We Keep Coding

Reemplacing a list into a dictionary by another dictionary

I have a dictionary with some values that are type list, i need to convert each list in another dictionary and insert this new dictionary at the place of the list.
Basically, I have this dictionary
Dic = {
'name': 'P1',
'srcintf': 'IntA',
'dstintf': 'IntB',
'srcaddr': 'IP1',
'dstaddr': ['IP2', 'IP3', 'IP4'],
'service': ['P_9100', 'SNMP'],
'schedule' : 'always',
}
I need to reemplace the values that are lists
Expected output:
Dic = {
'name': 'P1',
'srcintf': 'IntA',
'dstintf': 'IntB',
'srcaddr': 'IP1',
'dstaddr': [
{'name': 'IP2'},
{'name': 'IP3'},
{'name': 'IP4'}
],
'service': [
{'name': 'P_9100'},
{'name': 'SNMP'}
],
'schedule' : 'always',
}
So far I have come up with this code:
for k,v in Dic.items():
if not isinstance(v, list):
NewDic = [k,v]
print(NewDic)
else:
values = v
keys = ["name"]*len(values)
for item in range(len(values)):
key = keys[item]
value = values[item]
SmallDic = {key : value}
liste.append(SmallDic)
NewDic = [k,liste]
which print this
['name', 'P1']
['srcintf', 'IntA']
['dstintf', 'IntB']
['srcaddr', 'IP1']
['schedule', 'always']
['schedule', 'always']
I think is a problem with the loop for, but so far I haven't been able to figure it out.

You need to re-create the dictionary. With some modifications to your existing code so that it generates a new dictionary & fixing the else clause:
NewDic = {}
for k, v in Dic.items():
if not isinstance(v, list):
NewDic[k] = v
else:
NewDic[k] = [
{"name": e} for e in v # loop through the list values & generate a dict for each
]
print(NewDic)
Result:
{'name': 'P1', 'srcintf': 'IntA', 'dstintf': 'IntB', 'srcaddr': 'IP1', 'dstaddr': [{'name': 'IP2'}, {'name': 'IP3'}, {'name': 'IP4'}], 'service': [{'name': 'P_9100'}, {'name': 'SNMP'}], 'schedule': 'always'}

understanding nested python dict comprehension

I am getting along with dict comprehensions and trying to understand how the below 2 dict comprehensions work:
select_vals = ['name', 'pay']
test_dict = {'data': [{'name': 'John', 'city': 'NYC', 'pay': 70000}, {'name': 'Mike', 'city': 'NYC', 'pay': 80000}, {'name': 'Kate', 'city': 'Houston', 'pay': 65000}]}
dict_comp1 = [{key: item[key] for key in select_vals } for item in test_dict['data'] if item['pay'] > 65000 ]
The above line gets me
[{'name': 'John', 'pay': 70000}, {'name': 'Mike', 'pay': 80000}]
dict_comp2 = [{key: item[key]} for key in select_vals for item in test_dict['data'] if item['pay'] > 65000 ]
The above line gets me
[{'name': 'John'}, {'name': 'Mike'}, {'pay': 70000}, {'pay': 80000}]
How does the two o/ps vary when written in a for loop ? When I execute in a for loop
dict_comp3 = []
for key in select_vals:
for item in test_dict['data']:
if item['pay'] > 65000:
dict_comp3.append({key: item[key]})
print(dict_comp3)
The above line gets me same as dict_comp2
[{'name': 'John'}, {'name': 'Mike'}, {'pay': 70000}, {'pay': 80000}]
How do I get the o/p as dict_comp1 in a for loop ?

The select vals iteration should be the inner one
result = []
for item in test_dict['data']:
if item['pay'] > 65000:
aux = {}
for key in select_vals:
aux[key] = item[key]
result.append(aux)

Build a dictionary with single elements or lists as values

I have a list of dictionaries:
mydict = [
{'name': 'test1', 'value': '1_1'},
{'name': 'test2', 'value': '2_1'},
{'name': 'test1', 'value': '1_2'},
{'name': 'test1', 'value': '1_3'},
{'name': 'test3', 'value': '3_1'},
{'name': 'test4', 'value': '4_1'},
{'name': 'test4', 'value': '4_2'},
]
I would like to use it to create a dictionary where the values are lists or single values depending of number of their occurrences in the list above.
Expected output:
outputdict = {
'test1': ['1_1', '1_2', '1_3'],
'test2': '2_1',
'test3': '3_1',
'test4': ['4_1', '4_2'],
}
I tried to do it the way below but it always returns a list, even when there is just one value element.
outputdict = {}
outputdict.setdefault(mydict.get('name'), []).append(mydict.get('value'))
The current output is:
outputdict = {
'test1': ['1_1', '1_2', '1_3'],
'test2': ['2_1'],
'test3': ['3_1'],
'test4': ['4_1', '4_2'],
}

Do what you have already done, and then convert single-element lists afterwards:
outputdict = {
name: (value if len(value) > 1 else value[0])
for name, value in outputdict.items()
}

You can use a couple of the built-in functions mainly itertools.groupby:
from itertools import groupby
from operator import itemgetter
mydict = [
{'name': 'test1', 'value': '1_1'},
{'name': 'test2', 'value': '2_1'},
{'name': 'test1', 'value': '1_2'},
{'name': 'test1', 'value': '1_3'},
{'name': 'test3', 'value': '3_1'},
{'name': 'test4', 'value': '4_1'},
{'name': 'test4', 'value': '4_2'},
]
def keyFunc(x):
return x['name']
outputdict = {}
# groupby groups all the items that matches the returned value from keyFunc
# in our case it will use the names
for name, groups in groupby(mydict, keyFunc):
# groups will contains an iterator of all the items that have the matched name
values = list(map(itemgetter('value'), groups))
if len(values) == 1:
outputdict[name] = values[0]
else:
outputdict[name] = values
print(outputdict)

compare two different length lists of dictionaries in python

I want to compare below dictionaries. Name key in the dictionary is common in both dictionaries.
If Name matched in both the dictionaries, i wanted to do some other stuff with the data.
PerfData = [
{'Name': 'abc', 'Type': 'Ex1', 'Access': 'N1', 'perfStatus':'Latest Perf', 'Comments': '07/12/2017 S/W Version'},
{'Name': 'xyz', 'Type': 'Ex1', 'Access': 'N2', 'perfStatus':'Latest Perf', 'Comments': '11/12/2017 S/W Version upgrade failed'},
{'Name': 'efg', 'Type': 'Cust1', 'Access': 'A1', 'perfStatus':'Old Perf', 'Comments': '11/10/2017 S/W Version upgrade failed, test data is active'}
]
beatData = [
{'Name': 'efg', 'Status': 'Latest', 'rcvd-timestamp': '1516756202.632'},
{'Name': 'abc', 'Status': 'Latest', 'rcvd-timestamp': '1516756202.896'}
]
Thanks
Rajeev

l = [{'name': 'abc'}, {'name': 'xyz'}]
k = [{'name': 'a'}, {'name': 'abc'}]
[i['name'] for i in l for f in k if i['name'] == f['name']]
Hope above logic work for you.

The answer provided didn't assign the result to any variable. If you want to print it, add the following would work:
result = [i['name'] for i in l for f in k if i['name'] == f['name']]
print(result)

Extract multiple key:value pairs from one dict to a new dict

I have a list of dict what some data, and I would like to extract certain key:value pairs into a new list of dicts. I know one way that I could do this would be to use del i['unwantedKey'], however, I would rather not delete any data but instead create a new dict with the needed data.
The column order might change, so I need something to extract the two key:value pairs from the larger dict into a new dict.
Current Data Format
[{'Speciality': 'Math', 'Name': 'Matt', 'Location': 'Miami'},
{'Speciality': 'Science', 'Name': 'Ben', 'Location': 'Las Vegas'},
{'Speciality': 'Language Arts', 'Name': 'Sarah', 'Location': 'Washington DC'},
{'Speciality': 'Spanish', 'Name': 'Tom', 'Location': 'Denver'},
{'Speciality': 'Chemistry', 'Name': 'Jim', 'Location': 'Dallas'}]
Code to delete key:value from dict
import csv
data= []
for line in csv.DictReader(open('data.csv')):
data.append(line)
for i in data:
del i['Speciality']
print data
Desired Data Format without using del i['Speciality']
[{'Name': 'Matt', 'Location': 'Miami'},
{'Name': 'Ben', 'Location': 'Las Vegas'},
{'Name': 'Sarah', 'Location': 'Washington DC'},
{'Name': 'Tom', 'Location': 'Denver'},
{'Name': 'Jim', 'Location': 'Dallas'}]

If you want to give a positive list of keys to copy over into the new dictionaries:
import csv
with open('data.csv', 'rb') as csv_file:
data = list(csv.DictReader(csv_file))
keys = ['Name', 'Location']
new_data = [dict((k, d[k]) for k in keys) for d in data]
print new_data

suppose we have,
l1 = [{'Location': 'Miami', 'Name': 'Matt', 'Speciality': 'Math'},
{'Location': 'Las Vegas', 'Name': 'Ben', 'Speciality': 'Science'},
{'Location': 'Washington DC', 'Name': 'Sarah', 'Speciality': 'Language Arts'},
{'Location': 'Denver', 'Name': 'Tom', 'Speciality': 'Spanish'},
{'Location': 'Dallas', 'Name': 'Jim', 'Speciality': 'Chemistry'}]
to create a new list of dictionaries that do not contain the keys 'Speciality' we can do,
l2 = []
for oldd in l1:
newd = {}
for k,v in oldd.items():
if k != 'Speciality':
newd[k] = v
l2.append(newd)
and now l2 will be your desired output. In general you can exclude an arbitrary list of keys like so
exclude_keys = ['Speciality', 'Name']
l2 = []
for oldd in l1:
newd = {}
for k,v in oldd.items():
if k not in exclude_keys:
newd[k] = v
l2.append(newd)
the same can be done with an include_keys variable
include_keys = ['Name', 'Location']
l2 = []
for oldd in l1:
newd = {}
for k,v in oldd.items():
if k in include_keys:
newd[k] = v
l2.append(newd)

You can create a new list of dicts limited to the keys you want with one line of code (Python 2.6+):
NLoD=[{k:d[k] for k in ('Name', 'Location')} for d in LoD]
Try it:
>>> LoD=[{'Speciality': 'Math', 'Name': 'Matt', 'Location': 'Miami'},
{'Speciality': 'Science', 'Name': 'Ben', 'Location': 'Las Vegas'},
{'Speciality': 'Language Arts', 'Name': 'Sarah', 'Location': 'Washington DC'},
{'Speciality': 'Spanish', 'Name': 'Tom', 'Location': 'Denver'},
{'Speciality': 'Chemistry', 'Name': 'Jim', 'Location': 'Dallas'}]
>>> [{k:d[k] for k in ('Name', 'Location')} for d in LoD]
[{'Name': 'Matt', 'Location': 'Miami'}, {'Name': 'Ben', 'Location': 'Las Vegas'}, {'Name': 'Sarah', 'Location': 'Washington DC'}, {'Name': 'Tom', 'Location': 'Denver'}, {'Name': 'Jim', 'Location': 'Dallas'}]
Since you are using csv, you can limit the columns that you read in the first place to the desired columns so you do not need to delete the undesired data:
dc=('Name', 'Location')
with open(fn) as f:
reader=csv.DictReader(f)
LoD=[{k:row[k] for k in dc} for row in reader]

keys_lst = ['Name', 'Location']
new_data={key:val for key,val in event.items() if key in keys_lst}
print(new_data)