize function in Pandas for this task .
Reference - https://www.kaggle.com/jboysen/quick-tutorial-flatten-nested-json-in-pandas
import json
file=open('kk.json')
inp=json.load(file)
print(json_normalize(inp))
Where is your code? Please use the example provided here.
– Chiel
Nov 23 '18 at 14:15
The example you have provided can be solved using normal dictionary way but if you have highly nested file , use json_normalize : import json file=open('kk.json') inp=json.load(file) print(json_normalize(inp))
– kishan keswani
Nov 23 '18 at 17:35
I don't think this provides a solution that is asked for. Where is companyElements (the array of values used in the dot notation)? Where does it return the values "Apple Park Way" and "Deep House"?
– Chiel
Nov 24 '18 at 15:54
The documentation you provided is pretty useful though. I started experimenting with Pandas dataframe and it's performance.
– Chiel
Nov 24 '18 at 15:55
1
Hi Chiel , Deep house is there in hobby.genre.genreName and Apple Park Way is under industry.company.address.streetName .
– kishan keswani
Nov 24 '18 at 19:22
|
show 2 more comments
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3 Answers
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active
oldest
votes
3 Answers
3
active
oldest
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active
oldest
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active
oldest
votes
A possible solution is (from the example you provided):
def get_element(dictionary, array):
x = dictionary.copy()
for i in array:
x = x[i]
return x
companyElements = ["industry", "company", "address", "streetName"]
hobbyElements = ["hobby", "genre", "genreName"]
print(get_element(dictionary, companyElements))
print(get_element(dictionary, hobbyElements))
add a comment |
A possible solution is (from the example you provided):
def get_element(dictionary, array):
x = dictionary.copy()
for i in array:
x = x[i]
return x
companyElements = ["industry", "company", "address", "streetName"]
hobbyElements = ["hobby", "genre", "genreName"]
print(get_element(dictionary, companyElements))
print(get_element(dictionary, hobbyElements))
add a comment |
A possible solution is (from the example you provided):
def get_element(dictionary, array):
x = dictionary.copy()
for i in array:
x = x[i]
return x
companyElements = ["industry", "company", "address", "streetName"]
hobbyElements = ["hobby", "genre", "genreName"]
print(get_element(dictionary, companyElements))
print(get_element(dictionary, hobbyElements))
A possible solution is (from the example you provided):
def get_element(dictionary, array):
x = dictionary.copy()
for i in array:
x = x[i]
return x
companyElements = ["industry", "company", "address", "streetName"]
hobbyElements = ["hobby", "genre", "genreName"]
print(get_element(dictionary, companyElements))
print(get_element(dictionary, hobbyElements))
edited Nov 23 '18 at 13:37
answered Nov 23 '18 at 13:32
FMarazziFMarazzi
328213
328213
add a comment |
add a comment |
You could write a function that iterates the given keys.
Beware that the following implementation will not catch exceptions if one or more keys are missing in your JSON:
import json
import copy
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
def get_dict_value(data, keys):
result = copy.deepcopy(data)
for key in keys:
result = result[key]
return result
print( get_dict_value(dictionary, companyElements) )
print( get_dict_value(dictionary, hobbyElements) )
Result:
Apple Park Way
Deep house
add a comment |
You could write a function that iterates the given keys.
Beware that the following implementation will not catch exceptions if one or more keys are missing in your JSON:
import json
import copy
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
def get_dict_value(data, keys):
result = copy.deepcopy(data)
for key in keys:
result = result[key]
return result
print( get_dict_value(dictionary, companyElements) )
print( get_dict_value(dictionary, hobbyElements) )
Result:
Apple Park Way
Deep house
add a comment |
You could write a function that iterates the given keys.
Beware that the following implementation will not catch exceptions if one or more keys are missing in your JSON:
import json
import copy
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
def get_dict_value(data, keys):
result = copy.deepcopy(data)
for key in keys:
result = result[key]
return result
print( get_dict_value(dictionary, companyElements) )
print( get_dict_value(dictionary, hobbyElements) )
Result:
Apple Park Way
Deep house
You could write a function that iterates the given keys.
Beware that the following implementation will not catch exceptions if one or more keys are missing in your JSON:
import json
import copy
#create dict
jsonData = '{"name":"Chiel","industry":{"IndustryName":"Computer Science","company":{"companyName":"Apple","address":{"streetName":"Apple Park Way","streetNumber":"1"}}},"hobby":{"hobbyName":"Music production","genre":{"genreName":"Deep house","genreYearOrigin":"1980"}}}'
dictionary = json.loads(jsonData)
#Referencing dict for 'streetName', from array, hardcoded.
companyElements = ["industry", "company", "address", "streetName"]
#Referencing dict for 'genreName', from array, hardcoded.
hobbyElements = ["hobby", "genre", "genreName"]
def get_dict_value(data, keys):
result = copy.deepcopy(data)
for key in keys:
result = result[key]
return result
print( get_dict_value(dictionary, companyElements) )
print( get_dict_value(dictionary, hobbyElements) )
Result:
Apple Park Way
Deep house
answered Nov 23 '18 at 13:37
Mike ScottyMike Scotty
5,95052135
5,95052135
add a comment |
add a comment |
You can use pandas library . It handles file operations very efficiently in Python because it's written in C.
You could use json_normalize function in Pandas for this task .
Reference - https://www.kaggle.com/jboysen/quick-tutorial-flatten-nested-json-in-pandas
import json
file=open('kk.json')
inp=json.load(file)
print(json_normalize(inp))
Where is your code? Please use the example provided here.
– Chiel
Nov 23 '18 at 14:15
The example you have provided can be solved using normal dictionary way but if you have highly nested file , use json_normalize : import json file=open('kk.json') inp=json.load(file) print(json_normalize(inp))
– kishan keswani
Nov 23 '18 at 17:35
I don't think this provides a solution that is asked for. Where is companyElements (the array of values used in the dot notation)? Where does it return the values "Apple Park Way" and "Deep House"?
– Chiel
Nov 24 '18 at 15:54
The documentation you provided is pretty useful though. I started experimenting with Pandas dataframe and it's performance.
– Chiel
Nov 24 '18 at 15:55
1
Hi Chiel , Deep house is there in hobby.genre.genreName and Apple Park Way is under industry.company.address.streetName .
– kishan keswani
Nov 24 '18 at 19:22
|
show 2 more comments
You can use pandas library . It handles file operations very efficiently in Python because it's written in C.
You could use json_normalize function in Pandas for this task .
Reference - https://www.kaggle.com/jboysen/quick-tutorial-flatten-nested-json-in-pandas
import json
file=open('kk.json')
inp=json.load(file)
print(json_normalize(inp))
Where is your code? Please use the example provided here.
– Chiel
Nov 23 '18 at 14:15
The example you have provided can be solved using normal dictionary way but if you have highly nested file , use json_normalize : import json file=open('kk.json') inp=json.load(file) print(json_normalize(inp))
– kishan keswani
Nov 23 '18 at 17:35
I don't think this provides a solution that is asked for. Where is companyElements (the array of values used in the dot notation)? Where does it return the values "Apple Park Way" and "Deep House"?
– Chiel
Nov 24 '18 at 15:54
The documentation you provided is pretty useful though. I started experimenting with Pandas dataframe and it's performance.
– Chiel
Nov 24 '18 at 15:55
1
Hi Chiel , Deep house is there in hobby.genre.genreName and Apple Park Way is under industry.company.address.streetName .
– kishan keswani
Nov 24 '18 at 19:22
|
show 2 more comments
You can use pandas library . It handles file operations very efficiently in Python because it's written in C.
You could use json_normalize function in Pandas for this task .
Reference - https://www.kaggle.com/jboysen/quick-tutorial-flatten-nested-json-in-pandas
import json
file=open('kk.json')
inp=json.load(file)
print(json_normalize(inp))
You can use pandas library . It handles file operations very efficiently in Python because it's written in C.
You could use json_normalize function in Pandas for this task .
Reference - https://www.kaggle.com/jboysen/quick-tutorial-flatten-nested-json-in-pandas
import json
file=open('kk.json')
inp=json.load(file)
print(json_normalize(inp))
edited Nov 23 '18 at 17:37
answered Nov 23 '18 at 13:58
kishan keswanikishan keswani
309
309
Where is your code? Please use the example provided here.
– Chiel
Nov 23 '18 at 14:15
The example you have provided can be solved using normal dictionary way but if you have highly nested file , use json_normalize : import json file=open('kk.json') inp=json.load(file) print(json_normalize(inp))
– kishan keswani
Nov 23 '18 at 17:35
I don't think this provides a solution that is asked for. Where is companyElements (the array of values used in the dot notation)? Where does it return the values "Apple Park Way" and "Deep House"?
– Chiel
Nov 24 '18 at 15:54
The documentation you provided is pretty useful though. I started experimenting with Pandas dataframe and it's performance.
– Chiel
Nov 24 '18 at 15:55
1
Hi Chiel , Deep house is there in hobby.genre.genreName and Apple Park Way is under industry.company.address.streetName .
– kishan keswani
Nov 24 '18 at 19:22
|
show 2 more comments
Where is your code? Please use the example provided here.
– Chiel
Nov 23 '18 at 14:15
The example you have provided can be solved using normal dictionary way but if you have highly nested file , use json_normalize : import json file=open('kk.json') inp=json.load(file) print(json_normalize(inp))
– kishan keswani
Nov 23 '18 at 17:35
I don't think this provides a solution that is asked for. Where is companyElements (the array of values used in the dot notation)? Where does it return the values "Apple Park Way" and "Deep House"?
– Chiel
Nov 24 '18 at 15:54
The documentation you provided is pretty useful though. I started experimenting with Pandas dataframe and it's performance.
– Chiel
Nov 24 '18 at 15:55
1
Hi Chiel , Deep house is there in hobby.genre.genreName and Apple Park Way is under industry.company.address.streetName .
– kishan keswani
Nov 24 '18 at 19:22
Where is your code? Please use the example provided here.
– Chiel
Nov 23 '18 at 14:15
Where is your code? Please use the example provided here.
– Chiel
Nov 23 '18 at 14:15
The example you have provided can be solved using normal dictionary way but if you have highly nested file , use json_normalize : import json file=open('kk.json') inp=json.load(file) print(json_normalize(inp))
– kishan keswani
Nov 23 '18 at 17:35
The example you have provided can be solved using normal dictionary way but if you have highly nested file , use json_normalize : import json file=open('kk.json') inp=json.load(file) print(json_normalize(inp))
– kishan keswani
Nov 23 '18 at 17:35
I don't think this provides a solution that is asked for. Where is companyElements (the array of values used in the dot notation)? Where does it return the values "Apple Park Way" and "Deep House"?
– Chiel
Nov 24 '18 at 15:54
I don't think this provides a solution that is asked for. Where is companyElements (the array of values used in the dot notation)? Where does it return the values "Apple Park Way" and "Deep House"?
– Chiel
Nov 24 '18 at 15:54
The documentation you provided is pretty useful though. I started experimenting with Pandas dataframe and it's performance.
– Chiel
Nov 24 '18 at 15:55
The documentation you provided is pretty useful though. I started experimenting with Pandas dataframe and it's performance.
– Chiel
Nov 24 '18 at 15:55
1
1
Hi Chiel , Deep house is there in hobby.genre.genreName and Apple Park Way is under industry.company.address.streetName .
– kishan keswani
Nov 24 '18 at 19:22
Hi Chiel , Deep house is there in hobby.genre.genreName and Apple Park Way is under industry.company.address.streetName .
– kishan keswani
Nov 24 '18 at 19:22
|
show 2 more comments
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1
Don't post images of textual data, especially when they make it even less readable than a pure text version.
– Jim Stewart
Nov 23 '18 at 13:31
I changed it to beatified plain text.
– Chiel
Nov 23 '18 at 13:40