nested dict python keys

Question

I want something like following structure : y['1'][tuple(list)] = val as an nested dict in python but while i am trying i get KeyError :

data in csv file is like :

Rest_id, rates, items
1,4, burger
1,8, tofu_log
2,5, burger
2,8.5, tofu_log
3,4, chef_salad
3,8, steak_salad_sandwich
4,5, steak_salad_sandwich,salad
4,2.5, wine_spritzer
5,4, extreme_fajita3,test2,test4,test
5,8, fancy_european_water
6,5, fancy_european_water
6,6,  extreme_fajita, jalapeno_poppers, extra_salsa
7,1.5, wine_spritzer
7,5, extreme_fajita, jalapeno_poppers

following is the code :

y = defaultdict(dict)

with open('sample_data_tested_with.csv','r') as f:
            reader = csv.reader(f, delimiter=',', quoting=csv.QUOTE_NONE)
            reader = [[x.strip() for x in row] for row in reader]
            for i in reader:
                #cd[i[0]] = {tuple(i[2:]):i[1]}
                #cd[i[0]][tuple(i[2:])].update(i[1])
                print i[0], i[1], tuple(i[2:])
                y[i[0]][tuple(i[2:])].append(i[1])

Later I want to search in the dict like y['rest_id']['item'] and find rates for that. Thanks in advance.

full stack from ipython :

 In [49]: with open('sample_data_tested_with.csv','r') as f:
            reader = csv.reader(f, delimiter=',', quoting=csv.QUOTE_NONE)
            reader = [[x.strip() for x in row] for row in reader]
            for i in reader:
                #cd[i[0]] = {tuple(i[2:]):i[1]}
                #cd[i[0]][tuple(i[2:])].update(i[1])
                print i[0], i[1], tuple(i[2:])
                #x[tuple(i[2:])]=float(i[1])
                y[i[0]][tuple(i[2:])].append(i[1])
   ....:         
 1 4 ('burger',)
 ---------------------------------------------------------------------------
 KeyError                                  Traceback (most recent call last)
 <ipython-input-49-ab608c2dc33a> in <module>()
       7                     print i[0], i[1], tuple(i[2:])
       8                     #x[tuple(i[2:])]=float(i[1])
 ----> 9                     y[i[0]][tuple(i[2:])].append(i[1])
       10 

  KeyError: ('burger',)

i could have y = defaultdict(list) and append data but then im not able to search data based on the keys like : y['rest_id']['item'] — Snehal Parmar
– Snehal Parmar, Commented Feb 27, 2014 at 8:53

Guy · Accepted Answer · 2014-02-28 07:54:16Z

0

Looks like you could use itertools.groupby

>>>import itertools
>>>newreader,keys=[],[]
>>>for k,g in itertools.groupby(reader,key=lambda x:x[0]):
      newreader.append(tuple(g[1:]))
      keys.append(k)

This should group your data into tuples. Now we iterate through newreader converting each tuple into a dict.

>>>d={}
>>>for *i,j in newreader,keys:
     d[j]=dict(i)

edited Feb 28, 2014 at 7:54

answered Feb 27, 2014 at 7:27

Guy

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6 Comments

Snehal Parmar Over a year ago

I am getting following error now : ValueError Traceback (most recent call last) <ipython-input-59-145e6ba39c9a> in <module>() ----> 1 for i,j in newreader,keys: 2 d[j] = dict(i) 3 ValueError: too many values to unpack

Guy Over a year ago

@snehalparmar thanks for the feedback, let me check.

Guy Over a year ago

@snehalparmar could you edit in the output your print statement gives into your original question?

Guy Over a year ago

@snehalparmar does the updated code work? I am using Cpython so I don't know if this is implementation specific.

Guy Over a year ago

@snehalparmar check now. if not, then I got nothing.

|

Snehal Parmar · Accepted Answer · 2014-02-28 10:52:45Z

0

Here is the solution i got, please check and let know if anyones find any issues with it, thanks a lot.

def create_NestedDict(filename):
    NestedDict = defaultdict(dict)
    with open(filename,'rb') as f:
        reader = csv.reader(f, delimiter=',')
        for row in reader:
            #print "row :", row
            record = row
            if record[0] not in NestedDict:
                NestedDict[record[0]] = {}
            items = tuple([ i.strip() for i in record[2:]])
            [record[0]][items] = record[1]
    return NestedDict

answered Feb 28, 2014 at 10:52

Snehal Parmar

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