A = {
"Ajit": {
"Place": "Bharasar",
"Age": "20"
},
"Deepika": {
"Place": "Mankuva",
"Age": "19"
}
}
I want to print specific key Ajit with Ajit's key it self like:
{
'Ajit': {
'Place': 'Bharasar',
'Age':'20'
}
}
Do you mean:
A = {"Ajit":{"Place":"Bharasar","Age":"20"}, "Deepika":{"Place":"Mankuva","Age":"19"}}
key = "Ajit"
print(f"{{'{key}': {A[key]}}}")
And please remember to put four spaces before your code samples to get proper formatting
You just create a new Dict like the following code:
A = {
"Ajit": {
"Place": "Bharasar",
"Age": "20"
},
"Deepika": {
"Place": "Mankuva",
"Age": "19"
}
}
B = {
"Ajit": A["Ajit"]
}
print(B)
If you want Ajit value, you can get it with A["Ajit"]
However, if you want to have the key and its associated value, you can print
A = {
"Ajit": {
"Place": "Bharasar",
"Age": "20"
},
"Deepika": {
"Place": "Mankuva",
"Age": "19"
}
}
key = "Ajit"
print("{" + key + ":" + A[key] + "}")
Related
Need some help please.
I have a similar json file:
{
"timestamp": "2022-09-20T08:16:00.000Z",
"metadata": {
"orgID": "6780",
"projectId": 0988,
}
},
{
"data":
"workers": [
{
"identifiers": {
"FullName": null,
"NINumber": null,
"CompID": null
},
"lastName": null,
"costCenter": null
},
{
"codes": [
{
"source": {
"name": "net_salary",
"value": 11500
},
"name": "net_salary",
"code": "rt_sa",
"value": 11500
},
{
"identifiers": {
"FullName": null,
"NINumber": null,
Comp ID": null
},
"lastName": null,
"costCenter": null
},
{
"codes": [
{
"source": {
"name": "hiredate",
"value": 3.333
},
"name": "hiredate",
"code": "h_code",
"value": 3.333
},
I want to change the key names under source from name->fieldname and value to fieldvalue.
However, I don't want to change the keys where there are the keys: name, code, value.
I tried this but it is not correct:
with open(r'C:\Users\Administrator\Documents\test\PJSON.json') as f:
payrolldata = json.load(f)
source = payrolldata[1]['data']['workers'][1]['codes'][1]['source']
print(source)
oldvalue = source.keys()
print(str(oldvalue).replace('name', 'newname').replace('value', 'value2'))
payrolldata = str(oldvalue).replace('name', 'newname').replace('value', 'newvalue2')
for d in payrolldata:
d['newName':] = d.pop["'name':"]
with open(r'C:\Users\Administrator\Documents\test\PJSON.json', "w") as f:
json.dump(payrolldata, f, indent=4)
I suggest you don't convert your dict into string and use something like this on you dict read from json file (with json.load)
def deep_replace_key(
d,
old_key: str,
new_key: str,
branch_name: str = None,
replace: bool = False,
):
"""deep replace key in dict.
Only make replacement if the we are in the branch branch_name."""
if branch_name is None:
replace = True
if isinstance(d, dict):
d_copy = d.copy()
for key, value in d_copy.items():
if key == old_key and replace:
d[new_key] = d.pop(old_key)
else:
if branch_name and key == branch_name:
deep_replace_key(value, old_key, new_key, branch_name, True)
else:
deep_replace_key(value, old_key, new_key, branch_name, False)
elif isinstance(d, list):
for item in d:
deep_replace_key(item, old_key, new_key, branch_name, replace)
return d
Here is a working test for this code
import unittest
# test
class TestDeepReplaceKey(unittest.TestCase):
def test_deep_replace_key(self):
d = {
"codes": [
{
"source": {
"name": "hiredate",
"value": 3.333
},
"not_source": {
"name": "hiredate",
"value": 3.333
},
},
{
"source": {
"name": "hiredate",
"value": 3.333
},
"not_source": {
"name": "hiredate",
"value": 3.333
},
},
]
}
d = deep_replace_key(d, "name", "new_name", "source", )
self.assertEqual(d["codes"][0]["source"]["new_name"], "hiredate")
self.assertEqual(d["codes"][0]["not_source"]["name"], "hiredate")
d = deep_replace_key(d, "name", "new_name", )
self.assertEqual(d["codes"][0]["not_source"]["new_name"], "hiredate")
So you can see if I call deep_replace_key(d, "name", "new_name", "source", ) the change only happens in the source block.
If I omit mentioning "source" like this deep_replace_key(d, "name", "new_name", ) change happens everywhere.
I have this sample.json file with me:
{
"details":[
{
"name": "",
"class": "4",
"marks": "72.6"
},
{
"name": "David",
"class": "",
"marks": "78.2"
},
{
"name": "Emily",
"class": "4",
"marks": ""
}
]
}
As you can see for the first one; "name" is string datatype is actually empty.
For the second one; "class" with integer datatype is empty.
And for the third one; "marks" with float datatype is empty.
Now my task is;
to find the fields which are empty, if string is empty replace it with "BLANK", if integer is empty replace it with 0, and if float is empty replace it with 0.0
P.S: I'm doing this with Python like this:
import json
path = open('D:\github repo\python\sample.json')
df = json.load(path)
for i in df["details"]:
print(i["name"])
Also make sure that I don't want to hard-code the values. Coz here if we see there are only 3 fields(name, class, marks) but what if I have more that 3. Then what? How will I find which fields are empty or not?
Like you see here:
{
"code": "AAA",
"lat": "-17.3595",
"lon": "-145.494",
"name": "Anaa Airport",
"city": "Anaa",
"state": "Tuamotu-Gambier",
"country": "French Polynesia",
"woeid": "12512819",
"tz": "Pacific\/Midway",
"phone": "",
"type": "Airports",
"email": "",
"url": "",
"runway_length": "4921",
"elev": "7",
"icao": "NTGA",
"direct_flights": "2",
"carriers": "1"
},
This is just one block, I've N-number of blocks like this. That's why I can't hard_code the values right?
Can anybody help me with it!
Thank You so much!
Since the type info isn't available anywhere programmatically, and there seem to be only three hard-coded fields, I'd just check each of them explicitly.
Short-circuiting with the or operator would even allow you to achieve this fairly elegantly:
for d in df['details']:
d['name'] = d['name'] or 'BLANK'
d['class'] = d['class'] or '0'
d['marks'] = d['marks'] or '0.0'
You could check whether the string is empty with a simple if statement like so.
if not i['name'] == ""
Alternatively, you could also do
if not i['name']
The second if statement makes use of falsy and truthy values in Python. Here's a link to read more about it
You could create a dictionary empty_replacements mapping each key to its corresponding desired empty value:
import json
sample_json = {
"details": [
{
"name": "",
"class": "4",
"marks": "72.6"
},
{
"name": "David",
"class": "",
"marks": "78.2"
},
{
"name": "Emily",
"class": "4",
"marks": ""
}
]
}
empty_replacements = {"name": "BLANK", "class": "0", "marks": "0.0"}
sample_json["details"] = [{
k: v if v else empty_replacements[k]
for k, v in d.items()
} for d in sample_json["details"]]
print('sample_json after replacements: ')
print(json.dumps(
sample_json,
sort_keys=False,
indent=4,
))
Output:
sample_json after replacements:
{
"details": [
{
"name": "BLANK",
"class": "4",
"marks": "72.6"
},
{
"name": "David",
"class": "0",
"marks": "78.2"
},
{
"name": "Emily",
"class": "4",
"marks": "0.0"
}
]
}
I 'm assuming by the dictionary which you provided that marks & class are stored as String.
li=[]
for d in df["details"]:
for k,v in d.items():
if (v==''):
if (k=='name'):
d[k]="BLANK"
elif (k=='class') :
d[k]='0'
elif (k=='marks'):
d[k]='0.0'
li.append(d)
df['details']=li
I have the following list:
{
"id":1,
"name":"John",
"status":2,
"custom_attributes":[
{
"attribute_code":"address",
"value":"st"
},
{
"attribute_code":"city",
"value":"st"
},
{
"attribute_code":"job",
"value":"test"
}]
}
I need to get the value from the attribute_code that is equal city
I've tried this code:
if list["custom_attributes"]["attribute_code"] == "city" in list:
var = list["value"]
But this gives me the following error:
TypeError: list indices must be integers or slices, not str
What i'm doing wrong here? I've read this solution and this solution but din't understood how to access each value.
Another solution, using next():
dct = {
"id": 1,
"name": "John",
"status": 2,
"custom_attributes": [
{"attribute_code": "address", "value": "st"},
{"attribute_code": "city", "value": "st"},
{"attribute_code": "job", "value": "test"},
],
}
val = next(d["value"] for d in dct["custom_attributes"] if d["attribute_code"] == "city")
print(val)
Prints:
st
Your data is a dict not a list.
You need to scan the attributes according the criteria you mentioned.
See below:
data = {
"id": 1,
"name": "John",
"status": 2,
"custom_attributes": [
{
"attribute_code": "address",
"value": "st"
},
{
"attribute_code": "city",
"value": "st"
},
{
"attribute_code": "job",
"value": "test"
}]
}
for attr in data['custom_attributes']:
if attr['attribute_code'] == 'city':
print(attr['value'])
break
output
st
I've been trying to figure out how I can iterate over a json like object, so I could get a user id by its name.
json
{
"ApiSearchResult": [
{
"totalNumberResults": 55,
"type": "User",
"searchResults": [
{
"firstName": "shashank",
"name": "0o_shashank._o0",
"uid": 81097836
},
{
"firstName": "Shahnawaz",
"name": "0shahnawaz.0",
"uid": 83697589
},
{
"firstName": "Ashu",
"name": "ashu.-3",
"uid": 83646061
},
{
"bgImage": "photoalbum_491396460_user82597906-1-jpeg.jpg",
"firstName": "Garfield",
"name": "beast.boy",
"uid": 82597906
},
{
"firstName": "Bharath",
"name": "bharath_mohan69",
"uid": 80197615
},
{
"bgImage": "photoalbum_481041410_user79819261-1-jpg.jpg",
"firstName": "Wille-ICE",
"name": "blowhole",
"uid": 79819261
}
]
}
]
}
Python
def getidbyname(name):
event = response['ApiSearchResult'][0]['searchResults'][0]
for key, value in event.iteritems():
if value == name: continue
elif key == "uid":
return value
But, this won't work, I've never really worked with this many nested elements.
def getidbyname(name):
for i in data['ApiSearchResult'][0]['searchResults']:
if i['name'] == name:
return i['uid']
This might work if your response is already a python dictionary:
def getidbyname(name):
for event in data["ApiSearchResult"][0]["searchResults"]:
if event["name"] == name:
return event["uid"]
If your input is a text value, you need to use json.loads(response) to get a python dictionary out of it.
I have a very long and uneven JSON object and I want to output every attribute, value for the end points (leaves) of the object.
For instance, it could look like this:
data = {
"Response": {
"Version": "2.0",
"Detail": {
"TransactionID": "Ib410c-2",
"Timestamp": "04:00"
},
"Transaction": {
"Severity": "Info",
"ID": "2222",
"Text": "Success"
},
"Detail": {
"InquiryDetail": {
"Value": "804",
"CountryISOAlpha2Code": "US"
},
"Product": {
"ID": "PRD",
"Org": {
"Header": {
"valuer": "804"
},
"Location": {
"Address": [
{
"CountryISOAlpha2Code": "US",
"Address": [
{
"Text": {
"#Value": 2,
"$": "Hill St"
}
}
]
}
]
}
}
}
}
}
}
I want to output each potential leaf. It can output the (final attribute or the entire path) and the value.
I know I just need to add something to this:
data = json.loads(inputFile)
small = repeat(data)
for attribute,value in small.iteritems():
print attribute,value
You could use recursion:
def print_leaf_keyvalues(d):
for key, value in d.iteritems():
if hasattr(value, 'iteritems'):
# recurse into nested dictionary
print_leaf_keyvalues(value)
else:
print key, value
Demo on your sample data:
>>> print_leaf_keyvalues(data)
Version 2.0
valuer 804
Address [{'CountryISOAlpha2Code': 'US', 'Address': [{'Text': {'#Value': 2, '$': 'Hill St'}}]}]
ID PRD
CountryISOAlpha2Code US
Value 804
Text Success
Severity Info
ID 2222
This will not handle the list value of Address however. You can always add an additional test for sequences and iterate and recurse again.