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How to extract nested dictionaries from dictionary into single dictionary?

I have a dictionary which contains some key-value pairs as strings, but some key-values are dictionaries.
The data looks like this:
{'amount': 123,
'baseUnit': 'test',
'currency': {'code': 'EUR'},
'dimensions': {'height': {'iri': 'http://www.example.com/data/measurement-height-12345',
'unitOfMeasure': 'm',
'value': 23},
'length': {'iri': 'http://www.example.com/data/measurement-length-12345',
'unitOfMeasure': 'm',
'value': 8322},
'volume': {'unitOfMeasure': '', 'value': 0},
'weight': {'iri': 'http://www.example.com/data/measurement-weight-12345',
'unitOfMeasure': 'KG',
'value': 23},
'width': {'iri': 'http://www.example.com/data/measurement-width-12345',
'unitOfMeasure': 'm',
'value': 1}},
'exportListNumber': '1234',
'iri': 'http://www.example.com/data/material-12345',
'number': '12345',
'orderUnit': 'sdf',
'producerFormattedPID': '12345',
'producerID': 'example',
'producerNonFormattedPID': '12345',
'stateID': 'm70',
'typeID': 'FERT'}
for the dimensions and price keys, there are some nested dictionaries as values. How can I extract that data so that the final variable is a dictionary with only keys-values as strings. For the price, I would need something like:
{'pricecurrencycode':'EUR','priceamount':123} instead of 'price': {'currency': {'code': 'EUR'}, 'amount': 123}.
and the same happening to dimensions key->to extract all the nested dictionaries so that it could be easier to transform into a final dataframe.

You can define a recursive flatten function that gets called whenever the dictionary value is a dictionary.
Assuming python>=3.9:
def flatten(my_dict, prefix=""):
res = {}
for k, v in my_dict.items():
if isinstance(v, dict):
res |= flatten(v, prefix+k)
else:
res[prefix+k] = v
return res
A slightly more verbose option for older python versions:
def flatten(my_dict, prefix=""):
res = {}
for k, v in my_dict.items():
if isinstance(v, dict):
for k_flat, v_flat in flatten(v, prefix+k).items():
res[k_flat] = v_flat
else:
res[prefix+k] = v
return res

python according to the same value combining dictionary

i have a list of dict like this
[
{'id': 'A123',
'feature': {'name': 'jack', 'age' : '18' },
'create_time': '2022-5-17 10:29:47',
'is_fast': False},
{'id': 'A123',
'feature': {'gender': 'male'},
'create_time': '2022-5-17 10:29:47',
'is_fast': False},
{'id': 'A123',
'habit': {'name': 'read'},
'create_time': '2022-5-15 10:29:45',
'is_fast': False},
{'id': 'A456',
'feature': {'name': 'rose'},
'create_time': '2022-4-15 10:29:45',
'is_fast': False},
{'id': 'A456',
'habit': {'name': 'sport'},
'create_time': '2022-3-15 10:29:45',
'is_fast': False}
]
But I want to merge the same "id" values ​​together using something function
The desired output is as follows
[
{'id': 'A123',
'feature': {'name': 'jack', 'age' : '18' ,'gender': 'male'},
'habit': {'name': 'read'},
'create_time': '2022-5-19 10:29:47', #Get the latest time based on the same id
'is_fast': False},
{'id': 'A456',
'feature': {'name': 'rose'},
'habit': {'name': 'sport'},
'create_time': '2022-4-15 10:29:45',
'is_fast': False},
]
How can I merge the same "id" values ​​according to these dictionaries..

This should get you started... I put some inline notes to explain what the code is doing. You still need to implement a date time comparison.
def merge_dicts(lst):
final = {} # results
for row in lst: # iterate through list
if row['id'] not in final: # if current item id hasnt been seen
final[row['id']] = row # assign it to results with id as the key
else:
record = final[row['id']] # otherwise compare to data already stored
for k,v in row.items(): #iterate through dictionary items
if k not in record: # if key not in results
record[k] = v # add the key and value
continue
if record[k] == v: continue # if they are already equal move on
if isinstance(v, dict): # if its a dictionary
record[k].update(v) # update the dictionary
else: # must be date time sequence so do some datetime comparison
"""Do some date comparison and assign correct date"""
return [v for k,v in final.items()] # convert to list
print(merge_dicts(lst))
output:
[
{
'id': 'A123',
'feature': {'name': 'jack', 'age': '18', 'gender': 'male'},
'create_time': '2022-5-17 10:29:47',
'is_fast': False,
'habit': {'name': 'read'}
},
{
'id': 'A456',
'feature': {'name': 'rose'},
'create_time': '2022-4-15 10:29:45',
'is_fast': False,
'habit': {'name': 'sport'}
}
]

You can use the dict.setdefault method to initialize sub-dicts under keys that don't already exist to avoid cluttering up your code with conditional statements that test the existence of keys:
merged = {}
for d in lst:
s = merged.setdefault(d['id'], d)
for k, v in d.items():
if isinstance(v, dict):
s.setdefault(k, v).update(v)
elif v > s[k]: # the dates/times in the input follow alphabetical order
s[k] = v # later dates/times takes precedence
print(list(merged.values()))
Demo: https://replit.com/#blhsing/BlandCarelessPolygons#main.py

Update a list of Dict based on another Dict

I have a dict as follows.
dict = {'P': ['Demo'], 'Q': ['PMS']}
And I have a list of Dict as follows.
all = [{'Name': 'PMS'}, {'Name': 'Demo'}]
I need to have the dict's respective value in all as bellow.
new_list = [{'Name': 'PMS','Code': 'Q'}, {'Name': 'Demo','Code': 'P'}]

In this specific case, given that the values are just strings and therefore hashable objects, you can use a dictionary of reverse mappings. Be aware that it could not be used if the values were not hashable.
dct = {'P': ['Demo'], 'Q': ['PMS']}
all = [{'Name': 'PMS'}, {'Name': 'Demo'}]
reverse_mapping = {v[0]:k for k, v in dct.items()}
new_list = [d.copy() for d in all]
for d in new_list:
d['Code'] = reverse_mapping[d['Name']]
print(new_list)
This gives:
[{'Name': 'PMS', 'Code': 'Q'}, {'Name': 'Demo', 'Code': 'P'}]

dct = {'P': ['Demo'], 'Q': ['PMS']}
all_ = [{'Name': 'PMS'}, {'Name': 'Demo'}]
out = [dict(**l, Code=next(k for k, v in dct.items() if l['Name'] in v)) for l in all_]
print(out)
Prints:
[{'Name': 'PMS', 'Code': 'Q'}, {'Name': 'Demo', 'Code': 'P'}]
Or: you can make temporary dictionary:
tmp = {v[0]:k for k, v in dct.items()}
out = [dict(**l, Code=tmp[l['Name']]) for l in all_]
print(out)

You could make an inverted dictionary of codes, then go through the list of dictionaries and add the codes in:
codes = {"P": ["Demo"], "Q": ["PMS"]}
lst = [{"Name": "PMS"}, {"Name": "Demo"}]
inverted_codes = {value: key for key, values in codes.items() for value in values}
# {'Demo': 'P', 'PMS': 'Q'}
for dic in lst:
code = dic["Name"]
dic["Code"] = inverted_codes[code]
print(lst)
Output
[{'Name': 'PMS', 'Code': 'Q'}, {'Name': 'Demo', 'Code': 'P'}]

how to create a new key from a value of another key Python

I have a list of dictionaries that looks like the following:
data = [{'Name': 'Paul', 'Date': '20200412', 'ID': '1020'}, {'Name': 'Frank', 'Date': '20200413', 'ID': '1030'}, {'Name': 'Anna', 'Date': '20200414', 'ID': '1040'}]
I need to create a new list of dictionaries, where ID's value would be the key, and the value is another dictionary with key/values associated with this specific ID.
This is the desired output:
new_data = [{'1020': {'Name': 'Paul', 'Date': '20200412'}},
{'1030': {'Name': 'Frank', 'Date': '20200413'}},
{'1040': {'Name': 'Anna', 'Date': '20200414'}}]
I have tried:
for index, my_dict in enumerate(data):
new_data = []
key = my_dict['ID']
new_data.append(key)
But that only assigned the key value, not sure how to push it into into a new dict along with other key/values.

>>> [{i['ID']: {k:v for k,v in i.items() if k != 'ID'}} for i in data]
[{'1020': {'Name': 'Paul', 'Date': '20200412'}},
{'1030': {'Name': 'Frank', 'Date': '20200413'}},
{'1040': {'Name': 'Anna', 'Date': '20200414'}}]

new_data = []
for index, my_dict in enumerate(data):
key = my_dict['ID']
del my_dict['ID']
new_data.append({key:data[index]})

To add the other values you simply need to create a new dict like this:
new_data.append( key:{
'name':my_dict['name']
'Date':my_dict['date']
}
You also don't need to make the 'key' variable, you can just use 'my_dict['ID']'

You could try this list comprehension:
[{x["ID"]: {k: v for k, v in x.items() if k != "ID"}} for x in data]
Which assigns ID as the parent key to the dictionary, and filters out the ID key from the child dictionary inside a dict comprehension
Which could be broken down into this:
result = []
for x in data:
result.append({x["ID"]: {k: v for k, v in x.items() if k != "ID"}})
And even to a straightforward loop approach:
result = []
for x in data:
dic = {x["ID"]: {}}
for k, v in x.items():
if k != "ID":
dic[x["ID"]][k] = v
result.append(dic)
Output:
[{'1020': {'Name': 'Paul', 'Date': '20200412'}}, {'1030': {'Name': 'Frank', 'Date': '20200413'}}, {'1040': {'Name': 'Anna', 'Date': '20200414'}}]

Change value in dictionary

I would like to know how I can change a value in a dictionary using list of keys and 1 value
my_dict = {
'bob': {
'name': {'first': 'FirstName', 'last': 'LastName'},
'job': 'Developer'
}
}
string1 = 'bob.name.first=Bob'
string1 = string.split('=')
string2 = string1[0].split('.')
string2.append(string[1])
Here I end up with a list of 4 items, the first 3 are keys and the last is the value.
How can I use this given list to change the value in my_dict considering that the given list keys number can be changed for example if I want to change bob.job=QA

You can write:
string1 = 'bob.name.first=Bob'
string1,string2 = string1.split('=')
string1 = string1.split('.')
my_dict[string1[0]][string1[1]][string1[2]] = string2

I suppose the following function is what you are looking for, it works with any number of keys and creates intermediates dictionaries if not exist yet.
d = {
'bob': {
'name': {
'first': 'FirstName',
'last': 'LastName'
},
'job': 'Developer'
}
}
def update_dict_by_expr(d, expr):
keys_value = expr.split('=')
keys = keys_value[0].split('.')
value = keys_value[1]
item = d
while len(keys) > 1:
key = keys.pop(0)
if key not in item:
item[key] = {}
item = item[key]
key = keys[0]
item[key] = value
print(d)
update_dict_by_expr(d, 'bob.name.first=Bob Junior')
update_dict_by_expr(d, 'bob.name.birth.date=01/01/2017')
update_dict_by_expr(d, 'bob.name.birth.place=NYC')
print(d)

You want a dict with keys that can be accessed as attributes. You can achieve that by subclassing dict class, and add support for your need. I think this is more pythonic solution as it is much more intuative:
class MyDict(dict):
def __getattr__(self, attr):
return self[attr] if attr in self.keys() else None
def __setattr__(self, attr, value):
self[attr] = value
my_dict = MyDict({
'bob': MyDict(
{'name':
MyDict({'first': 'FirstName', 'last': 'LastName'}),
'job':'Developer'})})
>>> my_dict.bob
{'job': 'Developer', 'name': {'last': 'LastName', 'first': 'FirstName'}}
>>> my_dict.bob.job
'Developer'
>>> my_dict.bob.name
{'last': 'LastName', 'first': 'FirstName'}
It does require some overhead, as you will need to build your dicts based on MyDict. Regular dicts won't work if added to this dict.
This supports setting a new value as well:
>>> my_dict.bob.job = 'QA'
>>> my_dict.bob.job
'QA'

If you want to update Bob's job you can access it using my_dict['bob']['job']
my_dict = {
'bob': {
'name': {'first': 'FirstName', 'last': 'LastName'},
'job': 'Developer'
}
}
my_dict['bob']['job'] = 'QA'
print(my_dict)
>> {'bob': {'name': {'last': 'LastName', 'first': 'FirstName'}, 'job': 'QA'}}
or by splitting your string:
my_dict = {
'bob': {
'name': {'first': 'FirstName', 'last': 'LastName'},
'job': 'Developer'
}
}
bobjob_key_value = 'bob.job=QA'
key, value = bobjob_key_value.split('=')
key = key.split('.')
my_dict[key[0]][key[1]] = value
print(my_dict)
>> {'bob': {'job': 'QA', 'name': {'last': 'LastName', 'first': 'FirstName'}}}

import yaml
def get_dictionary_replace_value(file, new_value, strip_qoutes=True):
with open(file, 'r') as rf:
yaml_doc = yaml.load(rf)
rf.close()
key, value = new_value.split('=')
keys = key.split('.')
inner_dict = yaml_doc
for i in keys[:-1]:
inner_dict = inner_dict[i]
inner_dict[keys[-1]] = value
with open(file, 'w') as wf:
if strip_qoutes:
wf.write(yaml.dump(yaml_doc,
default_flow_style=False).replace("'", "").replace('"', ""))
else:
wf.write(yaml.dump(yaml_doc, default_flow_style=False))
wf.close()